Final report.pdf

Error! No text of specified style in document.
The Economic Case for
Investing in Europe’s Defence
Industry
September 2013

- 1 -

Europe Economics is registered in England No. 3477100.  Registered offices at Chancery House, 53-64 Chancery Lane, London WC2A 1QU.
Whilst  every  effort  has been  made to  ensure  the  accuracy  of  the information/material  contained in  this  report,  Europe Economics assumes no
responsibility  for  and  gives  no  guarantees,  undertakings  or  warranties  concerning  the  accuracy,  completeness  or  up  to  date  nature  of  the
information/analysis provided in the report and does not accept any liability whatsoever arising from any errors or omissions © Europe Economics.

Executive Summary
1  Executive Summary
1.1  Broad macroeconomic impacts of defence investment
The primary purposes of defence spending are the preservation of peace, the protection of security,
the maintenance of safe trade and transport routes, the underpinning of international diplomacy, and
the  support  of  the  projection  of  national  political  values.    These  primary  purposes  have  profound
macroeconomic  implications  —  few  countries  can  flourish  economically  without  secure  defence
arrangements.
But defence  expenditure,  like  other  forms of  public spending,  has  narrower  short- to  medium-term
macroeconomic implications.  Cuts to public spending can be vital to making government budgets and
debt  positions  sustainable.    But  not  all  spending  is  the  same  in  its  short-  to  medium-term
macroeconomic impacts.  Cuts to some forms of government spending are likely to induce larger shifts
(often, in the short-term, falls) in GDP than other forms of spending.
In this context, the EDA asked Europe Economics to consider a hypothetical investment of €100m in
the EU defence industry and to compare the short- to medium-term impacts of this investment with
an equivalent level of investment in other industries.
1.1.1  Multiplier effects
Economists distinguish between the short-term macroeconomic impacts of different forms of spending
by  estimating  what  are  called  “multipliers”  —  i.e.  the  multiple  by  which  GDP  changes  for  a  given
change in spending.  Multipliers are defined such that if a GDP multiplier is 1, then for every €100m of
spending cut in that area GDP will fall (in the short-term) by €100m; whilst if a GDP multiplier is 0.5,
then for every €100m of spending cut in that area GDP will fall (in the short-term) by €50m; and so
on.
Where some part of spending will be on imports, a nationally-estimated multiplier may be lower than a
globally-estimated multiplier.  So, for example, if the delivery of some defence contract in Germany
requires the contractor to import an intermediate product from Sweden, the German multiplier will
be lower than the EU multiplier.
Similar  multipliers  can  be  defined  for  other  macroeconomic  variables  such  as  employment,  taxation
and capital intensity.
1.1.2  GDP impacts
The total impact of an investment in a particular sector is calculated as the sum of the direct and less
direct impacts on various different sectors of the economy.
The  following table  compares  multipliers  for  defence  expenditure,  for  a  selection  of  Member  States
with significant defence sectors  – the Letter of Intent (LOI) countries  – and for the EU as a whole,
with multipliers for other key sectors of public spending:  health; education; and transport.
At the EU level, the GDP multiplier is almost equal across the four sectors, lying between 1.5 and 1.6.
With respect to defence, these estimates show the combined impact of different types of expenditure.
Defence expenditure is spread across a range of activities and sectors, such as computers, transport
equipment, fabricated metal products, construction, and scientific research.  Different forms of defence
- 1 -

Executive Summary
spending  therefore  have  slightly  different  short-term  macroeconomic  implications.    With  respect  to
GDP, the largest impacts come from expenditure on Weapons and Ammunition.
In general, at the Member State level, there is a very clear ranking, with education having the highest
multiplier,  followed  by  health,  transport  and  defence.    When  considering  multipliers  applying  within
Member States, the differences between sectors are substantial.  However, as  we can see from the
final column on multipliers as they apply across the EU as a whole, not too much should be read into
within-Member State multipliers, as sectors significantly vary in terms of their international ‘leakages’
(often  referred  to  hereafter  as  “Rest  of  World”  leakages),  i.e.  the  proportion  of  value  added
domestically, as opposed to overall, varies substantially in each of these sectors.  In general, defence
has  more  linkages  with  the  rest  of  the  world  and,  since  intra-EU  trade  is  not  captured  in  national
multipliers, within-Member State multipliers are bound to be lower.  By contrast, when we consider
the impact on the EU as a whole we see that the multiplier for defence is almost identical to that for
other sectors that experience significant public expenditure.

GDP multipliers of public expenditure changes
Sector
DE
FR
ES
IT
SE
UK
EU
Transport
1.1
1.9
1.3
1.8
1.0
1.8
1.5
Education
1.4
2.1
1.8
2.1
1.3
2.0
1.6
Health
1.3
2.0
1.6
1.9
1.3
1.9
1.6
Defence
0.8
1.3
0.8
1.3
0.7
1.2
1.6
Source: Europe Economics’ calculations
1.1.3  Tax revenue impacts
At  the  EU  level,  the  total  tax  receipts  (excluding  social  contributions)  multiplier  is  nearly  identical
across the four sectors.  The results by LOI Member State are shown below.
Tax revenue multipliers of public expenditure

changes
Sector
DE
FR
ES
IT
SE
UK
EU
Transport
0.3
0.5
0.3
0.5
0.4
0.5
0.4
Education
0.3
0.5
0.4
0.6
0.5
0.6
0.4
Health
0.3
0.5
0.4
0.5
0.5
0.5
0.4
Defence
0.2
0.3
0.2
0.4
0.2
0.3
0.4
Source: Europe Economics’ calculations
1.1.4  Employment impacts
An  investment  in  the  defence  sector  has  employment  effects  that  are  comparable  to  those  in  the
transport and health sectors.  It is unsurprising that education has the highest employment multiplier,
given its intrinsically high-labour intensity.
At the Member State level, education typically has the highest multiplier.  Moreover, in most cases the
defence multiplier is the smallest by a fair margin.  As with GDP multipliers this is due to the greater
international ‘leakages’ associated with the defence sector at a Member State level.
- 2 -

Executive Summary
Employment multipliers of public expenditure

changes
Sector
DE
FR
ES
IT
SE
UK
EU
Transport
16.7
27.6
15.2  26.7  14.3  29.9
28.5
Education
28.9
32.4
18.0  40.2  29.3  39.8
36.4
Health
26.9
31.1
16.8  33.9  21.2  37.9
30.9
Defence
13.8
17.8
18.4  21.9  8.7  18.9
28.7
Source: Europe Economics’ calculations
1.1.5  Skilled employment
At the EU level, defence has markedly the highest skilled employment multiplier.  This is followed by
transport,  health  and  education.    It  is  interesting  to  note  that  education  has  the  lowest  skilled
employment multiplier despite having the highest employment multiplier.
The  results  by  Member  State  are  shown  below.    As  above,  the  greater  international  ‘leakages’
associated with the defence sector at a Member State level lead the skilled employment multipliers of
some of the other sectors to exceed that of the defence sector for individual countries.
Skilled employment multipliers of public expenditure

changes
Sector
DE
FR
ES
IT
SE
UK
EU
Transport
4.3
6.0
4.2
5.6
2.0
6.6
2.6
Education
2.2
5.5
5.7
2.8
2.3
6.4
3.9
Health
2.5
5.5
5.1
2.9
2.1
6.2
4.6
Defence
2.4
5.7
4.6
2.7
1.5
5.4
7.6
Source: Europe Economics’ calculations
1.1.6  R&D potential
R&D  is  classified  as  a  sector  in  the  tables we  used  to  estimate  the  impacts  of an  investment  in the
defence sector.  Therefore, the impact of an investment on R&D potential was calculated using exactly
the same method as the impact on GDP.  The key difference is that the multipliers presented in the
table  below  focus  on  the  R&D  sector  alone,  rather  than  considering  impacts  on  all  sectors  of  the
economy.
At the EU level, investment in defence has by far the largest R&D multiplier.  The defence multiplier is
between 12 and 20 times the multipliers for the comparison sectors.

R&D multipliers of public expenditure changes
Sector
DE
FR
ES
IT
SE
UK
EU
Transport
2.2
10.0
3.3
9.2
5.4
6.4
5.7
Education
4.6
10.8
3.7
9.0
5.6
7.9
5.6
Health
3.4
11.8
4.2
9.0
5.1
8.6
8.7
Defence
72.1
131.4
58.1  33.9  52.7  117.4
111.4
Source: Europe Economics’ calculations
1.1.7  Exports
A  statistical  comparison  of  export  intensity  multipliers  between  sectors  is  not  possible,  because
exports  are  an  exogenous  final  use  in  the  I-O  framework  and  so  are  invariant  to  changes  in  other
variables.  Therefore, it is impossible to calculate the effects of the investment on exports.
- 3 -

Executive Summary
Our approach to this issue is, therefore, qualitative in nature and uses information on the quantity of
exports in each comparison sector in conjunction with heuristic arguments to infer the likely effect on
exports following investments in these sectors.  We then compared this to the estimated effect for the
defence sector.
Overall, we find that an investment in the defence sector is likely to have a much greater impact on
exports than would an equivalent investment in the transport, education or health sectors.
The  transport,  education  and  health  sectors  tend  to  export  little  to  countries  outside  the  EU.    By
contrast, EU defence companies sell arms and ammunition to several countries outside the EU.  The
EU is a major supplier of arms to many lesser-developed countries and so any investment which would
result in a more competitive EU offering could lead to the potential capturing of markets from other
major  arms  suppliers  such  as  the  US  and  Russia.    By  virtue  of  being  a  more  geographically  open
industry, an investment in EU defence is likely to have a much more substantial effect on EU exports
than is an equivalent investment in the transport, health or education sectors.
1.1.8  Capital intensity
At the EU level, defence investment would lead to a higher level of consumption of fixed capital than
investments  in the  education  and  health sectors, but a lower  level than investment in the transport
sector.
Results for the Member State level analysis are shown below, although data are not available for four
of the LOI countries.

Capital multipliers of public expenditure changes
Sector
DE
FR
ES
IT
SE
UK
EU
Transport
No data  No data
No data  163.7  187.1  No data
254.1
Education
No data  No data
No data  198.2  141.1  No data
171.0
Health
No data  No data
No data  179.8  137.4  No data
193.1
Defence
No data  No data
No data  218.8  89.5  No data
223.9
Source: Europe Economics’ calculations
1.1.9  Summary of broad macroeconomic impacts
At the EU level, the impacts on GDP, tax and employment of investing €100m in the health, education,
transport and defence sectors are extremely similar.
Taking  these  results  alone  shows  that  defence  spending  has  a  macroeconomic  role  alongside  other
forms of public spending.  However, there are several reasons to believe that, in some key dimensions,
the overall macroeconomic benefit of investing in the defence sector should exceed that of investing in
other sectors.
First, while the employment impacts of investing in the defence sector are broadly equivalent to the
impacts of investing in the health and transport sectors, defence investments have a far greater impact
on  skilled  employment  than  do  investments  in  the  other  sectors  considered  in  this  report.    In  an
increasingly  knowledge-based  and  skills-based  European  economy,  our  analysis  suggests  that
investments in the defence sector are more likely to create jobs that will be sustainable in the long
term and will add value to the European economy than would equivalent investments in other sectors.
Second, the importance of R&D to the past, current and future success of the European economy is
widely  acknowledged,  and  has  a  sound  economic  basis  in  R&D  models  of  endogenous  growth.
Investments in the defence sector are likely to make a significant contribution to the future economic
growth of the EU, due to the significant impact that such investments have on R&D.
- 4 -

Executive Summary
The impact on R&D due to defence investments is between 12 and 20 times greater than the impact of
investments  in  the  other  key  components  of  public  expenditure  (transport,  health  and  education).
Defence  R&D  can  create  significant  spin-offs  and  technology  transfer  to  other  civil  and  defence
applications.  Therefore, the economic impact of investing in the defence sector exceeds that which
has been captured in the I-O analysis.
1.2  Unpacking  the  mechanisms  by  which  defence  spending  affects  the
broader economy
To explore in more detail the mechanisms through which defence expenditure converts into broader
impacts on GDP, employment, tax revenue, exports and technology transfers to civilian sectors, we
set out a series of case studies of specific defence projects:
  Air:
  JAS Gripen,
  Dassault Rafale,
  Eurofighter Typhoon;
  Land – Leopard 2 Main Battle Tank;
  Maritime – Compact naval guns;
  R&T Case Study:  Intelligence, Surveillance and Reconnaissance Unmanned Air Systems; and
  Defence aerospace technology transfer and spin-offs.
1.2.1  Lessons
We draw a number of lessons from the case studies:
  Defence  spending  can  take  different  forms,  reflected  in  the  acquisition  of  Gripen,  Rafale  and
Typhoon  (or  other  types  of  defence  equipment).    Studies  based  solely  on  the  macroeconomic
impacts of defence spending, by their blunt nature fail to identify the more detailed microeconomic
impacts of such spending.
  There  remain  considerable  opportunities  for  increasing  the  efficiency  of  European  collaborative
defence  equipment  programmes.    For  example,  work-sharing  for  both  development  and
production could be allocated on the basis of competition; a single prime contractor might manage
the  programme  rather  than  an  industrial  consortium  and  committee  arrangements;  and  the
number  of  major-partner  nations  might  be  restricted  to  two  partners  so  as  to  minimise
transaction costs (bilateral collaboration).
  Investment in defence capabilities can sometime produce spectacular economic as well as defence
benefits, when a Ministry of Defence identifies a military requirement that is shared by a number of
nations,  and  then  commissions  a  national  supplier  to  develop  a  cost-effective  solution.    The
resulting export sales, over several decades, far exceed the numbers required for that country’s
own defence requirements (in the case of Oto Melara’s 76mm naval guns, by a factor of three).
  Investments in the EU defence sector can also lead to a significant cost saving relative to the next
best  alternative.    For  example,  Germany’s  investment  in  the  Leopard  2  enabled  it  to  equip  its
cavalry regiments with a highly capable system for a cost that was 45 per cent lower than the next
best alternative.
- 5 -

Executive Summary
  There is some indicative support for the claim that arguments for defence spending might be based
on  wider  economic  and  industrial  benefits,  including  technology  spin-offs.    Further  work  is
necessary to ascertain whether sufficient robust evidence exists to substantiate this.
  Economic  spill-overs  affect  air,  land  and  maritime  industrial  sectors.    While  detailed  published
evidence  is  lacking  on  spill-overs  by  the  defence  industry  sector,  some  indications  suggest  that
aerospace is a leading spill-over sector.
  EU defence companies appear to earn economic rent on their operations and, in some cases, this
rent appears to be substantial.1  For example, the economic rent earned on exports of Leopard 2s
was equivalent to 18 per cent of the cost of the Leopard programme.  The earning of economic
rent  indicates  that  the  sector  makes  a  net  contribution  to  the  economy,  over  and  above  the
contribution that the same resources would make if employed elsewhere.  Moreover, our analysis
suggests that a significant proportion of this economic rent is earned outside the EU; and so the
rent is more than simply a transfer between EU taxpayers and EU defence companies.
  Defence  spending  can  re-purpose  resources  from  the  manufacturing  sector  in  general,  i.e.  from
occupations  where  labour  productivity  is  probably  around  the  sector  average,  to  uses  in  areas
within  the  defence  sector  in  which  productivity  is  exceptional.    In  2010  and  2011,  Oto  Melara
achieved a turnover per employee that was over one-third higher than both that of the industry to
which it belongs, and the average for Italian manufacturing.
  Defence  investment  enables  nations  to  discover  solutions  that  are  cost-effective  for  them.
Purchasing defence systems “off-the-shelf” is often advocated as a way of avoiding the enormous
development costs and risks of new systems.   Whether or not this is the right choice, there is
usually  a  good  case  for  examining  this  option,  as  a  default  position.    Sometimes,  however,  the
“shelf”  lacks  systems  that  suit  a  nation’s  circumstances  and  defence  philosophy.    Compact naval
guns  are  such  a  case.    The  relatively  small  ships  deployed  by  European  coastal  navies  require
capable, compact and multi-purpose guns.  Their absence may have made different types of ships
necessary, resulting in a lower level of naval capability or significantly higher costs.
  Although there are clearly some advantages in purchasing non-EU “off-the-shelf” defence products
and services in some areas (and such products and services are purchased at present), it should
also  be  recognised  that  non-EU  “off-the-shelf”  solutions  can  have  some  potentially  adverse
consequences:
  For example, the Typhoon was estimated to have created 100,000 high-wage / high-skill jobs,
exports valued between €13.4bn and €17.8bn, and import-savings valued between €39.3bn and
€67.1bn  while  maintaining  European  independence  and  security  of  supply.    These  benefits
would be lost if non-EU off-the-shelf solutions were purchased.
  Purchasing  non-EU  off-the-shelf  solutions  could  create  classic  issues  of  security  of  future.
Absent  a  sufficient mass  of  investment  in  the  EU  defence  industry,  skills  and  capacities  could
deteriorate; rebuilding these would potentially be slow and expensive.  For example, even if the
EU were to undertake some work on the Joint Strike Fighter (JSF), it is unlikely that this work
alone would be sufficient to maintain the design skills necessary for developing a new European
combat aircraft.
As regarding whether defence research is better funded by direct investment in research or by the
sellers of defence equipment themselves, we have argued that because, in the defence sector:
  it will often be the case that (a) one buyer (or group of buyers agreeing amongst themselves to all
purchase the same technology) will comprise the overwhelming majority of purchases — often the

1   ‘Economic rent’ is a factor’s earnings in excess of what they could use in the next-best use (their ‘opportunity
cost’).  For example, if an industry’s cost of capital is 10 per cent and it earns 20 per cent on capital employed
of €1billion, it could be said to earn an annual economic rent of €100m.
- 6 -

Executive Summary
national defence agency of the country of the defence supplier; and (b) more fundamentally, other
buyers will not purchase a product that has not been endorsed by being purchased by the national
defence agency of the country of the defence supplier; and
 the key buyer typically has specific known needs arising from its strategic plans;
it is unsurprising and natural that advanced technology equipment projects research is often buyer-
funded in the defence sector.
- 7 -

Introduction
2  Introduction
The primary purposes of defence spending are the preservation of peace, the protection of security,
the  underpinning  of  international  diplomacy,  and  the  support  of  the  projection  of  national  political
values.    These  primary  purposes  have  profound  macroeconomic  implications  —  few  countries  can
flourish economically without secure defence arrangements.
However, defence expenditure, like other forms of public spending, has narrower short- to medium-
term macroeconomic implications.  Cuts to public spending can be vital to making government budgets
and  debt  positions  sustainable.    But  not  all  spending  is  the  same  in  its  short-  to  medium-term
macroeconomic impacts.  Cuts to some forms of government spending are likely to induce larger shifts
(often, in the short-term, falls) in GDP than other forms of spending.
In  this  context,  the  European  Defence  Agency  (EDA)  asked  Europe  Economics  to  consider  a
hypothetical investment of €100m in the EU defence industry and to compare the short- to medium-
term impacts of this investment with an equivalent level of investment in other industries.
We have employed a range of different methods in this project, so as to provide a rounded analysis of
the impacts of investment in the defence sector.  Each method is contained within a separate Chapter
of this report and is summarised in the following paragraphs.
Estimating short-term macroeconomic effects
We have used Input-Output (I-O) analysis to assess the impacts of a €100m investment on the EU
economy.  Our approach assumes that the additional investment would be distributed in accordance
with  past  expenditure,  and  so  those  activities  that  have  proven  to  be  in  demand  would  receive
proportionally  more  of  the  additional  investment.    Our  analysis  includes  impacts  on:    GDP;  tax
revenue; employment; skilled employment; R&D; exports and capital intensity.
Our estimates of the impacts of a €100m investment in the defence sector are contained in Chapter 3
of this report, while comparisons with other sectors are in Chapter 4.
Case studies
I-O  analysis  identifies  the  macroeconomic  impacts  of  increased  defence  spending  in  the  European
Union.  The focus is on economic impacts in terms of GDP, employment, tax revenue, exports and
technology transfers to civilian sectors.
We completed six case studies of specific investments, taking a microeconomic approach to identifying
the impacts of defence expenditure.  The case studies contained in Chapter 5 of this report show the
economic impacts of increased defence spending where that spending is reflected in the acquisition of
different types of new defence equipment.
Each  case  study  focuses  on  the  economic  impacts  of  the  project.    Various  performance  indicators
reflecting  competitiveness  are  used  including  unit  prices,  delivery  dates,  output  and  exports.    The
defence aerospace case studies also provide an insight into technology transfer (spin-offs) by providing
numerous examples of such spin-offs, although we consider that significant opportunities  remain for
further research in this area.
Defence R&D
One  of  the  defining  characteristics  of  the  defence  sector  is  its  dynamism.    R&D  is  continually
undertaken with the aim of improving both the quality and range of defence equipment and production
processes.  Chapter 6 of this report considers a number of issues related to defence R&D, using both
a theoretical and an empirical approach.
- 8 -

Introduction
Using the theoretical approach, we explain why the typical funding mechanism for defence R&D is one
of buyer-funding rather than the seller-funding model that exists in certain other sectors. We explain
the implications of the funding mechanism for private-venture funding in the defence sector.
Using the empirical approach, we report the views of stakeholders on various aspects of defence R&D.
The information that is contained within this section of the report was gathered during the course of
this project through a stakeholder survey.
Conclusions
The final chapter of this report draws together the different strands of the analysis described above
and identifies the key lessons that emerge from this study.
- 9 -

Macroeconomic Impacts
3  Macroeconomic Impacts
The EDA asked Europe Economics to consider a hypothetical investment of €100m in the EU defence
industry and to compare the impacts of this investment with an equivalent level of investment in other
sectors.  We have used I-O analysis to assess the impacts of a €100m investment on the EU economy.
I-O  analysis  is  a  very  simple  general-equilibrium  model  which  links  various  sectors  in  the  economy
through fixed linear relationships between the output of a sector and the inputs it requires from other
sectors.
The main attraction of I-O analysis is that fixed linear relationships make it possible to calculate the
effects of an increase in final demand for one sector on every other sector of the economy and on
various  macroeconomic  variables  –  GDP,  employment,  tax  revenue,  incomes  and  so  on.    Another
interesting  feature  is  that  ‘multipliers’  may  be  easily  calculated.    These  ‘multipliers’  indicate  the
percentage change in any macroeconomic quantity (GDP, tax revenue, income, employment, etc.) as a
result of a unit increase in final demand for a particular sector.2
There are, however, two main drawbacks of I-O analysis.
  The  reliance  on  fixed  linear  relationships  assumes  no  change  in  production  technologies.
Consequently,  I-O  is  not  accurate  when  analysing  long-run  effects.    The  results  of  I-O  analyses
should always be viewed as rough approximations to true short-run effects.
  I-O  analysis  only  produces  close  approximations  when  economies  are  not  close  to  full
employment.    Close  to  full  employment,  the  additional  resources  required  to  produce  extra
output would simply not be available.
In the case of the current research, we focus on the short-run impacts of a hypothetical investment
and  so  technological  change  does  not  present  any  difficulties.    Furthermore,  given  the  current
economic circumstances of the EU, for the purposes of this study we operate on the assumption that
no EU economy is currently operating close to full employment.
In preparation for I-O analysis, we divided the €100m defence investment across I-O sectors for all
Member  States.    Appendix  1  describes  how  we  addressed  a  number  of  conceptual  issues  such  as
defining the defence activities that are covered by the investment, distributing the investment across
the participating Member States of the EDA and distributing the expenditure between I-O sectors.  A
final distribution is also given.
For each macroeconomic variable included in our analysis, we have calculated three kinds of effects:
  Direct  effects:    These  are  the  first  round  effects  caused  by  an  increase  in  output  of  a  sector.
Direct effects include the increases in output, value added, employment, tax and so on that occur
in those sectors that increase their output in order to meet the additional demand.
  Indirect  effects:    These  are  caused  by  all  sectors  adjusting  outputs  to  allow  for  an  increase  in
demand for intermediate inputs that would accompany any increase in output by any sector.
  Induced effects:  These are the higher order effects caused by the factors of production (including
providers of labour, capital and entrepreneurship) spending the additional income arising from the
direct and indirect increases in output.  An important point to note is that the structure of the I-O

2   We calculate direct, indirect and induced effects.  Direct effects occur in the defence I-O sectors that receive
additional investment.  Indirect effects occur as other sectors adjust to increased demand for intermediate
inputs.  Induced effects arise as the higher output boosts wages and employees spend their additional income.
- 10 -

Macroeconomic Impacts
tables available from Eurostat does not allow us to calculate induced effects using I-O analysis, and
so we have used national income multipliers as the basis for these calculations.
In this section, we report results that include all of these effects.  Results excluding induced effects are
presented in Appendix 4.3
3.1  GDP
3.1.1  Approach
We  used  the  linear  relationships  inherent  in  the  I-O  tables  to  calculate  the  impacts  of  the  €100m
defence investment on the GDP of each Member State and the EU as a whole.  In particular we used
the tables as follows.
  To  estimate  the  extra  output  required  of  each  sector  in  order  to  fulfil  the  direct  additional
demand  due  to  the  investment,  we  relied  on  the  relationships  between  sectors  inherent  in  the
tables.  We also estimated the indirect effects arising from the increase in demand for inputs by
various  sectors.4    Given  sectoral  estimates  we  simply  summed  the  additional  output  across  all
sectors to obtain the total additional output for the Member State.
  To calculate the additional GDP as a result of the investment, we first calculated the proportion of
output  of  each  sector  that  represents  value  creation.5    We  then  used  the  same  proportions to
estimate the value added consistent with the increased outputs as a result of the investment.
  To calculate the GDP multiplier due to direct and indirect effects, we simply divided the additional
GDP by the additional investment in that Member State.
  The induced effects of an increase in demand (i.e. the impacts of an increase in consumption due
to the increase in household incomes associated with an increase in demand) cannot be calculated
by using I-O tables because the household sector is regarded as extraneous.  We have calculated
these effects indirectly using data on income multipliers.  To do this, we first  estimated income
multipliers  based  on  savings  and  import  rates.6    We  then  multiplied  the  GDP  effects  (excluding
induced effects) by the income multipliers to arrive at the total effects (including induced effects).
It should be noted that this analysis was conducted only at the Member State and EU levels, not at
the sectoral levels.
  The higher order effects of an increase in demand for products of other geographical regions (as
represented by ‘Rest of World Multipliers’) could not be calculated in this study.7

3   Appendix 2 contains a more detailed description of I-O models, and how each of the effects and multipliers
are calculated.
4   Technically, the additional output vector was calculated according to the formula (     )       , where   is
the input coefficients matrix and    is the vector of additional demand.  See Appendix 2.
5   This proportion was calculated as value added divided by sectoral output.
6   The formula used was    , where   is the gross savings rate (that part of GDP that is not consumed by either

the government or the private sector) and   is the import rate (that part of GDP which is spent on imports).
The denominator of  any  multiplier formula  contains that  part of GDP which does not immediately lead to
new value addition in the economy.  Savings lead to investment, which leads to capital formation in the future,
whereas imports lead to immediate value creation in the rest of the world.  The other components of GDP
(domestic consumption and exports) lead to direct value creation in the home economy, and are thus not
included.
7   ‘Rest of the world multipliers’ operate as follows.  An increase in demand in a geographical region increases
demand for products from the rest of the world.  In turn, this increases demand within countries outside the
geographical region that experienced the increase in demand.  Assuming that there is two-way trade between
- 11 -

Macroeconomic Impacts
3.1.2  Results
Our calculations suggest that EU GDP would rise in the short term by €156m after taking induced
effects into account.  This equates to a multiplier of 1.56 when direct, indirect and induced effects are
accounted for.
The detailed results by Member State are shown in the table below.
Table 3.1: GDP effects and multipliers by Member State (including induced effects)
Member
Income multiplier
Increase in GDP (€m)
GDP Multiplier (incl.
State
(incl. induced effects)
induced effects)
AT
1.23
0.36
0.45
BE
1.00
0.29
0.35
BG
Not available
Table not available
Table not available
CY
Not available
Table not available
Table not available
CZ
1.32
0.57
0.67
EE
0.93
0.08
0.37
FI
1.78
1.64
0.88
FR
2.19
32.18
1.28
DE
1.49
13.55
0.79
EL
2.75
2.09
0.52
HU
1.02
0.13
0.38
IE
1.16
0.06
0.28
IT
2.18
8.72
1.27
LV
1.34
0.07
0.61
LT
1.23
0.06
0.48
LU
Not available
Table not usable
Table not usable
MT
Not available
Table not available
Table not available
NL
1.20
1.62
0.43
PL
1.79
2.74
0.87
PT
1.88
0.41
0.56
RO
1.58
0.32
0.66
SK
0.99
0.13
0.40
SI
1.14
0.11
0.54
ES
1.89
4.24
0.84
SE
1.45
1.49
0.65
UK
2.24
29.01
1.17
EU-27
1.62
155.98
1.56
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
We have found that the multipliers for individual Member States are all below that for the EU-27.  This
is  because  the  Member  State  level  analysis  does  not  take  into  account  the  spill-over  effects  of  an
increase in demand for products of other EU Member States, while the EU level analysis does.8
The  income  multipliers  differ  significantly  between  Member  States  due  to  differences  in  savings  and
import  rates.    For  example,  countries  such  as  Greece  and  Portugal  have  high  income  multipliers
because they have low savings rates, while the UK and France have high income multipliers because of
relatively  low  import  rates.    It  is  interesting  to  note  that  the  Member  States  with  a  substantially
developed defence industry (France, UK, Germany, Spain, Italy and Sweden) have a similar dispersion
of multipliers to the other Member States.

the countries, this will create a feedback effect that results in a further increase in demand in the geographical
region which experienced the original boost to demand.
8   More  specifically,  the  input  coefficients  in  the  EU-27  table  reflect  inputs  produced  anywhere  in  the  EU;
whereas  in  the  Member  State  level  tables  they  reflect  only  inputs  produced  in  that  Member  State.    The
structure  of  the  I-O  tables  available  from  Eurostat  makes  it  impossible  to  include  spill-over  effects  arising
from increases in imports at the Member State level.  As such, the estimates for Member States in the above
table should be regarded as lower bounds.
- 12 -

link to page 16 Macroeconomic Impacts
Countries with high income multipliers generally have high GDP multipliers.  However, it should be
noted  that  the  positive  impact  of  low  savings  rates  on  GDP  would  apply  only  in  the  short  term.
Countries with lower savings rates also have lower rates of capital formation and investment, and so
might face growth constraints in the medium to long term.  Therefore, it is possible that short-term
increases in income come at the expense of long-term growth in countries with low savings rates.  We
cannot  test  this  hypothesis  here,  however,  as  the  estimation  of  medium-  and  long-term  changes  is
beyond the scope of this study.
Moreover,  it  should  be  noted  that  this  analysis  assumes  that  the  same  proportion  of  each  sector’s
output  would  be  imported  as  at  present.    However,  it  would  be  possible  to  target  the  additional
investment at domestic / European activities.  If this were the case, multipliers would be larger.  Such
an effect cannot be captured in traditional I-O analysis and so the effects identified in Table 3.1 may be
seen as underestimates.
3.2  Tax revenue
3.2.1  Approach
We combined the tax data contained in the I-O tables and supplementary tax data from Eurostat with
our results on GDP effects to calculate the impact of the €100m investment on tax revenue.
Our analysis of production taxes proceeded as follows:
  We  first  divided  total  production  taxes  in  each  sector  (including  ‘taxes  less  subsidies  on
production’ and ‘other net taxes on production’) by sectoral output to obtain an estimate of the
proportion of the value of output that was appropriated by tax.
  To calculate direct effects, we multiplied these tax rate estimates by the direct increase in sectoral
output, i.e. the amount of investment in each sector.
  To  calculate  indirect  effects,  we  multiplied  the  tax  rate  estimates  by  the  direct  and  indirect
increase in sectoral output.
The results of our analysis of production taxes are presented in Appendix 4.
We  then  moved  to  our  analysis  of  the  effect  on  total  tax  receipts.    In  order  to  incorporate  taxes
which do not appear in I-O tables (i.e. income taxes, capital taxes, etc.) we used data from Eurostat on
tax  receipts  as  a  percentage  of  GDP.    We  conducted  two  sets  of  calculations,  one  for  total  tax
receipts and another for total tax receipts plus social contributions.
  We  obtained  data  from  Eurostat  on  tax  receipts  as  a  percentage  of  GDP  in  the  years
corresponding to the various national and EU I-O tables.
  To calculate direct effects, we multiplied these percentages by the direct increases in GDP in each
Member State and the EU.
  To include indirect effects, we multiplied these percentages by the direct plus indirect increases in
GDP in each Member State and the EU.
  To include induced effects, we multiplied these percentages by the total increase in GDP (including
induced effects) in each Member State and the EU.
This method is consistent with the assumption that the additional GDP (direct, indirect and induced)
has the same composition in terms of tax liability as pre-existing GDP.  This assumption is unlikely to
be  entirely  accurate  because  the  direct  and  indirect  GDP  increases  have  a  different  sectoral
composition when compared to pre-existing GDP, which in turn may not have the same tax liability as
- 13 -

Macroeconomic Impacts
each  other.    Therefore,  estimates  obtained  using  this  method  should  be  regarded  as  an
approximation.9
3.2.2  Results (total tax receipts excluding social contributions)
Taking induced effects into account, a €100m investment in the EU defence sector would lead to an
increase  in  total  tax  receipts  (excluding  social  contributions)  by  €42m.    This  is  consistent  with  a
multiplier of 0.42, i.e. each euro of investment would add €0.42 to total tax receipts (excluding social
contributions).
The detailed results by Member State are shown in the table below.
Table  3.2:    Total  tax  effects  (excluding  social  contributions)  and  multipliers  by  Member  State
(including induced effects)
Member
Total tax rate (%)
Increase in total tax
Total tax multiplier (incl.
State
receipts (€m) (incl.
induced effects)
induced effects)
AT
28.4
0.10
0.13
BE
31.1
0.09
0.11
BG
Table not available
Table not available
Table not available
CY
Table not available
Table not available
Table not available
CZ
18.5
0.11
0.12
EE
20.4
0.02
0.08
FI
30.1
0.49
0.26
FR
25.6
8.24
0.33
DE
23.7
3.21
0.19
EL
20.6
0.43
0.11
HU
26.6
0.04
0.10
IE
22.5
0.01
0.06
IT
27.7
2.41
0.35
LV
22.3
0.02
0.14
LT
20.3
0.01
0.10
LU
Table not usable
Table not usable
Table not usable
MT
Table not available
Table not available
Table not available
NL
24.4
0.39
0.10
PL
20.8
0.57
0.18
PT
24.0
0.10
0.13
RO
18.7
0.06
0.12
SK
18.6
0.03
0.08
SI
24.5
0.03
0.13
ES
24.2
1.03
0.20
SE
37.2
0.55
0.24
UK
29.1
8.44
0.34
EU-27
26.8
41.80
0.42
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
We note that the Member State multipliers are lower than the EU multiplier.  Of the Member States
with  major  defence  investment,  the  UK,  Italy  and  France  have  high  multipliers  of  between  0.33  and
0.35, while Spain and Germany have moderate multipliers of 0.20 and 0.19.  The high multipliers for
the UK, Italy and France are due to a combination of large GDP effects, high income multipliers and
high tax rates.  Slovakia has the lowest multiplier, due to a combination of a small GDP multiplier, a

9   A more exact way to calculate the impacts on tax revenue would be to calculate effects within an I-O model
where  households,  capital  and  government  are  endogenous  sectors.    Here,  payments  by  households  and
owners of capital to government would be regarded as tax, and the effects of income, production and capital
taxes  could  be  analysed.    However,  the  structure  of  Eurostat  I-O  tables  regard  households  and  the
government as exogenous, making such analysis infeasible.
- 14 -

Macroeconomic Impacts
low  income  multiplier  and  a  low  tax  rate.   The  Netherlands,  Lithuania  and  Hungary  also  have  small
multipliers.
These  estimates  can  be  regarded  as  more  accurate  in  that  the  additional  income  generated  by  the
direct and indirect effects is spent according to the same sectoral pattern as existing GDP.  Thus, the
sectoral composition of additional GDP including induced effects is likely to be closer to that of pre-
existing GDP.  This would reduce the errors coming from differential sectoral tax rates.
3.2.3  Results (total tax receipts including social contributions)
We have also calculated the effects for a definition of tax receipts that includes social contributions.
These are shown in the table below.
Table  3.3:    Total  tax  effects  (including  social  contributions)  and  multipliers  by  Member  State
(including induced effects)
Member
Total tax rate (%)
Increase in total tax
Total tax multiplier (incl.
State
receipts (€m) (incl.
induced effects)
induced effects)
AT
44.2
0.16
0.20
BE
47.0
0.14
0.17
BG
Table not available
Table not available
Table not available
CY
Table not available
Table not available
Table not available
CZ
33.4
0.19
0.22
EE
30.7
0.02
0.11
FI
43.0
0.70
0.38
FR
44.1
14.19
0.57
DE
40.2
5.45
0.32
EL
34.0
0.71
0.18
HU
40.4
0.05
0.15
IE
29.9
0.02
0.08
IT
40.3
3.51
0.51
LV
32.9
0.02
0.20
LT
28.7
0.02
0.14
LU
Table not usable
Table not usable
Table not usable
MT
Table not available
Table not available
Table not available
NL
38.9
0.63
0.17
PL
32.8
0.90
0.29
PT
35.9
0.15
0.20
RO
28.8
0.09
0.19
SK
31.5
0.04
0.13
SI
38.9
0.04
0.21
ES
36.7
1.56
0.31
SE
45.9
0.68
0.30
UK
37.4
10.85
0.44
EU-27
40.4
63.02
0.63
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
3.3  Employment
3.3.1  Approach
We used employment data in conjunction with I-O data and the results of our GDP impacts analysis to
estimate the number of jobs created by sector and by Member State.  In particular:
  We used Eurostat data on employment by NACE code to derive employment by I-O sector for
the year corresponding to the latest available I-O tables for each Member State and the EU-27.
- 15 -

Macroeconomic Impacts
  We then divided total employment by sectoral output (in €m) to obtain the number of domestic
workers per €m output.
  We multiplied the additional output (in €m, calculated during the GDP impacts analysis) in each
sector and Member State by the number of domestic workers per €m output in order to estimate
the  number  of  jobs  that  would  be  created.10    This  was  estimated  for  both  direct  effects
(multiplying with direct increases in output) and indirect effects (multiplying with indirect increases
in output).
  Induced effects on output were not calculated due to the absence of households from the Eurostat
I-O tables.  Therefore, a different methodology was required to calculate the induced employment
effects:
  Using  national  level  employment  data  and  data  on  GDP  at  current  prices  from  Eurostat,  we
calculated the number of domestic workers per €m GDP for the year  corresponding to the
latest available I-O table.
  We  multiplied  this  figure  by  the  additional  GDP  due  to  induced  effects  in  €m  to  obtain  an
estimate of the number of additional jobs created due to induced effects.
3.3.2  Results
After  accounting  for  induced  effects  we  find  that  2,870  new  jobs  would  be  created  in  the  EU  as  a
result  of  the  €100m  investment  in  the  defence  sector.    This  equates  to  a  multiplier  of  28.7,  which
means that each €1m invested would create 28.7 jobs.
The results of the Member State level analysis are shown in the table below.

10   It is important to distinguish between additional employment and jobs created.  An increase in employment
opportunities  would  almost  always  be  higher  than  the  actual  increase  in  employment,  as  those  that  fill  the
new jobs might leave another job to do so.  Such ‘displacement effects’ depend on several factors, including
the level of unemployment, the mix of skills and so on.  Estimating these effects is beyond the scope of the
project, and hence they are not taken into account here.
- 16 -

Macroeconomic Impacts
Table 3.4: Employment effects and multipliers by Member State (including induced effects)
Member
No. of domestic
No. of jobs created (incl.
Employment multiplier (no.
State
workers per €m GDP
induced effects)
of new jobs per €m
investment) (incl. induced
effects)
AT
14.5
5.5
7.0
BE
14.0
5.3
6.4
BG
Table not available
Table not available
Table not available
CY
Table not available
Table not available
Table not available
CZ
34.7
22.4
26.0
EE
54.3
4.9
23.1
FI
14.3
26.3
14.1
FR
13.6
447
17.8
DE
15.6
237
13.8
EL
19.8
49.6
12.5
HU
36.8
5.9
16.4
IE
12.0
1.0
5.1
IT
15.7
151
21.9
LV
160
Employment data insufficient
Employment data insufficient
LT
70.3
Employment data insufficient
Employment data insufficient
LU
Table not usable
Table not usable
Table not usable
MT
Table not available
Table not available
Table not available
NL
15.0
24.8
6.6
PL
57.8
16
51.2
PT
30.2
14.7
20.1
RO
67.0
21.8
44.6
SK
57.6
7.7
23.1
SI
33.0
4.3
20.6
ES
20.9
92.5
18.4
SE
13.0
20.0
8.7
UK
15.5
470.1
18.9
EU-27
17.7
2,870
28.7
Source: Europe Economics’ calculations
Note: LV and LT employment data are missing for several key investment sectors
Note:  LU tables are too sparsely populated – several sectors are restricted
Our  results  show  that  there  is  a  wide  spread  of  employment  multipliers  after  induced  effects  have
been  accounted  for,  reflecting  the  spread  in  labour  productivities  and  GDP  effects.    Somewhat
unsurprisingly, most jobs would be created in the Member States that receive the highest investment,
i.e.  the  UK,  France,  Germany  and  Italy.    There  would  be  a  disproportionately  high  number  of  jobs
created in Poland due to that country’s relatively low labour productivity.
The fact that the EU level multiplier is relatively high does not mean that as a whole EU workers are
unproductive.    Rather,  this  reflects  the  relatively  higher  GDP  impact  at  the  EU  level  due  to  the
incorporation of intra-EU trade.  Moreover, the fact that the EU employment multiplier is smaller than
that of some Member States, despite the EU GDP multiplier being higher than those of all Member
States, is because some Member States have labour productivities that are so low relative to the EU
average that even a relatively small GDP increase can only be achieved by a relatively large addition to
the workforce.
- 17 -

Macroeconomic Impacts
3.4  Skilled employment
3.4.1  Approach
In estimating the impacts on skilled employment, we used data from the EU Labour Force Survey (LFS)
on highest levels of education in conjunction with our results on total employment.  Our methodology
for direct and indirect effects was:
  define skilled employment;
  calculate the percentage of skilled workers in each sector; and
  apply these percentages to the total increases in employment calculated in the previous section.
For  induced  effects,  a  similar  methodology  was  followed  with  percentages  being  calculated  at  the
Member State and the EU level, and applied to our estimates of induced employment impacts.
Regarding  the  first  step  of  our  methodology,  we  defined  skilled  employment  as  employment  that
requires  at  least  a  tertiary  qualification.    This  coincides  with  levels  five  and  six  in  the  ISCED  1997
classification.11  We then assumed, for simplicity, that skilled jobs are filled by skilled workers only (i.e.
those with tertiary education) and non-skilled jobs are filled by non-skilled workers only.  Then, the
proportion of skilled jobs would simply be the proportion of workers with education levels five or six.
The second step of our methodology was more problematic because data on education levels attained
by sector are not readily available.  Even for Member States with abundant data availability, such as the
UK,  a  cross-tabulation  of  education  levels  and  economic  sectors  is  not  available  at  a  sufficiently
granular  level.    Moreover,  although  organisations  such  as  CEDEFOP  regularly  publish  material
regarding skill levels in Europe, they do so based on EU Labour Force Survey (EU-LFS) micro-data, and
a skills level breakdown by I-O sector is not available from CEDEFOP publications.  We are aware that
the EU-LFS micro-data set contains, for each observation, the highest level of education according to
the ISCED 1997 classification as well as the economic activity according to NACE codes.  However,
access to the EU-LFS micro-data is severely limited.12
Given these constraints, it was necessary to adopt the following (second-best) approach based on a
simple  economic  model.13    We  assumed  that  (i)  there  are  only  two  types  of  workers  –  skilled  and
unskilled  –  each  with  a  given  level  of  productivity;  and  (ii)  workers  earn  wages  in  proportion  to
productivity.  In such a setup, we can show that productivity at a national level is given by the average
of productivities of skilled and unskilled workers, weighted by the proportion of skilled and unskilled
workers.
To calibrate the model we gathered the following data:
  Eurostat data on value added per worker in the year of the latest I-O table.
  EU-LFS  data  on  the  proportion  of  workers  with  tertiary  education  in  the  economy,  i.e.  the
proportion of skilled workers.

11   The International Standard Classification of Education (ISCED) was designed by UNESCO in the early 1970s.
For the 1997 classification of education levels, see
http://www.unesco.org/education/information/nfsunesco/doc/isced_1997.htm .
12   According to Eurostat, “Access is in principle restricted to universities, research institutes, national statistical
institutes,  central  banks  inside  the  EU  and  EEA  countries,  as  well  as  to  the  European  Central  Bank”.  If  an
exception  cannot  be  made,  then  a  formal  application  procedure  would  take  6  months,  which  would  mean
that the data would not be available in time for the completion of the project.  See
  http://epp.eurostat.ec.europa.eu/portal/page/portal/microdata/documents/EN-LFS-MICRODATA.pdf
13   The model is described in technical detail in Appendix 3.
- 18 -

Macroeconomic Impacts
  Eurostat  data  on  income  distribution,  which  shows  the  average  income  earned  by  those  with
various levels of education.  By assumption, in our model incomes are in proportion with value
added  per  worker.    Combined  with  data  from  the  EU-LFS  on  the  number  of  workers  at  each
education level, this gave us the relative productivity level of skilled and unskilled workers.
Using these data, and the fact that national productivity is a weighted average of skilled and unskilled
productivities in our model, we calculated the absolute levels of skilled and unskilled productivity for
each Member State.
We estimated the proportions of highly skilled workers in each  sector that are consistent with the
sector level productivity (as calculated when analysing employment impacts) while keeping the absolute
levels of skilled and unskilled productivity levels constant.  The main drawback of this method is the
assumption that there are two groups of homogeneous workers, implying two levels of productivity
and  two  levels  of  income.    In  reality,  we  know  that  there  is  a  wide  spread  of  productivities  across
sectors, and even within sectors.
Moreover, the share of wages in total value added per worker in a capital-intensive industry might be
smaller than that in a labour-intensive industry.  It is therefore not surprising that our analysis resulted
in  numerous  cases  where  actual  sector  productivity  was  below  the  calculated  unskilled  worker
productivity, or above the calculated skilled worker productivity.  In such cases, we assumed that the
sector  comprised  entirely  unskilled  and  skilled  workers,  respectively.    Given  the  abundance  of  such
cases, the estimates should be viewed with caution.14
Skilled and unskilled productivities derived from this model are shown in the table below.

14   More precise estimates for direct and indirect effects could be obtained with access to the EU-LFS micro-
data.    This  problem  does  not  apply  to  our  estimates  of  induced  effects  because  the  actual  proportions  of
skilled workers are easily and reliably available at the national and EU level.
- 19 -

Macroeconomic Impacts
Table 3.5: Estimates of skilled and unskilled productivities
Member
Proportion of
National
Derived skilled
Derived unskilled
State
skilled workers
productivity (€ per
productivity (€ per
productivity (€ per
worker)
worker)
worker))
AT
18.2%
69,100
86,300
65,300
BE
36.8%
71,600
86,900
62,700
BG
Table not available
Table not available
Table not available
Table not available
CY
Table not available
Table not available
Table not available
Table not available
CZ
17.1%
28,800
38,800
26,800
EE
35.9%
18,400
23,000
15,900
FI
37.9%
70,100
86,100
60,400
FR
32.4%
73,500
92,500
64,500
DE
26.2%
64,200
79,000
58,900
EL
27.6%
50,600
71,500
42,700
HU
23.1%
27,200
36,600
24,400
IE
40.7%
83,600
102,000
71,100
IT
14.7%
63,700
95,500
58,200
LV
19.2%
6,260
1998 data not available  1998 data not available
LT
30.5%
14,200
20,600
11,400
LU
Table not usable
Table not usable
Table not usable
Table not usable
MT
Table not available
Table not available
Table not available
Table not available
NL
32.3%
66,700
81,800
59,500
PL
21.4%
17,300
27,000
14,700
PT
15.2%
33,100
60,700
28,100
RO
14.8%
14,900
27,800
12,700
SK
16.5%
17,400
21,900
16,500
SI
21.7%
30,300
42,700
26,800
ES
32.2%
47,900
63,000
40,800
SE
33.8%
77,000
87,600
71,600
UK
30.7%
64,400
82,300
56,500
EU-27
26.9%
56,400
77,000
48,800
Source: Europe Economics’ calculations
Note:  LV I-O table is for the year 1998, but productivity data are not available for that year
Note:  LU tables are too sparsely populated – several sectors are restricted
3.4.2  Results
Including induced effects, 761 skilled jobs would be created across the EU, representing 26.5 per cent
of all jobs.  This is consistent with a multiplier of 7.61, i.e. each €1m investment in EU defence would
create approximately eight skilled jobs.  The results of the Member State level analysis are shown in
the table below.15

15  These  estimates  should  be  treated  with  some  caution,  given  that  we  have  followed  a  second-best
methodology in absence of access to micro-data.  The necessity for such caution is indicated by the fact that
our model suggests that several sectors are composed only of skilled or unskilled labour, which is unlikely to
be supported by evidence.  While these are the best estimates that may be calculated given the data available,
they are likely to be less accurate than, for instance, the results on total employment.
- 20 -

Macroeconomic Impacts
Table 3.6: Skilled employment effects and multipliers by Member State (including induced effects)
Member  No. of skilled jobs created
No. of skilled jobs created
Skilled employment
State
(incl. induced effects)
as a proportion of total
multiplier (no. of new
jobs created
skilled jobs per €m
investment) (incl. induced
effects)
AT
1.4
25.4%
1.8
BE
0.8
14.1%
0.9
BG
Table not available
Table not available
Table not available
CY
Table not available
Table not available
Table not available
CZ
2.9
12.9%
3.4
EE
0.7
14.1%
3.3
FI
6.6
25.1%
3.5
FR
144
32.1%
5.7
DE
42.0
17.8%
2.4
EL
9.9
20.0%
2.5
HU
0.7
12.2%
2.0
IE
0.2
15.6%
0.8
IT
18.4
12.2%
2.7
LV
Employment data insufficient
Employment data insufficient
Employment data insufficient
LT
Employment data insufficient
Employment data insufficient
Employment data insufficient
LU
Table not usable
Table not usable
Table not usable
MT
Table not available
Table not available
Table not available
NL
5.1
20.5%
1.4
PL
37.3
23.2%
11.9
PT
1.9
12.9%
2.6
RO
4.1
19.0%
8.5
SK
1.6
21.1%
4.9
SI
0.7
17.1%
3.5
ES
22.9
24.7%
4.6
SE
3.5
17.3%
1.5
UK
135
28.8%
5.4
EU-27
761
26.5%
7.6
Source: Europe Economics’ calculations
Note: LV and LT employment data are missing for several key investment sectors
Note:  LU tables are too sparsely populated – several sectors are restricted
Our results suggest that the greatest numbers of jobs are created in those Member States receiving
the highest investment, and in Poland.  Only Poland and Romania have higher multipliers than the EU-
wide figure, owing to relatively low productivity rates.
3.5  R&D
3.5.1  Approach
The direct and indirect additions to value added in the R&D sector were calculated during the process
of  estimating  GDP  impacts  (where  the  GDP  impacts  in  each  sector  were  estimated).    In  order  to
include induced effects, we first calculated the percentage of national value added accounted for by the
R&D  sector  and  then  applied  this  percentage  to  the  additional  GDP  due  to  induced  effects  in  each
Member State and the EU.
3.5.2  Results
Upon including induced effects, R&D value added would increase by €11.14m.  Member State specific
results are shown in the table below.
- 21 -

Macroeconomic Impacts
Table 3.7: R&D effects and multipliers by Member State (including induced effects)
Member  Share of R&D in total value
Addition to R&D value
R&D multiplier (addition
State
added (%)
added (€’000) (incl.
to R&D value added in €
induced effects)
per €1,000 investment)
(incl. induced effects)
AT
0.5
4.6
5.8
BE
0.7
9.1
10.9
BG
Table not available
Table not available
Table not available
CY
Table not available
Table not available
Table not available
CZ
0.4
20.9
24.3
EE
0.4
1.3
6.2
FI
0.6
31.2
16.8
FR
0.9
3,300
131
DE
0.5
1,240
72.1
EL
0.1
6.0
1.5
HU
0.5
1.9
5.3
IE
0.3
0.1
0.5
IT
0.8
233
33.9
LV
0.3
0.2
2.0
LT
0.0
0.0
0.1
LU
Table not usable
Table not usable
Table not usable
MT
Table not available
Table not available
Table not available
NL
0.4
68.4
18.1
PL
0.4
123
39.1
PT
0.3
11.4
15.6
RO
0.3
4.3
8.7
SK
0.2
3.0
9.1
SI
0.7
15.1
72.3
ES
0.4
292
58.1
SE
1.1
121
52.7
UK
0.5
2,920
117
EU-27
0.6
11,100
111
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
The bulk of the EU increase in R&D value added would be concentrated in three Member States  –
France, the UK and Germany.  This is both because most R&D investment would take place in these
States, and because these States have large and well-developed defence research establishments.  This
is confirmed by the fact that these three States have three of the four highest national multipliers.
The wide spread in national multipliers arises from the fact that several countries do not spend large
portions of their defence spend on R&D.
3.6  Exports
3.6.1  Approach
Since exports are an exogenous final use in the I-O framework they are invariant to changes in other
variables,  and  so  it  is  impossible  to  calculate  the  effects  of  the  investment  on  exports  though  I-O
analysis.    We  have  therefore  employed  an  alternative  approach  involving  econometric  analysis  of
macroeconomic data to determine the relationship between defence exports and defence expenditure.
3.6.1.1  Data
We procured the following data for 81 countries for the years 2000-11.
- 22 -

Macroeconomic Impacts
  Defence export data in $m in 1990 prices from the Arms Trade database.16  For some of these
years, data were missing for several countries.
  Defence  expenditure  data  in  $m  in  2010  prices  from  the  SIPRI  Military  Expenditure  Database
2011.17  Again, data were missing for some countries for some of these years.
  GDP data in $ in 2005 prices from the National Accounts Estimates of Main Aggregates, United
Nations Statistics Division.18  Here, data were available for all countries in all years.
The 81 countries included in our master sample are shown in the table below.
Table 3.8: Countries in master sample for export analysis
EU Member States
Others
Austria
Lithuania
Albania
China
Jordan
Oman
Thailand
Belgium
Luxembourg
Angola
Colombia
Kazakhstan
Pakistan
Turkey
Bulgaria
Malta
Argentina
Costa Rica
Korea, South
Peru
UAE
Czech Rep.
Netherlands
Australia
Croatia
Kyrgyzstan
Philippines
Ukraine
Denmark
Poland
Bahrain
Eritrea
Lebanon
Qatar
Uruguay
Finland
Portugal
Belarus
Georgia
Libya
Russia
Uzbekistan
France
Romania
Bosnia-Herz.
Ghana
Malawi
Saudi Arabia
Venezuela
Germany
Slovakia
Brazil
India
Malaysia
Serbia
Viet Nam
Greece
Spain
Brunei
Indonesia
Moldova
Singapore
Zimbabwe
Hungary
Sweden
Cambodia
Iran
Montenegro
South Africa
USA
Ireland
UK
Canada
Israel
New Zealand
Switzerland

Italy

Chile
Japan
Norway
Syria

Data  on  defence  exports  were  not  available  within  the  EU  for  Cyprus,  Estonia,  Latvia  or  Slovenia,
hence it was impossible to include them within our sample.
3.6.1.2  Methodology
Our methodology centred on trying to establish a relationship between defence spending and defence
exports, and then to use this relationship to determine the effect on exports of a €100m increase in
defence expenditure.  To do this, we used multiple regression analysis19 to determine the effects of an
increase  in  defence  expenditure  on  defence  exports,  controlling  for  the  effects  of  GDP  on  defence
exports.
The  first  step  in  our  approach  was  to  convert  the  three  data  series  (defence  exports,  defence
expenditure and GDP) into a common unit with the same base year.  To do this, we converted the
GDP figures from $ to $m, and converted defence exports and defence expenditure figures into 2005
prices using price deflator data.
Given that our dataset was in the form of a panel,20 we employed random effects panel data models.
Panel  data  models  exploit  variations  both  across  individual  countries  as  well  as  within  the  same

16   http://armstrade.sipri.org/armstrade/page/toplist.php
17   http://milexdata.sipri.org.
18 http://data.un.org/Data.aspx?q=gdp+at+constant+price&d=SNAAMA&f=grID%3a102%3bcurrID%3aUSD%3bp
cFlag%3a0
19   Multiple regression analysis is a statistical technique aimed at finding the effects of changes in independent or
explanatory variables on dependent variables, controlling for changes in other variables that might affect the
dependent variable.  The goal is to discover underlying relationships between variables which are consistent
with the observed data.  For an overview of multiple regression analysis, see any textbook on econometric
analysis (e.g. Greene, William H. (2003) Econometric Analysis, 5th Edition, New Jersey: Prentice Hall).
20   In econometric terminology, a dataset is in panel form when there it involves both a cross-sectional as well as
a  time  component.    Here,  the  cross-sectional  component  was  fulfilled  by  the  81  countries,  and  the  time
- 23 -

Macroeconomic Impacts
country over time to uncover underlying relationships that would have given rise to the data.  The use
of panel data models specifically allows country-specific effects to be taken into account.
Choosing  the  correct  sample  is  of  the  utmost  importance,  as  an  implicit  assumption  in  running  a
regression is that the underlying relationships between variables are the same across the entire sample
(unless specifically modelled otherwise).  We constructed three samples, and all our regressions were
run over these three samples.
  all 81 countries in the master sample;
  the 23 EU Member States in the master sample; and
  the 22 EDA participating Member States in the master sample.
It  was  impossible  to  conduct  analysis  at  the  individual  Member  State  level  due  to  the  fact  that  the
maximum  number  of  data  points  for  any  one  country  was  12,  which  is  not  enough  for  reliable
econometric analysis.
All our regressions had the following basic form:
Table 3.9: Basic form of regressions for export effect analysis
Dependent variable
Explanatory variables
Control variables
Defence exports
Defence expenditure
GDP
Square of defence expenditure
Square of GDP

The inclusion of squared terms aimed to allow for non-linearities in the relationships.  While the basic
form of the regressions remained the same, we investigated five different models, depending on how
the terms were defined.
  Absolute levels:  all the variables were defined as absolute levels.
  First differences:  here all the variables were defined as the difference between the absolute levels
of  this  period  and  the  previous  period.    First  differencing  is  beneficial  in  that  it  removes  any
systematic error that is constant within a country.
  Logarithms:  all variables were defined as logarithms of absolute levels.  This is consistent with a
multiplicative relationship between variables rather than the additive relationship consistent with
the absolute levels and first differences models.
  Growth  rate:    all  variables  were  defined  as  growth  rates  of  absolute  levels  over  the  previous
period’s absolute levels.  This is almost exactly equal to first differencing logarithms, which is how
the  calculations  were  done  in  the  modelling  exercise.    Due  to  first  differencing,  any  country-
specific systematic errors would be removed.
  Arellano-Bond:  this is a more sophisticated model, where a lag of the dependent variable is also
included as an explanatory variable.  We applied the Arellano-Bond framework to the growth rate
model,  so  that  the  growth  rate  of  defence  exports  could  potentially  depend  not  only  on  the
growth rates of defence expenditure and GDP (and their squares), but also on the growth rate of
the previous year.  This framework allows for the introduction of dynamism, i.e. causal links across
time.
In order to evaluate which models were to be chosen for the final analysis,  we relied on two main
tests.
  Normality of residuals.  An important assumption of all the models we used was that the random
errors  associated  with  each  observation,  i.e.  the  part  of  the  variation  in  defence  exports  that

component was fulfilled by the fact that each country had data for up to 12 years.  Random effects models
allow for each country to have its own idiosyncratic effect on the dependent variable.
- 24 -

Macroeconomic Impacts
cannot be explained by variations in defence expenditure or GDP, are distributed according to the
normal distribution.21  In order to test whether the residual variations in defence exports (after
accounting for the part consistent with the relationships uncovered through the regression) were
normally distributed, we plotted the distribution of the residuals and visually compared this to the
normal distribution.
  Specification of functional form.  To test whether the functional form of the model was correct
(i.e. multiplicative vs. linear, omission of non-linear terms), we relied on the Ramsey RESET test.22
3.6.2  Results
We found that the absolute levels, first differences and logarithms models were inconsistent with the
normality of  residuals  assumption  (though the  residuals  were  closer  to  normal  for the EU  and  pMS
sub-samples),  and  so  these  were  discarded  outright.    This  left  the  growth  rate  and  Arellano-Bond
models.  The growth rate model showed residuals close to normal for all three sub-samples, and the
Ramsey  RESET  test  indicated  that  the  functional  specification  was  also  correct.    The  Arellano-Bond
model also showed residuals close to normal, although the deviation from normal was higher than for
the growth models.  Moreover, the Arellano-Bond model passed the RESET test only for the EU and
pMS  sub-samples.23    However,  the  additional  explanatory  variable,  i.e.  lagged  export  growth  rate,
turned out to be a strongly significant determinant of current export growth rate, and so this model
was chosen as the central model for results.24
At the EU level, the Arellano-Bond model suggests that a one percentage point increase in the growth
rate of defence expenditure is associated with a 4.07 percentage point increase in the growth rate of
defence exports.  Applied to 2005 growth rates (since this is the base year for the export analysis), a
€100m increase in defence expenditure is associated with a €16.61m increase in defence exports.  The
magnitude of the increase in exports would be different when the relationship is applied to data for
different years.
The results of the growth rate model at the EU level suggested that a one percentage point increase in
the  growth  rate  of  defence  expenditure  is  associated  with  a  2.67  percentage  point  increase  in  the
growth rate of defence exports.  This corresponds to a €10.87m increase in defence exports applied
to  2005  figures.    However,  the  result  of  the  growth  rate  model  was  weaker,  in  that  it  was  not

21   The normal distribution is a  special distribution where a  majority of observations  are  in the vicinity of the
mean, and the frequency of observations deviating from the mean reduces as the deviations become larger.
The normal distribution is very commonly used in statistics and econometrics because of its abundance in the
real world, and the fact that it has several attractive statistical properties.
22   Ramsey,  J.B.  (1969)  ‘Tests  for  Specification  Errors  in  Classical  Linear  Least  Squares  Regression  Analysis’
Journal of the Royal Statistical Society, Series B., Vol 31, No 2, p350–371.
23   These two would also not have passed if we chose a tighter significance level for the test.
24   A few caveats to these results need to be outlined:
i)  The analysis does not differentiate between intra-EU and extra-EU exports – it is impossible to do so without
a breakdown of exports between intra- and extra-EU for each country in each time period.
ii)  This  analysis  is  unable  to  distinguish  between  the  various  types  of  defence  expenditure,  and  as  such  the
implicit assumption is that either (i) the relationship with defence exports holds true for all kinds of defence
expenditure, and / or (ii) the investment occurs in the same pattern as defence expenditure in general (i.e.
including operations and maintenance and other defence expenditure heads).
iii)  Our  results  should  be  read  as  support  for  correlation,  not  causation.    While  it  is  possible  to  uncover  the
relationships between different sets of variables through multiple regression analysis, it is much more difficult
to  establish  the  direction  of  causation.    In  most  cases,  the  direction  of  causation  comes  from  economic
theory or other logic.
- 25 -

Macroeconomic Impacts
significant  at  the  five  per  cent  level  (but  only  at  the  10  per  cent  level),  whereas  the  result  of  the
Arellano-Bond model was significant at the five per cent level.25
Results for the pMS sub-sample were very similar to those for the EU-sub sample.
3.7  Capital intensity
3.7.1  Approach
To  estimate  the  impact  on  capital  intensity,  we  derived  the  additional  fixed  capital  that  would  be
required to sustain output increases consistent with those derived in the GDP impacts section.  To do
this, we relied on data on the consumption of fixed capital (CFC) in the I-O tables.
To calculate direct and indirect effects, we first calculated, for each sector, the percentage of output
that was accounted for by CFC by dividing the CFC figure by total output.  We then multiplied this
figure  in  each  sector  with  the  corresponding  direct  and  indirect  output  increase  as  a  result  of  the
additional investment.
To calculate induced effects we calculated the proportion of national and EU GDP accounted for by
CFC, and multiplied the increase in GDP as a result of induced effects with these percentages for each
Member State and the EU.
3.7.2  Results
After including induced effects, the addition to consumption of fixed capital would be €22.39m.  This is
consistent with a multiplier of 223.88, i.e. a €1,000 investment in European defence would lead to an
increase in the consumption of fixed capital by €223.88.
The results of the Member State level analysis are shown in the table below.

25   The  level  of  significance  here  refers  to  the  probability incorrectly  rejecting  the  hypothesis that  there  is no
association  between  the  growth  rates  of  defence  expenditure  and  defence  export.    A  lower  level  of
significance makes rejecting the hypothesis harder.
- 26 -

Macroeconomic Impacts
Table 3.10: Capital intensity effects and multipliers by Member State (including induced effects)
Member
CFC as a proportion of
Addition to consumption
Capital intensity multiplier
State
national GDP
of fixed capital (€000) (incl.
(addition to consumption
induced effects)
of fixed capital in € per
€1,000 investment) (incl.
induced effects)
AT
16.9%
48.5
61.2
BE
17.7%
46.4
55.8
BG
Table not available
Table not available
Table not available
CY
Table not available
Table not available
Table not available
CZ
21.1%
93.9
109
EE
13.9%
7.2
34.4
FI
19.5%
274
147
FR
CFC data not available
CFC data not available
CFC data not available
DE
CFC data not available
CFC data not available
CFC data not available
EL
18.3%
367.2
92.1
HU
17.4%
14.6
40.6
IE
11.6%
6.6
32.2
IT
17.2%
1,500
219
LV
14.9%
8.2
69.7
LT
13.0%
5.9
50.9
LU
Table not usable
Table not usable
Table not usable
MT
Table not available
Table not available
Table not available
NL
17.2%
200
53.1
PL
14.7%
380
121
PT
19.9%
69.3
94.6
RO
CFC data not available
CFC data not available
CFC data not available
SK
21.7%
22.6
67.8
SI
17.7%
16.5
78.8
ES
CFC data not available
CFC data not available
CFC data not available
SE
15.3%
205
89.5
UK
CFC data not available
CFC data not available
CFC data not available
EU-27
15.6%
22,300
224
Source: Europe Economics’ calculations
Note:  IT I-O table provides aggregate CFC figure; estimates constructed by applying percentage to total GDP effects
Note:  LU tables are too sparsely populated – several sectors are restricted
Several Member States do not publish data on the consumption of fixed capital in their input-output
tables,  including  the  five  biggest  recipients  of  the  hypothetical  defence  investment.    Therefore,  the
value of a Member State level analysis is limited in this case.
However, Italy publishes aggregate consumption of fixed capital even as it does not publish sector-wise
consumption of fixed capital.  This allowed us to construct an estimate for Italy by first calculating the
percentage of GDP attributable to the consumption of fixed capital, and then applying this percentage
to the total increase in GDP (including induced effects) in Italy.  The resultant estimate places Italy’s
multiplier  a  long  way  above  the  next  best  (Finland).    The  variation  in  multipliers  in  general  has
increased upon taking induced effects into account, due to the varying importance of the consumption
of fixed capital in GDP and the varying magnitudes of induced GDP increases.
3.8  Impacts at a sectoral level
All the impacts presented in this section are at the Member State or EU level.  The I-O framework
allows us to calculate direct and indirect effects by I-O sector.  The tables describing these results are
extremely detailed and so are not included in this report.  However, we would be pleased to provide
these results on request.
- 27 -

Macroeconomic Impacts
3.9  Sensitivity analysis
We tested the sensitivity of our results to two kinds of variation – by countries of investment and by
sectors of investment.
3.9.1  Geographic scenarios
We considered six scenarios in the geographic sensitivity analysis, each relating to a different set of
Member States over which the €100m investment would be divided.  These are:
  all Member States;
  UK and FR;
  LOI (DE, ES, FR, IT, SE, UK);
  LOI plus CZ, PL, NL;
  LOI plus Visegrad; and
  Visegrad (PL, CZ, HU, SK).
We followed the methodologies described above for calculating the effects in each scenario.  The key
point  to  note  is  that  the  distribution  across  sectors  in  each  case  was  based  on  the  actual  relative
defence spending of only the set of Member States receiving investment in each scenario.
The main EU-level multipliers for each scenario are given in the table below.
Table 3.11: Main multipliers in various geographic scenarios
Scenario
GDP
Employ-
Skilled
Total tax
R&D
Capital
ment
employ-
intensity
ment
All
1.6
28.7
7.6
0.4
111.4
223.9
UK and FR
1.6
28.2
8.1
0.4
158.6
221.6
LOI (DE, ES, FR, IT, SE, UK)
1.6
28.5
7.8
0.4
128.5
223.1
LOI plus CZ, PL, NL
1.6
28.6
7.7
0.4
121.4
223.5
LOI plus Visegrad
1.6
28.6
7.7
0.4
123.9
223.4
Visegrad (PL, CZ, HU, SK)
1.6
29.4
6.8
0.4
44.2
228.6
Source: Europe Economics’ calculations
The main observations are as follows.
  GDP multipliers are similar across all scenarios.
  Employment multipliers are also fairly similar, but slightly higher in scenarios where investment is
concentrated in geographic areas with relatively lower labour productivities.
  Skilled employment multipliers are higher in scenarios where investment is concentrated in areas
with higher labour productivities.
  Total tax multipliers are similar across all scenarios.
  R&D  multipliers  are  highest  when  investment  is  concentrated  in  areas  with  historically  large
investment in defence R&D.  The multiplier for the Visegrad scenario is substantially lower than all
other scenarios, highlighting the LOI countries’ importance as centres for defence R&D.
  Capital  intensity  multipliers  are  similar,  but  show  a  small  tendency  to  increase  as  investment  is
shifted to lesser-developed Member States.
- 28 -

Macroeconomic Impacts
3.9.2  Sectoral scenarios
We  considered  three  scenarios  in  the  sectoral  sensitivity  analysis  where  the  scenarios  differed  in
terms of the defence sectors to which the investment was allocated.  These are
  all;
  weapons and ammunition; and
  construction.
Again, we followed the same methodology as earlier, but divided investment in proportion to historical
defence spending of only the sectors receiving investment.  For all these scenarios, we assumed that
the geographic scenario ‘all’ applied, i.e. the geographic scope of investment was not restricted.
The main EU-level multipliers for each scenario are given in the table below.
Table 3.12: Main multipliers in various geographic scenarios
Scenario
GDP
Employ-
Skilled
Total tax
R&D
Capital
ment
employ-
intensity
ment
All
1.6
28.7
7.6
0.4
111
224
Weapons and ammunition
1.6
29.8
6.4
0.4
8.0
235
Construction
1.6
30.4
5.6
0.4
6.2
247
Source: Europe Economics’ calculations
The main observations are as follows.
  GDP  multipliers  are  slightly  higher  for  weapons  and  ammunition  and  construction,  but  the
difference is negligible.
  Employment multipliers are also higher when the two sectoral restrictions apply.
  However, skilled employment multipliers fall as employment multipliers rise.
  Total tax multipliers are similar across scenarios.
  R&D  multipliers  are  a  lot  lower  for  the  two  sectoral  restrictions.    This  is  mainly  due  to  the
complete absence of direct effects in the scenarios with sectoral restrictions.
  Capital intensity multipliers are also higher for the two sectoral restrictions.
- 29 -

Comparison with Other Sectors
4  Comparison with Other Sectors
Comparisons  across  sectors  were  carried  out  by  calculating  the  various  multipliers  for  three  other
sectors with high levels of public spending, and comparing these to defence. The three sectors chosen
were:
  transport  services,  particularly  land  transport,  as  public  subsidies  in  the  transport  sector  are
focused mainly on bus and rail;
  public health services; and
  education services.
Each of these areas either corresponds directly, or is a subset of, a single I-O sector in both the NACE
Rev. 1.1 and NACE Rev. 2 classification systems.  The methodology used was as follows.
  For  each  type  of  impact, we  calculated  the  increase  that  would  result  from  a  €1  investment  in
every sector.26  This corresponds to the multiplier covering only direct and indirect effects.
  To  incorporate  induced  effects,  we  employed  the  same  methodology  used  to  calculate  induced
effects for each type of macroeconomic effect.
  The comparisons were completed for each Member State and for the EU as a whole.
4.1  GDP
At the EU level, the GDP multiplier is almost equal across the four sectors, lying between 1.53 and
1.59.  Defence has a slightly higher multiplier than transport, a slightly lower multiplier than education
and the same as health.  The results by Member State are shown below.

26   For a technical account of how such multipliers are calculated, see Appendix 2.
- 30 -

Comparison with Other Sectors
Table 4.1: GDP multiplier comparison by Member State
Member
Transport (land
State
transport services)
Education
Health
Defence
AT
0.75
1.16
1.05
0.45
BE
0.58
0.96
0.83
0.35
BG
No tables available
No tables available
No tables available
No tables available
CY
No tables available
No tables available
No tables available
No tables available
CZ
1.02
1.23
1.06
0.67
EE
0.54
0.81
0.71
0.37
FI
1.41
1.59
1.54
0.88
FR
1.85
2.10
2.02
1.28
DE
1.07
1.39
1.34
0.79
EL
1.91
2.69
2.25
0.52
HU
0.67
0.92
0.80
0.38
IE
0.75
1.03
1.05
0.28
IT
1.76
2.13
1.93
1.27
LV
0.88
1.14
0.99
0.61
LT
1.01
1.13
1.02
0.48
LU
Tables unusable
Tables unusable
Tables unusable
Tables unusable
MT
No tables available
No tables available
No tables available
No tables available
NL
0.91
1.11
1.04
0.43
PL
1.23
1.67
1.55
0.87
PT
1.24
1.79
1.54
0.56
RO
1.29
1.40
1.18
0.66
SK
0.61
0.87
0.75
0.40
SI
0.70
1.03
0.94
0.54
ES
1.34
1.79
1.62
0.84
SE
0.97
1.29
1.26
0.65
UK
1.80
2.04
1.87
1.17
EU-27
1.53
1.59
1.56
1.56
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
In  general,  there  is  a  very  clear  ranking  at  Member  State  level,  with  education  having  the  highest
multiplier, followed by health, transport and defence.  The differences between sectors are substantial.
However, not too much should be read into this as the four sectors have varying degrees of ‘rest of
the  world  leakages’,  i.e.  the  proportion  of  value  added  in  each  of  these  sectors  domestically  varies
substantially.    In  general,  defence  has  more  linkages  with  the  rest  of  the  world  and,  since  intra-EU
trade is not captured in national multipliers, these multipliers are bound to be lower.
It  is  also  worth  noting  that  the  multipliers  differ  between  Member  States  that  are  economically
comparable (e.g. the Baltic states).  As per the discussion of GDP effects in Chapter 3, the explanation
for  this  is  differences  in  savings  and  import  rates.    For  example,  Estonia  has  historically  had  both  a
higher saving rate and higher import rate than Latvia and Lithuania.  Both of these factors mean that
the  income  multiplier  for  Estonia  is  lower  than  that  of  the  other  Baltic  states  and  hence  its  GDP
multipliers are also lower.
4.2  Tax revenue
At  the  EU  level,  the  total  tax  receipts  (excluding  social  contributions)  multiplier  is  nearly  identical
across  the  four  sectors,  lying  between  0.41  and  0.43.    Defence  has  a  slightly  higher  multiplier  than
transport, a slightly lower multiplier than education and the same as health.  The results by Member
State are shown below.
- 31 -

Comparison with Other Sectors
Table  4.2:    Total  tax  revenue  (excluding  social  contributions)  multiplier  comparison  by  Member
State
Member
Transport (land
State
transport services)
Education
Health
Defence
AT
0.21
0.33
0.30
0.13
BE
0.18
0.30
0.26
0.11
BG
No tables available
No tables available
No tables available
No tables available
CY
No tables available
No tables available
No tables available
No tables available
CZ
0.19
0.23
0.20
0.12
EE
0.11
0.16
0.15
0.08
FI
0.42
0.48
0.46
0.26
FR
0.47
0.54
0.52
0.33
DE
0.25
0.33
0.32
0.19
EL
0.39
0.55
0.46
0.11
HU
0.18
0.25
0.21
0.10
IE
0.17
0.23
0.24
0.06
IT
0.49
0.59
0.53
0.35
LV
0.20
0.26
0.22
0.14
LT
0.21
0.23
0.21
0.10
LU
Tables unusable
Tables unusable
Tables unusable
Tables unusable
MT
No tables available
No tables available
No tables available
No tables available
NL
0.22
0.27
0.25
0.10
PL
0.26
0.35
0.32
0.18
PT
0.30
0.43
0.37
0.13
RO
0.24
0.26
0.22
0.12
SK
0.11
0.16
0.14
0.08
SI
0.17
0.25
0.23
0.13
ES
0.32
0.43
0.39
0.20
SE
0.36
0.48
0.47
0.24
UK
0.52
0.59
0.54
0.34
EU-27
0.41
0.43
0.42
0.42
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
Again,  there  is  a  very  clear  ranking  at  the  Member  State  level,  with  education  having  the  highest
multiplier, followed by health, transport and defence.  The differences between sectors are substantial.
Again, not too much should be read into this, as these multipliers depend directly on the GDP effects,
which are sensitive to the extent of ‘rest of the world leakages’.
4.3  Employment
Investments in the defence sector have employment effects that are comparable to those in transport
and health.  The results by Member State are shown below.
- 32 -

Comparison with Other Sectors
Table 4.3: Employment multiplier comparison by Member State
Member
Transport (land
State
transport services)
Education
Health
Defence
AT
10.83
19.43
19.33
6.99
BE
11.11
21.64
20.23
6.42
BG
No tables available
No tables available
No tables available
No tables available
CY
No tables available
No tables available
No tables available
No tables available
CZ
40.74
57.27
46.34
26.00
EE
33.92
92.13
77.27
23.12
FI
23.38
27.58
27.68
14.13
FR
27.61
32.41
31.13
17.83
DE
16.65
28.86
26.85
13.75
EL
45.67
61.95
47.53
12.45
HU
34.08
59.73
44.97
16.41
IE
15.96
17.29
12.04
5.08
IT
26.67
40.18
33.88
21.92
LV
Employment data
Employment data
Employment data
Employment data
insufficient
insufficient
insufficient
insufficient
LT
Employment data
Employment data
Employment data
Employment data
insufficient
insufficient
insufficient
insufficient
LU
Tables unusable
Tables unusable
Tables unusable
Tables unusable
MT
No tables available
No tables available
No tables available
No tables available
NL
14.45
22.29
20.06
6.59
PL
73.12
125.69
117.06
51.17
PT
39.75
58.69
43.79
20.08
RO
67.86
103.22
91.45
44.60
SK
25.80
87.98
74.74
23.13
SI
27.15
50.04
36.69
20.62
ES
15.21
17.96
16.82
18.42
SE
14.30
29.33
21.21
8.72
UK
29.92
39.83
37.88
18.89
EU-27
28.48
36.38
30.91
28.70
Source: Europe Economics’ calculations
Note: LV and LT employment data are missing for several key investment sectors
Note:  LU tables are too sparsely populated – several sectors are restricted
At the Member State level, education almost universally has the highest multiplier.  Moreover, in most
cases the defence multiplier is the smallest by a fair margin; but this is, again, due more to the greater
‘rest of the world leakages’ associated with the sector at a Member State level.
4.4  Skilled employment
At the EU level, defence has the highest skilled employment multiplier.  This is followed by transport,
health  and  education.    It  is  interesting  to  note  that  education  has  the  lowest  skilled  employment
multiplier despite having the highest employment multiplier.  Again, due to the reliance on the second-
best model for estimating skilled employment effects, skilled employment multiplier estimates should
be viewed as less precise than other estimates.
The results by Member State are shown below.
- 33 -

Comparison with Other Sectors
Table 4.4: Employment multiplier comparison by Member State
Member
Transport (land
State
transport services)
Education
Health
Defence
AT
1.22
0.91
1.42
1.78
BE
1.08
0.22
0.92
0.90
BG
No tables available
No tables available
No tables available
No tables available
CY
No tables available
No tables available
No tables available
No tables available
CZ
4.22
2.73
3.27
3.35
EE
3.36
1.45
1.61
3.26
FI
3.93
4.41
4.38
3.54
FR
5.98
5.54
5.52
5.73
DE
4.34
2.23
2.48
2.44
EL
7.89
9.53
9.25
2.48
HU
3.05
1.02
1.95
2.00
IE
1.44
1.05
6.03
0.79
IT
5.57
2.83
2.87
2.68
LV
Employment data
Employment data
Employment data
Employment data
insufficient
insufficient
insufficient
insufficient
LT
Employment data
Employment data
Employment data
Employment data
insufficient
insufficient
insufficient
insufficient
LU
Tables unusable
Tables unusable
Tables unusable
Tables unusable
MT
No tables available
No tables available
No tables available
No tables available
NL
1.58
1.47
1.47
1.35
PL
13.12
11.35
11.64
11.85
PT
3.78
4.34
9.39
2.59
RO
25.80
9.20
10.81
8.49
SK
22.35
1.23
2.95
4.88
SI
2.45
1.91
2.51
3.52
ES
4.24
5.65
5.10
4.55
SE
1.96
2.28
2.13
1.51
UK
6.61
6.36
6.24
5.43
EU-27
5.62
3.85
4.61
7.61
Source: Europe Economics’ calculations
Note: LV and LT employment data are missing for several key investment sectors
Note:  LU tables are too sparsely populated – several sectors are restricted
Among the comparison sectors, the general ranking of transport, health and education is not universal.
This could be due to different employment patterns regarding the proportions of skilled workers in
each sector across Member States, but the imprecision introduced by using the second-best model in
the absence of micro-data would also probably be an important factor.
4.5  R&D
At the EU level, investment in defence has by far the largest R&D multiplier.  The defence multiplier is
between  12  and  20  times  the  multipliers  for  the  comparison  sectors.    This  result  is  not  surprising
because  a  significant  portion  of  investment  in  defence  is  channelled  directly  into  the  R&D  sector
leading to the presence of direct effects, whereas investment in the comparison sectors would only
generate indirect and induced effects.
- 34 -

Comparison with Other Sectors
Table 4.5: R&D multiplier comparison by Member State
Member
Transport (land
State
transport services)
Education
Health
Defence
AT
1.46
1.50
1.44
5.76
BE
0.25
0.16
0.86
10.93
BG
No tables available
No tables available
No tables available
No tables available
CY
No tables available
No tables available
No tables available
No tables available
CZ
1.41
1.21
1.47
24.33
EE
-0.04
1.40
0.38
6.19
FI
3.96
4.73
4.37
16.76
FR
10.00
10.83
11.83
131.40
DE
2.16
4.62
3.35
72.06
EL
1.42
4.40
1.92
1.50
HU
1.61
0.64
1.19
5.27
IE
0.55
0.70
1.47
0.52
IT
9.19
9.02
9.02
33.86
LV
1.20
1.21
1.28
2.01
LT
0.18
1.49
1.10
0.11
LU
Tables unusable
Tables unusable
Tables unusable
Tables unusable
MT
No tables available
No tables available
No tables available
No tables available
NL
0.82
1.60
1.01
18.14
PL
3.36
4.01
3.86
39.14
PT
3.03
3.20
5.74
15.23
RO
3.05
5.20
4.71
8.72
SK
0.25
0.14
0.57
9.07
SI
0.99
1.47
1.56
72.28
ES
3.26
3.71
4.21
58.13
SE
5.37
5.63
5.10
52.71
UK
6.44
7.93
8.55
117.35
EU-27
5.65
5.58
8.73
111.38
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
The EU level result is replicated in magnitude at the Member State level, except for countries which
invest little or nothing in defence R&D (including Greece, Ireland, Latvia, Lithuania and Romania).  The
difference between defence and the other sectors is amplified for Slovenia, perhaps indicating that it
invests significantly in defence R&D but does not have a strong indigenous R&D sectors otherwise.
4.6  Exports
A statistical comparison of export intensity multipliers between sectors is not possible because of the
fact that exports are an exogenous final use in the I-O framework and so are invariant to changes in
other  variables.    Therefore,  it  is  impossible  to  calculate  the  effects  of  the  investment  on  exports
though I-O analysis.
While we conducted a separate econometric analysis to estimate the export intensity of the defence
industry,  similar  exercises  for  the  comparison  sectors  were  beyond  the  scope  of  this  study.    We
therefore offer a more qualitative comparison, using information on the quantity of exports in  each
comparison  sector  in  conjunction  with  heuristic  arguments  to  infer  the  likely  effect  on  exports
following investments in these sectors.  We then compare this to the estimated effect for the defence
sector.
At  the  EU  level,  3.04  per  cent  of  the  output  of  the  land  transport  sector  is  exported.    The
corresponding  numbers  for  the  education  and  health  sectors  are  much  lower  at  0.31  and  0.05  per
cent.  We discuss each of these in turn.
  By their very nature, land transport services may only be exported at borders – transport within
the EU cannot be exported.  Thus, in this sense, the sector is largely ‘domestic’ when we consider
- 35 -

link to page 41 link to page 41 Comparison with Other Sectors
regions rather than individual countries.  Any investment in land transport would increase exports
from the EU only to the extent that, on the land borders of the EU, EU-based transport services
would become better alternatives than non-EU-based transport services.  The vast majority of the
effect  would  be  felt  within  the  EU,  so  the  export  effect  of  an  investment  in  the  land  transport
sector is likely to be small.
  The education  sector is highly domestic and the small amount of  exports is, presumably, due to
students from outside the EU coming to study within the EU, or due to EU institutions conducting
distance-learning  programmes.    Both  of  these  are  most  likely  to  be  significant  in  only  the  higher
education  sub-sector.    Therefore,  any  investment  in  EU  education  is  mostly  likely  to  benefit  EU
consumers of education services.
  The  health  sector  is  almost  entirely  domestic.    Exports  could  be  due  to  instances  of  ‘medical
tourism’,  i.e.  patients  from  other  countries  coming  to  the  EU  for  medical  treatment.    However,
medical tourism is much more prevalent in developing countries that are able to offer significantly
cheaper treatments while boasting a reasonably high level of expertise.  While medical equipment
might  have  significant  exports  this  is  not  included  in  the  health  services  sector,  which  is  the
recipient of most public funding.  The effects of an investment in the health sector are most likely,
therefore, to be felt domestically.  While the costs of treatment might be lowered, it is unlikely that
they  would  be  lowered  enough  to  attract  a  significant  amount  of  medical  tourism,  as  €100m  is
negligible when compared to the size of the health sector.27
It  is  not  possible  to  directly  compare  these  effects  to  the  defence  sector  export  intensity  effect
estimated  in  the  previous  chapter,  as  that  number  did  not  distinguish  between  intra-  and  extra-EU
trade.  However, we understand that the EU defence sector exports a lot more than any of the three
comparison sectors.  EU defence companies sell arms and ammunition to several countries outside the
EU.  According to the European Council’s Fourteenth Annual Report on the Control of Exports of
Military  Technology  and  Equipment,28  the  EU  exported  arms  worth  €37.52bn  worldwide  in  2011.29
The EU is a major supplier of arms to many lesser-developed countries, and so any investment that
would lead to a more competitive EU offering could lead to the potential capturing of markets from
other major arms suppliers such as the US and Russia.  By virtue of being a more geographically open
industry, an investment in EU defence is likely to have a much more substantial effect on EU exports
than is an equivalent investment in the transport, health or education sectors.
Looking at country level effects, the picture is more ambiguous than that for the EU as a whole.  Table
4.6  shows  the  percentage  of  output  for  each  of  the  comparison  sectors  that  is  accounted  for  by
exports.

27   The output of the human health services sector in the EU in 2005 was €881.94bn.
28   http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:C:2012:386:0001:0431:EN:
29   This included €7.98bn to the Middle East, €1.2bn to North Africa,  €3.59bn to North America, €0.85bn to
North  East  Asia,  €0.95bn  to  Oceania,  €1.84bn  to  other  European  countries,  €0.71bn  to  South  America,
€2.46bn to South Asia, €1.78bn to South East Asia and €0.49bn to Sub-Saharan Africa.
- 36 -

Comparison with Other Sectors
Table 4.6: Exports as percentage of total output by Member State
Member
Transport (land transport
State
services)
Education
Health
AT
31.21%
0.10%
1.08%
BE
10.42%
0.20%
0.09%
BG
No tables available
No tables available
No tables available
CY
No tables available
No tables available
No tables available
CZ
26.81%
0.04%
0.00%
EE
26.06%
0.10%
0.05%
FI
7.85%
0.08%
0.11%
FR
11.80%
0.00%
0.60%
DE
3.19%
0.00%
0.00%
EL
2.94%
0.20%
0.29%
HU
27.02%
0.08%
0.16%
IE
5.00%
0.00%
0.00%
IT
2.38%
0.00%
0.00%
LV
44.41%
1.27%
1.07%
LT
54.73%
0.00%
0.64%
LU
Tables unusable
Tables unusable
Tables unusable
MT
No tables available
No tables available
No tables available
NL
34.61%
3.42%
0.53%
PL
14.13%
0.05%
0.18%
PT
22.07%
0.02%
0.02%
RO
24.39%
0.00%
0.00%
SK
32.14%
0.58%
3.43%
SI
40.71%
0.07%
0.06%
ES
14.10%
0.00%
0.00%
SE
1.38%
0.68%
0.25%
UK
4.10%
1.94%
0.10%
EU-27
3.04%
0.31%
0.05%
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
The table shows that the shares of exports in the transport sector are sometimes very high, especially
for small countries on mainland Europe.  This  is presumably  because the consideration of individual
countries rather than the EU as a whole means that the total length of borders has increased, making
more transport cross-border in nature.  The effect on the exports of individual Member States of an
investment in EU transport is extremely ambiguous, as in most cases an increase in exports by one
Member State would be at the expense of exports by neighbouring Member States.  This is because
transport is mostly an undifferentiated commodity on any given route. One could take either a French
or a Belgian bus to travel from Lille to Brussels.  If the French offering becomes more competitive,
then there will be a shift of traffic from Belgian to French buses.  This differs from the impacts on a
sector  such  as  defence,  where  more  differentiated  offerings  are  available  and  competition  does  not
occur at such a narrow level.
Education and health services are still predominantly domestic at the Member State level and therefore
any investment will generally benefit domestic consumers.
Investments  in  the  defence  sector  are  likely  to  have  a  greater  impact  on  the  exports  of  individual
Member States than are the comparison sectors.  The pattern of EU defence production is generally
complementary at the Member State level.  For instance, there are very few Member States that can
produce sophisticated warships, and so the remaining EU Member States must buy from either these
suppliers or from other international suppliers.  In 2009, France won export orders worth €8.2bn.30  In

30   Annuaire Statistique de la Défense, 2010-11, Secrétariat Général pour l’Administration, Chapitre 4, page 82.
- 37 -

Comparison with Other Sectors
2009  and  2010,  Britain  won  export  orders  worth  £7.3bn  and  £5.8bn,  respectively.31    In  2010,
Germany’s total exports of defence equipment to EU countries amounted to €1,528m.32
The  main  difference  between  the  export  patterns  in  the  transport  and  defence  sectors  are  that
transport exports are more likely to be to neighbouring countries, and are more likely to exist in equal
measure  in  both  directions  while  defence  exports  are  less  balanced  and  are  made  irrespective  of
geographical distance.  This, along with imports from the US, is indicative of global rather than regional
markets  for  defence  products.    Therefore,  any  investment  that  makes  European  firms  more
competitive  would  be  likely  to  lead  to  increased  exports,  as  business  would  be  captured  from
international competitors rather than just other EU firms.
In conclusion, it seems that both at the EU and Member State level, investment in defence is likely to
have a much greater export impact than in any of the three comparison sectors.
4.7  Capital intensity
At the EU level, defence investment would lead to a higher level of consumption of fixed capital than
investments  in the  education  and  health sectors, but a lower  level than investment in the transport
sector.
Results for the Member State level analysis are shown below.

31   United  Kingdom  Defence  Statistics  2011,  Table  1.13.  The  Air  sector  accounted  for  68  per  cent  of  2010
exports.
32   Bericht  der  Bundesregierung  über  ihre  Exportpolitik  für  konventionelle  Rüstungsgüter  im  Jahre  2010:
Rüstungsexportbericht  2010,  seite  38  (“sämtliche  Kriegswaffenausfuhren  2010  (kommerziell  und  BMVg)”.
Exports by the Bundesministerium für Verteigigung (BMVg) accounted for 2 per cent of total exports in 2010
(page 38).
- 38 -

Comparison with Other Sectors
Table 4.7: Capital intensity multiplier comparison by Member State
Member
Transport (land
State
transport services)
Education
Health
Defence
AT
225.62
105.64
120.23
61.24
BE
118.75
50.58
102.93
55.82
BG
No tables available
No tables available
No tables available
No tables available
CY
No tables available
No tables available
No tables available
No tables available
CZ
266.65
259.83
143.26
109.24
EE
100.15
65.44
55.28
34.37
FI
246.42
242.31
207.53
146.86
FR
CFC data not available  CFC data not available  CFC data not available  CFC data not available
DE
CFC data not available  CFC data not available  CFC data not available  CFC data not available
EL
441.16
378.74
324.72
92.11
HU
126.47
103.74
64.88
40.64
IE
121.31
58.27
52.07
32.22
IT
163.72
198.19
179.80
218.77
LV
198.06
111.40
139.93
69.70
LT
147.65
122.35
136.19
50.94
LU
Tables unusable
Tables unusable
Tables unusable
Tables unusable
MT
No tables available
No tables available
No tables available
No tables available
NL
143.32
141.26
80.29
53.08
PL
220.54
168.80
171.85
120.69
PT
284.45
228.68
215.17
94.49
RO
CFC data not available  CFC data not available  CFC data not available  CFC data not available
SK
182.29
71.88
134.21
67.76
SI
147.99
79.62
92.58
78.76
ES
CFC data not available  CFC data not available  CFC data not available  CFC data not available
SE
187.12
141.14
137.38
89.45
UK
CFC data not available  CFC data not available  CFC data not available  CFC data not available
EU-27
254.08
170.97
193.10
223.88
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
The  transport  sector  has  the  highest  multiplier  among  the  comparison  sectors  almost  universally.
Moreover, the defence multipliers are generally the smallest, but not too much should be read into
this considering the high level of ‘rest of the world leakages’ in the sector.
- 39 -

Case Studies - Unpacking how defence spending affects the broader economy
5  Case Studies - Unpacking how
defence spending affects the
broader economy
5.1  The contribution of these case studies
In this section we explore in more detail the mechanisms through which defence expenditure converts
into broader impacts on GDP, employment, tax revenue, exports and technology transfers to civilian
sectors, by setting out a series of case studies of specific defence projects.
Various  performance  indicators  reflecting  competitiveness  are  used  including  unit  prices,  delivery
dates,  output  and  exports.    Only  published  data  are  available  some  of  which  might  be  unreliable,
especially data on prices and the military-operational performance of the various combat aircraft.
Project  case  studies  are  also  valuable  in  providing  insights  to  technology  transfer  (spin-offs)  arising
from  aircraft  programmes.    Numerous  examples  are  presented  of  such  spin-offs,  although  there
remain major opportunities for further research in this area.
The  case  studies  also  identify  the  major  prime  contractors  whose  financial  performance  can  be
assessed.  Firm performance indicators include labour productivity and profitability, and comparisons
can be made between the military aerospace firms and non-defence firms.
An economic evaluation of specific cases will consider their costs and benefits, as well as the costs and
benefits of competitor products.  Costs include acquisition and operational costs over the project’s
life-cycle.    Benefits  include  the  contribution  of  the  equipment  to  national  defence  as  reflected  in
security, protection, deterrence and peace.
A challenge for our analysis lies in the fact that defence output is difficult to measure, and typically it is
assumed that output equals inputs.  Since that approach ignores entirely the impact of productivity, it
is not a satisfactory way to measure defence output.  In addition to national defence output, military
aircraft contribute to wider economic and industrial benefits reflected in jobs, technology and exports.
Ideally, these wider economic benefits need to be included in any economic evaluation of new defence
equipment and we attempt to reflect at least a significant portion of such wider benefits for each case
considered in this section.
5.2  Cases Studied
The cases studied in this section are as follows:
  Air:
  JAS Gripen;
  Dassault Rafale; and
  Eurofighter Typhoon.
  Land – Leopard 2 Main Battle Tank;
  Maritime – Compact naval guns;
- 40 -

link to page 46 link to page 46 Case Studies - Unpacking how defence spending affects the broader economy
  R&T Case Study:  Intelligence, Surveillance and Reconnaissance Unmanned Air Systems; and
  Defence aerospace technology transfer and spin-offs.
5.3  Air – JAS Gripen
The JAS 39 Gripen is a Swedish multi-role affordable lightweight fighter aircraft.  Gripen was designed
to  replace  the  Swedish  Saab  Draken  and  Saab  Viggen.    It  is  a  single-seat  and  single-engine  multi-
purpose combat aircraft for which initial development work started in June 1980.  The initial Swedish
air  force  contract  was  awarded  in  June  1982  for  five  prototypes  and  30  production  aircraft  with
options for the next 110 aircraft.  Gripen was designed to be a small and relatively cheap multipurpose
aircraft, with half the weight of the previous third generation Viggen and greater operational capability
at only 60-65 per cent of the life-time cost of the Viggen.33
The  contract  for  the  Gripen  specified  its  performance  characteristics,  costs  and  delivery  schedules
with  the  consortium  partners  guaranteeing  the  contract.    The  contract  was  for  a  fixed  price  with
variation of price clauses (with the Swedish procurement agency accepting the foreign exchange risk).
Previously, Swedish defence contracts were cost-plus contracts with separately negotiated charges for
modifications.  Saab was the prime contractor and systems integrator for the Gripen which involved
the company in substantial risk-taking:  some of these technical and financial risks were shifted to its
sub-contractors.    The  major  sub-contractors  included  Volvo  Aero  for  the  engine;  Ericsson  for  the
radar  and  flight  control  system;  BAE  Systems  for  the  fuselage  and  wing;  Martin  Baker  (UK)  for  the
ejector seat; and other French, UK and US firms also acted as sub-contractors (note the absence of
Swedish  sub-contractors  who  were  reluctant  to  accept  the  risks  of  the  project:    Eliasson,  2010,
Supplement I).
Sweden  ordered  a  total  of  204  Gripen  aircraft  with  the  final  aircraft  delivered  in  late  November
2008.34    In  relation  to  the  contract,  Gripen  was  delivered  ahead  of  time  and  at  a  lower  cost  than
estimated.  Such a performance is unusual for major defence projects which are usually characterised
by substantial cost overruns and delays in delivery.  In addition to sales to Sweden, Gripen has been
exported to South Africa, the Czech Republic, Hungary, Thailand and Switzerland (see Table 5.1).
5.3.1  Costs and sales of Gripen
Published  data  on  development  and  production  costs  for  combat  aircraft  are  often  unreliable  and
Gripen  is  no  exception.    Various  estimates  suggest  its  development  costs  ranged  from  €2.3bn  to
€10bn, with unit production costs varying between €35.5m and €67.5m at 2012 prices.  In terms of
opportunity  costs,  Gripen  at  the  peak  of  the  programme  employed  6,000  engineers;  but  Eliasson
(2010) claims that its spill-overs were so large that there was no net cost to society of the project:  in
fact, it is claimed that in net terms society benefited from the Gripen development (even setting aside
the security gains).
Table  5.1  presents  some  of  the  features  of  the  Gripen  programme,  including  its  contractors,
performance, timescales, output and exports.

33   Eliasson,  G  (2010).    Advanced  Public  Procurement  as  Industrial  Policy:  Aircraft  Industry  as  a  Technical  University,
Springer Sciences and Business Media, New York.
34   In  2004,  Sweden  operated  200+  Gripen.    After  2008,  the  Swedish  Air  Force  operated  100  Gripen  and
reports suggest that in future, it will equip with some 60 Gripen Next Generation (NG).
- 41 -

link to page 46 Case Studies - Unpacking how defence spending affects the broader economy
Table 5.1:  Major features of Gripen multi-role fighter aircraft
Contractors
Aircraft performance
Prime:  Saab
Speed:  Mach 2
Major suppliers:
Combat radius: 497 miles
Volvo Aero
Single seat
Ericsson
Single engine
Timescales
Dates
Start of funded development work
June 1980
Programme approved
6 May 1982
Initial contract for 5 prototypes
June 1982
First flight
9tDecember 1988
Initial operating capability (IOC)
September 1997
Development  timescales
Total months
Total time from start to first flight
102
Time from programme approval to first flight
79
Time from start to IOC
207
Time from approval to IOC
184
Output
Number of units
Sweden
204
South Africa
26
Switzerland
22
Thailand
6
Hungary (lease)
14
Czech Republic (lease)
14
TOTAL (excluding leases)
258
Notes: Next Generation Gripen was ordered in early 2013. It involves the modification of existing Gripen aircraft operated by the Swedish
Air  Force.    Leased  aircraft  were  leased  from  Sweden:  hence,  their  numbers  are  deducted  from  the  Sweden  total  and  reflected  in  the
aggregate total.  Output figures include orders and are at March 2013. The order for Switzerland awaits confirmation at April 2013.  Where
no exact dates are available, it was assumed that the relevant date was the middle of the month.
5.3.2  An Economic Evaluation of the Gripen
Gripen was developed as a relatively cheap multi-role combat aircraft.  It was designed for the specific
operational requirements of the Swedish Air Force (e.g. short take-off and landing; simple maintenance
requirements;  rapid  turn-around  between  missions;  multi-role,  etc).    At  the  time  of  the  original
procurement choice for Gripen, how did its unit costs compare with the next-best alternative combat
aircraft?  Table 5.2 shows some comparators.
Table 5.2:  Gripen and rival aircraft unit prices, 2011-12
Aircraft
Unit production cost
Operational costs
(€m, 2011 prices)
(€ per flying hour, 2012 prices)
Gripen
60.1
3,620
Rafale
62.0
12,705
Typhoon
85.0
13,860
F-16
26.4
5,390
F-18E/F
60.0
8,470 to 18,480
F-35
144.4
23,870
Sources: Hartley, White Elephants? New Directions, Brussels, 2012; Janes, All the World’s Aircraft, 2012; and StratPost, July, 2012.
The US F-16 is considerably cheaper than the Gripen on unit acquisition costs but more expensive on
operational  costs,  and  it  is  not  suited  to  Sweden’s  operational  requirements.    Also,  the  F-16  was
introduced  in  1978  whereas  Gripen  was  introduced  in  1997,  so  the  F-16  is  probably  not  a  valid
comparator.
- 42 -

Case Studies - Unpacking how defence spending affects the broader economy
More  suitable  comparators  include  the  US  F-18E/F  and  the  French  Rafale  which  had  similar  unit
production costs but both were costlier to operate. On a purely cost basis, the Swedish Gripen was a
least-cost purchase.35
Gripen also provided Sweden and other European countries with wider benefits such as jobs, exports,
technology  and  spin-offs,  tax  revenue,  independence,  security  of  supply  and  so  on.    Such  benefits
would  have  been  ‘lost’ with  the  acquisition  of  a  foreign  aircraft.    Additional  economic  benefits  have
been derived from the 82 export sales of Gripen (including leased aircraft).
5.3.3  The Technology Contribution of Gripen
The  technology  contribution  of  Gripen  is  well-documented.36    Three  findings  are  relevant  to  an
economic analysis of the Gripen project.
First,  Sweden  views  its  aircraft  industry  as  an  advanced  technical  university  that  provides  research,
education and training services free of charge to other firms and related industries.
Second, Eliasson argues that the capacity to develop a complete military aircraft combat system or a
large  commercial  airliner  and  the  associated  systems  is  an  extremely  scarce  industrial  competence.
This skill is only available in possibly six nations, namely, France; the UK; Russia; the USA; and possibly
China and Sweden.
Third, Gripen has generated numerous spill-overs, including:
  general engineering technologies;
  critical software engineering;
  systems integration;
  development of lightweight structure technologies;
  medical spin-offs;
  unmanned aircraft;
  space –e.g. cheap satellites;
  technology transfer to industrialising economies (e.g. as part of the sale of Gripen to South Africa,
Saab agreed that South African engineers would work at Saab for periods of 6 months to 2 years);
  maintenance of advanced Swedish producers of civilian aircraft and aircraft engine subsystems for
international markets (Saab and Volvo); and
  further  examples  of  Gripen’s  spill-overs  include  telephone  systems,  civil  security,  heavy  trucks,
engines and automobiles.
Estimates have been made of Gripen’s spill-over effects.  Spill-over multipliers are additional returns to
society of a particular military investment over and above the value of the product being developed as
a multiple of the original investment (in constant prices and present value terms).  The spill-overs from
Gripen are estimated at 188bn to 344bn SEK based on a total programme cost for Gripen of 124bn
SEK  (2007  prices).37    Eliasson  concludes  that  it  is  “difficult,  probably  impossible,  to  find  another
industry  in  the  markets  for  public  goods  and  services  that  rivals  military  aircraft  in  generating
spillovers”.38

35   The issue of operational performance in relation to military requirements is not considered here.
36   See Eliasson, G (2010), Advanced Public Procurement as Industrial Policy: Aircraft Industry as a Technical University,
Springer Science and Business Media, New York. Eliasson provides the basis for this section.
37   Eliasson, 2010
38   Eliasson,  2010, p36
- 43 -

link to page 48 Case Studies - Unpacking how defence spending affects the broader economy
5.3.4  Performance of Saab Company
The  annual  Company  Reports  for  Saab  allow  a  comparative  assessment  of  its  performance  on
aerospace  and  other  divisions  of  the  Company.    Two  performance  indicators  are  used,  namely,
productivity and profitability.  The key question for our purposes is whether Saab’s defence business is
more successful than alternative uses of its resources.  In the event, this apparently simple exercise
shows the problems of testing such a hypothesis.
Table 5.3 presents the performance results for all Saab Company divisions.
Table 5.3:  Saab company performance, 2012
Employment
Labour
Defence
Company
Sales
Profitability
Export
division
(€m)
(full-time
productivity
(%)
sales (% of
sales (%)
equivalent)
(€000s)
total sales)
Aeronautics
728
2,932
248
5.9
83
39
Dynamics
572
1,568
365
13.0
92
88
Electronic
defence
512
2,578
199
2.7
98
76
systems
Security and
defence
716
3,105
231
7.0
71
76
solutions
Support and
services
409
1,805
226
12.0
78
29
Combitech
169
1,245
136
8.7
51
3
Whole
Not
2,876
13,900
207
8.5 (14.2)
Not available
company
available
Source: Saab Company Report, 2012
Notes: Labour productivity is sales divided by employment. Profitability is operating margin which is operating income as a percentage of
sales. Under profitability, figure in brackets is return on capital employed for the Company as a group.
Aeronautics comprises sales of Gripen, UAVs and components for Saab and other aircraft (Airbus; Boeing). Dynamics comprises missiles,
torpedoes, etc. Electronic Defence Systems comprises radar, electronic warfare and data links. Security and Defence Solutions comprises
C4R, AEW and civil security. Support and Services is for markets where Saab is active. Combitech is a consulting firm.
Compared with the Company average, the Aeronautics division has a higher labour productivity but
lower profitability.  The Dynamics and Electronics divisions are more defence-intensive, with almost
100 per cent defence sales.  The productivity and profitability results for these two divisions differed
markedly,  with  the  Dynamics  division  substantially  above  and  Electronics  substantially  below  the
Company  averages  for  productivity  and  profitability.    Various  rank  correlations  were  estimated
between productivity, profitability, the defence/civil split and export shares, but none was statistically
significant.39    The  absence  of  reliable  correlations  probably  reflects  the  small  sample  size  (six
observations).  Overall, the evidence from Saab is suggestive rather than conclusive.
5.4  Air – Dassault Rafale
The  Rafale  is  a  French  twin-engine,  delta-wing,  multi-role  combat  aircraft  manufactured  by  Dassault
Aviation.    There  are  single-seat  and  two-seat  variants  for  the  French  Air  Force  (Rafale  A  and  B
models) and a carrier-based variant for the French Navy (Rafale M and N models).
It is claimed to differ from other current European combat aircraft in that it is built almost entirely by
one country, involving most of France’s major defence contractors such as Dassault, Thales and Safran.
There  is  a  network  of  500  sub-contractors.    Estimates  suggest  that  the  programme  employs  7,000

39   The  following  Spearman  rank  correlations  were  estimated:  productivity  and  profitability  gave  r=  +0.31;
profitability and defence/civil split r= --0.26; productivity and defence/civil split gave r= +0.37; for productivity
and export shares, r= +0.57; and for profitability and export shares, r= --0.11.

- 44 -

Case Studies - Unpacking how defence spending affects the broader economy
workers although this appears a low figure and might apply to employment at Dassault only.40  There is
an annual production rate of 11 aircraft; each aircraft takes 24 months to build.
Rafale was planned to replace the Jaguar, Crusader, Mirage, Entendard and Super Entard operated by
the  French  Armed  Forces.    Initially,  in  1979,  Dassault  joined  the  UK-German  European  Combat
Aircraft project which developed into the 5-nation Future European Fighter Aircraft project (with Italy
and Spain).  By 1985, France had withdrawn from the project to pursue its own national programme.
The French withdrawal was due to differences in operational requirements, including its requirement
for  a  carrier-capable  version  and  its  demand  for  a  leading  role  in  project  management.    Next,  in
October 1982, Dassault was awarded a contract to build a technology demonstrator which became
the Rafale A which first flew in July 1986.  In April 1988, the French government awarded Dassault a
contract for four Rafale prototypes.  At the time, there was a planned requirement for 330 Rafales and
the aircraft was expected to enter service in 1996.  The end of the Cold War and reductions in the
French  defence  budget,  together  with  political  and  economic  uncertainties,  resulted  in  considerable
delays to the Rafale’s development time.  The prototype Rafale C model flew in May 1991 and the first
squadron of Rafale M for the Navy was formed in May 2001 (Rafales for the French Air Force were
delivered  several  years  later  in  2006).    At  December  2011,  a  total  of  180  Rafale  aircraft  had  been
ordered for the French Air Force and Navy.
5.4.1  Costs and sales of Rafale
Various estimates of unit procurement costs in 2012 prices range from €57.1m (Rafale C version) to
€62.4m (Rafale M version) to €105.25m (Rafale F3 version).  In 2012, Rafale was awarded an export
contract to India for 126 aircraft comprising 18 aircraft supplied by Dassault with the remaining 108
aircraft manufactured in India.  The total value of the Indian contract was €8bn, giving a unit cost of
€63.5m (2012 prices).
Table 5.4:  Major features of Rafale multi-role combat aircraft
Contractors
Aircraft performance
Prime:  Dassault Aviation
Speed:  Mach 1.8
Major Suppliers:
Combat radius: 655-1,093 mls
Safran/SNECMA
Single/two seat
Thales
Twin engine
Timescales
Dates
Start of technology demonstrator
October 1982
Contract for 4 prototypes
April 1988
First flight Rafale C
May 1991
Entry to service (IOC:  Navy version)
June 2001
Development timescales
Total months
Total time from start to first flight
103
Time from contract to first flight
37
Time from start to service entry
224
Time from contract to service entry
158
Output
Numbers
France
180
India
126
Total
306
Note: Output and export data at April 2013. The Indian order awaits confirmation.
5.4.2  An Economic Evaluation of Rafale
Both  Rafale  and  Gripen  demonstrate  that  France  and  Sweden  were  capable  of  the  independent
national development of a modern combat aircraft.  Compared with the Swedish Gripen, the French

40   This employment estimate is low compared with Typhoon employment. Also, total employment at Dassault
in 2012 was 11.472 employees comprising all activities (Rafale and civil aircraft production).
- 45 -

link to page 46 link to page 51 Case Studies - Unpacking how defence spending affects the broader economy
Rafale started later and was in service much later.  Rafale achieved shorter development times to its
first flight but required longer from start to service entry.  Development timescales based on specific
points in the development cycle obviously need to be interpreted with caution, since aircraft can differ
in their operational status at first flight and at service entry (e.g. at first flight, the aircraft might lack its
avionics and its design engine).
Compared  with  Gripen,  the  Rafale  had  a  higher  unit  cost  and  operational  cost  (see  Table  5.2).
However,  in  terms  of  international  competitiveness,  Rafale  has  achieved  higher  total  exports  and  a
higher proportion of its output has been exported (41 per cent for Rafale compared with 32 per cent
for Gripen).
5.4.3  The Technology Contribution of Rafale
A  French  study  has  considered  spin-offs  from  the  Rafale  project.41    The  study  separated  the  Rafale
programme  into  eleven  building  blocks  (“briques”)  and  then  mapped  them  into  the  eight  broadly-
defined technologies that were judged by the Ministry of Industry (in 2008) to be key to the French
economy in 2010.  Like many other studies in this field, there is an impressive list of technologies and
spin-offs from Rafale, but any money valuation is lacking for the economic benefits of the technologies
and their transfers.
The study assessed the contribution of each of the technologies stimulated by the Rafale programme
to each of the eight key technologies, according to the degree of correlation between them.  These
correlations were qualitative and were characterised as:
  very strong:  when the contribution is decisive and relatively direct, or when the corresponding
technology would not have attained the same level of performance (or would not have existed)
without the Rafale programme;
  strong:  when Rafale’s contribution is indirect, or when the contribution of other programmes or
national policies are equally important; and
  related:  when the Rafale programme contributed to the technology only in an indirect way.
The results of this exercise are reported in Table 5.5.

41   This section summarises a non-attributed paper: 'Quel es retombees du Rafale pour la France?’(June 2008).
- 46 -

Case Studies - Unpacking how defence spending affects the broader economy
Table 5.5: Rafale’s technologies and the technologies judged to be key to the French economy

Technologies judged to be key to the French economy in 2010
Rafale's
Information  Materials
Energy &
Health
Distribution  Production
Building Blocks  technology
&
Construction
&
Transport
&
chemicals
environment  safety
consumption  technology
Complex
software
S

R
R
S
S
S
Real-time
critical
VS

R
R
S
S
S
software
Data fusion
S

R
R
S
S
S
Cryptology
S

R
R
R
VS
R
Man-machine
interfaces
S

R
R
R
R
R
Tools for
conceptualising
R
R

R
R
S

S
virtual reality
Materials
R
R

R

S

R
Sensor
R
R

R

R

R
technology
Motorisation

R

R

R

R
Tools for
R
R

R
R
S

R
engineering
Modelling
aerodynamics
R

R

S

R
Note: VS is very strong; S is strong; and R is Related.  A fourth correlation classed as ‘marginal or non-existent’ is disregarded and shown as
an empty cell.
Looking first across the table, the Rafale technologies that seem most likely to generate spin-offs widely
through the economy concern software and information technology.  Among the major gains from the
programme are:
  engineering tools developed by Dassault Systems (described as one of the rare French industrial
‘start-ups’ in the style of Google or Microsoft);
  developments in encrypting data, which is a tool of sovereignty in the fight against terrorism;
  tools  for  conceiving,  modelling  and  simulating  that  are  indispensable  for  designing  modern  civil
aircraft; and
  man-machine interfaces – one of the “keys” for future competitiveness.
Looking  down  the  table,  the  sectors  that  seem  most  likely  to  benefit  from  these  spin-offs  are
information technology and transport.42
In parallel, each of Rafale’s eleven technological categories was evaluated according to:
  their strategic importance for France, in terms of its national defence, and ability to export civil or
military systems; and
  their potential for economic and technological development.
Six of Rafale’s technological categories were judged to be exceptionally important (rated six or higher
on a scale of zero to 10) on both these criteria:  real-time critical software; data fusion; man-machine
interfaces; modelling and simulating aerodynamics; sensors; and materials.  Cryptology was judged to
be the most important technology strategically.

42   There is an alternative, less impressive, interpretation of the data in Table 6. The Table shows 88 cells. Of
these 88 cells, only 2 showed ‘very strong’ (2%); 18 showed ‘strong’ (20%); 40 were ‘related’ (45%); and 28
were ‘marginal or non-existent’ (32%: mainly in materials and chemicals and construction).
- 47 -

Case Studies - Unpacking how defence spending affects the broader economy
Complex  software  and  tools  for  engineering  were  judged  to  have  exceptional  economic  and
technological potential.
One  of  these  engineering  tools  is  what  is  known  as  ‘simultaneous  engineering’  –  the  technique  of
establishing interfaces between parts of a programme that permit the partners in the programme to
have  visibility  of  it  as  a  whole,  and  to  share  responsibilities  and  risks.  ‘Simultaneous  engineering’  is
made  possible  by  communication  networks  that  permit  exchanges  of  data  and  virtual  platforms.
Predictive models can be applied to these platforms to simulate their performance and maintenance
requirements.  These techniques have reduced the time required to develop new models.
The aerospace sector has pioneered these techniques because it faces the most demanding constraints
and  requirements.    The  techniques  tend  then  to  spread  to  all  those  complex  industrial  sectors  in
which the development phase is a decisive one.
The  automobile  industry  is  a  major  user  because  of  its  desire  to  reduce  development  times  and  to
generate multiple versions of the same product.  Engineering and, notably, the petroleum industry, are
also intensive users, seeking to optimise the use of its facilities.  Shipbuilding and steel are following the
automobile industry.
The aerodynamics sector, which forms the basis of the aerospace industry, also has wider applications.
Aerodynamic flows need to be predicted whenever objects move at high speed, as in transport.  These
technologies can address the effects of vibration and noise induced within aircraft and vehicles, both
for those on board and for those nearby.  Such simulations are also relevant to wind generators, the
effects of turbulence between high buildings, sport, and estimating the behaviour of pollutants in the
atmosphere.    A  programme  such  as  Rafale  requires  particularly  sophisticated  means  of  investigating
such topics, theoretically and experimentally, and contributes to both.
There  were  also  spin-offs  from  Rafale  within  the  aerospace  industry.    The  development  of  Rafale’s
engine permitted Safran (Snecma) to propose a civil version to power the Russian regional jet (the RRJ
or Superjet 100), thus permitting Safran to “enter the top rank of global engine integrators”.  Dassault
also transferred some of its military technology to the development of its Falcon business jet.
5.4.4  Conclusion
Rafale  supports  the  general  finding  that  the  aerospace  industry  is  a  source  of  high  technology
knowledge  and  associated  spin-offs.    However,  the  findings  reported  above  are  simply  a  list  of
examples  with  two  key  weaknesses.    First,  there  are  no  monetary  valuations  for  these  technical
benefits  and,  second,  little  is  known  about  whether  other  industries  generate  similar  or  ‘better’
technology benefits and spin-offs.
5.5  Air – Eurofighter Typhoon
Eurofighter Typhoon is a single-seat, twin-engine, delta-wing, multi-role combat aircraft.  Unlike Gripen
and  Rafale  which  are  national  projects,  Typhoon  is  an  international  collaboration  involving  four
European nations:  Germany; Italy; Spain; and the UK.
In 1979, France, Germany and the UK began exploring the possibility of jointly developing a European
Combat  Aircraft.    This  project  collapsed  in  1981  over  different  operational  requirements,  a  French
insistence on design leadership, and British preference for a Rolls-Royce engine and French preference
for their Snecma engine.  By August 1985, after further collaboration plans, West Germany, Italy and
the  UK  announced  their  decision  to  proceed  with  the  Eurofighter  programme.    Spain  joined  the
programme in September 1985 but France withdrew to pursue a national project which became the
Dassault Rafale.
- 48 -

link to page 54 Case Studies - Unpacking how defence spending affects the broader economy
At  the  start,  the  planned  Eurofighter  procurement  was  for  the  UK  and  Germany  to  acquire  250
aircraft each, Italy 165 aircraft and Spain 100 aircraft.  Delays to the programme occurred in 1991 due
to  the  costs  of  German  reunification  and  a  German  desire  to  cancel  the  project.    However,  the
cancellation costs were unacceptable to Germany and the project continued.  First flight was achieved
in March 1994 and the first production contract was signed in January 1998.  At this stage, the four
partners  planned  to  buy  a  reduced  total  of  620  aircraft  with  the  UK  planning  to  buy  232  aircraft,
Germany 180 aircraft, Italy 121 aircraft and Spain 87 aircraft.
5.5.1  Costs and sales of Typhoon
Typhoon  entered  operational  service  in  August  2003.    Typhoon  work  shares  are  based  on
specialisation for parts of the aircraft, with each nation building the same parts for all the aircraft but
with each nation assembling its own aircraft - resulting in four final assembly lines.  On this basis, EADS
Germany builds the main centre fuselage; BAE Systems builds the front fuselage, canopy and the rear
fuselage section; EADS CASA builds the right wing and Alenia the left wing.   Work shares  are also
designed so that no money crosses national borders.
At March 2013, the planned purchase of Typhoon by the four partner nations was 160 aircraft for the
UK, 143 aircraft for Germany, 96 aircraft for Italy and 73 aircraft for Spain giving a total buy for the
four nations of 472 aircraft.  The economic and financial crisis in Europe and  the UK might lead to
further  reductions  in  these  orders.    At  March  2013,  a  total  of  99  Typhoons  had  been  exported  to
Saudi Arabia, Austria and Oman (see Table 5.6).  Further delays to the programme occurred in 2010
when the partners agreed to slow down production rates to retain industrial capability.
The  UK  National  Audit  Office  has  published  detailed  costs  for  the  UK  component  of  the  Typhoon
programme and these are reported in this section.43
The UK costs are 37 per cent of Typhoon total costs for all four partner nations.  The contracts for
the UK airframe and engine were non-competitive.  For the UK Typhoon, total development costs are
estimated at €8.2bn and total production costs at €16.6bn, giving total programme costs of €24.85bn
and unit production costs at €90m (UK costs only: 2012 prices and exchange rates).
Total  life-cycle  costs  for  the  UK  Typhoons  are  estimated  at  €46bn  with  equipment  acquisition
accounting for 61 per cent of this total.  UK employment on Typhoon at BAE Systems, Rolls-Royce
and Selex Galileo is estimated at 8,600 jobs but this number excludes other UK firms and their supply
chain  employment.    Broadly,  some  40  per  cent  of  Typhoon  production  costs  are  allocated  to  the
airframe, 40 per cent for equipment and 20 per cent for the engine.
The  UK  costs  can  be  ‘grossed-up’  to  provide  an  estimate  of  Typhoon’s  total  development  and
production costs for all four partner nations, assuming UK costs are typical of costs for all four partner
nations.    On  this  basis,  total  development  costs  for  Typhoon  are  estimated  at  €22.2bn,  total
production costs at €44.9bn and aggregate acquisition costs at €67.1bn (2012 prices).
For  the  UK,  total  programme  costs  are  estimated  to  have  increased  by  +20  per  cent  (over  fewer
aircraft).  Of the €4.3bn cost increase, some €2.7bn (63 per cent) was due to inefficient collaboration
arrangements, obligations to international partners and to project technical complexity.  Delays on the
UK Typhoon totalled 54 months, with 32 months of this delay due to technical factors and 22 months
(41 per cent) due to international collaboration.  At 2011, the National Audit Office concluded that
the  UK  had  not  achieved  value  for  money  from  its  investment  in  Typhoon  (National  Audit  Office,
Management of Typhoon Project, 2011, p9).

43   See, for example, National Audit Office: Major Projects Report 2012; and Management of Typhoon Project,
2011
- 49 -

Case Studies - Unpacking how defence spending affects the broader economy
Table 5.6:  Major features of Typhoon multi-national combat aircraft
Contractors
Aircraft performance
Prime:  Eurofighter
Speed:  Mach 2
Major suppliers:
Combat radius: 860 mls
Eurojet
Single seat
Euroradar
Twin engine
Timescales
Dates
Start of funded development work
May 1983
Programme approved
August 1985
First flight
March 1994
Entry to service
August 2003
Development timescales
Total months
Total time from start to first flight
130
Time from programme approval to first flight
103
Time from start to service entry
243
Time from approval to service entry
216
Output
Units
UK
160
Germany
143
Italy
96
Spain
73
Saudi Arabia
72
Austria
15
Oman
12
Total
571
Notes:
Funded development work led to the BAe Experimental Aircraft programme (EAP).
Output is based on orders at end-2012.
5.5.2  An Economic Evaluation of Typhoon
5.5.2.1  The costs of collaboration
Compared with Gripen and Rafale, Eurofighter Typhoon had much longer development times for each
phase  of  development  and  entered  operational  service  much  later  (August  2003  compared  to  June
2001 for Rafale and September 1997 for Gripen).
Collaboration tends to lead to cost penalties and delays in development and production.  Typical ‘rules
of  thumb’  suggest  that,  compared  with  a  national  project,  collaboration  development  costs  can  be
represented by the ‘square root’ of the number of partner nations and programme delays are likely to
be represented by cube root of the number of partner nations.  On this basis, a four-nation project
such  as  Typhoon  can  be  expected  to  have  development  costs  which  are  twice  those  of  a  similar
national programme; and its development timescale might be some 60 per cent longer than a similar
national project.  Similar cost inefficiencies on collaborative production mean that unit cost reductions
are about half those on national programmes.
There  is  evidence  to  support  these  ‘rules  of  thumb.’    A  UK  study  compared  the  estimated
development  costs  of  Typhoon  with  a  national  alternative,  finding  that  Typhoon  development  costs
were 1.96 times the costs of developing a national alternative which is consistent with the square root
rule.  On timescales and compared with both Gripen and Rafale, the Typhoon took some 10-40 per
cent longer to develop, which is less than suggested by the cube root rule.
Collaboration inefficiencies often reflect work-sharing rules which are based on political-equity criteria
rather  than  competitiveness  and  comparative  advantage.    Similarly,  programme  delays  reflect  the
administrative, organisational and industrial arrangements of international collaboration.  Each partner
nation involves its government, defence ministries, armed forces and key defence firms in the project:
- 50 -

link to page 46 Case Studies - Unpacking how defence spending affects the broader economy
reaching decisions with large numbers of participants takes much longer than where only one nation is
involved.  However, whilst collaboration leads to higher development costs compared with a national
project, such costs are shared between all the partner nations.  As a result, each partner nation can
achieve  substantial  savings  in  development  costs  compared  with  a  similar  national  programme.    For
example, even if the square root rule applies, for a four-nation collaboration such as Typhoon, each
partner saves 50 per cent of the development costs compared with a national project.44  Similarly, a
comparison of the total development costs for the four-nation Typhoon compared with the national
Rafale project suggests that whilst Typhoon was costlier, it was less than 10 per cent more costly than
Rafale (i.e. less than predicted by the square root rule).
Output levels indicate the achievement of scale and learning economies while exports are an indicator
of international competitiveness.  Compared with Gripen and Rafale, the Typhoon has achieved the
greatest scale of output but inefficiencies in collaborative production mean that its scale economies are
only  50  per  cent  of  those  for  a  national  project.    This  means  that  it  needs  to  produce  twice  the
national volume to be equally competitive.  For exports, Typhoon has sold less than Rafale but more
than Gripen (99 units for Typhoon; 126 units for Rafale and 82 units for Gripen) but Typhoon has only
exported 17 per cent of its output compared with 32 per cent for Gripen and 40 per cent for Rafale.
In terms of unit procurement prices and operational costs, Typhoon is costlier than Rafale and Gripen
(see Table 5.2).  On this basis, European national projects such as Gripen and Rafale are competitive
with  multi-national programmes  such  as Typhoon.    All  defence  equipment  projects  obviously  create
wider economic and industrial benefits and these need to be included in any economic evaluation of
Typhoon.
5.5.2.2  Wider economic benefits of Typhoon
Wider  economic  and  industrial  benefits  include  employment,  technology  and  spin-offs,  exports  and
other  contributions  to  retaining  a  defence  industrial  base,  security  of  supply  and  re-supply  and
equipment  standardisation.    A  simple  identification  and  listing  of  the  wider  economic  benefits  of
projects such as Typhoon is useful but not sufficient for a comprehensive economic evaluation.  The
potential  benefits  have  to  be  identified,  quantified  and  expressed  in  monetary  terms.    Some  broad
estimates are available of the wider economic benefits from Typhoon.45
5.5.2.3  Employment
Typhoon  supports  large  numbers  of  highly-skilled,  highly-paid  and  high  value-added  jobs  in  the  four
partner  nations.   Estimates  show  that,  in  2006,  development  and production work  on the Typhoon
project supported some 100,000 to 105,000 personnel employed both directly and indirectly in over
400 companies throughout Europe (indirect employment comprises jobs in the supply chain).  These
jobs  were  distributed  between  the  partner  nations,  with  20,000  personnel  in  each  of  Germany  and
Italy, 25,000 personnel in Spain and 40,000 personnel in the UK.
Learning  curves  for  Typhoon  production  are  estimated  at  85  per  cent,  with  a  90  per  cent  learning
curve for combined labour and other operations.  Breaks in  production lead to the loss of learning
experience:  for example, a break of one year in Typhoon production is equivalent to returning to unit
one in production (i.e. learning has to re-start).

44   Consider a project costing €100bn for development on a national basis.  A four-nation collaboration might
cost twice that sum, namely, €200bn in development (the square root rule); but each nation will pay €50bn,
so  saving  €50bn  in  development  compared  with  a  similar  national  project.    However,  in  the  ideal  case
involving no collaboration inefficiencies, each nation would only pay €25bn for development.
45   Data on Typhoon are based  on a published study: Hartley, K (2008),  The Industrial and Economic Benefits of
Eurofighter Typhoon, Eurofighter, Munich.
- 51 -

Case Studies - Unpacking how defence spending affects the broader economy
5.5.2.4  Technology contribution of Typhoon
Typhoon  is  an  advanced,  high-technology  combat  aircraft  which  has  contributed  to  technical
knowledge, some of which has provided technical spin-offs to other sectors.  Typhoon requires special
skills  in  aerodynamics,  flight-control  systems,  structures,  avionics  and  systems  integration.   Typhoon
has  resulted  in  an  impressive  list  of  examples  of  technology  benefits.    Some  of  these  technology
benefits have created and supported world-class firms.  The following examples of technology benefits
and spin-offs have been identified for Typhoon:
  carbon-fibre technology with further applications to civil aircraft and Formula 1 racing cars;
  super-plastic forming and fusion-bonding;
  aero-engine technology based on the EJ200 engine for Typhoon with possible applications to other
military aircraft as well as civil aircraft (there are further spin-offs to power generation engines for
civil work and applications to the health sector);
  spin-offs to civil aircraft, to motor car industries and to firms in the supply chains.  In some cases,
technology  transfer  has  resulted  from  labour  mobility  where  the  labour  skills  on  Typhoon  have
been highly transferable; and
  impacts  on  supply  chains.    Typhoon  has  resulted  in  the  introduction  of  new  technology  and  a
whole  range  of  modern  business  practices  throughout  the  supply  chain  (e.g.  application  of  IT;
modern management and commercial practices; procurement and contracting skills, etc).
The market value of Typhoon technology spin-offs can be estimated by using other studies.  Eliasson
estimated that Gripen resulted in spill-overs valued at 1.8 to 2.3 times the value of the investment in
Gripen.  Assuming that this multiplier applies to Typhoon development costs only, the value of spin-
offs  from  Typhoon  might  be  some  €40bn  to  €51bn.    Another  study  of  the  Netherlands’  planned
purchase  of  US  F-35  aircraft,  estimated  technology  spin-offs  valued  at  13.2  per  cent  of  the  total
Netherlands’ development and production expenditure on its purchase of F-35 aircraft.46 Applied to
Typhoon such a percentage share would lead to spin-offs valued at €8.9bn.
Overall,  these  two  studies  suggest  spin-offs  on  Typhoon  valued  within  a  range  of  €9-51bn.    These
estimates of the market value of Typhoon spin-offs are based on other aircraft and show considerable
variation.  There remains scope for a proper economic study of the market value of Typhoon spin-offs.
It is not possible to assess and compare the technology benefits and spin-offs for Typhoon with those
for Gripen and Rafale.  However, some broad generalisations can be made.  All three aircraft are likely
to  have  resulted  in  similar  technology  benefits  but  Typhoon  and  Rafale  are  more  advanced  combat
aircraft than Gripen and used a new engine.  This means that their technology benefits are likely to be
greater per unit of expenditure compared to Gripen.  Similarly, Typhoon and Rafale are more likely to
have resulted in greater national technology spin-offs since they involved greater spending within their
national economies than Gripen (hence fewer leakages of spending).
5.5.2.5  Tax revenues
Some  analysts  argue that  tax  revenues  need  to  be  included  in  any  economic  evaluation  of Typhoon
(and other combat aircraft).  National treasuries often take a different view, and do not include tax
revenues since they are transfer payments and all economic activity generates tax revenues (similarly
for induced employment estimates).   Nevertheless, estimates for Typhoon show that, for Germany,
60-70 per cent of its costs accrued to the national treasury through taxes and similar dues, giving a net
cost of some 30-40 per cent of the total cost.  In comparison, for Germany, a similar purchase of US

46   See Vijver, M.V D and Vos, B (2006). The F-35 Joint Strike Fighter as a source of innovation and employment:
some interim results, Defence and Peace Economics, 17,2, 155-159.
- 52 -

link to page 58 Case Studies - Unpacking how defence spending affects the broader economy
F-18 aircraft provided a return to the national treasury of 14 per cent, therefore raising its net cost to
86 per cent of the total.  The licensed production in Germany of US F-18 aircraft led to taxes and dues
of 35 per cent and a net cost of 65 per cent of the total cost.
Exports and import-savings
Exports  provide  additional  employment,  maintain  a  national  defence  industrial  base  without  major
additional costs to the national economy and provide a future stream of economic benefits from the
sales of spares, training and mid-life updates.  Estimates suggest that the value of this life-cycle business
might  be  an  extra  50-100  per  cent  of  the  initial  price  over  35  years.    However,  not  all  exports
represent  net  gains  since  there  might  be  offset  requirements  (e.g.  200  per  cent  offsets  for  sale  of
Typhoons to Austria), the waiving of any R&D levy and generous financial terms on foreign sales.
Typhoon’s contribution to the balance of payments of the partner nations can be estimated.  By April
2013, total Typhoon exports were 99 units.  Assuming each aircraft sold at the UK unit production
price of €90m, this suggests total revenue of €8.9bn which might support some 16,000 jobs.  There is
additional  sales  revenue  over  the  aircraft  life-cycle  estimated  at  50-100  per  cent  of  the  initial
acquisition price over 35 years.  On this basis, aggregate sales revenue from Typhoon exports might
total €13.4-17.8bn which might support an aggregate total of some 24,000 to 32,000 jobs (based on
export sales at April 2013).
In  addition,  Typhoon  contributes  to  import-savings:    these  are  the  savings  on  imports  of  combat
aircraft which would be needed in the absence of Typhoon.  Here, various estimates are possible, each
sensitive to the assumptions made about the costs of Typhoon and its possible rival aircraft.  First, it
might be assumed that Typhoon represents the least-cost solution so that all its costs can be counted
as import-savings (i.e. both development and production).  On this ‘optimistic, best case’ scenario, the
import-savings from Typhoon totalled €67.1bn (total development and production costs for all partner
nations, excluding support costs).  Second, the unit costs of alternative and rival combat aircraft can be
compared  with  Typhoon  costs  to  determine  whether  there  are  lower-cost  alternatives.    Identifying
such lower-cost alternatives is complicated by the need to obtain reliable and accurate unit price data,
and by the need to compare differences in the operational capabilities of rival aircraft.  For example,
assuming that the four partner nations would have purchased 620 aircraft comprising a mix of US F-15
and  F-18  aircraft,  Typhoon  created  import-savings  of  €39.3bn.47    On  these  assumptions,  the  total
balance of payments contribution of Typhoon is some €52.7bn to €84.9bn (2012 prices).48
5.5.2.6  Industrial benefits
Industrial  benefits  arise  in  the  form  of  the  contribution  of  Typhoon  to  maintaining  an  independent
European aerospace industry as an internationally-competitive industry and a rival to the US industry.
It  also  ensures  independence  and  security  of  supply  and  re-supply  in  conflict.    Further  industrial
benefits take the form of demonstrating the ability to develop a modern complex combat aircraft and
to  manage  a  four-nation  multi-national  collaboration.    Society  has  to  reach  some  judgement  of  the
valuation it places on these industrial benefits.
5.5.2.7  Summary
The wider economic and industrial benefits of Typhoon are summarised in Table 5.7.

47   It was assumed that the 620 aircraft would comprise 200 F-15s and 420 F-18s at unit prices of $99.6m and
$68.7m, respectively.
48   The  estimates  are  based  on  the  lower-bound  of  export  sales  (including  support  sales)  of  €13.4bn  plus  the
costs of the US purchases of €39.3bn and the upper-bound estimates of exports sales of  €17.8bn and the
‘optimistic’ scenario of Typhoon import-savings of €67.1bn.
- 53 -

link to page 58 link to page 59 Case Studies - Unpacking how defence spending affects the broader economy
Table 5.7:  Wider economic and industrial benefits of Typhoon
Technology and
Exports and Import-
Employment
spin-offs
savings
Others
Examples:
Exports valued at €13.4bn
European independence and
to €17.8 bn.
100,000 jobs.
Carbon fibre
Import-savings valued at
security of supply.
High wage/ high
technology; aero-
Demonstration of ability to
engine technology.
€39.3bn to €67.1bn.
integrate complex systems and
skill jobs
Possibly valued at
Total balance of payments
contribution of €52.7bn to
manage a multi-national
€9bn to €51bn.
€84.9bn
collaboration

The net economic benefit of Typhoon for the four partner nations can be estimated by considering its
income  from  exports  minus  the  costs  of  developing  and  producing  Typhoon  minus  the  costs  of
creating exports plus the costs of importing from overseas.  The figures reported in this section show
that export values might be as much as €17.8bn (which might increase with future exports); Typhoon
costs are €67.1bn (these are acquisition costs only); and the costs of importing alternative aircraft are
estimated  at  €39.3bn  (there  are  no  data  on  the  costs  of  creating  Typhoon  exports).    Using  these
estimates, the net economic benefits of Typhoon are minus €10bn for the four partner nations (i.e. a
net  economic  cost).    However,  Typhoon  is  designed  to  meet  European  military  requirements
compared  with  imported  equipment;  it  has  also  provided  technology  spin-offs;  and  there  are  other
industrial and military benefits.  If these wider economic and industrial benefits are valued at €10bn or
more by the partner nations then Typhoon produces a net economic benefit.
5.6  Air – Comparative analysis
5.6.1  Domestic production and exports
The  three  European  case  studies  show  that  developing  combat  aircraft  for  national  purposes  also
generates  exports.    Table  5.8  shows  domestic  and  export  sales  and  proportions  for  the  three
European  combat  aircraft.    At  April  2013,  the  nationally-developed  Rafale  has  the  best  export
performance of the three European combat aircraft.
Table 5.8: National production and exports
Aircraft
Domestic sales
Export sales
Export/domestic sales
(number)
(number)
(%)
Gripen
204
82
40
Rafale
180
126
70
Typhoon
472
99
21
Note:  this table assumes that the Rafale sale to India wil  be formal y concluded.
5.6.2  Competitiveness
Prices and delivery dates are an indicator of international competitiveness.  Table 5.9 shows data on
unit production costs and unit total costs (i.e. including development and production costs).  Data are
also  shown  on  the  date  of  first  flight  and  the  date  of  service  entry.    These  data  suggest  two
conclusions.  First, Typhoon is costlier than its European rivals and some of its US rivals but the three
European aircraft are cheaper than the US F-22 and F-35 aircraft.  Second, the time between first flight
and  service  entry  of  the  US  F-15,  F-16  and  F-18E/F  aircraft  was  shorter  than  that  of  the  three
European aircraft.  This suggests that the US has a competitive advantage in development timescales.
- 54 -

link to page 59 link to page 60 Case Studies - Unpacking how defence spending affects the broader economy
Table 5.9:  Unit prices and delivery dates
Unit production
Unit total cost
Aircraft type
cost (€m, 2012
(€m, 2012
Date of first
Date of service
flight
entry
prices)
prices)
Gripen JAS-39C
60.1
66.4
December 1988
September 1997
Rafale C
54.0
118.0
May 1991
June 2001
Typhoon
90.5
124.9
March 1994
August 2003
F-15 Eagle
96.6
Na
July 1972
January 1976
F-16
33.1
Na
February 1974
August 1978
F-18E/F Super
69.9
85.1
November 1995
November 1999
Hornet
F-22 Raptor
158.5
302.4
September 1997
December 2005
F-35 JSF
105.4
123.8
December 2006
After 2016
Notes:  Data  for  al   aircraft  except  F-35  Joint  Strike  Fighter  from  Estimating  the  Real  Cost  of  Modern  Fighter  Aircraft,  Defense-
Aerospace.com, 2006. Data based on standard definitions and methodology except for JSF which is based on GAO Report, 2012.
Al  prices adjusted to 2012 prices using national inflation rates and exchange rates.
5.6.3  Life-cycle costs
Table 5.10 shows estimates of life-cycle costs for European and US combat aircraft.  The US F-16 and
Swedish Gripen are the least costly aircraft in the sample.  Both Gripen and Rafale are competitive
with the US F-18E/F.  In contrast, the US F-35 is the costliest aircraft in the sample.
Table 5.10:  Life-cycle costs
Annual acquisition
Annual operational
Total unit costs
Annual unit costs
Aircraft
costs
costs
(€m, 2012 prices)
index
(€m, 2012 prices)
(€m, 2012 prices)
(Gripen = 100)
Gripen
4.57
0.72
5.29
100
Rafale
4.71
2.54
7.25
137
Typhoon
6.46
2.77
9.23
174
F-16
2.01
1.08
3.09
58
F-18E/F
4.56
2.70
7.26
137
F-35
10.97
4.77
15.74
298
Note:  Annual  costs  are  annualised  based  on  aircraft  life  of 20  years,  200  operational  hours  per  year  and  a discount  rate  of  5%.    Annual
acquisition costs are production costs only.  Unfortunately, the data reported in this table are not available for the F-22.
5.6.4  Combat effectiveness
Unit prices, life-cycle costs and delivery dates are indicators of competitiveness, but they need to be
adjusted for aircraft quality in terms of operational performance to ensure that we compare like with
like.  While attempts have been made, the results from such adjustments have proven contradictory
and so we consider that there is not yet a sufficiently robust basis on which to compare the combat
effectiveness of different aircraft.
5.6.5  Output levels
Levels  of  output  are  a  further  indicator  of  competitiveness  as  they  may  suggest  the  achievement  of
scale and learning economies.  Table 5.11 shows output levels for European and US combat aircraft.
Typical national output levels for US combat aircraft exceed 1,000 units which is considerably greater
than European output levels.  For the European nations to achieve US scales of output requires either
export sales and/or international collaboration.
- 55 -

link to page 61 Case Studies - Unpacking how defence spending affects the broader economy
Table 5.11:  Output levels
Aircraft
Output levels (including exports)
Gripen
258
Rafale
306
Typhoon
571
F-15A-D
1,198
F-15 E (Eagle)
415
F-16
4,500+
F-18 Hornet
1,480
F-18E/F Super Hornet
628
F-22
195
F-35
2,457
Note: Outputs at end 2012 and including export sales.
5.6.6  Collaboration for the three European aircraft
International  collaboration  remains  a  procurement  policy  option  for  European  nations  (and  for  the
USA,  e.g.  the  F-35).    Consider  the  output  implications  if  the  European  nations  currently  producing
three different types of combat aircraft had chosen to collaborate.  The result would have been one
type  of  combat  aircraft  produced  for  the  air  forces  of  six  European  nations.    Total  orders  for  the
nations’ air forces would have been some 856 units (national orders only excluding exports) and so
the  achievement  of  scale  and  learning  economies  would  have  been  more  likely.    In  addition,  there
would have been savings in R&D costs since only one R&D bill would have been incurred.
For illustrative purposes only, assume that Rafale is selected by all six European nations.  Compared
with  the  current three  types,  the  selection  of  Rafale  would  lead  to  possible  savings  in  development
costs of €32.2bn (for Gripen and Typhoon) and possible savings in unit production costs of over 20
per  cent.    However,  some  of  these  cost  savings  might  be  reduced  if  the  six-nation  programme  is
characterised by inefficient work-sharing arrangements.
5.6.7  Comparative firm performance
Data  are  available  which  allow  a  comparative  assessment  of  firm  performance  for  the  major  firms
involved  in  the  three  air  case  studies.    These  firms  are  Saab  for  Gripen,  Dassault  Aviation  for  the
Rafale and BAE Systems, and EADS and Finmeccanica for Typhoon.  There are also data for the major
European aero-engine companies, for the major US aerospace companies and for a composite of Al
Companies which can be used to reflect the alternative use value of resources.  These data are shown
in  Table  5.12.    The  data  are  subject  to  limitations  because:    firms  have  different  combinations  of
defence and civil sales; the data are for one year only so do not show trends over time; and the R&D
data  do  not  reflect  government-funded  R&D  spending  which  will  be  a major  component of defence
R&D  expenditure.    Value  added  productivity  figures  more  accurately  reflect  a  firm’s  economic
performance since the alternative labour productivity data include bought-in parts and equipment (i.e.
purchases from other firms).
- 56 -

link to page 61 link to page 61 Case Studies - Unpacking how defence spending affects the broader economy
Table 5.12:  Comparative firm performance
Labour
Value added
R&D per
Company
Sales
R&D   Profits
(€m)
(%)
(%)
productivity
productivity
employee
(€000s)
(€000s)
(€000s)
All Companies
416
3.6
8.0
299.1
103.9
10.9
Aerospace
474
4.1
6.7
250.7
101.8
10.2
EADS
46,037
6.7
--1.1
385.2
111.6
25.9
BAE
24,652
1.1
4.4
262.2
85.4
3.0
Finmeccanica
17,740
11.7
7.0
244.5
109.6
28.6
Dassault
3,678
7.1
9.6
301.2
153.7
21.3
Saab
2,587
4.8
5.6
198.3
96.9
9.6
SAFRAN
11,395
5.9
4.3
206.3
93.9
12.2
Rolls-Royce
12,600
4.5
11.3
327.3
89.3
14.8
Boeing
51,161
5.1
3.1
325.6
Na
16.6
Lockheed Martin
33,860
1.7
10.2
241.9
Na
3.9
UK Automobiles
1,335
4.5
--1.1
302.7
54.8
13.6
Notes:
Sales are in Euros mil ions; RD is R&D as percentage of sales; Profits are profits as share of sales; Labour productivity is sales per employee in
Euros 000s; VA productivity is value added per employee in Euros 000s; RD per employee is R&D per employee in Euros 000s.
Value added is the difference between sales revenue and the cost of bought-in goods and services. Value added data are for 2007/08 and for
the top 750 European companies only. Al  other data in Table are for 2009/10 and are based on the top 1,000 global companies. The Al
Companies data are a composite based on the top 1,000 global companies which provides a benchmark for assessing the performance of the
Aerospace group. The Aerospace group is also based on the top 1,000 global companies. Na is Not available: the UK database only published
value added data for the major European companies.
The Aerospace group comprises the major aerospace and defence companies in the UK, Europe and the world.
Automobiles and parts are for the top 1,000 UK companies; but for value added data are for the top 800 UK companies.
Data are from the 2010 R&D Scoreboard and the 2009 Value Added Scoreboard, Department for Business Innovation and Skil s, UK. These
were the final years for each of these publications.
Table  5.12  allows  comparisons  between  the  Aerospace  and  Defence  sector  and  the  All  Companies
group as well as comparisons between the major aerospace companies (all based on global companies).
Compared  with  the  Aerospace  and  Defence  group,  the  All  Companies  group  achieved  higher
performance  for  all  indicators  except  for  R&D  shares,  suggesting  that  there  were  more  attractive
alternatives for use of resources.
Interestingly,  there  were  significant  variations  and  differences  between  the  major  aerospace  firms.
BAE Systems, which is one of the most defence-intensive companies, recorded the lowest value-added
productivity and one of the lowest profitability figures amongst the major European aerospace firms.
In contrast, Dassault Aviation ‘outperformed’ the All Companies group on all the indicators shown in
Table 5.12.
Amongst  the  Aerospace  firms,  the  two  with  a  large  civil  aircraft  business,  Boeing  and  EADS,  were
distinctive.  Each had better labour productivity record compared with the All Companies group and
EADS had better value added productivity.  The contrasting examples are BAE Systems and Lockheed
Martin, which are defence-intensive companies with lower labour productivity compared with Boeing
and  EADS  and  lower  value  added  productivity  for  BAE.    However,  both  these  defence-intensive
companies achieved higher profitability than Boeing and EADS.
Data are also shown for the UK Automobiles sector which is one alternative use of resources in the
UK economy.  BAE Systems and Rolls-Royce each achieved higher profitability and higher value added
productivity  figures  than  the  UK  Automobile  industry.    Rolls-Royce  also  achieved  higher  figures  for
labour productivity and R&D per employee.
Overall,  the  firm  level  data  show  mixed  results.    Some  Aerospace  and  Defence  companies  show  a
better  performance  than  for  the  alternative  uses  of  resources  but  other  firms  show  an  inferior
performance,  raising  serious  questions  as  to  why  such  firms  remain  in  the  Aerospace  and  Defence
industry.  One answer to this question might be that they view the industry as still offering their best
prospects of profitability with the perceived alternatives remaining less attractive.
- 57 -

Case Studies - Unpacking how defence spending affects the broader economy
5.6.8  Implications / lessons
We learn a number of lessons from the case studies in this section.
First, these cases illustrate that defence spending can take different forms, reflected in the acquisition
of Gripen, Rafale and Typhoon (or other types of defence equipment).  Studies based solely on the
macroeconomic impacts of defence spending, by their blunt nature fail to identify the more detailed
microeconomic impacts of such spending.
Second,  these  cases  suggest  that  considerable  opportunities  remain  for  increasing  the  efficiency  of
European  collaborative  defence  equipment  programmes.    For  example,  work-sharing  for  both
development and production could be allocated on the basis of competition:  a single prime contractor
might manage the programme rather than an industrial consortium and committee arrangements; and
the number of major partner nations might be restricted to two partners so as to minimise transaction
costs  (bilateral  collaboration).    The  A400M  highlights  the  problems  for  seven-partner  nation
collaborations (major cost overruns and delays) whilst Airbus civil aircraft demonstrate the success of
international collaboration based on a smaller number of major partners.  Similarly, the US Joint Strike
Fighter (F-35) example is based on a business model with a prime contractor (Lockheed Martin) which
selected its partner companies (BAE Systems and Northrop Grumman) and which has varying levels of
international partnerships (e.g. UK as level 1 partner; other nations as junior/minor partners).
Third, the case studies provide indicative support for the view that the arguments for defence spending
might be based on wider economic and industrial benefits, including technology spin-offs.
5.7  Land – Leopard 2 Main Battle Tank
5.7.1  Background
Main  battle  tanks  (MBTs)  are  the  modern  cavalry.    They  serve  three  principal  functions  on  the
battlefield – mobility, firepower and protection.  For example, the mission of the M1A2 Abrams Tank
is to “close with and destroy enemy forces using firepower, manoeuvre, and shock effect”.
The Leopard 2 was the result of an unsuccessful agreement between the USA and Germany in 1963 to
develop a common tank known as the “Main Battle Tank/ Kampfpanzer – 70” (MBT/ KPz-70).  Both
countries needed an improved MBT to counter the Soviet T-72s that were deployed in the 1970s, as
well as the anticipated T-80s.
In 1969, when vehicles became available for trials, it became obvious that they were too heavy.  No
agreement could be reached on how this should be addressed.  The programme was terminated in
1970,  following  the  expenditure  of  DM  830m.    However,  in  1969,  the  German  Office  for  Defence
Technology and Procurement (Bundesamt für Wehrtechnik und Beschaffung, BWB) initiated a study to
save the majority of the MBT/ KPz-70 development programme.
The  outcome  was  Leopard  2.    Krauss-Maffei  was  selected  as  the  main  contractor  and  systems
manager,  production  was shared  between  Krauss-Maffei  and  Maschinenfabrik Kiel  (MaK) on  a  55:45
basis, and Wegmann was appointed the turret integrator.  The main 120mm smooth bore gun was to
be supplied by Rheinmetall, with the turret.
In 1977, the BWB decided to order 1,800 Leopard 2s, in five batches.  By 1992, three more batches
had been delivered, bringing the total to 2,125.  Thereafter, the German army’s fleet of Leopards was
upgraded, using the existing chassis.
The purpose of this case study is to consider two economic impacts of this programme:
- 58 -

link to page 63 Case Studies - Unpacking how defence spending affects the broader economy
  whether  the  programme  enabled  the  BWB  to  meet  the  German  Army’s  requirements  for  the
2,125 MBTs delivered between 1980 and 1992 at a lower cost than that of the best alternative;
and
  whether the programme generated additional exports, and if so, whether they generated revenues
in excess of their estimated cost of production.
5.7.2  Would  Germany  (and  Europe)  have  had  to  pay  more  for  their  main  battle
tanks in the absence of the Leopard 2?
5.7.2.1  The cost of Leopard 2
The first step in our analysis of whether the Leopard 2 was cheaper than the next-best alternative is to
establish the cost of the Leopard 2 programme to BWB.  As shown in Table 5.13, we estimate that the
average unit price of the Leopard in this period was DM 5.24m and the total cost of the programme
was DM 11,100m, measured at 1992 prices.49
Table 5.13:  Estimated cost of the domestic Leopard deliveries
Years in  Estimated  Estimated  Estimated  Estimated
Number
German
which
programm
produced  producer
an
unit price,
unit price,
e cost, at
programme

1980-
price
upgrade  at current
at 1992
cost, at 1992
prices           prices
current
prices
1990
index*
was
(DM m)
(DM m)
prices
(DM m)
made**
(DM m)
1980
106
69.4

3.61
4.60
383
488
1981
229
73.6

3.83
4.60
877
1,054
1982
45
77.1

4.01
4.60
181
207
1983
450
78.2
1
4.41
4.98
1,982
2,241
1984
300
80.4

4.53
4.98
1,359
1,494
1985
300
82.1
1
5.00
5.39
1,501
1,616
1986
0
80.2

4.89
5.39
0
0
1987
370
79.9
1
5.26
5.83
1,947
2,156
1988
0
81.2

5.35
5.83
0
0
1989
150
83.9

5.53
5.83
829
874
1990
100
85.1

5.61
5.83
561
583
1991
0
87.0

5.73
5.83
0
0
1992
75
88.4

5.83
5.83
437
437
Total
2,125

10,100
11,100
*OECD, 2005 = 100
**It  was  assumed  that  the  unit  price  of  the  1980  deliveries  was  in  line  with  the  original  1977  budget  provision  (DM  6,500m  for  1,800
Leopards), and that the cost of the seventh batch of 100 Leopards completed in 1990 was DM 561m, as reported by Global Security.org
(www.globalsecurity.org/military/world/europe/leopard2.htm).   The unit prices for other years were interpolated between 1980 and 1990,
using the German PPI and estimating an uplift factor (of about 8 per cent) for each of the three Leopard upgrades.
5.7.2.2  The next-best alternative to Leopard 2
In the absence of the Leopard, which tank would have been selected by the BWB?
It  seems  probable  that  in the  absence of the  Leopard  2 the  German  army  would  have  adopted  the
Abrams M1.  As already noted, both the Leopard 2 and the Abrams M1 grew out of the collaborative

49   This is very close to the DM 5.3m figure reported by Global Security.org.  However, it is not clear whether
this figure is an average of prices in different years or is a costing at prices in a particular year.  It may have
included the upgrade of the Leopard 2 (to become 2A3s), whereas our estimate does not.
- 59 -

link to page 64 Case Studies - Unpacking how defence spending affects the broader economy
German-US  programme.    They  were  then  developed  in  parallel  and  were  introduced  into  their
respective armies from about 1980.
The general consensus among the defence community (those, at least, who write knowledgably on this
subject) is that these were, and remain, the two best tanks in the world.  They have both been widely
adopted.    Although  the  British  FV4030/4  Challenger  (later  designated  Challenger  1)  and  the  French
AMX-56  Leclerc  were  both  considered  to  be  highly  capable  tanks,  they  were  commercial
disappointments.    Each  won  orders  in  just  one  country  –  Jordan  and  the  United  Arab  Emirates,
respectively.    Differences  in  national  replacement  cycles  also  played  a  part.    Challenger  1  and  the
French AMX-56 Leclerc did not enter service until 1983 and 1990, respectively.50
For these reasons, it seems likely that in the absence of the Leopard 2, the German Army would have
been equipped with the Abrams M1.
5.7.2.3  The cost of the next-best alternative to Leopard 2
A counterfactual of this kind is necessarily a thought-experiment.  There are few reliable data in the
public domain with which to construct it:  neither Ministries of Defence nor defence companies are in
the habit of revealing details of their negotiations, so a number of assumptions have to be made.51
The same is true about the way the German government would have handled the DM/US$ exchange
rate.    As  shown  in  Figure  5.1,  the DM/US$  exchange  rate  was  quite  volatile  in  the  relevant  period.
The values of defence export contracts are often reported in US$ (by SIPRI, for example) but it is not
clear which exchange rate was used to calculate these values – was it the rate prevailing at the time
the contract was concluded, or the rate at the time of delivery, several years later?
Figure 5.1:  The DM/$ exchange rate 1975-1995
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
1975
1980
1985
1990
1995


50   The fact that the German Army needed a MBT replacement several years earlier than the British Army was
one of the factors that led to the cancellation of an Anglo-German Future Main Battle Tank programme in the
1970s (FMBT/KPz3). The Challenger 1’s availability as early as 1983 could not have been anticipated when the
Leopard was being developed. It was the result of the cancellation by Iran, following the 1979 revolution, of
an order for a modified Chieftain, which was then taken over by the UK MoD.
51  The average price of 1,155 Abrams M1A2 ordered by the US Department of Defense between 1980 and
1999 was reported in 1999 to be $6.2m, but it is not clear whether this was the total cost divided by the
number of tanks or whether it is expressed at 1999 prices; and whether it includes the cost of the
development programme.
- 60 -

link to page 65 link to page 64 link to page 66 Case Studies - Unpacking how defence spending affects the broader economy
For our purposes, the relevant price comparator to the Leopard 2 is the price at which new Abrams
tanks were exported.  Table 5.14 reports five such contracts and, for comparison, the corresponding
export  prices  for  the  Leopard.    These  comparisons  are  necessarily  approximate.    Contracts  may
contain differing provisions for spares, peripheral equipment and training, and would also have been
subject to different offset obligations.
Table 5.14:  Unit prices at which Abrams and Leopard tanks were exported (current prices)

Abrams
Leopard
Number
Purchaser
Source of price/value data
M1 ($m)
2 ($m)
1980
-
1.76
445
Netherlands
Jerchel and Schnellbacher, p.36.
1984
-
3.68
380
Switzerland
SIPRI
1988
5.15
-
524
Egypt
SIPRI
1990
4.76
-
315
Saudi Arabia
SIPRI
1999
5.64
-
100
Egypt
SIPRI
2001
5.90
-
100
Egypt
SIPRI
2003
-
5.88
170
Greece
Army Guide
2004
6.85
-
59
Australia(1)
SIPRI
2007
-
5.70
20
Canada
SIPRI
Source: SIPRI Arms Transfer Database.

(1) This $420-475m deal also included seven M88A2 armoured recovery vehicles (ARVs). We adjusted for this on the basis of the unit prices
for the order for 13 of these vehicles by Egypt in 2001, adjusted for inflation.
To  take  account  of  the  fact  that  these  unit  prices  tend  to  increase  over  time,  partly  as  a  result  of
inflation and partly as a result of periodic upgrades, we regressed these prices against the year in which
the contracts were awarded.  To test whether the export prices of the two tanks differed significantly
we  included  a  dummy  variable  that  took  the  value  unity  for  Abrams  M1  contracts  and  zero  for
Leopard 2 contracts.52
This analysis suggests that the unit export price for an Abrams M1 tended to be 38 per cent higher
than that of a Leopard.53
According to the SIPRI Arms Transfer Database, the Abrams did not win an export contract before
1988, i.e. during most of the period when German was building up its Leopard fleet.  This may have
been due to security concerns, but even if these had been absent an economic factor would probably
have ruled out such contracts.  The economic fact that the US$ appreciated significantly against the
DM after 1980, by over 60 per cent between 1980 and 1985 (see Figure 5.1) meant that it would have
been relatively expensive to purchase American tanks.  Only when the US$ depreciated did Abrams
win export orders (to Egypt in 1988 and Saudi Arabia in 1990).
5.7.2.4  Definition of a ‘no Leopard’ counterfactual
As shown in Table 5.15, the counterfactual suggests that if the investment in the Leopard had not been
undertaken, Germany would have had to pay 79 per cent more for the 2,125 tanks that it purchased
between 1980 and 1992.

52   We also tested whether unit prices reflected the size of the order:  they did not appear to do so.
53   We used a semi-log function in which the log of the unit price was regressed against the year and the Abrams
dummy variable, with the following result:
Log (unit price) = - 66.8 + 0.034*Year + 0.321*Abrams dummy

(5.21)            (2.65)
Adjusted R2 = 0.82
The t ratios are in parentheses. The Abrams dummy is statistically significant at the five per cent level.
The percentage impact of the dummy variable on unit price in this particular functional form is e0.287 – 1, or 38
per cent.
- 61 -

Case Studies - Unpacking how defence spending affects the broader economy
Does this estimate overstate the probable cost penalty?  For example, if the Abrams tank would have
given  Germany  a  superior  capability,  the  BWB  might  have  ordered  fewer  Abrams  than  the  2,125
Leopards that they ordered.
It is true that, in a physical sense, an Abrams M1 offered ‘more tank’ than a Leopard 2:  the Abrams
was significantly heavier (61.3 tonnes compared to the Leopard 2’s 55 tonne combat weight, 52 tonnes
empty)  and  had  superior  frontal  armour.    On  the  other  hand,  the  Leopard  2  was  equipped  with  a
Rheinmetall 130 mm gun with which the Abrams was not equipped until 1986.
The Abrams’ Avro-Lycoming 1,500 hp turbine engine gave it a higher acceleration and ‘burst’ speed,
but this involved significantly higher fuel consumption rates, required correspondingly more tankers in
support  and  additional  training  for  the  crews  that  operate  them.    Other  armed  forces  that  have
considered the Abrams have been deterred by these factors.
In addition, the Leopard 2’s lower weight and greater manoeuvrability and ‘fightability’ corresponded
more closely to the German concept of operations.
Taking these and other factors into account it would be hard to claim that the Abrams M1 would have
provided a superior all-round capability that would justify ordering fewer of them.
If anything, the financial penalty may have been understated.  These two tanks are widely regarded as
the  two  best  tanks  in the  world.    Hence, they  are close  competitors.   The  unit  prices  that  we  can
observe are conditioned by the competition between them.  In the absence of the Leopard, the export
price of the Abrams might well have been higher than it was.
Table 5.15:  Costing a no-Leopard counterfactual
Deliveries
Assumed  Assumed
of
Implied
Leopards
Estimated
Estimated
unit
unit price
Abrams’
cost of the

to the
unit price
Cost of
price of
of
price
Leopards
exported  exported  premium
Abrams’
German
alternative
Army
Abrams
Abrams

DM m
DM m
$ m
DM m

DM m

(1)
(2)

1980
106
3.6
380
3.6
6.5
81%
690
1981
229
3.8
880
4.0
7.2
88%
1,650
1982
45
4.0
180
4.2
7.6
90%
340
1983
450
4.4
1,970
4.3
7.9
79%
3,550
1984
300
4.5
1,360
4.5
8.2
82%
2,470
1985
300
5.0
1,510
4.7
8.5
70%
2,560
1986
0
4.9
0
4.8
8.7
78%
0
1987
370
5.3
1,910
4.9
9.0
71%
3,330
1988
0
5.3
0
5.2
9.4
75%
0
1989
150
5.5
830
5.4
9.8
78%
1,470
1990
100
5.6
560
5.7
10.3
85%
1,030
1991
0
5.7
0
5.9
10.8
88%
0
1992
75
5.8
440
6.1
11.1
91%
830
Total
2,125

10,010

79%
17,900
At
1992

11,100

79%
19,900
prices
Cost
differe-

8,800
nce
(1)Assuming that the BWB would have been required to pay the same unit price in 1988 as Egypt is reported to have paid then for their 524
Abrams. The unit $ price for Abrams in other years is estimated from this 1988 figure, on the basis of the US Consumer price Index.
(2)Assuming that the BWB would have bought US$ in 1980 to cover the cost of an Abrams programme, at the 1980 exchange rate of 1.82
DM/$.
- 62 -

link to page 67 link to page 67 link to page 63 Case Studies - Unpacking how defence spending affects the broader economy
5.7.3  Exports
The Netherlands was the first country to import Leopard 2s – a total of 465 were ordered by 1980.
After  extensive  comparisons  with  the  Abrams  M1A2,  Switzerland  ordered  380  Leopard  2s  in  1984,
most of which were built in Switzerland under licence.  Table 5.16 reports the exports of Leopards to
date.  We estimate that the value of exports of new Leopards was $3,880m at 1992 prices.
Table 5.16:  Export sales of Leopard 2 (US$ m)
Of
Year
Unit
Recipient
Type  Number
which
of
Years of
Value  Value
price
new
order  deliveries
$m
€m
$m
Netherlands
A4
465
465
1979
1981-1986
812

1.7
Switzerland
A4
380
380
1984
1987-1993
1,194

3.1
Sweden*
A4**
160
0
1994
1994
770

Sweden
A5
120
120
1994
1996-2002
450

3.8
Spain*
A4**
108
0
1995
1995-1996
33

Denmark*
A4**
51
0
1997
2002-2005
91

2.9
Finland*
A4**
124
0
2002
2003
66

0.5
Poland*
A4**
128
0
2002
2002-2003

Greece
A6
170
170
2003
2006-2009
1,000
1,700
5.9
Greece*
A4**
183
0
2005
2007

420
1.8
Turkey*
A4**
298
0
2005
2006-2010

365
1.4
Chile*
A4**
172

2006
2007-2009
125

1.4
Canada
A6**
20
20
2007
2007
114

5.7
Singapore*
A4**
99

2007
2007-2011

Total

2,478

Of which new

1,155

3,570

At 1992 prices

3,880

Sources: SIPRI, Arms Transfer Database, Army Guide and Forum Europa websites.
*Built under licence; ** Second-hand;
Many more new Leopard 2s would have been exported had the Cold War continued.  Its termination
left Germany with a large stock of surplus Leopard 2s.  A decision in 2007 to adopt “Structure 2010”
involved  reducing  the  German  fleet  of  Leopard  2s  from  2,528  to  only  350.   This  explains  the  large
number  of  second-hand  Leopard  2s  that  were  exported  (and  re-exported)  in  the  table  above.    A
number of nations were able to acquire Leopard 2s at bargain prices.
The Leopard 2 soon became the European tank of choice.  Other capable European tanks, such as the
Leclerc  AMX-56  and  the  Challenger  1,  were  not  able  to  compete  on  price  and  effectiveness  with
second-hand Leopard 2s.  Conversely, the sales revenues from these second-hand Leopard 2s enabled
the German Army to upgrade its Leopard 2 fleet at lower cost than would otherwise have been the
case.
We focus here on the five reported export orders for new Leopards, shown in Table 5.16.  These
orders  involved  a  total  of  1,155  Leopards,  with  an  estimated  value  of  DM  7,220m.    These  exports
were equivalent to 54 per cent of the number of domestic deliveries of new Leopards between 1980
and 1992, and 72 per cent of their value (see Table 5.13).
It does not seem likely that these exports would have occurred had the BWB not invested in Leopard
2’s development and then ordered Leopards.
- 63 -

link to page 68 Case Studies - Unpacking how defence spending affects the broader economy
5.7.3.1  Economic rents earned on Leopard exports
It  would  be  tempting  to  count  the  entire  value  of  these  sales  (DM  7,220  m)  as  a  benefit  from  the
Leopard programme; as indeed they are, in a gross sense.  We need to recognise, however, that those
who have been employed on Leopard 2 production – highly-skilled and employable for the most part –
would  have  found  alternative  employment  if  Germany  had  opted  to  import  Abrams  tanks.    Many
would  probably  have  been  employed  producing  Abrams  under  licence,  with  a  value  added  per
employee not dissimilar to that which was achieved producing the Leopard.
Krauss-Maffei Wegmann’s turnover per employee in 2005 was €753,000, according to Statista.  This
was 3.3 times the average for German manufacturing and 4.2 times the average for EU manufacturing
(Eurostat).    This  is  why  the  exports  were  important:    they  allowed  this  exceptionally  productive
company to expand.
The  concept  of  ‘economic  rent’  is  relevant  here.    The  economic  rent  earned  by  an  activity  is  the
difference between the value of its output and cost of producing it, including a normal commercial rate
of  return  on  the  capital  employed.    It  measures  any  ‘super-normal’  incomes  (profits,  wages  and
salaries) that are earned from exceptional and product-specific skills and intellectual property.
It is not easy to estimate whether these rents were earned on the sales of Leopards to the German
Government, or  whether  they  would  have  been  greater  or  lower  if  Abrams  had  been  ordered  and
then  manufactured  in  Germany.    What  is  clear,  however,  is  that  in  such  a  scenario  the  German
economy would have lost any economic rents that were earned on its exports of Leopards.
In estimating the economic rents earned on exports we have assumed that the unit price cost paid by
the BWB for its Leopard 2s was equal to the unit cost of production, including a commercial rate of
return  on  capital.    On  this  basis  we  estimate  that  the  economic  rents  earned  on  the  five  export
contracts in Table 5.17 amounted to DM 1,990m at 1992 prices, i.e. equivalent to 18 per cent of the
cost to the BWB of the Leopard programme.
Table 5.17:  Economic rents earned on exports of new Leopard 2
No.
Reported /
Assumed
Assumed
Year
export
Purchaser
estimated
Estimated
unit cost
cost of
Economic
ed
unit price
value
production  production
rent

DM m
DM m
DM m
DM m
DM m

(1)

(2)

(3)
1980
445
Netherlands
3.2
1,420
3.6
1,610
-180
1984
380
Switzerland
8.0
3,030
4.5
1,720
1,320
1994
120
Sweden
6.1
730
5.9
700
20
2003
170
Greece
11.0
1,860
6.3
1,080
790
2007
20
Canada
8.5
170
6.9
140
30
Total
1,135
-
-
7,210
-
5,250
1,980
At
1992

7,720

1,990
prices
(1)The unit  cost  of  the  Leopards  for  the  Netherlands  was  reported  to be  DM 3.2m by  Jerchel and  Schnellbacher, op.  cit., page  36.    For
Switzerland we have used the unit price of 6.6m Swiss francs, equivalent then to DM 8.0m. The huge and unexplained difference between this
figure and the unit cost agreed in 1978 by the Netherlands for their Leopard 2s provoked a lively debate, analysed later in a seminar at the
University of Bern, 30 April 1999 (Das "Kesseltreiben" um die Leopard-2 Beschaffung von 1984: Ein politischer Skandal oder landesubliche
Perteipolitik?").
(2)Assumed to be equal to the unit cost paid by the BWB in those years.
(3)The value of the exports less their estimated cost.
- 64 -

link to page 69 Case Studies - Unpacking how defence spending affects the broader economy
5.7.4  Summary and Conclusions
To  conclude  this  case  study,  it  seems  probable  that  the  investment  in  Leopard  2  made  a  significant
economic  contribution  to  the  German  economy  by  enabling  the  German  Army  to  equip  its  cavalry
regiments with a highly capable system at a much lower cost than the best alternative.  We estimate
that  the  BWB  spent  DM  11,100m  at  1992  prices  between  1980  and  1992  acquiring  2,125  Leopard
tanks.
In the absence of the Leopard 2, the BWB would have needed to spend an additional DM 8.8bn (at
1992 prices) – 79 per cent more – in order to acquire an equivalent armoured capability.
In  addition,  this  investment  generated  additional  exports  of  1,135  new  tanks  worth  DM  7,730m  at
1992 prices – equivalent to 69 per cent of the investment in the Leopard programme.  The German
economy derived an estimated ‘economic rent’ on these exports of DM 1,990m, i.e. revenue in excess
of the full cost of producing these 1,135 tanks.
We estimate that the sum of these two benefits – the savings and the economic rent on exports – was
in  the  region  of  DM  10,790m,  equivalent  to  97  per  cent  of  the  value  of  the  BWB’s  DM  11,100m
investment in Leopard 2s between 1980 and 1992.
Table  5.18  summarises  the  economic  benefits  that  are  estimated  to  have  flowed  from  the  Leopard
programme.
Table 5.18:  Economic benefits from the Leopard 2 programme (at 1992 prices)
Savings,
Economic
Number
rent on
Total

of
Cost
compared
to best
exports of
resource
Leopards
alternative
new
benefits
Leopards


DM m
DM m
DM m
DM m
Investment in Leopard 2s by the
German government, 1980-1992
2,125
11,100

Abrams alternative
2,125
19,900
8,800



Exports of new Leopards

7,720

Economic rents earned on exports
1,135

1,990

sales of new Leopard 2s
Savings compared to buying
Abrams M1 plus the economic
rent earned on exports of new

10,790
Leopard 2s
As proportion of Leopard
investment

97%
5.8  Maritime – Compact naval guns54
Europe’s two main producers of compact naval guns are the Italian company, Oto Melara, located in La
Spezia,  and  now  part  of  the  Finmeccanica  Group;  and  the  Swedish  company,  Bofors,  located  in

54   The technical material for this case is drawn largely from a website
http://www.navweaps.com/Weapons/WNUS_3-62_mk75.htm compiled from a number of authoritative
sources, "Jane's Pocket Book 9:  Naval Armament" edited by Denis Archer, "The Naval Institute Guide to
World Naval Weapon Systems 1991/92" by Norman Friedman, "Jane's Ammunition Handbook:  Ninth Edition
2000-2001" edited by Terry J. Gander and Charles Q. Cutshaw, updated 8 January 2013.
- 65 -

Case Studies - Unpacking how defence spending affects the broader economy
Karlskoga.  Bofors was acquired by BAE Systems in 2005 and became known as Bofors Defence AB. It
is now a subsidiary of BAE Systems Land and Armaments, based in the USA.
This  case  mainly  concerns  Oto  Melara.    With  sales  revenues  of  €416m  in  2011,  the  company  is
relatively modest in comparison with Europe’s major defence companies:  naval guns are not a major
item of defence expenditure. However, the case is of interest because it illustrates how a nation can:
  identify a military requirement that is shared by many nations;
  commission one of its companies to develop a cost-effective solution, and
  thereby generate defence exports that far exceed its own military requirements.
5.8.1  Background
In the mid-1950s the Italian Navy began planning to modernise.   At that time, Italian warships were
equipped for the most part with US-built 5-inch guns and the Bofors 40mm/L60.  The view was taken
that 5-inch guns were too heavy for many warships, whereas 40mm/L60 guns were too light for use as
a corvette’s main weapon.
The  Italian  Navy  concluded  that  the  best  compromise  was  a  dual  purpose,  medium-calibre  cannon,
capable of engaging both ships and aircraft.  This weapon would be the primary armament on smaller
warships, like corvettes, and the secondary armament on larger-class warships, e.g. frigates, destroyers
and primary cannon armament of the planned helicopter cruisers.  The Italian government contracted
Oto Melara to design and manufacture it.
The result was the Compact 76 mm naval gun (the 76 mm Compatto).  It was designed in 1963 and
entered service with the Italian Navy in 1964.  The gun's high rate of fire of 80-85 rounds per minute
(rpm)  makes  it  suitable  for  short-range  anti-missile  point  defence,  and  its  calibre  also  allows  it  to
function in anti-aircraft, anti-surface, and ground support roles.
The Super Rapid ("Super Rapido") began to be produced in 1988 and is the current production version
of the standard gun.  It has selectable firing rates of 1, 10, or 120 rpm.  The increased rate of fire was
achieved by a cooling system which reduces the time required to transfer ammunition from magazine
to barrel and fire.  The Italian Navy is thought to be currently equipped with up to forty 76mm guns. 55
Many others of both types have been produced under license, in Australia, India, Japan, Spain and the
USA.  They are manufactured in the United States by United Defense (now part of BAE Systems), in
Japan by Japan Steel Works and in Spain by FABA (formerly IZAR, formerly Bazán).
For forty years the Oto Melara company has been an outstandingly successful manufacturer of naval
guns.  Forecast International commented that:
“The Oto Melara 76mm L62 has become an iconic naval weapon.  It has been used on virtually every
type  of  warship  –  from  AEGIS-equipped  destroyers  to  small,  offshore  patrol  vessels.    It  fills  almost
every imaginable naval role – from air and missile defense to anti-piracy and maritime law enforcement.
Indeed, the question is not why this gun should be selected for any specific program, but why anyone
would want to install anything else.” 56
To convey an idea of what is claimed the latest standard version (the Super Rapid) can do,  Oto Melara
estimate that the Super Rapid can begin engaging missiles at about 6,000 metres, with the first rounds
arriving on target at 5,500 metres.  With these ranges, a single gun can deal with up to four subsonic
sea-skimmer missiles, arriving simultaneously 90 degrees apart, before any reaches 1,000 metres.

55   Forecast International, “The Market for Naval Surface Warfare Systems”, 2011.
56   Forecast International, “The Market for Naval Surface Warfare Systems”, 2011.
- 66 -

Case Studies - Unpacking how defence spending affects the broader economy
5.8.2  Economic significance
Two ways of thinking about the economic contribution of this programme, and about compact naval
guns in general, involve the questions:
  How important were the exports that flowed from the Italian investment in these systems, and
what was their value to the Italian economy?
  What is the counterfactual, for Italy and other European users of such systems, in the absence of
these compact guns?
It  is  easier  to  be  specific  about  the  first  of  these  questions.    According  to  data  published  by  the
Stockholm  International  Peace  Research  Institute  (SIPRI),  the  company  has  exported 877  such  naval
guns over the past four decades.  An indicator of Oto Melara’ pre-eminence in compact naval guns is
that in this period its closest rival in this field, Bofors, exported 92 such systems.  In contrast to the
Leopard case, there is/was no obvious non-European alternative.  It is a question, then, of how the
Italian and other European navies would have armed themselves in the absence of such guns, and what
would have been the operational and financial costs involved.
Table 5.19:  Export deliveries of compact naval guns57
Oto Melara
1970s
1980s
1990s
2000s
2010s
Total
Compact 76mm
137
189
121
83

530
Super rapid 76mm

28
51
37

116
Compact 127mm
4
1
7
9

21
Compact 40L70

118
64
25
3
210
Total
141
336
243
154
3
877


Bofors

SAK-70 Mk-1 57mm
38
9
1
0
0
48
SAK-70 Mk-2 57mm
0
5
14
18
7
44
Total
38
14
15
18
7
92
Source: SIPRI Arms Transfer Database, generated 1 March 2013.
According to Forecast International, Oto Melara had produced 854 76mm guns by the end of 2010.58
Table 2 indicates that 646 such guns had been exported up to that point.  This suggests that 208 such
guns had been produced for the Italian Navy.  In other words, for every 76mm gun that was produced
for the Italian Navy, more than three had been exported.
On the basis that the unit price of the Super Rapid lay between $1.5m and $2m in 2011, depending on
the  number  of  units  ordered  and  the  customer,59  the  value  of  these  exports  was  perhaps  $970  –
1,290m (€700 – 930m) at 2011 prices.

57   Table  notes: Some  arbitrary  allocations  were  made  across  two  or  more  periods  involving  major  orders  of
Compact 76mm guns (49 to Japan, 68 to South Korea and 81 to the USA) and Compact 40L70 guns (55 to
South Korea).
The Compact weighed 7.5 tonnes (empty) and was capable of firing at the rate of 80-85 rounds per minute
(rpm), each round weighing 12 kilograms. The “Super Rapid” (SR) is an improved, faster-firing (120 rounds
per minute) version designed to counter anti-ship missiles.  The magazine for the SR is independent of the
turret, which means that the feed can be interrupted to insert different kinds of ammunition, making the gun
more flexible against multiple targets.
The Oto-Melara/Otobreda twin 40L70 compact / “fast forty” gun system is a high-performance anti-missile,
anti-aircraft and ship-to-ship close-in weapon system (CIWS), with a rate of fire  of 600 rounds per minute
(compact) / 900 rounds per minute (fast forty).
58   This is less than the number reported by Oto Melara reported in December 2002: that about 1,000 Compact
and Super Rapid guns were in service in 51 navies.
59   Forecast International, “The Market for Naval Surface Warfare Systems”, 2011.
- 67 -

Case Studies - Unpacking how defence spending affects the broader economy
The economic significance of an achievement of this kind is that it brings about a transfer of employees
(and  other  resources)  from  the  manufacturing  sector  in  general,  i.e.  from  occupations  where  their
productivity is probably around the sector average, to one where their productivity is exceptional.  In
2010 and 2011, Oto Melara achieved a turnover per employee that was over one-third higher than
both that of the industry to which it belongs, and the average for Italian manufacturing.
Table 5.20:  Turnover per employee comparisons, 2011 (€000)

2010
2011
Oto Melara1
294
342
Italian weapons & ammunition industry2
239
252
Italian manufacturing sector2
218
252
Premium over manufacturing sector
35%
36%
(1) Company website
(2)  2010,  Eurostat,  Annual  detailed  enterprise  statistics  for  industry;  2011,  estimated  on  basis  of  2009  and  2010  data.  Value  added  per
employee would be a better measure of productivity but company accounts do not enable this to be estimated.
5.8.3  Counterfactuals
The counterfactuals are more conceptual and speculative, but important to consider.  One could think
of them in any of a number of ways, but the two that seem to us to be the most plausible are:
  that Oto Melara had not developed their compact naval guns, but other European producers had
done so; or
  that Europe had not developed compact naval guns, so that its navies would have had to rely on
more traditional gun designs, adopted by the UK and the US.
Regarding the first possibility, the  10 European navies that adopted the Oto Melara Compact or its
Super  Rapid  successor  would  probably  have  adopted  the  Bofors  57mm  L70  -  its  closest  rival  and
substitute - also favoured by a number of navies, including three European navies (Finland, Ireland and
Sweden) the US Coastguard.60
Another  alternative  would  have  been  the  Creusot-Loire  100mm  naval  gun  which,  although  not  as
successful  commercially  as  the  Oto Melara  or the Bofors  systems,  has  been  used  by  four  European
navies (those of Bulgaria, Belgium, Germany and Portugal), and has been exported to China, Malaysia,
Portugal and Saudi Arabia.  However, apart from a 1957 deal to supply Germany with 57 Medele-1953
100mm  guns,  Creusot-Loire  is  reported  to  have  exported  only  26  naval  guns  and  to  have
manufactured another eight in China.
The following comparison was made between the Oto Melara 76mm Mk3 and the Bofors 57mm L70.61
“Both guns are similar in terms of installation weight, ship impact and throw weight (the 57mm throws
a shell half the weight of that thrown by the 76mm but at twice the rate of fire).  The 76mm has met
and matched the challenge mounted by the smaller gun.  The deciding factor was that, while the 76mm
shell is twice the weight of the 57mm, it is much more than twice as destructive; the explosive content
of  the  bigger  round  is  proportionally  much  greater,  demonstrated  in  a  Canadian  Navy  Sinkex  (navy
exercise to practice sinking ships).  This used a decommissioned destroyer to demonstrate a variety of
weapons’ effects.  The ship was sent down by an Oto Melara 76mm in short order after a 57mm had
failed to achieve the same result.”

60   The  company  was  founded  in  1944  and  is  based  in  Karlskoga,  Sweden.  It  was  formerly  known  as  Bofors
Defence AB. It was acquired by BAE Systems in August 2005, and is now known as BAE Systems Bofors AB,
operating as a subsidiary of BAE Systems Land and Armaments.
61   Forecast International, “57mm vs. 76mm”.
- 68 -

Case Studies - Unpacking how defence spending affects the broader economy
Despite this, the Bofors 57mm is now catching up with Oto Melara, particularly in the USA (a previous
76mm user) where the Bofors has been selected for all three of the Coast Guard Cutter, DDG1000
and Littoral Combat Ship programmes.
To conclude on this aspect, the revealed preferences of European navies have been strongly in favour
of the Oto Melara systems. 62  In their absence, several European navies would have had to adopt what
they regard as a second-best alternative.
The second counterfactual – that Europe producers had not developed compact naval guns  - would
have had more far-reaching consequences.  The guns adopted by the US Navy - the Mk45 5-inch gun
produced by United Defense (now part of BAE Systems Land & Armaments) - weigh about four times
as much as the Oto Melara Super Rapid gun (21-28 tonnes compared to 7.5 tonnes), and fire a much
heavier shell (32.75 kg compared to 7.5kg), at a lower rate of fire (16-20 rounds per minute compared
to 120).
The US gun would probably have been too heavy for the smaller of the European vessels.  It would
have been necessary to deploy fewer, larger vessels, or to deploy less capable smaller vessels.
In any case, ships that are armed in this way would not have met the requirements of most European
navies.  As Anthony Williams explains,63 navies hold differing views about the role of gunnery.  During
the  1960s  two  completely  different  schools  of  thought  developed  among  the  world's  navies.    The
Americans and the British believed that missiles or carrier aircraft would be the primary armament in
dealing with both aircraft and enemy warships.  This meant that medium-calibre guns would mainly be
used  for  shore  bombardment  with  a  backup  role  in  dealing  with  smaller-ship  targets  not  worth  a
missile.  In fact both navies went through a period when they assumed that certain classes of warships
did not need a medium calibre gun at all.
“Other navies, including most of those in Western Europe, decided that the gun still had an important
general purpose role and would need to deal with targets such as fast missile boats, and even anti-ship
missiles as well as aircraft.
These philosophies led to different approaches in gun design.  The British and American requirement
did not call for a high rate of fire, so their mountings, the 4.5" Mk.8 and the 5" Mark 45, respectively,
achieve only 20-25 rpm but have the benefit of being simple and relatively light at around 25 tons, as
well as low on manpower demands.” The Europeans prefer high rates of fire (the Super Rapid’s 120
rpm and Creusot-Loire’s 90 rpm).64
In short, in the absence of the three rapid-fire compact guns that we have mentioned here, it is difficult
to  see  how  the  majority  of  European  navies  could  have  equipped  themselves  in  the  way  that  they
obviously prefer.  They would have faced the prospect of either a lesser capability, or greater expense
(more ships, or heavier ships armed with US or UK guns).
5.8.4  Conclusions
There are three main conclusions that can be drawn from this case study.
The  first  is  that  investment  in  defence  capabilities  can  sometimes  produce  spectacular  economic  as
well as defence benefits, when a Ministry of Defence identifies a military requirement that is shared by
a  number  of  nations,  and  then  commissions  a  national  supplier  to  develop  a  cost-effective  solution.

62   Oto  Melara’s  76mm  gun  was  preferred  to  the  French  100mm  naval  gun  both  for  the  joint  French/Italian
Horizon frigate and the FREMM frigate.
63   Anthony  G  Williams,  “Naval  Armament:  the  MCG  (medium  calibre  gun)  Problem”,  blog  posted  on  23
October 2011.
64   Anthony  G  Williams,  “Naval  Armament:  the  MCG  (medium  calibre  gun)  Problem”,  blog  posted  on  23
October 2011.
- 69 -

Case Studies - Unpacking how defence spending affects the broader economy
The resulting export sales, over several decades, far exceed the numbers required for that country’s
own defence requirements (in the case of Oto Melara’s 76mm naval guns, by a factor of three).
The second conclusion concerns the economic significance of an achievement of this kind.  It involves a
transfer  of  resources  from  the  manufacturing  sector  in  general,  i.e.  from  occupations  where  labour
productivity  is  probably  around  the  sector  average,  to  one  in  which  productivity  is  exceptional.    In
2010 and 2011, Oto Melara achieved a turnover per employee that was over one-third higher than
both that of the industry to which it belongs, and the average for Italian manufacturing.
The third conclusion concerns the way defence investment enables nations to discover solutions that
are cost-effective for them.  Purchasing defence systems “off-the-shelf” is often advocated as a way of
avoiding the enormous development costs and risks of new systems.  Whether or not this is the right
choice, there is usually a good case for examining this option, as a default position.  But sometimes the
“shelf” lacks systems that suit a nation’s circumstances and defence philosophy.  Compact naval guns
are  such  a  case.  The  relatively  small  ships  deployed  by  European  coastal  navies  require  capable,
compact and multi-purpose guns. Their absence would probably have required different types of ships,
resulting in a lower level of naval capability, or significantly higher costs.
5.9  R&T  Case  Study:  Intelligence,  Surveillance  and  Reconnaissance
Unmanned Air Systems
Intelligence,  Surveillance  and  Reconnaissance  Unmanned  Air  Systems  (ISR  UAS)  are  a  sub-group  of
Unmanned Air Vehicles (UAV) that focus on intelligence, surveillance and reconnaissance roles.
To date, the focus of research and development with respect to UAVs has been in the USA and Israel.
Indeed,  research  into  the modern  UAV  began  in  earnest  in  the  late  1970s,  heavily  influenced  by  an
Israeli  aerospace  engineer  named  Abe  Karem.65    Karem,  a  former  chief  designer  for  the  Israeli  Air
Force,  developed  the  Albatross,  which  could  remain  airborne  for  56  hours  compared  to  just  a  few
minutes for previous UAVs.
Comparatively  fewer  resources  have,  in  the  past,  been  devoted  to  UAV  research  within  Europe.
However, European countries such as Belgium, France, Germany, Italy, the Netherlands, and the UK
are also increasingly active in UAV research, design and production.66
5.9.1  Development of ISR UAS
ISR  systems  include  reconnaissance  satellites,  manned  aircraft  and  UAS.    They  provide  ‘top-level’
policy-makers  with  information  and  knowledge  about  the  military  capabilities  of  foreign  nations,  the
location of their key defence plants and industrial sites, the presence of weapons of mass destruction
and the plans of foreign countries and terrorist groups.  Military commanders rely on intelligence for
information  on  the  location  and  activities  of  enemy  forces  ranging  from  conventional  forces  to
terrorist units.
UAS are a relatively new technology that was developed in response to military demands, especially in
the USA.
They  were  first  used  in  the  Vietnam  conflict  but  their  use  was  limited  until  1990-1991  when  they
supplied location data for targeting precision guided munitions during the first Gulf War (Operation
Desert Storm).

65 This paragraph draws on “The dronefather” (The Economist, 1 Dec 2012) and an internal EDA summary of
UAV developments
66  Hatzigeorgopoulos,  M.  (2012),  “European  Perspectives  on  Unmanned  Aerial  Vehicles”,  European  Security
Review
- 70 -

Case Studies - Unpacking how defence spending affects the broader economy
UAS  have  now  become  an  essential  part  of  US  military  operations  and  have  expanded  with  the
conflicts in Iraq and Afghanistan.  Indeed, US Forces have increased the number of UAS deployed from
167  in  2002  to  more  than  6,000  in  2008.    There  was  a  corresponding  increase  in  US  defence
investment in UAS from $284m in 2000 to $2.5bn in 2008.  There was also a $4.1bn budget request in
2011.67  The Armed Forces of other advanced nations are similarly adopting UAS.
UAS can provide data at a much lower cost than satellites and have emerged as substitutes for them.
UAS vary in size, complexity and range from small systems which can be launched by a single soldier
for  short-range  tactical  missions  (‘seeing  over  the  hill’)  to  the  high-altitude  Global  Hawk  which  can
acquire much the same information as reconnaissance satellites.
The development of UAS has been subject to substantial cost escalation.  For example, there was a
development cost escalation of 284 per cent on the Global Hawk, 97 per cent on the Reaper, 80 per
cent on the Shadow and 60 per cent on the Predator.  The average cost escalation of 10 American
programmes was 37 per cent.68
Cost  escalation  has  been  just  one  argument  posed  by  critics  of  the  American  UAS  programmes.
Concerns have also been expressed about lengthy delays, wasteful duplication (as each Armed Force
has  purchased  its  own  UAS)  and  the  difficulty  of  anticipating  the  rapid  technical  changes  associated
with UAS and UAV.69
5.9.2  A new and emerging industry
UAS and UAV are an example of rapid technical change which has created a new industry with some
new entrants.  The situation bears some resemblance to  the early development of aircraft between
1903 and 1918 when a variety of new firms were created, each developing and testing different types
of aircraft.  That industry expanded with major military orders during World War I.
Overall,  the  United  States  UAS  and  UAV  industry  has  not  been  dominated  by  the  traditional  and
established aerospace companies.  The industry has seen numerous new entrants, some of which are
new small firms while others are new divisions of established companies from other industries.
In the US market, new entrants include independent small firms such as ShadowAir, ISR and Arcturus
UAV.  Other small firms specialising in UAS/UAV have been acquired by established aerospace firms.
For example, Insitu Inc – which built the successful ScanEagle – was acquired by Boeing in 2008.
IT  companies  such  as  the  Computer  Science  Corporation  and  DRS  Technologies  have  entered  the
market.    The  latter  of  these  supplies  the  Sentry  and  was  acquired  by  the  Italian  defence  company,
Finmeccanica  in  2008.    Similarly,  research  and  engineering  companies  such  as  Applied  Research
Associates and Altavian have entered the market.
5.9.3  The industry’s technology
There  is  an  absence  of  well-documented  studies  on  the  technologies  required  to  produce  UAS.
However, some indications can be deduced from the firms involved in the industry and the missions of
their UAS.
Some companies are IT, defence electronics, and research and engineering firms (CSC; ARA); others
are  established  aerospace  companies  (Northrop  Grumman).    UAS  technologies  for  ISR  services

67   CRS  (2013)  “Intelligence,  Surveillance  and  Reconnaissance  (ISR)  Acquisition:  Issues  for  Congress”,
Congressional Research Services, US Congress, Washington DC, April.
68   CRS  (2013)  “Intelligence,  Surveillance  and  Reconnaissance  (ISR)  Acquisition:  Issues  for  Congress”,
Congressional Research Services, US Congress, Washington DC, April, pages 11-12
69   CRS  (2013)  “Intelligence,  Surveillance  and  Reconnaissance  (ISR)  Acquisition:  Issues  for  Congress”,
Congressional Research Services, US Congress, Washington DC, April.
- 71 -

Case Studies - Unpacking how defence spending affects the broader economy
include miniaturisation, guidance systems, the development of small and long-endurance engines, small
and  accurate  cameras,  sensor  technology,  data  collection  and  analysis,  communication  links  and
simulation technologies.
5.9.4  Civil applications
The  military  applications  of  unmanned  systems  for  ISR  missions  will  continue  to  expand  as  the
technology develops.  Unmanned systems will substitute for manned aircraft, especially for ‘dangerous,
dirty and dull tasks’.
There  are  also  extensive  civil  applications  of  unmanned  ISR  systems.    Known  examples  include:
homeland security; search and rescue; border and coastal patrol and surveillance; domestic policing;
agricultural, forestry, fisheries and ocean management; pipeline security; weather information; strategic
infrastructure and sensitive facilities; and the policing and management of remote locations.
Unmanned  aerial  ISR  systems  provide  new  and  valuable  information  and  can  replace  costly  labour-
intensive  operations.    For  example,  unmanned  aerial  ISR  systems  can  access  forests  in  remote
locations and can fly through forest fires (a task which would be too dangerous for manned aircraft)
and so can provide support to fire-fighting services.  They can also perform long-range inspections of
power lines, pipelines,  roads, hydro-electric facilities and off-shore wind farms.  Further applications
include transferring some of the aerial technology to unmanned ground and unmanned marine systems
(e.g. underwater inspection).
5.9.5  Future prospects
The military demand for unmanned aerial ISR systems will decline following the end of the Afghanistan
conflict in 2014.  The reduced demand will be especially significant in the USA with specific economic
impacts  on  its  UAS/UAV  industry,  together  with  the  general  reduction  in  US  military  expenditure
following the economic and fiscal crisis.
For  the  industry,  reduced  demand  will  mean  job  losses,  plant  closures,  the  exit  of  some  firms  and
mergers between firms.  The industry will also respond by seeking new market opportunities including
export markets and new civilian markets for UAS and UAV.
5.10 Defence aerospace technology transfer and spin-offs
5.10.1 Background
There  is  no  shortage  of  examples  of  spin-offs  from  the  defence  sector  of  the  aerospace  industry.
Technical advances in military aircraft have been transferred and applied to civil aircraft; and the US
space  agency,  NASA,  has  identified  an  impressive  list  of  spin-offs  from  the  US  space  programme.
Examples  of  spin-offs  from  military  aircraft  include  radar,  the  jet  engine,  flight  control  systems  and
composite materials.  Spin-offs from the US space programme include light-emitting diodes (LEDs), by-
pass  operations  and  a  range  of  applications  in  health  and medicine, transportation,  public  safety  and
computer technology.
Some  of  these  technologies  have  been  applied  to  markets  outside  the  aerospace  industry.    For
example,  aerospace  technology  has  been  applied  to  motor  cars,  including  Formula  1  racing  cars
(lightweight materials; anti-skid braking; Global Positioning Systems).  Helicopter blade technology has
been  applied  to  the  turbine  blades  used  for  wind  farms;  jet  engine  technology  has  led  to  the
development of new materials able to withstand high temperatures; and jet engines have been used for
marine propulsion.
- 72 -

Case Studies - Unpacking how defence spending affects the broader economy
Given  the  substantial  number  of  spin-offs  from  defence  aerospace,  it  is  not  possible  to  provide  a
comprehensive  review  within  this  report.    Therefore,  this  section  reviews  technology  transfer  and
spin-offs from Unmanned Air Vehicles and satellite navigation (including Global Positioning Systems and
other Global Navigation Satellite Systems).
5.10.2 Unmanned Air Vehicles (UAVs)
UAVs, also known as unmanned aircraft systems (UAS) or drones, are a new aerospace technology
which  offers  opportunities  for  replacing  manned  aircraft.    UAVs  comprise  an  unmanned  aircraft,  a
control  system  usually  with  a  ground  control  station,  a  control  link  and  other  support  equipment.
Whilst they lack a human pilot, UAVs require substantial inputs of human and physical capital (e.g. to
operate the ground control stations).  They have been used extensively by all branches of the armed
forces and by state intelligence agencies.
The military role of UAVs is expanding rapidly, especially as rapid technical change is leading to greater
capability  being  installed  in  smaller  airframes.    The  military  role  of  UAVs  includes  intelligence,
surveillance  and  reconnaissance  (ISR)  missions,  strike  missions,  destruction  of  enemy  air  defences,
communications, and search and rescue roles.  Some UAVs are small enough to be hand-launched and
used by ground troops to obtain intelligence about towns and villages.  Unit costs of UAVs range from
a  few  thousand  Euros  for  small  hand-launched  models  to  millions  of  Euros  for  larger  and  more
advanced versions (e.g. Global Hawk).  Some UAVs are capable of long endurance:  for example, the
Predator UAV has achieved flights of some 40 hours.
As  an  example  of  technology  transfer,  UAVs  are  developing  new  civilian  uses.    These  include  land
management;  remote  inspection of  road  and  rail  earthworks;  monitoring  coastal  erosion;  forest  fire
detection  and  monitoring;  disaster  relief;  pipeline  monitoring;  traffic  congestion;  conservation  of
wildlife  regions;  and  oil,  gas  and  mineral  exploration.    In  their  civilian  use,  UAVs  are  involved  in
scientific research (e.g. of hurricanes) as well as domestic policing and homeland security, and in search
and rescue operations.
5.10.2.1 Applications of UAV technology
UAV technology has extensive applications, both in spin-offs and dual-use applications.  The following
examples are just a small number of the technologies which have resulted from UAV developments:
  the development of simulator training;
  composite  materials;
  cameras and imaging systems (e.g. the development of smaller infrared cameras);
  data and communications;
  ground control systems and equipment;
  navigation and guidance systems;
  robotics;
  the delivery of electric power over long distances via lasers;
  cloud-cap technology;
  rapid communications and intelligence, surveillance and reconnaissance capabilities;
  measurement  systems (e.g. for inspecting  complex parts  such  as  aero-engine blades, automotive
blocks and gears);
  the development of autonomous technology; and
- 73 -

Case Studies - Unpacking how defence spending affects the broader economy
  applications to the aerospace and medical equipment sectors.
5.10.3 Satellite Navigation
Satellite  navigation  comprises  Global  Positioning  Systems  (GPS)  and  Global  Navigation  Satellite
Systems  (GNSS)  where  there  is  global  coverage.    These  systems  comprise  a  set  of  satellites  and
ground-based stations.  They require a rocket launcher to place the satellite into its space orbit.
The  USA  and  Russia  operate  global  GNSSs  and  Europe  is  developing  its  alternative  Galileo  system.
Galileo will allow free access to basic services, but high precision capabilities will only be accessible to
paying commercial customers and to military users.  Other nations such as China, India and Japan are
developing regional satellite navigation systems under national control and for their national region.
Originally,  satellite  navigation  was  developed  for  military  uses  (e.g.  precision  delivery  of  weapons;
direction of military forces and location of enemy forces; disabling enemy satellite navigation systems).
Over time, however, the technology has come to be used in many civilian applications.
5.10.3.1 Spin-offs from Satellite Navigation
Not surprisingly, some of the spin-off technologies from satellite navigation are similar to those from
UAVs.  They include a complete range of navigation uses in the land, sea, air and space domains.  Spin-
off technologies from satellite navigation include:
  surveying, mapping and exploration (e.g. oil exploration);
  precision tracking:  examples include GNSS equipment for the visually-impaired and the tracking of
criminal offenders on parole;
  weather forecasting;
  scientific research and experiments.  For example, the greater understanding and observation of
natural disaster events (e.g. earthquakes);
  road safety, traffic management and road pricing systems;
  robotics;
  improving the efficiency of agriculture (e.g. precision agriculture and driverless tractors);
  marketing;
  removal of unexploded ordnance;
  satellite phone networks; and
  improved aircraft safety through better navigation and landing aids.
5.10.4 Facilitating spin-offs
The European Space Agency (ESA) publishes a list of technologies transferred from its space activities.
It suggests that space technologies are being used to enhance the life and wellbeing of citizens through,
for example, healthcare products, improved waste management, water recovery, safety improvements
and new sports equipment in motor racing, sailing, skiing and cycling.
The  ESA  has  created  a  specialist  agency,  the  Technology  Transfer  Programme  Office,  which  has
responsibility for technology transfer.   This Office facilitates technology transfer through technology
brokers, national initiatives and competitions.  For example, the Office organises an annual competition
to promote the wider business application of satellite navigation technology.  The competition (known
as the Galileo Masters Competition) invites individuals and teams to submit ideas for the creation of
- 74 -

Case Studies - Unpacking how defence spending affects the broader economy
new  businesses  in  the  emerging  satellite  navigation  market.    Previous  winners  of  the  competition
included  a  novel  application  to  guide  visitors  around  indoor  exhibition  centres,  a  system  for  the
accurate positioning of offshore ships and a system to locate water pollution.  Other previous winners
included  a  navigation  device  for  blind  and  visually-impaired  persons,  entertainment  and  tracking
devices, and a management system for automotive accidents with hazardous cargo.  The 2013 Satellite
Navigation Competition invites bids in six areas concerned with high precision, smart moving, safety
and security, public and social services, mobile location-based services and industry applications.
The US space agency, NASA, has also identified a list of spin-off technologies from its activities.  These
include  health  and  medicine,  transportation,  public  safety,  consumer  goods,  energy  and  the
environment, information technology and industrial productivity.  NASA estimated that by 2012, space
spin-offs  had  generated  $5bn  in  revenues  and  saved  $6.2bn  in  costs.70    Other  US  studies  of  the
economic benefits of NASA spending have estimated discounted rates of return from 33 per cent to
43 per cent; multiplier effects of 7 to 23.4; and employment multiplier effects of about 8 to 19 (these
are jobs created for every $1m (2009 dollars) invested in NASA).71
5.10.5 Conclusion
A  list  of  examples  of  spin-offs  from  UAVs  and  space  and  satellite  navigation  are  useful,  but  not
sufficient for developing a convincing economic case for state investment in these activities.  There is a
general absence of independent published economic studies of spin-offs in defence aerospace markets.
Economic analysis suggests that spin-offs are external economic benefits.  In the presence of external
benefits, private markets are likely to ‘under-invest’ in such socially-desirable activities and so there is a
case for state intervention in such activities.  However, this only represents a general case for state
intervention  in  R&D  markets.    The  case  for  state  intervention  in  such  specific  markets  as  defence
aerospace and space markets needs more supporting analysis and data.
Economic  studies  of  spin-offs  need  an  underlying  economic  model  together  with  an  accurate  and
reliable database using a common methodology and assumptions.  An economic model is required to
identify the various causal determinants of economic benefits.  Next, there is a need to identify the
economic benefits of spin-offs and how they are to be measured.  For example, the economic benefits
of  spin-offs  might  comprise  revenue  generated,  jobs  created  by  numbers  and  skills,  productivity
improvements,  lives  saved  and  life  improvements.    A  mere  listing  of  such  economic  benefits  would
produce  a  list  of  non-comparable  benefits  (e.g.  numbers  of  jobs  and  revenue  generated)  whereas  a
proper  benefit  analysis  requires  that  all  the  economic  benefits  be  valued  in monetary  terms  so  that
they are comparable.  Finally, there is a need to identify the contribution of a specific R&D programme
to  the  creation  of  economic  benefits,  and  whether  such  benefits  would  have  emerged  without  the
specific R&D programme.
5.11 Section Appendix:  Economic Rents
Earlier sections of this report focused on estimating the impact of a one-off €100m investment in the
EU  defence  sector  and  comparing  these  impacts  with  those  that  would  arise  if  an  equivalent
investment were to be made in alternative sectors, whilst certain case studies suggested that there are
rents in some parts of the defence sector.  In this appendix, we build on that analysis by how defence
investments  can  create  economic  rent for the  EU  as  a  whole,  rather than (as  is  more  normally the
case) such rents constituting an inefficient transfer from consumers to producers.

70   NASA, Spin-Off, 2012.
71   Comstock,  D,  et  al  (2010),  “A  structure  for  capturing  quantitative  benefits  from  the  transfer  of  space  and
aeronautics technology”, International Astronautical Congress, Cape Town South Africa.
- 75 -

link to page 80 link to page 81 Case Studies - Unpacking how defence spending affects the broader economy
‘Economic  rent’  is  a  factor’s  earnings  in  excess  of  what  they  could  use  in  the  next-best  use  (their
‘opportunity cost’).  For example, if an industry’s cost of capital is 10 per cent and it earns 20 per cent
on capital employed of €1bn, it could be said to earn an annual economic rent of €100m.72
Economic rent is an indication  – provided that markets reallocate resources fairly smoothly  – of an
industry’s net contribution to the economy.  If this industry ceased to exist this is what the economy
would lose, once it had adjusted to its disappearance.  The industry’s assets would be redeployed and
could be expected to earn a return which is typical of the economy (10 per cent, the cost of capital).
GDP would then be lower by €100m a year (the economic rent that the industry had earned before it
ceased to exist).
While it has not been possible to make meaningful comparisons of rates of return on capital employed
within  this  study  –  in  part  because  definitions  of  ‘capital  employed’  differ  both  between  and  within
countries – we have sought to draw lessons from the limited data on profit margins that are available.
First, we obtained data on the profit margins of the 17 largest European defence companies in 2009.
These data are shown in Table 5.21.
Table 5.21: Profit margins of major European defence companies (2009)
Arms sales
Company
Country
Arms sales
Total sales
Total profit  Profit/ total
($m)
($m)
as % of total
($m)
sales
sales
BAE
Systems
UK
33,250
34,914
95
-70
0%
Finmeccanica
Italy
13,280
25,244
53
997
4%
Thales
France
10,200
17,890
57
178
1%
DCNS
France
3,340
3,342
100
179
5%
Saab
Sweden
2,640
3,220
82
91
3%
Rheinmetall
Germany
2,640
4,750
55
-72
-2%
Cobham
UK
2,260
2,929
77
290
10%
Babcock
UK
2,010
2,952
68
169
6%
Navantia
Spain
1,980
2,197
90
-115
-5%
QinetiQ
UK
1,770
2,532
70
-99
-4%
Krauss-
Maffei-
Germany
1,630
1,715
95
211
12%
Wegmann
Groupe
Dassault
France
1,360
4,751
67
438
9%
VT Group
UK
1,240
1,950
64
328
17%
Nexter
France
1,230
1,232
100
196
16%
Ultra
Electronics
UK
810
1,014
80
122
12%
Chemring
Group
UK
750
785
96
109
14%
Patria
Finland
660
749
88
24
3%
Total

81,050
112,166
72
2,976
3%
Source: SIPRI.  Considers the largest companies for whom defence accounted for more than 50 per cent of sales.
The two most interesting insights that can be drawn from this table are:
  the  largest  of  these  companies  traded  on  very  modest  margins  in  the  year  2009  (although  it  is
worth noting that BAE Systems’ profit margins had recovered by 2010 – see Table 5.22); and
  six specialists  (Cobham,  VT, Nexter, Krauss-Maffei-Wegmann, Ultra  Electronics  and    Chemring)
were highly profitable, with margins in excess of 10 per cent, even in what was a bad year for the
industry.
These figures suggest that the economic rent earned by defence companies can be substantial.

72   Calculated as GDP loss = (20%-10%)*€100bn = €100m
- 76 -

link to page 81 link to page 80 Case Studies - Unpacking how defence spending affects the broader economy
We have also considered the potential of company accounts for assessing the economic rent earned
by  the  defence  sector.    A  limitation  of  company  accounts  is  that  they  do  not typically  segment  the
company’s activities in ways that we would wish, so that it may be difficult to assess the profitability of
the defence-related activities of companies such as EADS that supply both defence and civil markets.
Another consideration is that if EU defence companies do succeed in earning economic rent, do they
do  so  in  their  respective  domestic  market,  in  the  EU  market,  or  in  non-EU  markets?    It  could  be
argued that any rents that are earned within the EU do not add to the EU’s economic welfare.  They
are  simply  transfers  within  the  EU,  from  its  taxpayers  to  the  defence  companies.    Therefore,  the
economic rent that is of primary interest in the context of this study is that which is earned in non-EU
markets.
The accounts published by BAE Systems are helpful in this context.  BAE Systems is both a specialised
defence company and it provides an exceptional amount of segmental detail in its accounts.
Table 5.22 shows the profit margins of BAE systems by market segment.  The figures show that BAE
Systems' margins on sales on its international Platforms & services operations in 2010 and 2011 were
more than double those on their combined US and UK Platforms and Services operations.
These figures suggest that BAE systems earned some economic rent from its international operations.
Given the figures reported in Table 5.21, it would not be surprising if many other defence companies
also earned economic rent on their overseas operations.
Table 5.22:  BAE Systems’ profit margins by market segment
Revenue from
Market segment
Reported profits
Margin on sales
external customers

2011
2010
2011

£m
£m
£m
Electronic systems
2,527
2,850
371
Cyber & intelligence
1,377
1,173
72
Platforms & services (US)
5,176
7,497
256
Platforms & services (UK)
5,942
6,154
592
Platforms & services (US
& UK)
11,118
13,651
848
Platforms & services
2,748
3,306
439
(International)*
Total
17,770
20,980
1,730
Source: BAE Systems Annual Report 2011, pages 120-122.
* The Group's business in Saudi Arabia, Australia, India, and Oman, together with its 37.5 % interest in MBDA
- 77 -

link to page 83 R&D in the Defence Sector
6  R&D in the Defence Sector
Previous  chapters  in  this  report  have  presented  a  quantitative  assessment  of  the  macroeconomic
benefits of investing in the defence sector relative to equivalent investments in other sectors that are
heavily funded by the public sector.
In this chapter, we build on that analysis by explaining when and why it is appropriate for defence to
receive  R&D  funding  from  the  public  sector  and  how  this  funding  acts  as  a  spur  to  private  sector
investment.  In particular, we first examine the scale of R&D expenditure in the defence sector.  We
then describe two stylised models of R&D funding and explain how the features of the defence sector
influence  the  choice  of  funding  model.    We  then  complement  that  discussion  with  evidence  from  a
survey  of  stakeholders  on  the  importance  of  R&D  to  the  performance  of  defence  sector  and  the
funding models that are used to support R&D activities.
We intentionally focus on research that is conducted by individual companies as this is the most likely
to be affected by an investment of €100m in the defence sector.  However, we acknowledge that the
range of defence research is far broader than that considered here and can involve collaboration both
between companies and across countries / Member States.
The discussion in this chapter is significantly more qualitative in nature than that of preceding chapters
because it seeks to explain the rationale for a €100m public investment in the defence sector rather
than simply assuming that such funding would be available.
6.1  Defence R&D
R&D is a key component of defence expenditure due to its many short-term and long-term impacts on
a nation’s defence capabilities and its economy.  Figure 6.1 shows average defence R&D expenditure,
by category, for each participating Member State between 2008 and 2010.
As indicated in the Figure, R&D spending is concentrated in three Member States  – France, the UK
and Germany.  Taken together, these account for more than 90 per cent of total R&D spending by the
participating Member States.  Germany devotes a third of its R&D spend to R&T – the proportions for
France  and  the  UK  are  a  quarter  and  a  fifth.    Other  Member  States  spending  material  amounts  on
defence R&D include Spain, Italy, Sweden, Poland and the Netherlands.

- 78 -

R&D in the Defence Sector
Figure 6.1:  Average defence R&D spend by participating Member States, 2008-2010 (€m)

6.2  R&D Funding
6.2.1  Two Models of R&D Funding
It is useful to distinguish between two broad models of research and development funding.73  In the
most  common  model,  companies  or  individuals  have  ideas,  research  them,  prove  the  concepts
involved, and develop them into final products, and it is only once a final product is available that it is
sold to customers.  This is the model, for example, in the mobile phone sector.  Apple conceived of
the iPhone, developed working iPhones, all funded from their own internal research budgets, then sold
them to customers.  Let us refer to this as the “seller-funded research model”.
In an alternative model, the potential customer for a product or idea commissions research into the
feasibility of the product’s development, and may then go on to commission and fund testing and the
production  of  final  products.    This  model  is  common  for  many  forms  of  analytical,  as  opposed  to
product, research — e.g. much economics research is specifically commissioned by one buyer, rather
than the researchers producing a report that they then attempt to sell to multiple interested parties.
It  is  also  the  model  used  sometimes  in  response  to  specific  disease  outbreaks  —  e.g.  government
health agencies funding research into cures for a specific strain of bird ‘flu.  Let us refer to this as the
“buyer-funded research model”.
In the defence sector the buyer-funded research model is much more common than the seller-funded
model.    Governments  usually  specifically  commission  and  fund  the  research  and  development  of

73   We note that other models of funding exist, including mixed models, third-party funding models, government
funding without foreseen purchase etc.  For the purpose of this report we have chosen to focus on the two
most extreme cases – complete buyer funding and complete seller funding.  This approach makes  it easier
both to highlight the key differences between models and to highlight the circumstances in which each model
is most appropriate.  Little is lost by focusing on the extremes since inferences can be drawn by comparing
the  analysis  of  the  extremes.    For  example,  a  mixed  model  is  likely  to  be  appropriate  where  the  market
context is somewhere in between that described for the seller-funded and buyer-funded models.
- 79 -

R&D in the Defence Sector
advanced  technology  equipment  such  as  advanced  combat  aircraft,  specialised military  transport  and
special  mission  aircraft,  main  battle  tanks,  surface  warships  and  nuclear-powered  submarines.
However,  some  commentators  on  defence  equipment  projects  claim  that  such  projects  could  and
should be funded according to the first model — i.e. private contractors researching, proving concept,
and  developing military  equipment  via their  own funding  (like  Apple  and  the  iPhone),  and  only  then
selling finished products to governments.  In this section we consider the relative merits of these two
models of research funding in the defence sector.
6.2.2  Broad  characteristics  of  seller-funded  versus  buyer-funded  research  model
markets
Seller-funded markets will tend to have the following features:
  There are multiple potential buyers.
  Potential buyers are relatively uncertain, in advance of viewing a final product, of what is technically
feasible, what they want, and how much they would be prepared to pay for it.
  Final  prices  paid  include  an  economic  component  which  compensates  for  the costs  of  research
that exceed the actual costs incurred in researching the specific product sold.  The reason for this
is  that  the  rewards  of  a  successful  product  must  also  compensate  for  the  risks  of  researching
unsuccessful products.
Buyer-funded markets will tend to have the following features:
  there is one overwhelmingly majority buyer;
  buyers  have  specific  narrow  needs,  know  in  some  detail  what  final  product  they  would  like  to
purchase and approximately how much they would be prepare to pay for it, and have some sense
of what ought to be technically feasible; and
  final prices paid for research fund only the actual research costs incurred.
We can illustrate these features by contrasting the extent to which research in the pharmaceuticals
industry follows the seller-funded model and to what extent the buyer-funded model.
In the case of most major pharmaceuticals products used in the developed world, there are multiple
potential buyers — a new pharmaceuticals product of wide developed-world application can be sold to
health  insurers,  charitable  hospitals,  and  government  health  agencies  in  multiple  countries.    These
potential  buyers  have  a  broad  range  of  needs  —  there  are  many  diseases  that  they  would  be
interested,  in  principle,  in  treating  better,  rather  than  just  one  or  two.    The  potential  buyers  are
relatively  uncertain  regarding  what  is  technically  feasible  in  any  given  timescale  —  it’s  not  clear
whether the easiest drug to develop next will be one that reduces back pain or one that cures MRSA.
The efficacy of any treatment, even if it worked, is uncertain in advance (how completely will that back
pain be reduced?) and thus there is uncertainty concerning how much it would be worth paying.
As  a  consequence  of  these  features,  the  most  natural  model  for  most  major  developed  world
pharmaceuticals is seller-funding of research and development.  As a consequence of that, and the high
uncertainty of pharmaceuticals products (on some estimates one must research 10,000 potential drugs
to  produce  one  wide-selling  one),  when  a  new  pharmaceutical  is  successful  it  produces  what  are
referred as “blockbuster” returns, vastly exceeding the costs of researching an individual drug.
But this is not the only model of pharmaceuticals research.  When there are epidemic threats (e.g. a
particular new strain of bird ‘flu) or diseases/disorders of high public policy significance (e.g. malaria),
there  may  be  just  one  buyer  (government)  that  knows  precisely  what  it  needs.    In  such  cases
governments  often  commission  and  fund  specific  research,  sometimes  through  universities  and
sometimes through companies.
- 80 -

R&D in the Defence Sector
6.2.3  Nature of defence equipment projects and markets
Armed  with  our  understanding  of  why  some  research  is  seller-funded  and  other  research  buyer-
funded, we can understand better the models used in the defence sector.
In  the  defence  sector,  there  can  be  multiple  potential  buyers  —  e.g.  governments  in  a  number  of
countries  —  but  it  will  often  be  the  case  that  (a)  one  buyer  (or  group  of  buyers  agreeing  amongst
themselves  all  to  purchase  the  same  technology)  will  comprise  the  overwhelming  majority  of
purchases — often the national defence agency of the country of the defence supplier; and (b) more
fundamentally,  other  buyers  will  not  purchase  a  product  that  has  not  been  endorsed  by  being
purchased by the national defence agency of the country of the defence supplier.  In combination, this
means  that  although  in  due  course  there  may  be  several  potential  buyers,  everything  is  contingent
upon satisfying one key buyer.
The  key  buyer  typically  has  specific  known  needs  that  arise  from  its  strategic  plans.    It  wants  a
particular  sort  of  plane  or  ship  or  military  vehicle.    It  may  not  rule  out  considering  innovative  new
ideas initiated by the defence contractor itself, but it is much less often interested in novel ideas than
in the high-quality delivery of what its own internal analysis suggests is possible.  The key buyer might
also want to retain the option of the fruits of research not initially being shared with others — a new
leap forward in some defence technology might provide a strategic advantage for that country that it
does  not  wish  to  give  up.    The  key  buyer  is  likely  to  have  an  interest  in  ensuring  that  its  national
defence companies remain active for precisely these reasons.
As  a  consequence  of  the  above,  it  is  unsurprising  and  natural  that  advanced  technology  equipment
projects research in the defence is often buyer-funded.  Although some forms of defence research may
well be suitable for seller-funding, it could be highly problematic were the seller-funding model to be
imposed universally.  For example, some defence projects might involve research that would only be of
relevance  and  value  to  one  specific  buyer  —  e.g.  the  technology  required  for  nuclear-powered
submarines  is  only  of  value  on  such  submarines  since  there  are  not  many  alternative  uses  for  such
technologies.
Were  such  projects  relatively  inexpensive  and  the  costs  relatively  certain,  perhaps  a  defence
contractor could diversify sufficiently that seller-funded research which did not produce a final product
the buyer wanted and this  could be offset against successful cases.  But much defence equipment is
costly  and  subject  to  uncertainty  over  costs.    For  example,  unit  production  costs  for  an  advanced
combat aircraft are some €100m; an electronic platform aircraft (e.g. for airborne early warning) might
cost  some  €500m  per  unit;  and  a  nuclear-powered  attack  submarine  might  cost  some  €1.8bn  per
copy.  Development costs are a multiple of unit production costs.  For an advanced combat aircraft,
total development costs are at least 100 times unit production costs and might be 200 times.  For such
an  aircraft,  development  costs  might  be  €10-20bn.    These  are  large  magnitudes  to  be  funded  by  a
private  firm  for  one  customer.    High  costs  also  mean  that  few  units  will  be  purchased  and  so
production runs will be small.
The technical requirements of advanced defence equipment can also create great uncertainty.  Neither
the  buyer  nor  the  contractor  can  anticipate  correctly  all  future  technological  unknowns  and  their
ability  to  resolve  them  at  reasonable  cost  (i.e.  there  exist  internal  uncertainties).    There  are  also
external  uncertainties  associated  with  changing  threats,  the  emergence  of  new  substitutes  and  a
governments’ continued willingness to purchase the equipment.
When  projects  are  very  costly  to  reach  final  product  stage,  seller-funding  would  leave  firms  highly
vulnerable to a form of what economists call “non-renegotiation-proofness”:  the buyer could indicate
a general interest in a product and a likely price it would be prepared to pay, then once all the sunk
costs of research had been borne, the buyer could significantly drop its offer price at the last moment.
This could leave the defence contractor with the invidious choice between accepting a bad return or
entering bankruptcy.  Being vulnerable to such threats might mean that very little advanced research
- 81 -

R&D in the Defence Sector
would be done in the defence sector on a seller-funded model, except insofar as a government could
credibly commit to maintaining a repeat relationship with researchers (e.g. to keep the researcher in
business),  even  if  circumstances  changed  (an  arrangement  likely  to  introduce  its  own  alternative
inefficiencies).
6.2.4  Implications for private venture funding
As  noted,  this  analysis  does  not  mean  that  there  will  never  be  seller  funding  of  defence  equipment
projects.  Indeed, of all respondents to our survey, 80 per cent have developed new defence systems
on  a  private  venture  basis,  independent  from  the  national  MOD.    The  value  of  products  developed
through a private venture can be substantial – one respondent stated that one of the products it had
developed on this basis had achieved sales of €40m.
By  identifying  the  features  of  defence  markets  which  mean  that  seller  funding  is  less  efficient,  it  is
possible to identify the characteristics that a defence equipment project should have if seller funding is
to  be  available.    Specifically,  we  consider  that  seller  funding  might  be  available  where  defence
equipment is not too costly and risky, where it involves few new technical challenges and where there
are substantial export market opportunities.
A good example of seller funding is the BAE Hawk.  This was originally sold to the UK RAF with an
order  for  175  aircraft  in  1972.    BAE  subsequently  used  its  own  funds  to  develop  an  advanced  jet
trainer and light combat aircraft for export markets.  By early 2013, sales and orders for the Hawk jet
aircraft totalled almost 1,000 units (including total sales to the UK of 203 units).  Another example of
the seller-funding of major defence equipment concerned UK main battle tanks.  Vickers-Armstrongs
developed and produced a main battle tank – the Vickers MBT – which was a private venture project
aimed  at  export  markets.   This  tank  was  simple  and  low-cost  and  produced  over  the  period  1963-
1984.  It was sold to a number of African nations and a total of 331 units were produced (including all
variants).
Interestingly, both the Vickers tank and the Hawk jet trainer were developed from previous successful
designs where the technical problems had been resolved (Centurion tank and Hunter jet fighter).  This
behaviour  further  supports  the  need  for  buyer  funding  of  research  and development  in  the  defence
sector:  seller funding may not have been secured had the initial public investment in the designs not
been available.
6.3  Stakeholders’ Perspectives on Defence R&D
As discussed above, a defining characteristic of the defence sector is its dynamism and the significant
role played by R&D in the sector’s past, current and future development.  In order to gain a  better
understanding of the importance of R&D to participants in the defence sector, we invited stakeholders
to take part in an online survey.
A link to the online survey was initially sent to the 183 email addresses of companies involved in the
air, land and sea defence industries using contact details provided by the EDA.  The initial email was
not delivered to 11 email addresses and so the total number of contacts made was 172.
To  ensure  that  the  greatest  possible  response  rate  was  achieved,  email  reminders  were  sent  to  all
potential respondents and the initial completion deadline was extended.  In addition, the EDA sent a
number of emails to its industry contacts to emphasise the importance of the study to the Agency.
In  total,  we  received  26  responses  (15  per  cent of those  successfully  contacted)  but  some of these
were incomplete.  While the absolute number of responses may seem to be small, we understand that
this  is  typical  of  surveys  in  the  defence  sector.    Nonetheless,  due  to  the  small  sample  size,  any
conclusions drawn from this questionnaire should be treated with care.
- 82 -

link to page 87 link to page 88

R&D in the Defence Sector
6.3.1  Characteristics of respondents
Of the 26 responses received, 21 defence companies identified the sector(s) in which they operate and
their home Member State.  Responses were received from companies based in nine Member States.
As shown in Figure 6.2, more than half of respondents operate in the land sector, 10 in the air sector
and eight operate in the sea sector.  Some respondents operate in more than one sector.
Figure 6.2:  Defence sectors in which respondents operate

Responses were received from a diverse group of defence companies.  The smallest company employs
fewer than 10 people and achieved defence sales of less than €1m in the most recent year for which
data  were  available.    By  contrast,  the  largest  respondent  employs  more  than  100,000  people  and
achieved defence sales of approximately €17bn.
With respect to defence export sales, it is clear that the importance of exports relative to domestic
sales  differs  significantly  between  respondents.    Interestingly,  based  on  the  responses  received  it
appears that exports to non-EU countries are more important to companies that operate in all three
defence sectors than to those that operate in fewer sectors.
6.3.2  Sources of funds
As shown in Figure 6.3, responses to our survey suggest that the most important source of funding for
R&D is the companies’ own resources.  Domestic government is the second greatest source, although
this is generally more important for larger companies.  European Commission grants, other overseas
funds and other domestic businesses contribute very little to defence R&D funding.
- 83 -

R&D in the Defence Sector
Figure 6.3:  Percentage of R&D funds from certain sources

6.3.3  R&D activities
In order to understand the importance of different types of R&D to the future success of the business,
we asked respondents to rate the importance of input-focused and output-focused R&D, respectively.
We  defined  input-focused  R&D  as  that  which  aims  to  introduce  new  or  substantially  changed
production processes and output-focused R&D as that which aims to introduce new or substantially
improved defence systems.
A majority of respondents believe output-focused R&D is critical to the success of their businesses.
Only one respondent stated that it is not important; this firm did, however, state that input-focused
R&D is important.
In contrast, only 40 per cent of respondents rated input-focused R&D as very important to the success
of their business.  All those that stated that input-focused R&D was not important to their business
reported that output-focused R&D is important.
These findings suggest that R&D is important to all those that operate in the defence sector, although
the type of R&D that is considered most important to the success of the firm is not consistent across
the industry.  The findings further suggest that firms that operate in more than one sector generally
consider  both  input-  and  output-focused  R&D  to  be  critical  to  the  success  of  their  business,  while
those that operate in only one sector may consider one type of R&D to be relatively less important.
- 84 -

link to page 90

R&D in the Defence Sector
Figure 6.4:  Importance of input-focused R&D and output-focused R&D

We then asked respondents to specify the number of new defence systems that had been developed
by the company over the past 10 years, and the total value of these systems.
Respondents generally found it difficult to answer this question, and so the response rate was relatively
low  and  the  range  of  responses  extremely  wide.    With  respect  to  the  number  of  new  systems,
responses ranged from zero to “more than 50 platforms and large systems”.74  Estimated values ranged
from €2m to more than €2bn.
6.3.4  Pattern of sales of new defence systems
6.3.4.1  Sales to the public sector
The objective of any R&D activity is to develop a product or process that can improve the profitability
of the company.  Input-focused R&D seeks to improve production processes and so should lead to a
reduction in manufacturing costs, thereby improving profitability by influencing the supply-side of the
market.  Output-focused R&D aims to introduce new or substantially improved defence systems and
so aims to secure an increase in sales, thereby improving profitability by influencing the demand side of
the market.
With  respect  to  output-focused  R&D,  the  process  by  which  innovations  developed  through  R&D
activities reach the market is of interest to this study since new products and defence systems would
be worth little to a company if sales are not achieved.  We asked stakeholders to explain both how
their  products  reach  the  market  and  to  explain  the  extent  to  which  the  national  MOD  (which  we
supposed  would  be  a  key  route  to  market  in  many  cases)  influenced  exports  of  new  systems  and
products.
Figure 6.5 shows that the national Ministry of Defence (MOD) is typically the launch customer for new
defence systems.  Companies are generally successful in achieving additional orders from non-domestic
MOD, especially those from countries outside of the EU.

74   One respondent stated that 350 product lines had been developed, which we consider would include more
than defence systems. Therefore, this response was excluded when analysing responses to this question.
- 85 -

link to page 90 link to page 91

R&D in the Defence Sector
Figure 6.5:  Launch path for new systems and products

To  further  develop  an  understanding  of  the  pattern  of  sales  for  a  new  defence  system,  we  asked
respondents to  specify the importance of sales to  the national MOD for achieving defence exports.
Figure  6.6  shows that more  than 50  per  cent of those  that  responded  to  this question believe  that
sales to national MOD are essential, if not pre-requisite to achieving defence exports.  Only 7 per cent
believe that sales to MOD have no influence on defence exports at all.
Figure 6.6:  Importance of sales to national MOD for achieving export sales
Rating Scale:
• 1 = not at all important
• 5 = critically important
Building on the above questions, we asked respondents to estimate the value of total export sales as a
percentage  of  the  total  value  of  orders  placed  by  its  own  MOD.    Our  survey  found  that  while  the
national  MOD  is  generally  the  launch  customer  for  new  defence  systems,  exports  are  a  significant
component of total sales for many respondents.  As shown in Figure 6.7, more than half of those that
responded to this question indicated that the value of their export sales is greater than 50 per cent of
the value of their national MOD orders.
- 86 -

link to page 92

R&D in the Defence Sector
Figure 6.7:  Value of export sales as a percentage of value of order by national MOD

6.3.4.2  Involvement of the private sector
Of  all  respondents  to  our  survey,  80  per  cent  have  developed  new  defence  systems  on  a  private
venture  basis,  independent  from  the  national  MOD.    The  value  of  products  developed  through  a
private venture can be substantial – one respondent stated that one of the products it had developed
on this basis had achieved sales of €40m.
6.3.4.3  Offsets
Offsets can be an important element of defence sales to non-domestic customers and so our survey
asked stakeholders about the use of offsets in the defence sector.75
Respondents were first asked if they have transferred technology to another Member State as part of
an offset (i.e. only intra-EU transfers were considered).  Ten of 20 respondents to this question stated
that they have transferred technology to another Member State.
Respondents were then asked if they have received technology transfer from another Member State.
As  shown  in  Figure  6.8,  seven  of  the  10  respondents  that  have  transferred  technology  to  another
Member  State  have  also  received  a  technology  transfer  from  another  Member  State.    The  same
number of respondents had received a technology transfer from another Member State in the group of
respondents that had not transferred technology to another Member State.

75   An  ‘offset’  is  an  arrangement  whereby  an  importing  country  makes  it  a  condition  that  the  supplier  places
orders  with  national  suppliers.    It  can  take  the  form  of  ‘direct  offset’,  which  relates  to  the  equipment
concerned, or an ‘indirect offset’ that relates to products of other industries, or a combination of the two.
Offsets  are  scaled  to  the  size  of  the  transaction:    a  ‘100  per  cent  offset’  requires  the  supplier  to  make
purchases equal to 100 per cent of the value of the contract.
- 87 -

link to page 92

R&D in the Defence Sector
Figure 6.8:  Number of companies that have experienced technology to and from another EU MS

6.3.5  Impact of R&D
Our  survey  results  confirm  our  conjecture  that  spin-offs  and  technology  transfer  are  important
elements of the economic contribution of the defence sector.  However, as shown in Figure 6.9, more
respondents have created technologies that have led to a spill-over effect for their suppliers than have
created  a  spin-off  company  (or  companies)  to  commercialise  the  technology  developed  through
defence R&D / R&T.
Figure 6.9:  Downstream effects of investments in R&D/R&T

Unfortunately,  the  response  rate  to  questions  on  the  spill-over  effect  of  existing  investments  in
defence R&D was very low – only four responses were achieved.  We consider that this response rate
is too small for analytical purposes.
- 88 -

Conclusions
7  Conclusions
The analysis contained within this report demonstrates that, at the EU level, the impact on GDP, tax
and  employment  of  investing  €100m  in  the  health,  education,  transport  and  defence  sectors  are
extremely similar.
Taking  these  results  alone  shows  that  defence  spending  has  a  macroeconomic  role  alongside  other
forms  of  public  spending.    However,  there  are  several  reasons  to  believe  that  the  overall
macroeconomic  benefit  of  investing  in  the  defence  sector  should  exceed  that  of  investing  in  other
sectors.
First, while the employment impacts of investing in the defence sector are broadly equivalent to the
impacts of investing in the health and transport sectors, defence investments have a far greater impact
on  skilled  employment  than  do  investments  in  the  other  sectors  considered  in  this  report.    In  an
increasingly  knowledge-based  and  skills-based  European  economy,  our  analysis  suggests  that
investments in the defence sector are more likely to create jobs that will be sustainable in the long
term and will add value to the European economy than are equivalent investments in other sectors.
Second, the importance of R&D to the past, current and future success of the European economy is
widely  acknowledged  and  has  a  sound  economic  basis  in  R&D  models  of  endogenous  growth.
Investments in the defence sector are likely to make a significant contribution to the future economic
growth of the EU thanks to the significant impact that such investments have on R&D.
The impact on R&D due to defence investments is between 12 and 20 times greater than the impact of
investments  in  the  other  key  components  of  public  expenditure  (transport,  health  and  education).
Defence  R&D  can  create  significant  spin-offs  and  technology-transfer  to  other  civil  and  defence
applications.  Therefore, the economic impact of investing in the defence sector exceeds that which
has been captured in the I-O analysis.
We also draw a number of lessons from the case studies:
  Defence  spending  can  take  different  forms,  reflected  in  the  acquisition  of  Gripen,  Rafale  and
Typhoon  (or  other  types  of  defence  equipment).    Studies  based  solely  on  the  macroeconomic
impacts of defence spending, by their blunt nature fail to identify the more detailed microeconomic
impacts of such spending.
  There  remain  considerable  opportunities  for  increasing  the  efficiency  of  European  collaborative
programmes.  For example, work-sharing for both development and production could be allocated
on the basis of competition:  a single prime contractor might manage the programme rather than
an industrial consortium and committee arrangements; and the number of major partner nations
might be restricted to two partners so as to minimise transaction costs (bilateral collaboration).
  Investment in defence capabilities can sometimes produce spectacular economic as well as defence
benefits, when a Ministry of Defence identifies a military requirement that is shared by a number of
nations,  and  then  commissions  a  national  supplier  to  develop  a  cost-effective  solution.    The
resulting export sales, over several decades, far exceed the numbers required for that country’s
own defence requirements (in the case of Oto Melara’s 76mm naval guns, by a factor of three).
  Investments in the EU defence sector can also lead to a significant cost saving relative to the next
best  alternative.    For  example,  Germany’s  investment  in  the  Leopard  2  enabled  it  to  equip  its
cavalry regiments with a highly capable system for a cost that was 45 per cent lower than the next
best alternative.
- 89 -

Conclusions
  There is some indicative support for the claim that arguments for defence spending might be based
on  wider  economic  and  industrial  benefits,  including  technology  spin-offs,  but  there  is  a  lack  of
really robust evidence underpinning this view.
  EU defence companies appear to earn economic rent on their operations and, in some cases, this
rent appears to be substantial.  For example, the economic rent earned on exports of Leopard 2s
was equivalent to 18 per cent of the cost of the Leopard programme.  The earning of economic
rent  indicates  that  the  sector  makes  a  net  contribution  to  the  economy,  over  and  above  the
contribution that the same resources would make if employed elsewhere.  Moreover, our analysis
suggests that a significant proportion of this economic rent is earned outside the EU and so the
rent is more than simply a transfer between EU taxpayers and EU defence companies.
  Investment in the defence sector can have important benefits for companies that operate in the
civil sector.  For example, the civil and military aeronautics industries are closely linked.  Under-
investment in military aeronautics could endanger the position of the civil aeronautics industry in
the EU (as non-EU competitors would then benefit from greater military investment in R&D).
  Defence  spending  can  re-purpose  resources  from  the  manufacturing  sector  in  general,  i.e.  from
occupations  where  labour  productivity  is  probably  around  the  sector  average,  to  uses  in  areas
within  the  defence  sector  in  which  productivity  is  exceptional.    In  2010  and  2011,  Oto  Melara
achieved a turnover per employee that was over one-third higher than both that of the industry to
which it belongs, and the average for Italian manufacturing.
  Defence  investment  enables  nations  to  discover  solutions  that  are  cost-effective  for  them.
Purchasing defence systems “off-the-shelf” is often advocated as a way of avoiding the enormous
development costs and risks of new systems.   Whether or not this is the right choice, there is
usually  a  good  case  for  examining  this  option,  as  a  default  position.    But  sometimes  the  “shelf”
lacks systems that suit a nation’s circumstances and defence philosophy.  Compact naval guns are
such  a  case.    The  relatively  small  ships  deployed  by  European  coastal  navies  require  capable,
compact and multi-purpose guns.  Their absence would probably have required different types of
ships, resulting in a lower level of naval capability, or significantly higher costs.
  Although there are clearly some advantages in purchasing non-EU “off-the-shelf” defence products
and services in some areas (and such products and services are purchased at present), it should
also  be  recognised  that  non-EU  “off-the-shelf”  solutions  can  also  have  some  potentially  adverse
consequences:
  For example, the Typhoon was estimated to have created 100,000 high-wage / high-skill jobs,
exports valued between €13.4bn and €17.8bn, and import-savings valued between €39.3bn and
€67.1bn  while  maintaining  European  independence  and  security  of  supply.    These  benefits
would be lost if non-EU off-the-shelf solutions were purchased.
  Purchasing  non-EU  off-the-shelf  solutions  could  create  classic  issues  of  security  of  future.
Absent  a  sufficient mass  of  investment  in  the  EU  defence  industry,  skills  and  capacities  could
deteriorate; rebuilding these would potentially be slow and expensive.  For example, even if the
EU were to undertake some work on the Joint Strike Fighter (JSF), it is unlikely that this work
alone would be sufficient to maintain the design skills necessary for developing a new European
combat aircraft.
As regarding whether defence research is better funded by direct investment in research or by the
sellers of defence equipment themselves, we have argued that because, in the defence sector:
  it will often be the case that (a) one buyer (or group of buyers agreeing amongst themselves all to
purchase the same technology) will comprise the overwhelming majority of purchases — often the
national defence agency of the country of the defence supplier; and (b) more fundamentally, other
- 90 -

Conclusions
buyers will not purchase a product that has not been endorsed by being purchased by the national
defence agency of the country of the defence supplier; and
 the key buyer typically has specific known needs that arise from its strategic plans;
it is unsurprising and natural that advanced technology equipment projects research in the defence is
often buyer-funded.
- 91 -

Conclusions
Appendices

- 92 -

Appendix 1: Assumptions, conceptual issues and the €100m investment
8  Appendix 1: Assumptions,
conceptual issues and the €100m
investment
8.1  Conceptual Issues and Assumptions
8.1.1  Activities covered by defence investment
The EDA classifies defence expenditure into four broad categories:  personnel costs; investment; operation
and maintenance; and other.  We assumed that a €100m ‘investment’ would not be spent on deploying or
recruiting  more  personnel  (as  this  is  a  function  of  military  need),  and  would  therefore  be  spent  in  the
second  category  as  well  as  the  infrastructure  part  of  the  fourth  category.    In  2010,  the  ‘investment’
category  accounted  for  22.1  per  cent  of  defence  expenditure  in  EDA  participating  Member  States  and
infrastructure investment accounted for 2.8 per cent.76
We also note that the ‘investment’ category is further broken down into defence equipment procurement
expenditure  and  defence  R&D  expenditure  (which  has  a  further  Research  and  Technology  (R&T)  sub-
category).
We  therefore  assumed  that  the  €100m  investment  would  be  broken  down  between  the  following
expenditure categories:  equipment procurement; non-R&T R&D; R&T and infrastructure.  We inspected
recent trends in expenditure and based our calculations on the average of the last three years of defence
spending.
8.1.2  Geographical distribution of the investment
We  divided  the  total  expenditure  of  €100m  between  the  26  EDA  Member  States  in  proportion  to  the
average investment spending over the three most recent years for which data were available (2008-10).  To
do this, we calculated the total investment spending as the sum of equipment procurement, non-R&T R&D
R&T  and  infrastructure  spending  for  each  country.    We  then  calculated  the  proportion  of  total  EU
investment expenditure accounted for by each Member State and splitting the €100m according to those
proportions.
8.1.2.1  Supply side’s reaction to investment
In our quantitative analysis, we have treated the one-off €100m investment as an increase in final demand
for the relevant products and services.
The response of companies to this increase in demand would determine the follow through effect on the
various macroeconomic variables.  In particular, the level of capital formation as a response to this increase
in  demand  would  depend  on  whether  companies  respond  by  creating  additional  capacity  as  well  as

76   EDA  Additional  Defence  Data  2010.    At  the  time  of  writing,  2010  is  the  latest  year  for  which  defence  data  is
available.
- 93 -

Appendix 1: Assumptions, conceptual issues and the €100m investment
employment (a ‘long run’ response), or by temporarily increasing employment but working with the fixed
capital  already  in  place  (a  ‘short  run’  response).    This,  in  turn  depends  in  large  part  upon  whether
companies  view  the  additional  demand  as  permanent  or  temporary.    An  expectation  of  permanent
increases in demand usually leads to higher levels of capital formation than an expectation of  temporary
increases in demand.
The  relationships  inherent  in  the  input-output  tables  are  consistent  with  companies  responding  to  a
mixture  of  temporary  and  permanent  demand  changes,  and  would  therefore  not  be  useful  to  quantify  a
response to an event that companies know represents a wholly temporary demand increase.  However, we
consider that it is reasonable to assume that the nature of the €100m investment would be such that the
companies  would  initially  be  unable  to  fully  assess  whether  the  demand  increase  is  temporary  or
permanent.  As capacity building decisions are, in fact, made in response to expected rather actual future
demand, we assume that companies would build an expectation of the mix of temporary and permanent
demand changes likely to occur in their relevant industry, and respond accordingly.
Furthermore, as €100m is a negligible amount compared to total investment expenditure in the European
defence  sector,  we  consider  that  past  experience  would  serve  as  a  good  basis  to  form  expectation
regarding  the  mixture  of  temporary  and  permanent  demand  in  the  future.    Therefore,  the  relationships
inherent  in  input-output  tables  would  be  a  good  indicator  of  the  companies’  response  to  the  €100m
injection.
8.1.3  I-O classification system
The Eurostat I-O tables are divided sectorally according to the NACE classification system.77
One challenge for our analysis arose from the fact that a new classification, NACE Rev. 2, replaced the old
classification, NACE Rev. 1.1 in all official statistics on 1 January 2008.  For some Member States, the most
recent I-O table is from a year prior to the introduction of NACE Rev. 2 whereas tables are available for
later years.
We want our results to be as relevant as possible to the economy of the EU in 2013 and so chose to use
the  most  recent  I-O  table  that  was  available  for  each  Member  State.    This  required  us  to  conduct  two
separate  mapping  exercises,  given  differences  in  the  definitions  of  sectors  between  NACE  Rev.  1.1  and
NACE Rev 2.
8.2  Mapping of defence expenditure categories
8.2.1  Step 1:  Latest Available Tables by Member State
We collected the latest available I-O tables from Eurostat for each participating Member State and for the
EU.  No tables were available for three Member States, while for one Member State the available tables
were too sparsely populated to be useful for analysis.  Of the remaining 22 participating Member States, 10
were before 2008 (NACE Rev. 1.1) and 12 were from 2008 or later (NACE Rev. 2).  The EU table was
from 2008, but covered the EU-27, not just the participating Member States.  However, since there was no
table referring to the participating Member State, we decided used the EU-27 table for aggregate analysis.

77   “Nomenclature générale des Activités économiques dans les Communautés Européennes” (Statistical classification
of economic activities in the European Communities)
- 94 -

link to page 100 Appendix 1: Assumptions, conceptual issues and the €100m investment
Table 8.1: Latest available tables by MS
Member State
Latest available table
NACE classification Rev.
AT
2008
2
BE
2005
1.1
BG
No tables available
Not applicable
CY
No tables available
Not applicable
CZ
2009
2
EE
2005
1.1
FI
2009
2
FR
2009
2
DE
2008
2
EL
2010
2
HU
2008
2
IE
2009
2
IT
2005
1.1
LV
1998
1.1
LT
2005
1.1
LU
Tables unusable
Not applicable
MT
No tables available
Not applicable
NL
2009
2
PL
2005
1.1
PT
2008
2
RO
2008
2
SK
2005
1.1
SI
2005
1.1
ES
2005
1.1
SE
2010
2
UK
2005
1.1
EU-27
2008
2

8.2.2  Step 2:  Mapping defence categories to I-O sectors
The next step was to map the defence categories to I-O categories.  The mapping from the four defence
sector categories to I-O sectors was carried out as follows
  Official definitions (confidential) were received from EDA for (i) Equipment procurement, (ii) Research
and Development (R&D), (iii) Research and Technology (R&T) and (iv) Infrastructure.
  These definitions were used to identify the products and / or services that are included within each of
the four defence sector categories.
  Broad  NACE  Rev.  1.1  and  NACE  Rev.  2  sectors  containing  these  products  and  /  or  services  were
identified using official documentation on the NACE classification system.78
  The  relevant  I-O  sectors  were  identified  as  those  containing  the  corresponding  NACE  /  CPA  code.
Each I-O sector corresponds to at least one two digit NACE / CPA code level in both Rev. 1.1 and
Rev. 2 classifications.  Thus, no NACE sector had to be broken down to arrive at the corresponding I-
O sector.
Table 8.2 presents the results of the mapping exercise.

78   Eurostat  (2002)  ‘Statistical  Classification  of  Economic  Activities  in  the  European  Community,  Rev.  1.1’
http://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=LST_CLS_DLD&StrNom=NACE_1_1&St
rLanguageCode=EN&StrLayoutCode=EN
Eurostat  (2008)  ‘NACE  Rev.  2:  Statistical  classification  of  economic  activities  in  the  European  Community’
http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-RA-07-015/EN/KS-RA-07-015-EN.PDF
- 95 -

link to page 100 link to page 101 Appendix 1: Assumptions, conceptual issues and the €100m investment
Table 8.2:  Mapping exercise results
Defence
I-O sectors according to NACE Rev. 1.1
I-O sectors according to NACE Rev. 2
sector
29 – Machinery and equipment not elsewhere
classified (including weapons and ammunition)
30 – Office machinery and computers
31 – Electrical machinery and apparatus not
16 – Fabricated metal products, except
elsewhere classified
machinery and equipment (includes weapons
and ammunition)
32 – Radio, television and communication
equipment and apparatus
17 – Computer, electronic and optical
33 – Medical, precision and optical
products
18 – Electrical equipment
instruments; watches and clocks
19 – Machinery and equipment n.e.c.
Equipment
34 – Motor vehicles, trailers and semi-trailers
20 – Motor vehicles, trailers and semi-trailers
procurement  35 – Other transport equipment
50 – Trade, maintenance and repair services
21 – Other transport equipment
of motor vehicles and motorcycles; retail sale
28 – Wholesale and retail trade and repair
services of motor vehicles and motorcycles
of automotive fuel
51 - Wholesale trade and commission trade
29 – Wholesale trade services, except of
services, except of motor vehicles and
motor vehicles and motorcycles
30 – Retail trade services, except of motor
motorcycles
52 - Retail  trade services, except of motor
vehicles and motorcycles
vehicles and motorcycles; repair services of
personal and household goods
73 – Research and development services
47 – Architectural and engineering services;
R&D
74 – Other business services (including
technical testing and analysis services
48 – Scientific research and development
technical testing and analysis services)
services
73 – Research and development services
47 – Architectural and engineering services;
technical testing and analysis services
R&T
74 – Other business services (including
technical testing and analysis services)
48 – Scientific research and development
services
Infrastructure  45 – Construction work
27 – Constructions and construction works

8.2.3  Step 3:  From Mapping to Division of Expenditure
As shown in  Table 8.2, only one of the defence spending categories corresponds to a single I-O sector.
Therefore, it was necessary to divide the expenditure on each of the other categories between the several
corresponding I-O sectors.  In this section, we describe our approach to each defence category in turn.
8.2.3.1  Equipment Procurement
The optimal approach to allocating the total expenditure on equipment procurement between I-O sectors
would be to use data on relative expenditure on each I-O category.  The difficulty with this approach is that
breakdowns of defence spending by industrial sector are rarely published and, to our knowledge, only the
UK publishes a detailed enough breakdown.  Therefore, we chose to apportion equipment procurement
expenditure  to  I-O  categories  based  on  UK  data  and  assumed  that  similar  patterns  of  expenditure  are
observed across the EU.  The following paragraphs describe our approach in greater detail.
Table 8.3 shows the sectoral breakdown of UK defence expenditure from 2004/05 to 2010/11.
- 96 -

Appendix 1: Assumptions, conceptual issues and the €100m investment
Table 8.3: UK defence spending by sector

Source: United Kingdom Defence Statistics 2012, Table 1.12
Using these data, we estimated the percentage of equipment procurement expenditure accounted for by
individual product categories.  Our approach required the following assumptions:
  percentages are the same for equipment procurement and Operations and Maintenance spending;
  ships and aircraft are not purchased through retail or wholesale channels, but directly from producers;
  the breakdown between wholesale and retail is in proportion to the relative size of the wholesale and
retail sectors at the EU level;
  the relative spending across the sectors is the same for all participating Member States; and
  the manufacturing sub-categories correspond to I-O sectors as follows.
Manufacturing category
NACE Rev. 1.1 I-O sector
NACE Rev. 2 I-O sector
Weapons & Ammunition
29
16
Data Processing Equipment
30
17
Other Electrical Engineering
31
18
Electronics
32
17
Precision Instruments
33
17
Motor Vehicles & Parts
34
20
Shipbuilding & Repairing
35
21
Aircraft & Spacecraft
35
21

Given  these  assumptions,  we  calculated  the  total  expenditure  on  each  manufacturing  category  between
2004/05 and 2010/11:
- 97 -

link to page 100 Appendix 1: Assumptions, conceptual issues and the €100m investment
NACE Rev. 1.1 I-O
Expenditure (£ m)
NACE Rev. 2 I-O
Expenditure (£ m)
sector
sector
29
8,060
16
8,060
30
550
17
11,350
31
1,510
18
1,510
32
6,280
20
2,520
33
4,520
21
25,720
34
2,520

35
25,720

In  addition  to  the  manufacturing  I-O  sectors  presented  in  the  table  above,  three  service  sectors  are
included in our definition of equipment procurement.  As shown in Table 8.2, these are:
  wholesale and retail trade and repair services of motor vehicles;
  wholesale trade services other than motor vehicles; and
  retail trade services other than motor vehicles.
To allocate the equipment procurement expenditure to these I-O sectors we first considered the split of
manufacturing  expenditure  between  2004/05  and  2010/11  between  motor  vehicles  and  other  equipment
(excluding ships and aircraft):
Category
Expenditure (£ m)
Percentage
Motor vehicles
2,520
10.75%
Other manufacturing products
20,920
89.25%

We  assumed  that  the  breakdown  between  wholesale  and  retail  trade  services  of  motor  vehicles  and
wholesale  and  retail  trade  services  of  other  products  is  the  same  as  the  breakdown  between  the
manufacture of motor vehicles and that of other products.  Therefore, the spending on wholesale and retail
trade services can be divided in this proportion between motor vehicles and others.
We  then  assumed  that  the  spending  could  be  divided  between  wholesale  and  retail  according  to  the
relative  size  of  the  sectors  at  the  EU  level.    According  to  the  2008  EU  tables,  the  relative  sizes  of  the
sectors are as follows.
Category
Expenditure (£ m)
Percentage
Wholesale
1,202,984
59.73%
Retail
811,161
40.27%

Multiplying  the  proportion  of  expenditure  on  other  manufacturing  products  by  the  proportion  of
expenditure on wholesale products (and similarly for the other categories) leads to the following division of
wholesale and retail spending:
I-O sector
Percentage
Wholesale and retail of motor vehicles
10.75%
Wholesale other
53.31%
Retail other
35.94%

Combining these estimates with those of the manufacturing categories results in the following division of
defence equipment procurement expenditure between I-O categories:
- 98 -

link to page 104 link to page 105 Appendix 1: Assumptions, conceptual issues and the €100m investment
NACE Rev. 1.1
Expenditure
Percentage
NACE Rev. 2
Expenditure
Percentage
I-O sector
(£ m)
I-O sector
(£ m)
29
8,060
15.77%
16
8,060
15.77%
30
550
1.08%
17
11,350
22.21%
31
1,510
2.95%
18
1,510
2.95%
32
6,280
12.29%
20
2,520
4.93%
33
4,520
8.84%
21
25,720
50.32%
34
2,520
4.93%
28
210
0.41%
35
25,720
50.32%
29
1,039
2.03%
50
210
0.41%
30
701
1.37%
51
1,039
2.03%

52
701
1.37%

8.2.3.2  Research and Development
For  this  expenditure  category,  the  question  is  how  to  allocate  the  additional  funds  between  R&D  and
testing services, which fall under two different I-O sectors in both classifications.  We have allocated all the
additional funds solely to R&D for the following reasons.
  There  are  certain  types  of  testing  that  do  not  form  part  of  R&D,  e.g.  testing  that  finished  products
achieve certain functional or health and safety standards.
  While R&D typically involves some testing, the expenditure is made on a per-project basis, where the
organisation carrying out the project then employs testing services.  Technically, this is equivalent to
saying the R&D sector employs testing services as an input.  Thus, the boost to testing services would
be captured as an increase in requirements for testing services as a result of the increase in demand for
R&D services.
8.2.3.3  Research and Technology
As R&T forms a subset of R&D, we have allocated all the R&T funds to the I-O sector corresponding to
R&D.
8.2.3.4  Infrastructure
The  infrastructure  defence  category  corresponds  to  a  single  I-O  sector  and  so  the  full  additional
expenditure on infrastructure would be allocated to the I-O sector relating to construction.
8.2.4  Step 4:  Final Division of Funds
The following final steps were carried out
  We calculated the average over the three most recent years of defence expenditure in each of the four
defence categories.
  Using the preceding discussion, we broke this average down for each Member State and for the EU into
the  various  I-O  sectors,  using  NACE  1.1  sectors  for  States  with  tables  prior  to  2008  and  NACE  2
sectors for those with 2008 or later tables.
  We  divided  the  €100m  investment  across  Member  States  and  I-O  sectors  according  to  this
distribution.
Dividing investment funds according to the discussion above, the final demand broken down for each MS by
I-O sector is as shown in Table 8.4 and Table 8.5.
- 99 -

Appendix 1: Assumptions, conceptual issues and the €100m investment
Table 8.4: Additional demand by I-O sector – NACE Rev. 1.1 MS (€)
I-O
BE
EE
IT
LV
LU
LT
PL
SI
SK
ES
UK
Sector
1
-
-
-
-
-
-
-
-
-
-
-
2
-
-
-
-
-
-
-
-
-
-
-
5
-
-
-
-
-
-
-
-
-
-
-
10
-
-
-
-
-
-
-
-
-
-
-
11
-
-
-
-
-
-
-
-
-
-
-
12
-
-
-
-
-
-
-
-
-
-
-
13
-
-
-
-
-
-
-
-
-
-
-
14
-
-
-
-
-
-
-
-
-
-
-
15
-
-
-
-
-
-
-
-
-
-
-
16
-
-
-
-
-
-
-
-
-
-
-
17
-
-
-
-
-
-
-
-
-
-
-
18
-
-
-
-
-
-
-
-
-
-
-
19
-
-
-
-
-
-
-
-
-
-
-
20
-
-
-
-
-
-
-
-
-
-
-
21
-
-
-
-
-
-
-
-
-
-
-
22
-
-
-
-
-
-
-
-
-
-
-
23
-
-
-
-
-
-
-
-
-
-
-
24
-
-
-
-
-
-
-
-
-
-
-
25
-
-
-
-
-
-
-
-
-
-
-
26
-
-
-
-
-
-
-
-
-
-
-
27
-
-
-
-
-
-
-
-
-
-
-
28
-
-
-
-
-
-
-
-
-
-
-
29
103,815.74
21,003.59
944,879.28
10,014.46
24,064.06
15,543.24
364,002.46
21,670.50
40,502.77
640,239.23
2,639,569.63
30
7,084.20
1,433.25
64,476.87
683.37
1,642.09
1,060.64
24,838.88
1,478.76
2,763.84
43,688.78
180,119.52
31
19,449.35
3,934.92
177,018.33
1,876.16
4,508.28
2,911.95
68,194.01
4,059.86
7,587.99
119,945.56
494,509.94
32
80,888.69
16,365.08
736,208.67
7,802.83
18,749.67
12,110.61
283,614.82
16,884.71
31,557.99
498,846.45
2,056,637.38
33
58,219.25
11,778.69
529,882.67
5,616.05
13,494.98
8,716.56
204,130.41
12,152.69
22,713.71
359,042.35
1,480,254.93
34
32,458.52
6,566.88
295,421.31
3,131.07
7,523.75
4,859.67
113,807.22
6,775.39
12,663.40
200,174.05
825,274.87
35
331,282.98
67,023.86
3,015,173.08
31,956.83
76,790.04
49,599.52
1,161,556.23
69,152.02
129,247.07
2,043,046.29
8,423,043.54
36
-
-
-
-
-
-
-
-
-
-
-
37
-
-
-
-
-
-
-
-
-
-
-
40
-
-
-
-
-
-
-
-
-
-
-
41
-
-
-
-
-
-
-
-
-
-
-
45
152,802.98
74,562.89
555,308.21
54,417.58
8,702.29
16,861.01
655,266.94
46,125.12
70,368.09
465,306.06
1,911,164.29
50
2,704.88
547.24
24,618.44
260.92
626.98
404.97
9,483.94
564.62
1,055.28
16,681.17
68,772.91
51
13,382.70
2,707.53
121,802.68
1,290.95
3,102.05
2,003.65
46,922.90
2,793.51
5,221.14
82,532.08
340,262.14
52
9,029.14
1,826.74
82,178.71
870.99
2,092.92
1,351.84
31,658.28
1,884.74
3,522.64
55,683.34
229,570.51
55
-
-
-
-
-
-
-
-
-
-
-
60
-
-
-
-
-
-
-
-
-
-
-
61
-
-
-
-
-
-
-
-
-
-
-
62
-
-
-
-
-
-
-
-
-
-
-
63
-
-
-
-
-
-
-
-
-
-
-
64
-
-
-
-
-
-
-
-
-
-
-
65
-
-
-
-
-
-
-
-
-
-
-
66
-
-
-
-
-
-
-
-
-
-
-
67
-
-
-
-
-
-
-
-
-
-
-
70
-
-
-
-
-
-
-
-
-
-
-
- 100 -

Appendix 1: Assumptions, conceptual issues and the €100m investment
I-O
BE
EE
IT
LV
LU
LT
PL
SI
SK
ES
UK
Sector
71
-
-
-
-
-
-
-
-
-
-
-
72
-
-
-
-
-
-
-
-
-
-
-
73
19,753.98
2,039.32
319,811.01
250.09
2,598.38
-
183,318.71
25,588.39
6,229.08
495,208.46
6,236,249.20
74
-
-
-
-
-
-
-
-
-
-
-
75
-
-
-
-
-
-
-
-
-
-
-
80
-
-
-
-
-
-
-
-
-
-
-
85
-
-
-
-
-
-
-
-
-
-
-
90
-
-
-
-
-
-
-
-
-
-
-
91
-
-
-
-
-
-
-
-
-
-
-
92
-
-
-
-
-
-
-
-
-
-
-
93
-
-
-
-
-
-
-
-
-
-
-
95
-
-
-
-
-
-
-
-
-
-
-

Table 8.5: Additional demand by I-O sector – NACE Rev. 1.1 MS (€)
I-O
AT
CZ
FI
FR
DE
EL
HU
IE
NL
PT
RO
SE
EU
Sector
1
-
-
-
-
-
-
-
-
-
-
-
-
-
2
-
-
-
-
-
-
-
-
-
-
-
-
-
3
-
-
-
-
-
-
-
-
-
-
-
-
-
4
-
-
-
-
-
-
-
-
-
-
-
-
-
5
-
-
-
-
-
-
-
-
-
-
-
-
-
6
-
-
-
-
-
-
-
-
-
-
-
-
-
7
-
-
-
-
-
-
-
-
-
-
-
-
-
8
-
-
-
-
-
-
-
-
-
-
-
-
-
9
-
-
-
-
-
-
-
-
-
-
-
-
-
10
-
-
-
-
-
-
-
-
-
-
-
-
-
11
-
-
-
-
-
-
-
-
-
-
-
-
-
12
-
-
-
-
-
-
-
-
-
-
-
-
-
13
-
-
-
-
-
-
-
-
-
-
-
-
-
14
-
-
-
-
-
-
-
-
-
-
-
-
-
15
-
-
-
-
-
-
-
-
-
-
-
-
-
16
105,851.39
85,491.30
231,413.98
2,370,083.33
1,791,758.86
597,479.18
49,891.84
26,519.44
468,724.76
108,970.67
67,807.87
301,969.95
11,085,647.65
17
149,058.72
120,387.87
325,874.52
3,337,524.30
2,523,134.37
841,363.36
70,257.12
37,344.37
660,052.86
153,451.25
95,486.27
425,230.63
15,610,682.49
18
19,830.72
16,016.36
43,354.23
444,023.06
335,676.91
111,934.68
9,346.98
4,968.28
87,813.20
20,415.10
12,703.46
56,572.53
2,076,839.70
19
-
-
-
-
-
-
-
-
-
-
-
-
-
20
33,094.98
26,729.29
72,352.76
741,018.61
560,202.52
186,804.90
15,598.94
8,291.44
146,549.18
34,070.23
21,200.48
94,412.44
3,465,984.13
21
337,778.89
272,808.45
738,457.51
7,563,094.71
5,717,622.56
1,906,596.08
159,208.20
84,625.31
1,495,732.12
347,732.71
216,379.45
963,606.33
35,375,044.38
22
-
-
-
-
-
-
-
-
-
-
-
-
-
23
-
-
-
-
-
-
-
-
-
-
-
-
-
24
-
-
-
-
-
-
-
-
-
-
-
-
-
25
-
-
-
-
-
-
-
-
-
-
-
-
-
26
-
-
-
-
-
-
-
-
-
-
-
-
-
27
114,328.57
273,392.58
317,563.77
2,639,108.01
3,242,976.37
179,008.83
38,015.68
34,993.11
596,485.46
25,958.15
49,800.69
34,509.25
11,656,149.12
28
2,757.91
2,227.44
6,029.40
61,751.55
46,683.54
15,567.08
1,299.91
690.95
12,212.43
2,839.19
1,766.71
7,867.70
288,832.01
29
13,645.11
11,020.53
29,831.16
305,523.15
230,972.39
77,019.96
6,431.47
3,418.57
60,422.46
14,047.21
8,740.99
38,926.40
1,429,030.76
30
9,206.18
7,435.41
20,126.70
206,132.56
155,834.11
51,964.38
4,339.23
2,306.47
40,766.26
9,477.47
5,897.43
26,263.14
964,148.76
31
-
-
-
-
-
-
-
-
-
-
-
-
-
- 101 -

Appendix 1: Assumptions, conceptual issues and the €100m investment
I-O
AT
CZ
FI
FR
DE
EL
HU
IE
NL
PT
RO
SE
EU
Sector
32
-
-
-
-
-
-
-
-
-
-
-
-
-
33
-
-
-
-
-
-
-
-
-
-
-
-
-
34
-
-
-
-
-
-
-
-
-
-
-
-
-
35
-
-
-
-
-
-
-
-
-
-
-
-
-
36
-
-
-
-
-
-
-
-
-
-
-
-
-
37
-
-
-
-
-
-
-
-
-
-
-
-
-
38
-
-
-
-
-
-
-
-
-
-
-
-
-
39
-
-
-
-
-
-
-
-
-
-
-
-
-
40
-
-
-
-
-
-
-
-
-
-
-
-
-
41
-
-
-
-
-
-
-
-
-
-
-
-
-
42
-
-
-
-
-
-
-
-
-
-
-
-
-
43
-
-
-
-
-
-
-
-
-
-
-
-
-
44
-
-
-
-
-
-
-
-
-
-
-
-
-
45
-
-
-
-
-
-
-
-
-
-
-
-
-
46
-
-
-
-
-
-
-
-
-
-
-
-
-
47
-
-
-
-
-
-
-
-
-
-
-
-
-
48
6,580.21
44,110.05
77,240.61
7,419,418.86
2,616,789.35
18,260.46
4,594.30
-
199,959.83
14,979.59
8,273.39
346,216.14
18,047,641.00
49
-
-
-
-
-
-
-
-
-
-
-
-
-
50
-
-
-
-
-
-
-
-
-
-
-
-
-
51
-
-
-
-
-
-
-
-
-
-
-
-
-
52
-
-
-
-
-
-
-
-
-
-
-
-
-
53
-
-
-
-
-
-
-
-
-
-
-
-
-
54
-
-
-
-
-
-
-
-
-
-
-
-
-
55
-
-
-
-
-
-
-
-
-
-
-
-
-
56
-
-
-
-
-
-
-
-
-
-
-
-
-
57
-
-
-
-
-
-
-
-
-
-
-
-
-
58
-
-
-
-
-
-
-
-
-
-
-
-
-
59
-
-
-
-
-
-
-
-
-
-
-
-
-
60
-
-
-
-
-
-
-
-
-
-
-
-
-
61
-
-
-
-
-
-
-
-
-
-
-
-
-
62
-
-
-
-
-
-
-
-
-
-
-
-
-
63
-
-
-
-
-
-
-
-
-
-
-
-
-
64
-
-
-
-
-
-
-
-
-
-
-
-
-
65
-
-
-
-
-
-
-
-
-
-
-
-
-

- 102 -

Appendix 2: I-O Analysis
9  Appendix 2: I-O Analysis
Input-output (I-O) analysis was pioneered by Russian-American economist Wassily Leontief in the 1930s as
a  model  of  general  equilibrium  where  various  sectors  of  the  economy  are  inter-linked.79    The
computational  tractability  of  the  model  made  it  very  useful  for  analysing  the  effects  of  otherwise
complicated  inter-industry  transactions  on  the  economy.    This  work  won  Leontief  the  Nobel  Prize  in
Economics in 1973.
The tractability of the model arises from a very restrictive assumption regarding production technology –
that of fixed coefficients.  Producing one unit of any good or service requires certain quantities of various
inputs in a fixed proportion.  This means that inputs are not substitutable at all.  Fixed coefficients is an
extreme  assumption,  and  can  only  be  said  to  hold  true  in  the  short  run  –  in  the  medium  run  input
proportions  can  and  do  change.    Therefore,  all  I-O  analysis  must  be  understood  in  a  purely  short  run
context.  Moreover, the use of I-O analysis should be restricted to understanding or predicting the short
run effects of a change in status quo.  Its use by the former socialist bloc countries for setting production
targets in five-year plans and the resultant problems exposed its limited usefulness for long-term analysis.
9.1  Basic set up
For illustrative purposes, assume that the economy has three sectors:   agriculture, industry and services.
There  are  two  factor  inputs:    labour  and  capital.    The  end  uses  for  the  products  of  each  sector  are
surmised in one quantity called final demand (in a more complicated model, this would be broken down
into  household  consumption  expenditure,  government  consumption  expenditure,  gross  fixed  capital
formation and net exports).
In this simplistic model, the production of any sector can be looked at by use  – the produce is used as
inputs by any or all of the three sectors, and is sold to final demand.  The entire economy may be surmised
in the following three equations.



Here:
  Sectors are represented by the following subscripts:  A = agriculture, I = industry, S = services;
      is the intermediate demand for the produce of sector   by sector  , where                 ;
      is the final demand for the produce of sector  ;
     is the total production of sector  ; and
  all units are in money terms.
The assumption of fixed coefficients is interpreted in the following way.  Take the industry sector.  It needs
to use     of the produce of the agriculture sector to produce    of final produce.  Consequently, it needs

79   See  Leontief,  Wassily  (1936)  ‘Quantitative  Input  and  Output  Relations  in  the  Economic  System  of  the  United
States’  Review  of  Economic  Statistics,  Vol.  18,  p105-125,  Leontief,  Wassily  (1937)  ‘Interrelation  of  Prices,  Output,
Savings  and  Investment’  The  Review  of  Economic  Statistics,  Vol.  19,  p109-132  and  Leontief,  Wassily  (1941)  The
Structure of the American Economy 1919-1939, Cambridge (Mass.).
- 103 -

Appendix 2: I-O Analysis


    worth  of  the  agricultural  produce  that  to  produce  product  worth  one  unit  currency.    The

assumption is that     is the fixed technical coefficient of intermediate consumption that provides one link
between the industry and agriculture sectors – regardless of the amount that the industry sector produces
this proportion would remain constant.   Similar intermediate consumption coefficients may be calculated
for links between each pair of sectors.





The  system  of  equations  can  then  be  represented  in  terms  of  the  fixed  technical  coefficients,  the  total
production of each sector and the final demand facing each sector as follows.



Using matrix notation, this may be re-written as follows.



[
       ] [  ]   [   ]   [  ]



9.2  Changes in final demand
With this set up, it now becomes possible to analyse the effects on the economy when the final demand
changes for the produce of a certain sector.  The problem is straightforward – we have a new set of final
demands     (contained in the vector   ) and a set of technical coefficients     (which are contained in the
matrix  ) that are known.  We need to know what the total produce of each sector should now be, i.e. we
need to find the   s (contained in the vector  ).  In terms of the three-equation set up, the problem is
simple  –  there  are  three  equations  with  three  unknown  variables  to  solve  for.    Simple  algebraic
manipulation leads us to the new final outputs.
For computational reasons, it is easier to work with matrices, as in actual models the number of sectors is
much higher than three, and algebraic manipulation becomes harder.  Thus, in matrix terms, the solution is
given by manipulation of the basic set-up equation.
    (     )
Here
    is an identity matrix with   along the diagonal and   elsewhere; and
  (     )   is the inverse of the matrix (     )
Once the new total outputs have been calculated, the effects on several macro variables may be obtained.
  GDP effects:  Since GDP is simply the sum total of all goods and services produced in the economy, the
new GDP is obtained by adding up all new total production figures for all sectors in the economy.
  Income effects:  to calculate these, one simply needs to multiply the change in output in each sector
with the per unit compensation of employees in that sector.  This, again, is a fixed coefficient, and is
derived in the same way as the other technical coefficients.
  Employment effects:  to calculate these, one needs to multiply the change in output in each sector with
the number of employees it takes to produce one currency unit worth of produce.  This is also a fixed
coefficient, and can be calculated using initial total produce and initial employment.
- 104 -

Appendix 2: I-O Analysis
  Capital  effects:    to  calculate  the  increase  in  earnings  of  capital,  one  needs  to  multiply  the  change  in
output in each sector with the per unit contribution of capital.
  Tax effects:  in richer models (such as the one proposed for the project), with explicit inclusion of the
government and taxes, one would need to multiply the change in sectoral output by the tax rate, which
is also assumed to be fixed.
9.3  Multipliers
When the final demand for any particular sector changes, any effects on macro variables are the result of
three kinds of effect:
  Direct effect:  This is the effect of the concerned sector having to produce more output to meet an
increase in final demand.  This would result in additions to GDP, employment, income, taxes, etc.
  Indirect effect:  In order to produce more, the sector concerned would need more inputs from other
sectors than earlier, thus increasing the demands faced by a variety of sectors.  Other sectors would
then need to increase their production to fulfil this additional demand for intermediate consumption.
But,  in  turn,  such  increases  in  output  would  increase  demand  for  intermediate  consumption,
necessitating a further increase in output of various sectors.  The sum total of these knock-on effects is
the indirect effect.
  Induced effect:  In richer models than the one described here, an increase in incomes would lead to
further increases in final demand across some or all sectors, over and above the initial increase in final
demand.  The consequent changes to production, output, etc. are the induced effects.
A multiplier in the I-O context is simply the change in any macro variable as a result of a unit change in final
demand.  From the above, it is clear that if final demand for agricultural produce increased by a unit, the
increase in total agricultural produce would be greater than one unit, as the indirect effects of having to
produce more intermediate inputs and the induced effects of having to respond to higher final demand due
to  an  increase  in  incomes  would  mean  that  significantly  more  would  have  to  be  produced  than  just  to
satisfy a unit increase in demand.  Similarly, the increase in GDP would also be greater than one unit, given
that the direct, indirect and induced effects on all other sectors would also be taken into account.
Multipliers can be of various types.  The output/GDP multiplier is the increase in GDP as a result of a unit
increase  in  final  demand  for  the  sector.    Similarly,  we  may  have  income,  employment,  tax  and  other
multipliers.
The attraction of the I-O system as represented in matrix form is that multipliers for each sector can be
derived very simply from the (     )   matrix and comparisons can be made across sectors.  For instance,
once the GDP multipliers have been calculated for all sectors, the  one with the highest multiplier would
have  the  greatest  effect  on  GDP  for  a  unit  increase  in  final  demand.    The  derivation  of  the  various
multipliers is given as follows.
  Output/GDP multiplier:  for sector  , this is the sum of all elements in the  th column of the matrix
(     )
  Income multiplier:  for sector  , this is the  th element of the vector     (     )  , where   is the
vector of wage coefficients80 for each sector.
  Employment multiplier:  for sector  , this is the  th element of the vector     (     )  , where   is the
vector of employment coefficients81 for each sector.
  Tax multiplier:  for sector  , this is the  th element of the vector     (     )  , where   is the vector
of tax coefficients82 for each sector.

80   Calculated as the initial proportion of compensation of employees to total output for each sector.
81   Calculated as the initial proportion of sectoral employment to total output for each sector.
- 105 -

Appendix 2: I-O Analysis
  Capital  multiplier:    for  sector   ,  this  is  the   th  element  of  the  vector      (     )  ,  where     is  the
vector of capital coefficients83 for each sector.
Lastly,  it  must  be  noted  that  multipliers  can  be  calculated  with  or  without  induced  effects.    To  include
induced effects, households must be included as one of the productive sectors in the economy.
9.4  Richer models
The basic I-O framework can be modified or made richer through various extensions.  Some of them are as
follows.84
  Endogenous final demand:  here the final demand sections are regarded not as external, but dependant
on  the  level  of  output.    Household  consumption,  household  investment  and  government  are  all
included as productive sectors in the economy.
  Dynamic models:  here, linkages across time are allowed, and it is assumed that induced investment in
one period will lead to an increase in output in the next period.
The  model  chosen  in  this  proposal  is  a  static  model  with  exogenous  final  demand.    However,  the
granularity of sectors and final demand is more than in the simple example followed in this section.
9.5  Limitations
The primary limitation of the I-O framework is that it is essentially a short run approximation, and does not
work  well  when  sectors  are  operating  at  full  capacity.    To  capture  long-term  effects,  macro-economic
growth models would need to be used.
A  secondary  limitation  is  that  effects  of  an  increase  in  final  demand  may  be  greatly  exaggerated  if  the
economy is already close to full employment.  In full employment conditions, the extra resources required
to effect increased production may simply not be available.

82   Calculated as the initial proportion of net taxes to total output for each sector.
83   Calculated as the initial proportion of capital requirements to total output for each sector.
84   For  a  more  detailed  discussion,  see  Eurostat  (2008)  ‘Eurostat  Manual  of  Supply,  Use  and  Input-Output  Tables’
http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-RA-07-013/EN/KS-RA-07-013-EN.PDF, p510-534.
- 106 -

Appendix 3: Model of Skilled Employment
10 Appendix 3: Model of Skilled
Employment
Let the economy consist of a large but finite number ( ) of workers.
Let the following assumptions hold:
  Workers may be of two types:  skilled ( ) and unskilled ( ).  Thus, we have            , where    is
the number of workers of type  .  Each type is defined by a (constant) productivity level,    or   .
  The economy is close to competitive, so that wages are reflective of productivity.
Define the proportion of skilled workers as       .

Let       and    denote total, skilled and unskilled output, where            .
10.1 Relationship between productivities
Productivity is defined as output per worker.  It can be shown that national productivity (     ) and the

productivities  of  the  two  types  of  worker  (                    )  are  related  according  to  the  following

equation.
          (     )
10.2 Calibration
  Eurostat  data  would  give  value  added  per  worker  while  calculating  employment  impacts  for  the
Member State in question as a whole.  This would fix  .
  Publicly  available  EU-LFS  data  would  give  information  on  the  proportion  of  workers  with  tertiary
education in the economy as a proportion of total worker, i.e. this would fix  .
  Eurostat  data  on  income  distribution  would  give  the  average  income  earned  by  those  with  various
levels of education.  By assumption, wages equal productivity in our model.  Combined with data from
the  EU-LFS  on  the  number  of  workers  at  each  education  level,  this  would  give  us  the  relative

productivity level of skilled and unskilled workers, i.e. this would fix   .

  Solve for    and
10.3 Determination of sectoral proportions
The productivity relationship given above can also be shown to hold for each sector, i.e.
            (      )
Here, the superscript   denotes the sector.
To determine    we simply need to use the calibrated values of    and    and the sectoral productivity as
calculated based on Eurostat data.
- 107 -

Appendix 4: Additional Results
11 Appendix 4: Additional Results
11.1 GDP
According to our calculations, an additional investment of €100m in the EU defence sector would lead to
an increase in European GDP of €96.26m.  This is consistent with a multiplier of 0.96, i.e. each additional
Euro invested in European defence would lead to an increase of €0.96 in European GDP.
The increases in output and the GDP multiplier of each Member State are shown in the table below.
Table 11.1: GDP effects and multipliers by Member State (excluding induced effects)
Member
Increase in GDP (€m)
GDP multiplier
State
Investment (€m)
(excl. induced effects)
(excl. induced effects)
AT
0.79
0.29
0.36
BE
0.83
0.29
0.35
BG
0.32
Table not available
Table not available
CY
0.12
Table not available
Table not available
CZ
0.86
0.43
0.50
EE
0.21
0.08
0.40
FI
1.86
0.92
0.49
FR
25.09
14.71
0.59
DE
17.22
9.12
0.53
EL
3.99
0.76
0.19
HU
0.36
0.13
0.37
IE
0.20
0.05
0.24
IT
6.87
4.00
0.58
LV
0.12
0.05
0.46
LT
0.12
0.04
0.39
LU
0.16
Table not usable
Table not usable
MT
0.00
Table not available
Table not available
NL
3.77
1.35
0.36
PL
3.15
1.53
0.49
PT
0.73
0.22
0.30
RO
0.49
0.21
0.42
SK
0.33
0.14
0.41
SI
0.21
0.10
0.48
ES
5.02
2.25
0.45
SE
2.30
1.03
0.45
UK
24.89
12.97
0.52
EU-27
100.00
96.24
0.96
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
We have found that the multipliers for individual Member States are all below that for the EU-27.  This is
because the Member State level analysis does not take into account the spill-over effects of an increase in
demand for products of other EU Member States, while the EU level analysis does.85

85   More specifically, the input coefficients in the EU-27 table reflect inputs produced anywhere in the EU whereas in
the Member State level tables they reflect only inputs produced in that Member State.  The structure of the I-O
tables available from Eurostat makes it impossible to include spill-over effects arising from increases in imports at
the Member State level.  As such, the estimates for Member States in the above table should be regarded as lower
bounds.
- 108 -

Appendix 4: Additional Results
At  the  Member  State  level,  the  multipliers  are  generally  in  the  0.30-0.60  range.    France,  Italy,  the  UK,
Germany and the Czech Republic have high multipliers of 0.50 or higher, whereas Greece and Ireland have
low multipliers of below 0.25.  This clearly illustrates that investments in some Member States would lead
to higher GDP effects than others.
11.2 Production tax
The  €100m  investment  would  result  in  an  increase  in  EU  production  tax  receipts  by  €10.59m.    This  is
consistent with a multiplier of 105.91, i.e. an investment of €1,000 would lead to an increase in production
tax receipts by €105.91.
The detailed results by Member State are shown in the table below.
Table 11.2:  Production tax effects and multipliers by Member State (excluding induced effects)
Production tax multiplier
Member
Increase in production tax
(increase in production tax
State
Investment (€m)
receipts (€000) (excl. induced
receipts per €1,000
effects)
investment)  (excl. induced
effects)
AT
0.79
9.27
11.71
BE
0.83
6.50
7.82
BG
0.32
Table not available
Table not available
CY
0.12
Table not available
Table not available
CZ
0.86
6.79
7.89
EE
0.21
2.16
10.28
FI
1.86
1.69
0.91
FR
25.09
1,061.72
42.32
DE
17.22
185.12
10.75
EL
3.99
45.24
11.35
HU
0.36
4.81
13.41
IE
0.20
2.14
10.53
IT
6.87
116.65
16.99
LV
0.12
Production tax data not available
Production tax data not available
LT
0.12
0.74
6.43
LU
0.16
Table not usable
Table not usable
MT
0.00
Table not available
Table not available
NL
3.77
-   24.31
-     6.45
PL
3.15
61.42
19.52
PT
0.73
8.28
11.31
RO
0.49
15.46
31.67
SK
0.33
6.15
18.44
SI
0.21
4.64
22.17
ES
5.02
36.52
7.28
SE
2.30
52.13
22.71
UK
24.89
39.72
1.60
EU-27
100.00
10,591.25
105.91
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
The results differ vary widely by Member State, but Member State multipliers are universally lower than the
EU multiplier.  The production tax multiplier depends on the magnitude of additional GDP as well as sector
specific tax rates.  Among countries with large defence investment, France has the highest multiplier, owing
to a large GDP multiplier as well as moderate tax rates in the sectors with the largest increases in output.
Spain and the UK have much lower multipliers in contrast, given that some sectors that experience large
increases  in  output  are  subsidised  in  net  terms.    Of  particular  interest  is  the  Netherlands,  where
production tax receipts would decline, indicating heavy production subsidies in key sectors.
- 109 -

Appendix 4: Additional Results
11.3 Total tax
A €100m investment in the EU defence sector would lead to an increase in total tax receipts (excluding
social contributions) by €26m, excluding induced effects.  This is consistent with a multiplier of 0.26, i.e.
each euro of investment would add €0.26 to total tax receipts (excluding social contributions).
The detailed results by Member State are shown in the table below.
Table  11.3:    Total  tax  effects  (excluding  social  contributions)  and  multipliers  by  Member  State
(excluding induced effects)
Increase in total tax
Member
Total tax multiplier (excl.
State
Total tax rate
receipts (€m) (excl.
induced effects)
induced effects)
AT
28.40%
0.08
0.10
BE
31.10%
0.09
0.11
BG
Table not available
Table not available
Table not available
CY
Table not available
Table not available
Table not available
CZ
18.50%
0.08
0.09
EE
20.40%
0.02
0.08
FI
30.10%
0.28
0.15
FR
25.60%
3.76
0.15
DE
23.70%
2.16
0.13
EL
20.60%
0.16
0.04
HU
26.60%
0.04
0.10
IE
22.50%
0.01
0.05
IT
27.70%
1.11
0.16
LV
22.30%
0.01
0.10
LT
20.30%
0.01
0.08
LU
Table not usable
Table not usable
Table not usable
MT
Table not available
Table not available
Table not available
NL
24.40%
0.33
0.09
PL
20.80%
0.32
0.10
PT
24.00%
0.05
0.07
RO
18.70%
0.04
0.08
SK
18.60%
0.03
0.08
SI
24.50%
0.02
0.12
ES
24.20%
0.54
0.11
SE
37.20%
0.38
0.17
UK
29.10%
3.77
0.15
EU-27
26.80%
25.79
0.26
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
Member State multipliers are universally smaller than the EU multiplier, and lie general in the range 0.07-
0.17.  States that experience larger increases in GDP per unit investment and have higher tax rates would
have higher total tax multipliers.  Thus, Sweden, with the highest tax rate also has the highest tax multiplier.
States like the UK, Italy and France have high tax multipliers owing to large GDP multipliers and moderate
tax rates.  Greece and Ireland have the lowest multipliers, owing to below average tax rates and extremely
small GDP increases.
Since these results have been arrived at by applying the total tax rate to the total increase in GDP, they can
be  shown  to  be  accurate  to  the  extent  that  (i)  the  total  tax  rate  is  constant  across  all  sectors  of  the
economy and/or (ii) the increase in GDP follows the same pattern as existing GDP.  We know both these
conditions to be false.  The tax rate are unlikely to be constant across all sectors as production tax rates
vary across sectors, even as income tax rates might be more uniform.  From the section on GDP effects,
we  know  that  increases  in  GDP  are  concentrated  in  a  few  key  sectors.    Thus,  these  estimates  must  be
- 110 -

Appendix 4: Additional Results
treated  only  as  approximations,  with  a  lower  degree  of  confidence  attached  to  their  accuracy  than
estimates for production taxes.
Results (including social contributions)
We have also calculated the effects for a definition of tax receipts that includes social contributions.  These
are shown in the tables below.
Table  11.4:    Total  tax  effects  (including  social  contributions)  and  multipliers  by  Member  State
(excluding induced effects)
Increase in total tax
Member
Total tax rate (including
Total tax multiplier (excl.
State
social contributions)
receipts (€m) (excl.
induced effects)
induced effects)
AT
44.20%
0.13
0.16
BE
47.00%
0.14
0.17
BG
Table not available
Table not available
Table not available
CY
Table not available
Table not available
Table not available
CZ
33.40%
0.14
0.17
EE
30.70%
0.03
0.12
FI
43.00%
0.40
0.21
FR
44.10%
6.49
0.26
DE
40.20%
3.67
0.21
EL
34.00%
0.26
0.06
HU
40.40%
0.05
0.15
IE
29.90%
0.01
0.07
IT
40.30%
1.61
0.23
LV
32.90%
0.02
0.15
LT
28.70%
0.01
0.11
LU
Table not usable
Table not usable
Table not usable
MT
Table not available
Table not available
Table not available
NL
38.90%
0.52
0.14
PL
32.80%
0.50
0.16
PT
35.90%
0.08
0.11
RO
28.80%
0.06
0.12
SK
31.50%
0.04
0.13
SI
38.90%
0.04
0.19
ES
36.70%
0.82
0.16
SE
45.90%
0.47
0.21
UK
37.40%
4.85
0.19
EU-27
40.40%
38.88
0.39
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
11.4 Employment
Our calculations show that a €100m investment in the EU defence sector would lead to the creation of
1,809.65  jobs.    This  is  consistent  with  an  employment  multiplier  of  18.10,  i.e.  each  €1m  invested  would
create 18.10 jobs.
The results for the Member State level analysis are shown in the table below.
- 111 -

Appendix 4: Additional Results
Table 11.5: Employment effects and multipliers by Member State (excluding induced effects)
Member
No. of jobs created (excl.
Employment multiplier ( no. of
State
Investment (€m)
induced effects)
new jobs per €m investment)
(excl. induced effects)
AT
0.79
4.56
5.76
BE
0.83
5.32
6.41
BG
0.32
Table not available
Table not available
CY
0.12
Table not available
Table not available
CZ
0.86
17.48
20.34
EE
0.21
5.18
24.68
FI
1.86
16.10
8.65
FR
25.11
209.77
8.36
DE
17.23
167.82
9.74
EL
3.99
23.39
5.87
HU
0.36
5.78
16.10
IE
0.20
0.94
4.62
IT
6.87
76.45
11.13
LV
0.12
Employment data insufficient
Employment data insufficient
LT
0.12
Employment data insufficient
Employment data insufficient
LU
0.16
Table not usable
Table not usable
MT
0.00
Table not available
Table not available
NL
3.70
20.75
5.50
PL
3.15
91.17
28.97
PT
0.73
8.89
12.14
RO
0.49
13.79
28.24
SK
0.33
7.81
23.41
SI
0.21
3.86
18.46
ES
5.02
50.88
10.13
SE
2.30
14.01
6.10
UK
24.90
221.06
8.88
EU-27
100.00
1,809.65
18.10
Source: Europe Economics’ calculations
Note: LV and LT employment data is missing for several key investment sectors
Note:  LU tables are too sparsely populated – several sectors are restricted
Our  results  show  a  wide  spread  of  employment  multipliers.    Those  Member  States  that  have  relatively
higher per capita incomes and labour productivity tend to have lower multipliers.  This can be explained by
the fact that a given amount of output can be created by fewer people in these Member States.
The  fact  that  the  EU  level  multiplier  is  relatively  high  does  not  mean  that  as  a  whole  EU  workers  are
unproductive.    Rather,  this  reflects  the  relatively  higher  GDP  impact  at  the  EU  level  due  to  the
incorporation of intra-EU trade.  Moreover, the fact that the EU employment multiplier is smaller than that
of  some  Member  States  despite  the  EU  GDP  multiplier  being  higher  than  those  of  all  Member  States  is
because some Member States have productivities that are so low relative to the EU average that even a
relatively small GDP increase can only be achieved by a relatively large addition to the workforce.
11.5 Skilled employment
At the EU level, 475.93 full time skilled jobs would be created.  This accounts for 26.30 per cent of all jobs,
and is consistent with a skilled employment multiplier of 4.76, i.e. each €1m invested would create 4.76
jobs at the EU level.
The results of the Member State level analysis are shown in the table below.
- 112 -

Appendix 4: Additional Results
Table 11.6: Skilled employment effects and multipliers by Member State (excluding induced effects)
Skilled employment
Member
No. of skilled jobs created
No. of skilled jobs created
multiplier (no. of new
as a proportion of total
skilled jobs per €m
State
(excl. induced effects)
jobs created
investment) (excl. induced
effects)
AT
1.23
26.93%
1.55
BE
0.75
14.05%
0.90
BG
Table not available
Table not available
Table not available
CY
Table not available
Table not available
Table not available
CZ
2.05
11.73%
2.39
EE
0.80
15.47%
3.82
FI
2.72
16.92%
1.46
FR
66.77
31.83%
2.66
DE
23.92
14.25%
1.39
EL
2.65
11.34%
0.67
HU
0.69
11.97%
1.93
IE
0.12
13.15%
0.61
IT
7.53
9.85%
1.10
LV
Employment data insufficient
Employment data insufficient
Employment data insufficient
LT
Employment data insufficient
Employment data insufficient
Employment data insufficient
LU
Table not usable
Table not usable
Table not usable
MT
Table not available
Table not available
Table not available
NL
3.76
18.14%
1.00
PL
22.37
24.54%
7.11
PT
1.02
11.46%
1.39
RO
2.96
21.50%
6.07
SK
1.64
21.02%
4.92
SI
0.64
16.53%
3.05
ES
9.47
18.61%
1.89
SE
1.44
10.25%
0.63
UK
58.72
26.56%
2.36
EU-27
475.93
26.30%
4.76
Source: Europe Economics’ calculations
Note: LV and LT employment data is missing for several key investment sectors
Note:  LU tables are too sparsely populated – several sectors are restricted
The most jobs would be created in Member States receiving the most investment, along with Poland, due
to its low worker productivity. As a percentage of total jobs, skilled jobs are the highest in France, Austria,
the  UK  and  Poland,  and  the  lowest  in  Italy.    The  skilled  employment  multipliers  for  Member  States  are
lower  than  that  for  the  EU,  except  for  Poland  and  Romania.    This,  again,  is  due  to  the  low  worker
productivity in these countries.
In our view, these estimates are unlikely to be very accurate, given that we have followed a second best
methodology in absence of access to micro-level data.  The variance of the assumption of our model with
reality is exhibited by the frequent instances of sector productivity being either lower than the unskilled or
higher than the skilled productivities derived.86  Thus, our model tells us that several sectors are composed
only  of  skilled  or  unskilled  labour,  which  is  clearly  not  true  and  introduces  a  significant  degree  of
arbitrariness into the analysis.  While these are the best estimates that may be calculated given the data
available, they are likely to be less accurate than, for instance, the results on total employment.

86   For instance, in the EU table, only 17 of the 65 sectors had productivities lying between the calculated skilled and
unskilled productivities.
- 113 -

Appendix 4: Additional Results
11.6 R&D potential
In  the  EU,  the  €100m  investment  would  lead  to  an  increase  in  R&D  value  added  by  €10.77m.    This  is
consistent with a multiplier of 107.74, i.e. every €1,000 of investment in EU defence would raise R&D value
added by €107.74.
The results of the Member State level analysis are shown in the table below.
Table 11.7: R&D effects and multipliers by Member State (excluding induced effects)
R&D multiplier (addition
Member
Addition to R&D value
to R&D value added in €
State
Investment (€m)
added (€000) (excl.
induced effects)
per €1,000 investment)
(excl. induced effects)
AT
0.79
4.25
5.36
BE
0.83
9.08
10.92
BG
0.32
Table not available
Table not available
CY
0.12
Table not available
Table not available
CZ
0.86
20.40
23.73
EE
0.21
1.32
6.31
FI
1.86
27.05
14.52
FR
25.09
3,140.86
125.20
DE
17.22
1,217.70
70.71
EL
3.99
4.66
1.17
HU
0.36
1.88
5.23
IE
0.20
0.08
0.41
IT
6.87
196.97
28.68
LV
0.12
0.19
1.61
LT
0.12
0.01
0.07
LU
0.16
Table not usable
Table not usable
MT
0.00
Table not available
Table not available
NL
3.77
67.35
17.87
PL
3.15
117.96
37.49
PT
0.73
10.79
14.74
RO
0.49
3.85
7.90
SK
0.33
3.03
9.08
SI
0.21
15.03
71.86
ES
5.02
284.24
56.62
SE
2.30
116.08
50.57
UK
24.89
2,847.04
114.41
EU-27
100.00
10,773.60
107.74
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
The bulk of the EU increase in R&D value added would be concentrated in three Member States – France,
the UK and Germany.  This is because most R&D investment would take place in these States, and because
these States have large and well developed defence research establishments.  This is borne out by the fact
that these three States have three of the four highest national multipliers.  There is a wide spread when
looking at multipliers, which arises from the fact that several countries do not spend large portions of their
defence spend on R&D.
Our analysis also showed that the main factor leading to an increase in R&D spend is direct effects of R&D
investment – the addition to R&D value added from indirect effects is relatively modest.
- 114 -

Appendix 4: Additional Results
11.7 Capital intensity
A €100m investment in European defence would lead to an increase in the consumption of fixed capital by
€13.10m  by  way  of  direct  and  indirect  effects.    This  is  consistent  with  a  multiplier  of  130.97,  i.e.  every
€1,000 of investment would be accompanied by an increase in the consumption of fixed capital by €130.97.
The results of the Member State level analysis are shown in the table below.
Table 11.8: Capital intensity effects and multipliers by Member State (excluding induced effects)
Capital intensity multiplier
Addition to consumption
(addition to consumption
Member
State
Investment (€m)
of fixed capital (€000)
of fixed capital in € per
(excl. induced effects)
€1,000 investment) (excl.
induced effects)
AT
0.79
37.13
46.87
BE
0.83
46.28
55.70
BG
0.32
Table not available
Table not available
CY
0.12
Table not available
Table not available
CZ
0.86
64.34
74.85
EE
0.21
8.05
38.36
FI
1.86
133.88
71.89
FR
25.09
CFC data not available
CFC data not available
DE
17.22
CFC data not available
CFC data not available
EL
3.99
124.56
31.25
HU
0.36
14.07
39.20
IE
0.20
5.65
27.82
IT
6.87
CFC data not available
CFC data not available
LV
0.12
5.49
46.50
LT
0.12
4.52
39.12
LU
0.16
Table not usable
Table not usable
MT
0.00
Table not available
Table not available
NL
3.77
153.21
40.65
PL
3.15
202.57
64.37
PT
0.73
30.91
42.20
RO
0.49
CFC data not available
CFC data not available
SK
0.33
22.94
68.81
SI
0.21
14.06
67.21
ES
5.02
CFC data not available
CFC data not available
SE
2.30
134.42
58.56
UK
24.89
CFC data not available
CFC data not available
EU-27
100.00
13,096.78
130.97
Source: Europe Economics’ calculations
Note:  LU tables are too sparsely populated – several sectors are restricted
Several Member States do not publish data on the consumption of fixed capital in their input-output tables,
including  the  five  biggest  recipients  of  the  hypothetical  defence  investment.    Therefore,  the  value  of  a
Member State level analysis is limited in this case.  Of the countries that do publish information, the Czech
Republic and Finland have the highest multipliers, Estonia and Lithuania have the lowest, and Poland has the
highest absolute addition to consumption of fixed capital.
- 115 -

Appendix 5: Opportunities for Further Research
12 Appendix 5:  Opportunities for
Further Research
The research presented in this report has provided some instructive insights to the economic benefits that
derive from investments in the defence sector, and the extent to which these benefits exceed those that
could be achieved through public investment in alternative sectors.
However, we consider that there are a number of areas in which there is significant potential for further
research which would contribute to a fuller understanding of the contribution of the defence sector to the
European economy.  In this section, we discuss a number of potential avenues for this research.
12.1 Extension to individual Member States
The analysis presented in this report has relied entirely on I-O tables that are published by Eurostat.  These
tables  contain  only  64  sectors  but  we  are  aware  of  some  Member  States  where  the  national  statistical
offices produce I-O tables with a much more granular break-down of the economy.  For instance, Austrian
tables contain 65 sectors, German tables contain 73 sectors and UK tables contain 122 sectors.
We  consider  that  it  would  be  feasible  to  extend the  methodology  used  in this  report  to  the  I-O  tables
produced by individual Member States.  This research would allow the defence sector to be more tightly
defined and so should provide more robust estimates of the impacts of investing in the defence sector.
12.2 Wider macroeconomic benefits
Another potentially fruitful avenue for future research would be to analyse the macroeconomic benefits of
the provision of defence services (as opposed to defence investment or investment spill-overs).  Solid and
adequate defence forces provide the preservation of peace, the protection of security and trade routes, the
underpinning  of  international  diplomacy,  and  the  support  of  the  projection  of  national  political
values.  These primary purposes have profound macroeconomic implications — few countries can flourish
economically without secure defence arrangements.
We consider that it would be possible to model the macroeconomic implications of defence spending as
akin  to  an  insurance  premium,  and  to  model  changes  in  the  optimal  level  of  defence  spending  (e.g.
associated with changes in the perceived future balance of geopolitical or other risks) as a change in the risk
profile against which insurance was sought.
Using a fully specified insurance modelling and estimation approach would be the most robust approach to
this analysis but it could become a lengthy and involved task. In pursuing this analysis it would be important
to note that the timescales over which full impacts of any sub-optimality in defence investment would be
felt might be significant, but there could be some highly non-trivial macroeconomic impacts of sub-optimal
defence expenditure even in the short term.
12.3 Spin-offs
In this report, we have attempted to identify the economic impacts of defence spin-offs.  However, we have
found the availability of data to be limited, particularly for studies of spin-offs from defence aerospace.  We
- 116 -

Appendix 5: Opportunities for Further Research
consider that there is likely to be scope for further research on this issue although the risk that necessary
data and information would not be available (or would not be provided to the researchers) cannot be ruled
out.
- 117 -