Download Dynamics between Military Expenditures and

Dynamics between Military Expenditures and Economic Growth:
What is the relationship between military expenditures and real economic
growth for European countries?
Bachelor Thesis: International Economics & Finance at Tilburg University
R.P. Roborgh
369326
06-06-2010
Supervisor: A.C. Meijdam
Number of Words: 8496
Faculty of Economics and Business Administration
Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Table of Content:
Chapter 1: Introduction
2
Chapter 2: Literature
4
2.1 History of Theories
2.2 Major Channels
2.3 Hypotheses
Chapter 3: Research
4
16
18
20
3.1 Database
3.2 Research
20
21
Chapter 4: Conclusion
27
Literature List
29
Appendix A: Variables
31
Appendix B: Countries
32
Appendix C: Regressions
33
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
CHAPTER81:8INTRODUCTION
The financial crisis of 2007 was followed by a public debt crisis all over the Western-world.
Especially in European countries, markets have put a lot of pressure to improve state
finances. While the north of Europe is doing relatively well on economic growth and public
finances, the south of Europe is having more trouble to deal with the aftermath of the
financial crisis. To decrease budget deficits and to slow the pace at which debt-to-GDP ratios
increase around Europe, governments have made and will continue to make tough choices
on where to cut their spending. Military spending is one of the expenditures most targeted
by budget cutters and is also one of the expenditures where cuts are most visible to the
public. For example, in April 2011, the Dutch government announced to cut all tanks, four
(out of ten) minesweepers and all Cougar-helicopters, giving budget cuts a physical character
(Volkskrant,22011).
Not only do governments have to find billions of budget cuts, they are also in the danger
zone of choking the weak economic growth which should soften the impact of worsening
debt ratios and which is the source of their tax base. It is therefore important to analyze
what the impact is of specific government expenditures on economic growth. If there is a
strong positive relationship, it would be unwise to cut spending, while in the case of a
insignificant or negative relationship, cutting could even accelerate economic growth. In this
thesis I will research this relationship for military spending. Although the world is changing
fast and European countries face different threats every year, I will not look at strategic
determinants of military spending or the ideal amount of military spending from a security
perspective. The reason is that recent revisions in military spending have shown that military
spending cuts and preparing the army for the future, might go hand in hand. Last year, the
United Kingdom and France have announced to cooperate on aircraft carriers, while former
defense minister of Germany Zu Guttenberg planned to cancel obligatory conscription to
reduce spending. Military cooperation is a good way to economize on the military budget
while increasing security for the participants. Because of the ambiguous effects of military
budget cuts on security this research is solely aimed at showing the relationship between
military expenditures (to which I will refer in this paper with “milex”) and economic growth
and will only look at strategic factors when they have a direct influence on this relationship.
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
The8aim8of8the8research8and8a8first8definition8of8the8subject8matter
The aim of this research is to show the correlation between military spending and economic
growth for (Western) European countries. A lot of research, starting with Benoit in 1973 has
been done so far on this milex-growth relationship. However, this research was mostly based
on undeveloped countries and only exceptionally on Europe. The research was often straight
to the point and ignored special characteristics as neutrality or a strong domestic defence
industry (Military Industrial Complex). Therefore, in this research I will also compare
European countries based on their neutrality and domestic defence sector. An interesting
part of defence economics literature concerns hegemonic leadership decline. France and
England are the only two military superpowers left in Europe. I will research if leaders
receive a premium on their economic growth or a discount. This leaves me with the
following research questions:
- What is the relationship between military expenditures and real economic growth for
European countries?
- What does having a strong domestic defence industry mean to real economic growth
compared to having a small domestic defence industry?
- What is the effect of a foreign policy based on neutrality on real economic growth?
- Do European leaders grow stronger than non-leaders?
The8methods8and8approaches8to8be8used
This research consists out of four chapters. The second chapter will describe the history of
research done so far on defence economics. It is based on the most commonly used groups
of theories, namely: Marxist/Underconsumptionist, the Keynesian/Institutionalist and the
Neoclassical plus the most influential independent theories. Besides that, this chapter will
also name all channels that were not included in these theories but have been named or
proven by economists. The aim of this is to show how defence economics has developed
through the last forty years and how complex defence economics is. I will also include the
assumptions and theories behind the research questions in this chapter. In chapter 3 I will do
regressions to obtain the correlation between milex and economic growth and to obtain
specifics results for the sub-groups. I use the SIPRI (Stockholm International Peace Research
Institute) for data on milex and a combination of sources for data on economic variables. In
chapter 4 I will give my conclusions on this research and answer the research questions.
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
CHAPTER 2
2.1 History of Theories
The research on defense economics started with Benoit in 1973 who researched the milexgrowth relationship for developing nations. He found a positive relationship implying that an
increase in military expenditure leads to an increase in the growth rate. Not only did many
researchers question his research method, also his results have been criticized (Pieroni,
2007: 2). Since 1973, many have researched the milex-growth relationship. Where
researchers like Benoit started with ad-hoc models, later they could make use of more
sophisticated growth models (Ram, 1995: 8). Some looked at developing nations, others at
developed nations, some at countries in state of war, others at countries in peace.
Throughout the history of defense spending different groups of dominant theories existed,
supplemented with individual theories on channels through which milex might affect
economic growth The research aims, methods and results have been various and a .single
conclusion cannot be made. While some researchers have found a small significant positive
relationship, others found an insignificant relationship. However, after almost forty years of
research, most of the researchers agree on the fact that military spending has a small
depressing8effect8on8economic8growth8(Aizenman8&8Glick,82003:82).
Underconsumptionist-Theory and the Keynesian Approach
Already before Benoit in 1973, theories about defense economics existed. A defense
economics groups of theories is the Marxist´ Underconsumptionist-theory, which was
popular as early as the 1960s. The theory is based on the assumption that capacity will
outstrip demand, thereby creating a surplus which is increasingly difficult for the economy to
absorb. This will have major consequences for capitalist industries, bringing them on the
brink of stagnation and crisis. However, due to the capitalist nature of these systems, with
their particular distribution of power, there will be pressure on governments not to make
any anti-capitalist moves. Military expenditures enters the picture because it has a more
ideological ground, namely fostering national security, while it effectively would increase
demand, absorbing the available capacity surplus. It could therefore function as an effective
anti-cyclical tool, with little political resistance (Rasler & Thompson, 1988: 5).
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Related to the Underconsumptionist-theory is the Keynesian-approach, which also calls for
government intervention in order to use excess capacity output. Other than the Marxists,
the Keynesian-approach emphasizes multiplier effects through which an increase in the
exogenous milex will lead to an increase in capacity utilization. This is expected to improve
the profitability of firms, giving them a bigger investment power, leading to growth. Closely
connected to the Keynesian-approach is the Institutionalist-approach, which agrees with the
Marxists that defense spending is a gateway to corporate profits. While the Marxists see
them as a result of the capitalist system, the Institutionalists see it is a failing of the political
system. The Military Industrial Complex, a combination of interest groups benefiting from
military spending, puts pressure on governments to spend on defense even in the absence
of threats, thereby creating immoral profits (Dunne, 2008: 4-5). However, where the
Institutionalist-approach puts more emphasis on the demand for military spending, the
Underconsumptionists and Keynesians aimed to explain a positive relationship between
milex and economic growth.
Smith’s Burden-on-Growth-Theory
One of the major researchers of defense economics, Smith, strongly opposes the
Underconsumptionist-theory. He accepts the fact that military spending could increase
aggregate demand in the short run, but is opposing the idea that it could sustain higher
levels of demand. ‘He disagreed with other Marxists in not interpreting war or rearmament
as a deliberate instrument of economic policy´ (Cappelen et al., 1988: 12). The nature of
defense spending is that it is subject to time lags due to its capital intensity and is therefore
not useful in maintaining aggregate demand in the short run. Smith’s criticism started as
early as the 1970s, followed by Dunne in 1990. They both see a drop in unemployment
during periods of higher defense spending, however, they do not see a systematic response
of the state on its defense spending in times of increasing unemployment-levels. Except for
rejecting the ´Underconsumptionist´-theory, Smith and Dunne also reject the Keynesian
approach which states that growth will take place through private investments. These are
funded, according to the Keynesians, by improved revenues for defense companies.
However, the net effect of short run stimulation on investment-levels in the long run is
unlikely to be positive due to Smith’s negative crowding out-effect of military spending on
investment levels. Smith and Dunne introduce the burden-on-growth thesis, which
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
emphasizes the resource trade-off between military expenditure and investment. `Aggregate
production is strictly resource-constrained, so that military spending cannot but divert
resources from other activities´ while taking the `potential output, rate of growth and rate of
utilization´ as given. ´Military expenditure is determined exogenously in the light of strategic
considerations and constraints, and investment then adjusts´, giving the government the key
to this ´crowding out´-effect. This depressing effect on capital investment formation is likely
to decrease the economic growth rate. Later, Dunne extends this trade-off to not only
diverting resources from investment, but also consumption, the balance of payments and
other government expenditures (Pivetti, 1992: 3,6-7). The crowding out-effect, originating
from the Burden-on-Growth-theory, is throughout defense economics the most popular
channel and is expected to show a negative relationship between milex and economic
growth.
Smith’s Leadership-Theory
The investment-trade-off is the core argument of the guns-for-butter (or burden-on-growth)
theorists. In 1977 Smith includes this theory into his more strategic theory of hegemonic
leadership decline. This theory says that the goal of the hegemonic leader is to `organize the
system at a world level much as individual nation-states do at the national level´. The costs
for this are `proportionate to the magnitude of the relative military power needed to assume
and maintain the leadership role´. Since this military power functions as a defense for other
states as well, these are less inclined to spend on defense, allowing them to avoid the
crowding out-effect. This defense-umbrella further increases defense costs for the
hegemonic leader while allowing other capitalist nations to improve their relative economic
position. ´The economic costs of the defense burden tend to undermine the very hegemonic
military-political structure that it is intended to defend’. Especially neutral countries and
countries whose defense is guaranteed by others, like in Iceland’s case, take maximum profit
from this defense-umbrella. In 1981 Gilpin adds to Smith’s theory that not only the milex of
a hegemonic leader crowd out investments, also consumption shares of the economy
increase at the expense of investments. Rostow counters Smith´s theory by pointing at the
tendency of investments levels for hegemonic leaders to level off while the other countries
see higher investments levels to make up for their lagging position. (Rasler & Thompson,
1988: 7-9). Hegemonic decline is therefore a normal, unavoidable process. Also the PhoenixPage 6 of 42
Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
effect, observed by Organski and Kugler, might play a role. They find that defeated countries
need about twenty years to match their victor’s welfare. This catching up-tendency might be
the result of a strong work ethic to rebuild the country (Capellen et al., 1984: 11). Taken all
effects8into8consideration,8leadership8decline9appears9to9be9inevitable.
Feder-Ram-Model
While Benoit, Smith and others had done innovative research in the field of defense
economics, models through which the milex-growth relationship could be shown were still
missing to this point. This changed with the creation of the Feder-model in 1983. Special to
defense economics is that it distinguishes itself from mainstream growth literature by the
models it uses. While mainstream growth economists nowadays prefer the Augmented
Solow-Growth model and Barro-model, defense economists for a long time made use of the
Feder-Ram model. This model eyed to show the effects of exports on economic growth. This
model was based on two sectors: export and non-export. Three years later, Ram and Biswas
adapted this model to research the effects of military spending on economic growth (Ram,
1995: 8-9) The model consists of two sectors: military and civilian output, denoted as:
where (M) and (C) are the total outputs for the military and civilian sector. (Lm) and (Km), and
(Lc) and (Kc) respectively, are the inputs of labor and capital for the military sector and
respectively the civilian sector. The civilian production function allows for externality effects
originating from the size of the military sector through the subscript (M), which also is the
total military output. Furthermore, the model allows for differences in factor-productivity of
the two sectors where the founders assumed that inputs are more productive in the defense
sector:
where the difference across the sectors in the marginal products of both capital and labor is
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
equal to (δ). Therefore, for a given amount of resources, assigning inputs towards the
defense sector will increase total output. The Feder-Ram-model was thereby the first model
that showed mechanisms through which defense spending could affect output and allowed
for estimations. The first channel being the externality effect of military size on output, and a
second channel through taking advantage of a positive difference in input productivity of the
military sector compared to the civilian sector. Through these two channels, the Feder-Rammodel explains how defense spending positively affects economic growth.
However, there were major shortcomings and the Feder-Ram-model is replaced by
mainstream growth models as the Augmented Solow Growth-model and Barro-model. One
major shortcoming comes from empirical research that has shown that the factorproductivity difference works in the advance of the civilian sector, rather than the defense
sector. Meaning that the defense sector is less efficient in its resource-use of labor and
capital than the civilian sector is. Reasons mentioned are that the defense sector is “less
subject to the rigors of market discipline” and that “strong competitive pressure to induce …
efficiency in management and use of resources” is absent. (Dunne et al., 2004: 9, 12)
Another shortcoming of the Feder-Ram-Model was that it did not account for non-linearity.
However, this limitation was later solved by Crespo, Cueresma and Reitschuler in 2004.
Non-linearity
During the process of unraveling the complexities of defense economics, researchers have
found agreement in the fact that the milex-economic growth relationship is non-linear.
Neglecting to look for non-linearity is one of the biggest criticisms of recent researches on
older ones. The awareness of non-linearism in defense economics really took off with
Landau’s work in 1993. Non-linearity in the defense economics implies that “at low levels of
milex, there will be a positive impact on growth, at higher levels of milex, milex will lead to
lower growth” (Landau, 1993: 6). Due to the wide variety of researches, all focusing at
different channels and countries, there exist different views on through which channels this
non-linearity exist. One of the primary explanations given by researchers is Landau’s theory
that at lower levels positive security and efficiency channels dominate, while at higher levels
of growth, the negative investment-channel dominates. Landau’s investment-channel is
simply the crowding out effect on investments by milex. He adds to this that high milex
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
create a big government, putting a burden on economic growth, the so-called “ Pentagon”effect. His security channel is more controversial by assuming that higher milex, for any level
of threat, will increase economic growth by creating an environment that stimulates private
investment. The controversy lies in the assumption that an increase in milex is positive in the
wake of a threat. His efficiency channel, or “Patriotic”-effect, considers the political reality
that in the wake of a foreign threat, an increase in milex requires a broadening or better use
of the tax base. This can be done by on one hand, modifying policies aimed at improving
economic growth which increases the tax base, while on the other to take a close view on
other government expenses, mainly rent creating policies. The level of awareness of the
threat by the public plays a key-roll in this process in order to obtain social support. Both
ways through the efficiency-channel lead to improved economic performance. Which of the
channels dominate, determines the net-effect on growth, creating a mountain-shaped
relationship (Landau, 1996: 11).
Landau’s work was appreciated and formed the basis of future research. First in 2001 Stroup
and Heckelman adapted Landau’s theory but put a focus on marginal productivity of the
defense and civilian sector. Stroup and Heckelman accept the criticism on the Feder-Rammodel that marginal productivity in the civilian sector is higher than in the defense sector.
They conclude that this acceptance implies that increasing the share of defense in the total
economy results in an increase in the opportunity costs of defense spending at an increasing
rate. A second process they identified was a consequence of diminishing marginal
productivity in the military sector. Stroup and Heckelman noted that this implies that
increasing defense spending as a share of the economy will create benefits at a decreasingly
rate (Stroup & Heckelman, 2001: 6). These two processes lead to the following function:
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
(Stroup & Heckelman, 2001: 8)
where the economy benefits most of defense spending at M1 and where it has no influence
at M2. Cueresma and Reitschuler (Pieroni, 2007: 2) agree on this theory of marginal
productivity as an explanation of non-linearity in defense economics, but they see it as a
result of external threat levels. They add that this might even lead to the “existence of
multiple8growth8regimes”.
Threats
Except for his focus on the non-linearity aspect of the milex-growth relationship in 1993,
Landau also focused on the role of threats on defense economics. However, not until 2003
there was a clear theory on the role that threat plays in the milex-economic growth
relationship. Aizenman and Glick (2003: 2-16) found non-linearity also in the role of external
threats. They state that milex in the absence of threats reduces growth, a lack of milex in the
wake of an external threat also reduces growth, but that milex in the presence of sufficient
external threats improves economic growth. This means that below a certain threat level, an
increase in milex has a negative effect on growth, while above this threat level, military
spending stimulates economic growth. The model thus assumes that milex as a response to
external threats increases growth, while milex due to rent-seeking corruption or inefficiency
reduces growth. The optimum level of milex in the absence of threats is none at all, however
in the reality of external threats, a positive milex is optimal. The presence of corruption
works as a tax on defense spending, thereby raising the optimal amount of milex for any
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
threat level. Like Stroup and Heckelman, they find the source for non-linearity in the
inconsistency of the marginal productivity of milex. One of the complexities of defense
economics, which also puts Aizenman and Glick’s theory into uncertainty, is the effect of
milex on external threat levels. An increase in milex could invoke an arms-war, leading to
more insecurity, instead of its purpose. This ambiguity also puts in question the positive
relationship between milex and the creation of an environment that attracts investments
through spending on defense.
Peace Dividend
One of the practical aspects of defense economics is what would happen to economic
growth when a country decides to reduce its defense spending. This discussion appeared
after the Cold War in defense economics to give economic estimates for the ongoing process
of disarmament. The drop in milex as a result of the easing of international tensions is called
the Peace Dividend and gained popularity halfway the 1990s (Davoodi et al., 2001: 2).
However, except for milex itself, a reduction in defense spending also implies other gains on
the economy. Economic growth gains from the Peace Dividend through a reversal of the
flows through most of the channels that are mentioned in this chapter. Also social programs
are likely to benefit. Peace Dividend-economists mainly focused on the choice between
spending the saved money to stimulate investments or to transfer it to deficit reduction.
They concluded that stimulating investment is the best choice since it increases economic
growth the most (Ward & David, 1992: 7). The difficulty of determining the size of the Peace
Dividend is similar to the complexities of defense economics at large. The milex-growth
relationship is subject to long lags in time and is also subject to different impacts in the long
run than in the short run, making it difficult to predict the economic consequences of cutting
defense spending for public policy makers.
Exercising the Peace Dividend, thus reducing defense spending in the wake of peace, is
believed to have a possible negative impact on economic growth in the short run, but
positively affecting economic growth in the long run. While Smith and others dismissed the
military budget as a suitable tool to alter aggregate demand, the Peace Dividend is
appreciated for the role it could play in a structural long-run macroeconomic package to
increase economic growth through an increase in capacity output. It should be emphasized
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
that the Peace Dividend-gains are only obtained to its full extent in the presence of peace,
and spending reductions are therefore likely to be carried out in mutual agreement or
understanding. Not only does the smaller defense expenditure distort the economy less, the
affiliated presence of peace also is an improvement of security leading for example to more
civilian R&D, a boost for free trade and more investments (Knight et al., 1996: 49-50). The
emphasis of this approach lies at the political aspect. Is it a multilateral decision that does
not decrease security nor does it create threats, or is the choice unilaterally made,
stimulating economic growth through some channels, but losing some benefits due to
increased insecurity or foregone gains as free trade? The benefits of a mutual reduction
vastly outpace the gains of a unilateral decision due to the presence of multiplier effects for
all parties involved. Related to this observation is the approach that does not see defense
spending as a public good but as a “public bad”, referring to practice that increasing defense
spending is likely to provoke a similar policy reaction from neighboring countries, not
increasing security at all (Davoodi et al., 2001: 23).
Augmented Solow-Growth Model
One of the two Neoclassical mainstream growth models that are recommended by Dunne,
Smith and Willenbockel (2001: 3) is the “ Augmented Solow Growth Model”. The Augmented
Model originates from Mankiw et al. (1992), was first used for defense economics by Knight
et al. (1996) and helps to explain and calculate the effects of milex on economic growth. The
model is an appreciated alternative for the Feder-Ram-model and has the following
production function:
where (Yt) is aggregate real income, (Kt) is capital (physical and human), (Lt) is labor and (α) is
the share of capital in output. (At) is technological change which is assumed to grow and is,
next to population growth and investments/savings, the source of economic growth in this
model. This model further assumes that the savings rate is exogenous, a constant labor force
growth rate (n), and a given rate of depreciation (δ). Furthermore, output (Yt) is devoted to
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
(public and private) consumption (Ct), investment in physical and human capital (It) and
military expenditure (Mt):
or rewritten as shares of total output:
This equation shows the negative relationship between investments and milex and implies
that this relationship is one to one, as first stated in the work of Smith in 1980. The
Augmented Solow-model does not allow this relationship (or trade-off) to influence the
steady-state growth rate, in accordance with the original Solow-model. But similarly, it does
allow for changes in the growth rate during the transition to steady-state. The one by one
relationship between milex and investments means that an one percent-point decrease in
milex consequently leads to an one percent-point increase in investments. Increasing
investments, which are equal to savings, means an upward shift in the (SY)-line to (S1Y)-line.
In this case, the original position is a steady-state growth rate (A). The movement of the (SY)line means a rise in the capital-labor-ratio from (K0) to (K1) and also an increase in the
output-labor ratio from (Y0) to (Y1). During this transition from steady-state at point (A) to
point (B) higher economic growth occurs. However, the effect of this boost is finished when
arriving at the new steady-state, meaning a return to the former steady-state growth rate
but at a higher K/L-ratio and Y/L-ratio. In reality, the original position where we start from is
on the left of (A), at (C) for example. Through a positive net investment-level the economy
was still moving to the steady-state growth rate at (A), but will now movie further to (B). The
political choice for freeing money for investment at the expense of milex means that the
future steady-state capital intensity and output-labor ratio of (A) are replaced by (B). In the
Augmented Solow-model this gives a higher growth rate during the transition to the steadystate growth rate (Burda & Wyplosz, 2009: 55-77).
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
(Wikimedia, 2011)
The criticizers of the Augmented Solow Growth Model state that the model is to tight and
simple. Milex might influence savings, technological progress, the utilization labor and
capital and human capital. Another point of criticism is the excluding of other variables. For
this reason the Barro-model is gaining popularity. The Solow model and the Feder-Rammodel differ on a few points. While the Feder-Ram-model consists out of two sectors, the
Solow-model has only one. But more importantly, the Feder-Ram-model is a supply-side
model, while the Solow-model is in defense economics regarded as a demand-side because
of its focus on investment displacement by milex. But despite being a demand-model, the
Solow-model hardly looks like other (Keynesian) demand-models. The results in defense
economics have, for a large extent, been depending on the choice between supply- and
demand-models, with supply-models, like the Feder-Ram-model giving “either a small
positive defense impact on growth or no impact at all”. On the other hand, demand-models,
like the Solow-model, tend to find a negative relationship between milex and economic
growth (Dunne, 2001: 5). Where supply-models look at the defense sector as a provider of
public infrastructure, a contributor to human capital and a positive influence to private
production through R&D experience and imitation of arms, (Keynesian) demand-models see
in the defense sector a less-controversial political tool to absorb unemployment and raising
aggregate demand, while creating a safe environment for investments (Shieh et al., 2002: 2).
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Welfare Maximizing
However, just looking at the impact on economic growth to determine the optimum level of
milex is too narrow, and ignores special characteristics of defense economics. As Futugama
et al. (1993) and Greiner and Hanusch (1998) show: “maximizing economic growth is not
equivalent to maximizing social welfare” when public services is a variable which determines
welfare (Shieh et al., 2002: 2). Although the dynamics around the demand for defense
spending will not be addressed in this paper, it is important to note this criticism on the
Neoclassical approach. The explanation for this can be found in Deger and Sen’s (1995) work
that “the demand for milex ultimately comes from perceived security – both external and
internal” and therefore the “the causes of defense spending should be analyzed in terms of
social welfare”. However, the first researchers introducing an extensive work on welfare in
defense economics were Hamid Davoodi et al. (2002: 3).They stated that when security is
regarded as a public good, defense should be included in the welfare function:
where (W) is welfare, (C) is consumption, (M) is military spending, (O) is non-military
government spending and (Z) is state variables.( )Z affects the leadership’s choice through
attaching weights to (M) and (O). The welfare function shows the choice that leaders
confront between maximizing public welfare through either military spending or nonmilitary government spending and implies that defense spending is a positive determinant of
social welfare. Some empirical evidence for this statement could be found in the observation
that since the end of the Cold War, disarmament or milex reductions barely have taken
place. This suggests that economic reasons behind demand for milex, which should enforce a
reduction in milex, are decimated in favor of social welfare. Accordingly, the optimal amount
of defense spending, that maximizes economic growth, is smaller than the amount devoted
to milex in order to maximize social welfare (Shieh et al., 2002: 10). The researchers around
Hamid Davoodi acknowledge the negative impact of milex on economic growth, but suggest
that countries take on this economic burden to improve public welfare. Except for this issue,
it is hard to measure the economic effects of milex in the first place. Not only the benefits
are hard to describe in dollars, the same counts for the expenses or the costs. An example
given by Landau is the difference between the salaries of conscript and their actual
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
opportunity costs. Since salaries are lower than the opportunity costs of conscript, milex are
similarly likely to be lower than the opportunity cost that the defense sector puts on the
society and economy (Landau, 1996: 6)
2.2 Major Channels
Although the most important channels have briefly been mentioned and have been
connected to the theories they belong to, still two channels require special attention. Both
the investment-savings-channel and R&D-channel have been playing key-rolls in defense
economics and have received attention from nearly every researcher. What makes them
interesting is the difficulties for researchers to decide on which flows dominate through
these8two8channels.
Investments8&8Savings
Smith was the first researcher to focus on the negative relationship between military
spending and investments through his so-called crowding-out effect. However, since Smith
later researchers have found other ways through which the milex-investment relationship
works. The main channel is the crowding out-effect it has on public and private investments.
Government expenditures are basically financed through two ways: current taxes or
borrowing (which could be seen as future taxes). Both reduce the after-tax return on
investments, discouraging this economic activity (Knight et al., 1996: 16). At the same time
the availability of savings for investments is absorbed by the government. Though milex does
not only have a negative influence: if defense spending increases security it also shapes an
investment-friendly business environment for domestic and foreign investors. A second
positive effect is that defense spending has on investment is called the spin-off effect and
finds its origin in the Keynesian theory. Defense expenditure is (partly) spent on weapons,
which is positive for the private production of the defense sector, creating cash-flow
available for further private investments by this sector (Shieh et al., 2002: 2).
The level of milex also has a big influence on savings and thus on economic growth,
especially in undeveloped countries, but also in some developed countries as the United
States. If milex are funded by taxation, then there will be a direct negative effect on savings
due to a reduced after-tax return. However, there is also a second crowding-out effect, next
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
to the crowding-out of investments, namely on competing government expenses as
education and health. A reduced contribution by the government means a bigger financing
risk lies at the public which induces them to save more and consume less (Dunne, 2008: 6).
So defense has a two-way effect on savings, a positive and a negative. To see the influence
of defense on savings, a good example was the increase in savings after the Cold War was
ended, taking away the fear of a nuclear war and inducing people to plan for the future
(Mintz & Stevenson, 1995: 18).
R&D8&8Human8Capital
The existence and size of a country’s defense sector, along with actual military spending, has
both positive and negative effects on the knowledge and research of an economy. The effect
that the military has on human capital and labor markets differs for countries according to
their economic phase. In less developed countries, the military might lower the pain of
unemployment, while providing training and education to a largely uneducated population.
However, for rich countries, especially those with low unemployment, the military and
especially conscription will impose more negative effects on economic growth (Shieh et al.,
2002: 2). Well-educated citizens are displaced from the productive civilian sector, while
conscription keeps students out of universities in their most productive years (Dunne, 2008:
5) In the field of research and development, two channels exist through which economic
growth is affected. On one side, weapon production, especially in countries which possess
capital-intensive industries, might benefit from technological spillovers from the military
sector to the productive civilian sector. On the other side, fears exist that the military
replaces civilian R&D, thereby changing productive R&D into unproductive R&D.
The hope for technological spillovers, which is expected to improve the economy, is one
reason, along with reducing the pressure on the balance of payments, to agree with weapon
exporters on “arms trade offset-deals”, or producing under licenses. Especially small
countries, not possessing a strong defense sector make use of these trades. However, Dunne
& Brauer (2004) have shown that both deals neither have a positive impact on economic
development, nor does it create any sustainable employment and the hoped technological
spillovers8barely8take8place8(Dunne,82008:811).
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2.38Hypotheses
In this paper I will research the relationship between milex and economic growth and the
relationship between countries’ strategic characteristics and economic growth:
- What is the relationship between military expenditures and real economic growth for
European countries?
- What does having a strong domestic defence industry mean to real economic growth
compared to having a small domestic defence industry?
- What is the effect of a foreign policy based on neutrality on real economic growth?
- Do European leaders have stronger real economic growth than non-leaders?
Based on the literature and earlier researches, I expect to see a negative relationship for
milex and real economic growth based on the Augmented Solow-model and Smith’s theory
of investment crowding-out. Landau and Aizenman and Glick’s theory of non-linearity is also
expected to hold in reality. However, due to the strong convergence of milex-levels and
economic growth in the EU, there might not be enough observations obtain a clear quadratic
equation.
The literature so far has not focused on the effects of the size of the defence industry on real
economic growth. However, with the help of theories from defence economics predictions
could be made. The Underconsumptionist-theory predicts a positive effect of a strong
domestic defence industry on real growth. The defence sector is a high value-added industry
and an a source for foreign capital inflow. It is therefore an ideal sector to absorb the
capacity surplus in the economy. Using the Feder-Ram-model gives a similar conclusion. On
the other side, Smith and the Augmented Solow-model both give no clear expectation.
Having a strong defence industry is in itself not a source of investment crowding-out.
However, countries that possess a strong industry might be lured into overspending on milex
thereby8depressing8growth.
Also about the influence of neutrality on real economic growth not much is known. The only
theorists that might provide some guidance are Aizenman and Glick (2003). Countries
running a neutral foreign policy could be seen as having a smaller external threat than nonPage 18 of 42
Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
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neutral countries, or no threats at all, since they do not endanger others’ security. This
assumption divides the two sub-groups of countries on their optimal defence spending level.
For neutral countries, the optimal level will be lower than for non-neutral countries, since at
low external threat levels, negative channels dominate positive channels in the milex-growth
relationship. This would imply that for any level of milex being neutrality means a discount
on real economic growth. However, since these governments are aware of lower threatlevels, they have the opportunity to cut their military spending. According to Smith and the
Augmented
Solow-model,
cutting
milex
will
improve
real
economic
growth.
The answer of the question on leadership should be predicted with the help of Smith. His
leadership-theory says that the fall in leadership is almost inevitable, especially due to
security costs. It is therefore expected that being a leader puts a burden on real economic
growth.
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Chapter83:_Research
3.1_Countries
The relationship between military spending and economic growth has been researched
many times in many different ways, also solely for the EU-15 and particularly for the
Mediterranean countries. This paper differs from these researches on the sample that is
taken and on the emphasis. To obtain the best results, only countries which face similar
external threats will be used for this research. The sample therefore consists out of the EU15, minus Greece, but plus Malta, Norway and Switzerland. The reason that Greece is
excluded from this sample is due to their Cyprus dispute with Turkey which has led to overspending on milex compared to “peaceful” Europe. Malta, Norway and Switzerland have
been added due to their similarities with the EU-15 on milex and their threat-levels.
New for defense economics is that this paper investigates what effect the presence of a
strong domestic defense industry has on economic growth. Countries of the EU-15 have
been classified in either the big arms industry or the small arms industry based on how they
were categorized by Dunne and Nikolaidou (2011) as having a developed defense industry.
Malta is due to its size classified as having a small arms industry. Switzerland and Norway
however, are both grouped as having developed arms industries. Norway had the biggest
arms exports per capita in 2006 (Afterposten, 2006), while ranking 11th in the world in real
terms. Switzerland ranked 12th in arms exports in 2009 (SIPRI, 2011). The small states of
Europe have been ignored because of their minimal size or for the reason that their territory
is8protected8by8others,8as8the8United8States8does8for8Iceland.
Another innovation is to research the effect of neutrality on economic growth. Out of the
sample of 17 countries, only 6 are classified as neutral: Austria, Finland, Ireland, Malta,
Sweden and Switzerland, where some have a longer tradition of neutrality than others. All of
these 6 countries are member of the “Partnership for Peace”-program of the NATO, which
was founded in 1994 to create trust between NATO-member states and other countries in
Europe and former Soviet Union-states. Malta left the program in 1995 but reactivated its
membership in 2008. While this program was not seen as an breach of neutrality,
membership of the EU raised some questions on neutrality due to the Common Foreign and
Security Policy. Despite the CFSP, these countries are still accepted as neutral (NATO, 2011).
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
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Although research was done in the field of Smith’s leadership theory, it was never focused
on Europe and the existing research is outdated. Kasler and Thompson (1988) researched
Germany (1873-1913 and 1951-1978), France (1821-1913 and 1951-1978) and Great
Britain(1831-1913 and 1946-1978), next to the United States and Japan. Where Kasler and
Thompson included Germany as a major power, I will not. France and the United Kingdom
have a special military leadership role in Europe because of their nuclear deterrence, their
aircraft carriers, their overseas bases and their high defense spending compared to GDP.
3.2_Research
I will conduct the research by regressing various variables with real GDP-growth. As control
variables, which are expected to explain economic growth, I will take “(Real) Initial GDP” in
1993, “(Real) Interest Rate”, “Average Years of Schooling”, “Population Growth”,
“Investments as a share of GDP” and “Inflation rate”. The independent variable that is the
key of my research is “Milex”, which stands for military spending. The problem of two-way
causality arises when defense spending and education are included in the regression. The
levels of milex and education influence economic growth, but the funding of them also
depend on economic growth itself. To solve this I will take previous values for milex and
education. While I normally take the averages of five years, with 1995, 2000 and 2005 as
median-year, for these two variables I will scrap the years around 2005 but include the years
around 1990. This will block the reverse causality sufficiently. It was impossible, especially
due to a lack of military data, to obtain an instrumental variable that is unrelated to
economic growth but which is a good estimator for milex. The other variables will make use
of data running from 1993 to 2007 with every year taking in consideration and resulting in
three averaged observations per country. By selecting three time-periods instead of one, the
sample8increases8from8178possible8observations8to851.
When regressing only milex with real economic growth, the following scatter plot is
obtained. The plot shows a vague negative trend in economic growth while increasing the
level of milex to GDP. The observations reflecting exceptionally high economic growth are
Ireland, Luxembourg and Malta. The first two saw strong economic development through
the financial sector while the latter came from a low point of economic development
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On the right-flank of milex are France and the United Kingdom positioned, right after the
collapse of the Soviet-Union, when they still had to start the process of monetizing the Peace
Dividend.
The precise results can be found in table 1, column 1. Milex is significant (1,5%) at the 5%level (α=0,5) and has a beta of -0,678. This gives the regression equation: Y = 4,149 – 0,678X,
which complies with the main opinion of defense economists that milex has a depressing
effect on economic growth with a 0,678 percentage point decrease in the real economic
growth rate for every percentage point increase in milex. However due to the early work of
Landau and later by Stroup and Heckelman, non-linearity gained popularity and should be
checked for. To do that I add the square of milex to the regression. Table 1, column 2 shows
the results for this regression. From this data the regression equation for the effect of milex
on real economic growth can be obtained: Y = 6,625-3,497X+0,688X² for which milex (0,3%)
is significant at the 1%-level (α=0,01) and milex² (1,3%) is significant at the 5%-level (α=0,5).
Although the usefulness of the model increases from 11,5% to 22,2% by adding milex², the
results do not comply with the expectations. Instead of a mountain-shaped regression line, a
U-shaped regression line is formed. As Landau (1993: 6) puts it: ‘Initially increases in milex
are associated with faster growth and beyond a certain level they are associated with slower
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
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growth’. Instead we see the opposite: a decrease in growth rates at low levels of milex while
an increase in growth rates at high levels of milex. The minimum of the regression equation
lies at X = 2,54 where Y = 2,18 (see figure 1). This means that, according to the model, a
milex-level of 2,54% of GDP is the most harmful to the economy and both increasing milex or
decreasing it will improve economic performance. Based on the work of Landau (1993 and
1996) and Stroup and Heckelman (2001) it was expected to see a maximum somewhere
close on the left of the model’s minimum of 2,54% milex. However, the extent to which their
work is relevant to the European defense reality since the fall of the USSR is doubtable.
Fig. 1: Milex - Real Economic Growth
Real Economic Growth
10
8
6
4
Actual
2
Expected
0
0
1
2
3
4
5
6
Milex
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
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When I add the control variables, results are less fortunate for the hypothesis. Leaving aside
the milex², but adding all control variables makes milex highly insignificant (94,8%). The
variables “Real Initial GDP”, “Real Interest Rate”, “Average Years of Schooling” and
“Population Growth” are significant. Real initial GDP (0,3%) is significant at the 1%-level
(α=0,01) while showing a negative beta.. This complies with the “convergence-theory” which
implies that countries with lower initial GDP will grow faster than countries which are
further in their economic development. Real interest rate (8%) is significant at the 10%-level
(α=0,1) and also has a negative beta. This was expected since real interest rates have a
depressing effect on economic growth. Education is, together with real initial GDP, the most
significant variable (0,7%) at the 1%-level (α=0,01) and has a positive beta. This is in line with
Barro (1991) who proved that education is a contributor to economic growth. And last,
population growth is significant (1,3%) at the 5%-level (α=0,05) and has a positive beta. This
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
is in accordance with the Solow-model which mentions population growth as one of the
determinants of economic growth. Compared to only including milex in the regression, the
usefulness of the model has risen sharply from 11,5% to 48,1%. With milex² taken into
account, the usefulness increases from 22,2% to 48,1%. In that case the insignificancy of
milex drops slightly from 94,8% to 87,4%, which is close to the insignificancy of milex2 88,3%.
While the usefulness of the model has risen sharply after extending it, it makes the
relationship between military expenditures and economic growth very insignificant.
A way to obtain a significant level for milex is by removing population growth and education
from the regression. In that case, milex will be significant (6,5%) again at the 10%-level
(α=0,1). However, usefulness has dropped again to levels seen before (25,6%). Adding milex²
gives both a very significant milex (1,4%) and milex² (3,9%). Also the real interest rate (8,4%)
is significant at the 10%-level and usefulness has increased to 32,5%, but real initial GDP has
turned insignificant. The results implicate that population growth and education take over
military expenditures (and its square) as the determinants of economic growth in this model.
Defense8Industry
To research the effect of the size of the defense industry on economic growth I take the
extended model excluding milex and milex2 since they are both insignificant. Table 3, column
1 shows the results when including a dummy for the size of the industry (with 1=big and
0=small). The dummy has a beta of -0,515, but is insignificant (15,3%). Therefore, no
conclusions
can
be
made
about
its
relationship
to
real
economic
growth.
Neutrality
Changing the industry-dummy for the neutrality-dummy (with 1=neutral and 0=non-neutral),
gives a similar result. The dummy for neutrality shows a positive beta of 0,607, but is
insignificant (13,7%). Also about the effect of neutrality on real economic growth, no
conclusions8can8be8made.
Leadership
The leadership-dummy (with 1=leader and 0=non-leader) is by far the most insignificant
dummy (95,7%) and also its beta shows no clear direction (-0,029).
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Chapter84:8Conclusion
The results of the regressions have not answered the research questions satisfactory. The
main research question ‘What is the relationship between military expenditures and real
economic growth?’ was initially answered with the expected (significant) negative
relationship. The non-linearity-theory however failed to hold. Although there was nonlinearity, it was a positive instead of a negative relationship. When extending the model with
six other variables, both milex and milex2 turn insignificant. However, with all regressions
taken into account, I think it is safe to say that milex has a depressing effect on real
economic growth, albeit weak, in accordance with most recent findings of other researchers.
To prove non-linearity, a more diverse set of observations is required, preferably outside
Europe8to8include8observations8with8higher8levels8of8milex.
On the second question ‘What does having a strong domestic defence industry mean to real
economic growth compared to having a small domestic defence industry?’ , my research
gives no clear answer since the dummy is insignificant. A way to solve this for future
researchers might be to dig deeper into the defense industry. As I found out, defense
economics is a playing field with many different players, interests, channels, opportunity
costs and externalities. The emphasis should lie in analyzing the dynamics between
governments and their domestic Military Industrial Complex. How does the MIC itself
influence defense policies, how do defense policies change for economic reasons due to the
existence of a big domestic defense industry, how much defense money flows abroad or
comes in, and perhaps anno 2011 most importantly: how is your government’s milex
financed and at what expense? Based on such a comprehensive analysis a conclusion can be
made about the actual total benefits and costs of housing a big defense industry. The answer
on ‘What is the effect of a foreign policy based on neutrality on real economic growth?’ is
also disappointing since the neutrality-dummy was insignificant as well. Therefore no
statistical conclusion can be made about the economic consequences of changing your
foreign policy towards neutrality. However, since milex has a depressing effect on economic
growth and since neutral countries have substantial lower defense spending without being
attacked in recent history, you could conclude that neutrality is not a bad idea. At the same
time, these countries managed to sustain a big domestic defense industry, like Austria,
Sweden and Switzerland. Neutrality at the core of your foreign policy is in theory the only
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way to maximize the ‘Peace Dividend’. It gives you an advantage over your economic
competitors. This corresponds to Smith’s leadership-theory which sees the security-umbrella
of the hegemonic-leader as the reason for the leader’s decline and the rise of its allies, which
are at the same time its economic competitors. It is actually a reversion of the “Peace
Dividend”-theory by implying that the position of hegemonic-leader is maximizing rejecting
the “Peace Dividend”. Although my statistical research did not prove a relationship between
neutrality and economic growth, it is undeniable that Europe’s neutral countries are the
world’s most competitive. Today’s relevancy of Smith’s leadership-theory is questioned by
the results for ‘Do European leaders grow stronger than non-leaders?’ My research gives
insignificant results which cannot answer this question. The number of observations is
limited plus the convergence of milex-levels after the USSR-fall might have made Smith’s
leadership-theory irrelevant to the European situation anyway. Though, when looking at the
past decade the United States seem to be the ultimate proof of the correctness of the
leadership-theory. So we should be careful not to dismiss Smith’s theory because of the
weak results of my research. A better set of observations (followed by better research
results) might also allow for researching the effect of the dummies I took on the milexgrowth relationship itself through interaction-terms instead of directly on economic growth.
This might allow for conclusions on which European countries can use milex-levels for
balancing the overall budget through which part of the business cycles. Also, providing
better estimates of non-economic effects of milex could result in a overall conclusion on the
role of milex in the economy, but perhaps more importantly, its effect on social welfare.
European governments should take notice from this and earlier research that cutting milex
in the current budgetary turmoil might be a relieve to both the budget and the economy,
leaving strategic reasons for milex aside. To obtain the entire “Peace Dividend”, European
countries should consider building their foreign-policy around neutrality. The research was
too limited to conclude on the consequences of a big domestic defence industry. Perhaps
the best conclusion is that having one is a blessing, but it starts acting as a curse when policy
decisions are made based on having and maintaining this industry instead of sound security
interests, since it tends to drag scarce domestic resources from the national budget to an
unproductive8sector.
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Literature8List
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ANP, 2011. Defensie: 6.000 Mensen en Alle Tanks Weg. Volkskrant, [online], 8 April 2011.
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<http://www.volkskrant.nl/vk/nl/2824/Politiek/article/detail/1872359/2011/04/08/Defensi
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Appendix A: Variables
Av_Yrs_Schooling: Average years of schooling calculated with the data of 1990, 1995 and 2000.
Data source: World Bank.
http://siteresources.worldbank.org/EXTEDSTATS/Resources/3232763-1171296308277/34459081171320551553/3449375-1171320604454/total_age15.xls
D_Industry: Dummy for having a big (1) or a small (0) defense industry, based on “Defense
Spending and Economic Growth in the EU15” by J.P. Dunne and E. Nikolaidou and with data on
arms exports on SIPRI.
D_Leadership: Dummy for military leadership position (1) or non-leader position (0).
D_Neutrality: Dummy for being non-neutral (1) or neutral (0), based on CIA World Factbook.
Eco_Growth: Real annual economic growth calculated by taking an average of 5 years-periods
with 1995, 1995 and 2005 as median-year and data running from 1993 to 2007. Data source:
Eurostat.
http://epp.eurostat.ec.europa.eu/tgm/table.do?tab=table&init=1&language=en&pcode=tsieb02
0&plugin=1
Inflation_Rate: Inflation rate, as the annual percentage change in consumer prices, calculated by
taking 5 year-periods with 1995, 2000 and 2005 as median-year and data running from 1993 to
2007. Data source: World Bank.
http://data.worldbank.org/indicator/FP.CPI.TOTL.ZG
Initial_GDP: Real Initial GDP per capita in 1993, 1998 and 2003 (current US$). Data source: World
Bank. http://data.worldbank.org/indicator/NY.GDP.PCAP.CD?page=3
Interest_Rate: Real interest rate calculated by taking the average of 5 years-periods with 1995,
2000 and 2005 as median-year and data running from 1993 to 2007. Data source: Nationmaster.
http://www.nationmaster.com/graph/eco_rea_int_rat-economy-real-interest-rate
Invest_GDP: Investments as a share of GDP calculated by taking the average of 5 years-periods
with 1995, 2000 and 2005 as median-year and data running from 1993 to 2007. Data source:
World Bank.
http://data.worldbank.org/indicator/NE.GDI.TOTL.ZS
Milex: Military expenditures as a share of GDP calculated by taking the average of 5 yearsperiods with 1990, 1995 and 2000 as median-year and data running from 1988 to 2002. Data
source: SIPRI (Stockholm Institute for Peace Research Institute). http://milexdata.sipri.org/
Popul_Growth: Population growth as a percentage increase of the population calculated by
taking the average of 5 years-periods with 1995, 2000 and 2005 as median-year and data
running from 1993 to 2007. Data source: World Bank.
http://data.worldbank.org/indicator/SP.POP.GROW
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Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Appendix B: Countries
Total: Austria, Belgium, Denmark, Finland, France, Germany (FRG+GDR), Ireland, Italy,
Luxembourg, Malta, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland and United
Kingdom.
Neutral: Austria, Finland, Ireland, Malta, Sweden, Switzerland.
Non-Neutral: Belgium, Denmark, France, Germany, Italy, Luxembourg, Netherlands, Norway,
Portugal, Spain and United Kingdom.
Big Defense: Austria, France, Germany, Italy, Netherlands, Norway, Spain, Sweden,
Switzerland and United Kingdom.
Small Defense: Belgium, Denmark, Finland, Ireland, Luxembourg, Malta and Portugal.
Leaders: France and United Kingdom
Page 32 of 42
Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Appendix C: Regressions
Regression table 1, column 1:
Model Summary
Model
R
Std. Error of the
Square
Estimate
R Square
a
1
Adjusted R
,338
,115
,096
1,41774
a. Predictors: (Constant), Milex
b
ANOVA
Model
1
Sum of Squares
df
Mean Square
Regression
12,736
1
12,736
Residual
98,489
49
2,010
111,225
50
Total
F
Sig.
6,336
a
,015
a. Predictors: (Constant), Milex
b. Dependent Variable: Real_Growth
Coefficients
a
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
4,149
,528
Milex
-,678
,269
Coefficients
Beta
t
-,338
Sig.
7,852
,000
-2,517
,015
a. Dependent Variable: Real_Growth
Page 33 of 42
Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Regression table 1, column 2:
Model Summary
Model
R
R Square
a
1
,471
Adjusted R
Std. Error of the
Square
Estimate
,222
,190
1,34248
a. Predictors: (Constant), Milex_Squared, Milex
b
ANOVA
Model
1
Sum of Squares
df
Mean Square
F
Regression
24,716
2
12,358
Residual
86,509
48
1,802
111,225
50
Total
Sig.
a
6,857
,002
a. Predictors: (Constant), Milex_Squared, Milex
b. Dependent Variable: Real_Growth
Coefficients
a
Standardized
Unstandardized Coefficients
Model
1
B
(Constant)
Milex
Milex_Squared
Std. Error
6,625
1,083
-3,497
1,123
,688
,267
Coefficients
Beta
t
Sig.
6,117
,000
-1,745
-3,115
,003
1,445
2,578
,013
a. Dependent Variable: Real_Growth
Page 34 of 42
Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Regression table 2, column 1:
Model Summary
Model
R
R Square
a
1
,693
Adjusted R
Std. Error of the
Square
Estimate
,481
,390
1,12991
a. Predictors: (Constant), Popul_Growth, Av_Yrs_School, Invest_GDP,
Milex, Interest_Rate, Inflation_Rate, Initial_GDP
b
ANOVA
Model
1
Sum of Squares
df
Mean Square
Regression
47,246
7
6,749
Residual
51,068
40
1,277
Total
98,314
47
F
Sig.
a
5,287
,000
a. Predictors: (Constant), Popul_Growth, Av_Yrs_School, Invest_GDP, Milex, Interest_Rate,
Inflation_Rate, Initial_GDP
b. Dependent Variable: Real_Growth
Coefficients
a
Standardized
Unstandardized Coefficients
Model
1
B
(Constant)
Std. Error
,757
2,049
-,018
,273
-8,181E-5
Coefficients
Beta
t
Sig.
,370
,714
-,009
-,066
,948
,000
-,520
-3,201
,003
-,159
,089
-,260
-1,798
,080
Invest_GDP
,002
,034
,007
,051
,960
Inflation_Rate
,161
,279
,093
,577
,567
Av_Yrs_School
,402
,141
,458
2,843
,007
Popul_Growth
1,542
,592
,399
2,607
,013
Milex
Initial_GDP
Interest_Rate
a. Dependent Variable: Real_Growth
Page 35 of 42
Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Regression table 2, column 2:
Model Summary
Model
R
R Square
a
1
,693
Adjusted R
Std. Error of the
Square
Estimate
,481
,374
1,14398
a. Predictors: (Constant), Milex_Squared, Inflation_Rate,
Interest_Rate, Invest_GDP, Av_Yrs_School, Popul_Growth,
Initial_GDP, Milex
b
ANOVA
Model
1
Sum of Squares
df
Mean Square
Regression
47,275
8
5,909
Residual
51,039
39
1,309
Total
98,314
47
F
Sig.
a
4,516
,001
a. Predictors: (Constant), Milex_Squared, Inflation_Rate, Interest_Rate, Invest_GDP,
Av_Yrs_School, Popul_Growth, Initial_GDP, Milex
b. Dependent Variable: Real_Growth
Coefficients
a
Standardized
Unstandardized Coefficients
Model
1
B
(Constant)
Std. Error
,942
2,418
-,202
1,269
-8,030E-5
Coefficients
Beta
t
Sig.
,390
,699
-,101
-,159
,874
,000
-,511
-2,891
,006
-,157
,091
-,256
-1,717
,094
Invest_GDP
,001
,035
,004
,030
,976
Inflation_Rate
,167
,285
,096
,585
,562
Av_Yrs_School
,397
,146
,453
2,721
,010
Popul_Growth
1,517
,623
,392
2,436
,020
Milex_Squared
,041
,279
,089
,149
,883
Milex
Initial_GDP
Interest_Rate
a. Dependent Variable: Real_Growth
Page 36 of 42
Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Regression table 2, column 3:
Model Summary
Model
R
R Square
a
1
,506
Adjusted R
Std. Error of the
Square
Estimate
,256
,173
1,35612
a. Predictors: (Constant), Inflation_Rate, Interest_Rate, Invest_GDP,
Milex, Initial_GDP
b
ANOVA
Model
1
Sum of Squares
df
Mean Square
F
Regression
28,466
5
5,693
Residual
82,758
45
1,839
111,225
50
Total
Sig.
3,096
a
,017
a. Predictors: (Constant), Inflation_Rate, Interest_Rate, Invest_GDP, Milex, Initial_GDP
b. Dependent Variable: Real_Growth
Coefficients
a
Standardized
Unstandardized Coefficients
Model
1
B
Std. Error
(Constant)
4,733
1,633
Milex
-,560
,295
-9,091E-6
Interest_Rate
Invest_GDP
Initial_GDP
Inflation_Rate
Coefficients
Beta
t
Sig.
2,899
,006
-,279
-1,895
,065
,000
-,067
-,422
,675
-,201
,094
-,316
-2,142
,038
-,032
,038
-,114
-,828
,412
,406
,271
,220
1,502
,140
a. Dependent Variable: Real_Growth
Page 37 of 42
Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Regression table 2, column 4:
Model Summary
Model
R
R Square
a
1
,570
Adjusted R
Std. Error of the
Square
Estimate
,325
,233
1,30581
a. Predictors: (Constant), Milex_Squared, Inflation_Rate,
Interest_Rate, Invest_GDP, Initial_GDP, Milex
b
ANOVA
Model
1
Sum of Squares
df
Mean Square
F
Regression
36,199
6
6,033
Residual
75,026
44
1,705
111,225
50
Total
Sig.
a
3,538
,006
a. Predictors: (Constant), Milex_Squared, Inflation_Rate, Interest_Rate, Invest_GDP, Initial_GDP,
Milex
b. Dependent Variable: Real_Growth
Coefficients
a
Standardized
Unstandardized Coefficients
Model
1
B
(Constant)
Std. Error
6,911
1,876
-2,943
1,155
-1,059E-5
Interest_Rate
Invest_GDP
Coefficients
Beta
t
Sig.
3,685
,001
-1,469
-2,549
,014
,000
-,078
-,511
,612
-,163
,092
-,256
-1,770
,084
-,034
,037
-,121
-,912
,367
Inflation_Rate
,363
,261
,197
1,391
,171
Milex_Squared
,568
,267
1,193
2,130
,039
Milex
Initial_GDP
a. Dependent Variable: Real_Growth
Page 38 of 42
Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Regression table 3, column 1:
Model Summary
Model
R
R Square
a
1
,712
Adjusted R
Std. Error of the
Square
Estimate
,507
,420
1,10114
a. Predictors: (Constant), D_Industry, Interest_Rate, Av_Yrs_School,
Invest_GDP, Inflation_Rate, Popul_Growth, Initial_GDP
b
ANOVA
Model
1
Sum of Squares
df
Mean Square
Regression
49,814
7
7,116
Residual
48,500
40
1,213
Total
98,314
47
F
Sig.
a
5,869
,000
a. Predictors: (Constant), D_Industry, Interest_Rate, Av_Yrs_School, Invest_GDP, Inflation_Rate,
Popul_Growth, Initial_GDP
b. Dependent Variable: Real_Growth
Coefficients
a
Standardized
Unstandardized Coefficients
Model
1
B
(Constant)
Std. Error
1,010
1,799
-7,101E-5
,000
-,160
Invest_GDP
Coefficients
Beta
t
Sig.
,562
,578
-,452
-2,759
,009
,085
-,262
-1,888
,066
,004
,031
,015
,122
,903
Inflation_Rate
,156
,271
,090
,575
,569
Av_Yrs_School
,378
,135
,432
2,808
,008
Popul_Growth
1,421
,571
,367
2,487
,017
D_Industry
-,515
,354
-,174
-1,457
,153
Initial_GDP
Interest_Rate
a. Dependent Variable: Real_Growth
Page 39 of 42
Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Regression table 3, column 2:
Model Summary
Model
R
R Square
a
1
,713
Adjusted R
Std. Error of the
Square
Estimate
,509
,423
1,09885
a. Predictors: (Constant), D_Neutrality, Initial_GDP, Invest_GDP,
Popul_Growth, Interest_Rate, Inflation_Rate, Av_Yrs_School
b
ANOVA
Model
1
Sum of Squares
df
Mean Square
Regression
50,015
7
7,145
Residual
48,299
40
1,207
Total
98,314
47
F
Sig.
a
5,917
,000
a. Predictors: (Constant), D_Neutrality, Initial_GDP, Invest_GDP, Popul_Growth, Interest_Rate,
Inflation_Rate, Av_Yrs_School
b. Dependent Variable: Real_Growth
Coefficients
a
Standardized
Unstandardized Coefficients
Model
1
B
(Constant)
Std. Error
,867
1,786
-6,738E-5
,000
Interest_Rate
-,149
Invest_GDP
Coefficients
Beta
t
Sig.
,485
,630
-,429
-2,554
,015
,085
-,243
-1,749
,088
-,010
,032
-,037
-,304
,763
Inflation_Rate
,289
,284
,166
1,018
,315
Av_Yrs_School
,324
,143
,369
2,255
,030
Popul_Growth
1,316
,584
,340
2,252
,030
,607
,401
,205
1,516
,137
Initial_GDP
D_Neutrality
a. Dependent Variable: Real_Growth
Page 40 of 42
Bachelor Thesis Economics, Tilburg University: Dynamics of Military Expenditures and Economic Growth
What is the relationship between military expenditures and real economic growth for European countries?
Regression table 3, column 3:
Model Summary
Model
R
R Square
a
1
,693
Adjusted R
Std. Error of the
Square
Estimate
,481
,390
1,12993
a. Predictors: (Constant), D_Leadership, Initial_GDP, Popul_Growth,
Invest_GDP, Interest_Rate, Inflation_Rate, Av_Yrs_School
b
ANOVA
Model
1
Sum of Squares
df
Mean Square
Regression
47,245
7
6,749
Residual
51,070
40
1,277
Total
98,314
47
F
Sig.
a
5,286
,000
a. Predictors: (Constant), D_Leadership, Initial_GDP, Popul_Growth, Invest_GDP, Interest_Rate,
Inflation_Rate, Av_Yrs_School
b. Dependent Variable: Real_Growth
Coefficients
a
Standardized
Unstandardized Coefficients
Model
1
B
(Constant)
Std. Error
,736
1,968
-8,200E-5
,000
-,161
Invest_GDP
Coefficients
Beta
t
Sig.
,374
,710
-,522
-3,245
,002
,087
-,263
-1,842
,073
,002
,034
,007
,057
,955
Inflation_Rate
,158
,280
,091
,564
,576
Av_Yrs_School
,402
,143
,458
2,817
,007
Popul_Growth
1,550
,579
,401
2,675
,011
D_Leadership
-,029
,533
-,007
-,055
,957
Initial_GDP
Interest_Rate
a. Dependent Variable: Real_Growth
Page 41 of 42