Military Expenditures and Economic Growth in Asia by Khin Ma Ma Myo
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Transcript of Military Expenditures and Economic Growth in Asia by Khin Ma Ma Myo
Military Expenditures and Economic Growth in Asia
(Econometric analysis)
By Khin Ma Ma Myo (University of Aberdeen)
===========================================================
This paper analyzes the effects of military expenditures on economic growth in
Asian countries. Although the defense-growth relationship has been studied
through different types of economic models, these have produced conflicting
results and it is still not known whether military spending promotes or hinders the
growth of the economy. In this paper, the impact of defense spending is
investigated through a demand and supply-side model with simultaneous equation
methodologies. Empirical results indicate that there is no clear-cut impact of
defence spending on economic growth rate but has a negative impact on savings-
income ratio in Asian countries. The results also show that the military and
economic strategic factors play a significant role for low- income countries.
===========================================================
Khin Ma Ma Myo Page 1
Introduction
“The first duty of the sovereign, that of protecting the society from the
violence and invasion of other independent societies can be performed only
by means of a military force. But the expense both of preparing this military
force in time of peace, and of employing it in times of war, is very different
in the different states of society, in the different periods of
improvement” (Smith, 1776, bk v: 1)
The relationship between military expenditures and economic growth is an
important and controversial matter for defense economics. In his book of “An
inquiry into the Nature and causes of the Wealth of Nations”, Adam Smith
considered the implications of military expenditures by justifying the expense of
defense as a first duty of the government (Kennedy, 1983). He was one of the first
economists to discuss the impact of military expenditures on economic growth.
Since then, a substantial number of economists have analyzed the issue both
theoretically and statistically. In his version of Marxist economics, Mandel (1968)
Khin Ma Ma Myo Page 2
argued that defense spending as a share of national income is ‘ever greater’ in
capitalist countries (Mandel, 1968: 524). However, defense spending as a share of
national income was falling in that period due to its crowding out effects on public
expenditures. Indeed, military spending has an adverse effect on economic growth.
On the contrary, Benoit (1973, 1978) provided empirical evidences of the benefits
of defense burden on economic growth. According to Benoit, defense spending
stimulates rather than depresses the economy. Subsequent studies were followed
after Benoit; however, no clear- cut results have emerged about the nature and
extent of the effects of this expenditure on economic growth.
Hartley (2005) identified the adverse effects and benefits of military spending as
follows. The adverse growth effects of military spending might arise:
(i) Defense may divert resources away from public and private sector
investment which may be favorable to growth than defense spending
(ii) Adverse balance of payments impacts through imports of arms and
where resources are diverted away from the export sector.
Khin Ma Ma Myo Page 3
(iii) Defense, particularly defense R&D, might divert resources from
private sector R&D activities affecting both technology and spin-offs.
The resources diverted embrace both physical and human capital.
Accordingly, the possible economic benefits of defense spending include:
(i) In periods of high unemployment, both types of countries might
experience stimulative effects from defense spending
(ii) Defense provides direct technology benefits and spin-offs, where spin-
offs applied to the civil sector can promote growth
(iii) In less developed countries especially, defense spending might promote
growth if some of the expenditure is used to provide social infrastructure
(iv) Defense spending provides protection to a nation’s citizens where
internal and external security promotes market exchange
(v) Developing and supporting human capital, especially in less developed
nations. (Hartley, 2005 :2)
Khin Ma Ma Myo Page 4
This study attempts to find out whether military spending promotes or hinders
economic growth in Asian countries during 1985-2000.
Economic Effects of Military Spending
In the defence economics literature, the economic effects of military spending have
been the subject of theoretical and empirical studies. There are empirical studies
concerning defence- growth relationship for NATO countries (Macnair et al.,
1995), Latin American countries (Scheetz, 1991), OECD countries (Smith, 1980),
Middle Eastern countries (Yildirim, Sezgin & Ocal, 2005) and other less developed
countries (Benoit, 1978; Deger & Smith, 1983; Galvin, 2003).
In addition, there are single country analyses of military expenditures- economic
growth relationship for United States, Australia, Egypt, Israel, Syria, Turkey,
Cyprus, Greece, Peru, Taiwan, India, South Africa, China, etc. (Ward, 1991;
Madden, 1995; Kollias, 1997; Beenstock, 1998; Batchelor, 2000; Dunnie, 2001;
Sezgin, 2001;Klein, 2004; Lai, 2005)
Khin Ma Ma Myo Page 5
As there are several hypotheses regarding the relationship of economic growth and
defence expenditures, the above studies support each of these alternative
arguments empirically. In general, there are three main versions of the military
spending- economic growth proposition.
Firstly, military spending may stimulate economic growth through Keynesian-type
aggregate demand effects. Benoit (1978) suggested that defence spending can
enhance growth by increasing aggregate demand that leads to increased utilization
of capital costs, lower resource costs, high level of employment and higher profits.
Hence increasing in the profit rates induces higher investment that will generate
higher growth rates and short-run multiplier effects.
In his book of Defence and Economic Growth in Developing Countries, Benoit
identified the favorable effects of defence spending. According to Benoit, there are
four beneficial effects such as
Khin Ma Ma Myo Page 6
(1)Training effects
He argued that military training and experience can be assumed as
productivity-enhancing byproducts because these can generate knowledge
and skills such as discipline, acting on instructions, spending and saving
money, gaining familiarity with manufactured products, travelling around
the country and general inculcation of national values and attributes. The
trained military personnel can take these skills to the civilian sector after
demobilization. (Grobar & Porter, 1989)
(2) Infrastructure effects
The military may create the infrastructure such as roads, airports, docks that
can be available for civilian use. Moreover, disaster rehabilitation, mapping,
surveying, geological and meteorological Research & Development have
civilian spin-offs. (Kennedy, 1983)
(3)Consumable effects
Military production of close substitutes for civilian goods makes it “possible
for the civilian economy to devote a higher share of its total output to
investment”. It may include ‘civic action’ programs and ‘hearts and minds’
campaigns.
Khin Ma Ma Myo Page 7
(4)Security effects
The military may provide security for higher investment and long-term
planning decisions. The economy may disintegrate without it. So essential
security required for economic progress is provided more fully by more
defence spending (Benoit, 1973). Moreover, military tension has sometimes
led nations to cooperate more effectively and work extra hard (Benoit, 1978:
278)
In addition, defence spending produces some indirect gains thus help economic
growth through spillover benefits to private sectors of the economy. For example,
highways, sea and air navigational aids can help the transportation industry as well
as shipbuilding and aircraft manufacturing increase the scale of operations.
Moreover, the increased demand for scientists, engineers, electronics experts and
skilled technicians, stemming from both military operations and military research
and development causes extra investment in scientific skills (Hitch & McKean,
1967)
Furthermore, it has been suggested that military spending may induce economic
growth through a spin-off effect. Nevertheless, as the military is one of the most
Khin Ma Ma Myo Page 8
modern institutions in the LDCs, it can help in creating modernized socioeconomic
structure (Chowdhury, 1991). Deger (1986) also argued that economic growth may
be stimulated through this effect. Moreover, if countries are expressing under-
employment, military expenditures may have a stimulated effect, with higher
aggregate demand, production and employment (Yildirin, 2005)
A number of empirical studies support the positive relationship between military
spending and economic growth. Newman (1978) studied the effects of defence
spending on Iran and concluded that the modernizing of the Iranian military
program had a strong stimulation effect on higher economic growth. Ram (1986)
studied 115 countries by using cross-sectional time-series estimations and
concluded that military spending had a positive impact on growth.
Mueller and Atesoglu (1990& 1993) studied United States and provided a positive
effect of defence on growth but small. On the other hand, Mintz and Haung (1990)
studied the same country and concluded that military spending dampened
investment and, hence, growth. For Ward (1991) who studied India, defence
spending had a positive impact on economic growth.
Khin Ma Ma Myo Page 9
Similarly, Beenstock (1998) who studied Israel for the period of 1950-1994;
Sezgin (2001) who studied Turkey for the period of 1956-1994 and Lai, Huang &
Yang (2005) who studied China and Taiwan for the period of 1952- 2000 argued
that defence benefited growth, thus, a positive impact. Moreover, the results for
Turkey and middle eastern countries (1989-1999) studied by Yildirim, Sezgin &
Ocal (2005) indicate that defence sector is more productive than civilian sector and
defence spending enhances growth.
In contrast to this hypothesis, it has been argued that there is a trade-off between
military expenditures and productive investments, thus, military expenditure can
have a negative impact on economic growth. Chowdhury (1991) identified the
detrimental effects of defence expenditures in several ways such as
(1)Defence expenditures can divert available resources from domestic capital
formation, thus reducing potential savings available from investment and
this can increase the savings-investment gap, hence, it can eventually reduce
economic growth.
(2) If an increased defence burden reduces the amount of new capital formation
from the level it could have attained, then the economy suffers from a
Khin Ma Ma Myo Page 10
lowering of both the quantity and quality of its capital stock as Deger (1986)
suggested.
(3)There is also the possibility of a round-about effect of defense spending via
reduced availabilities of growth products for exports with consequent
growth-damping effects as Rothschild (1977) pointed out.
(4)The absorption of public expenditure in defence may lead to a shortage of
available funds in other fields such as education, health, development aid
and so on as Dabelko & McCormick (1977) found out.
(5) Defence burdens may also depress growth through the inflationary process
they generate.
Alternatively, Deger (1983) examined the growth-defence relationship by using
the four channels through which military expenditures may influence
production, namely
(1)Resource allocation
Military expenditures have direct opportunity costs in terms of foregone
investment, consumption, etc.; balance-of-payments cost in terms of
imported weapons and reduction of resource in terms of military aggregate
demand.
Khin Ma Ma Myo Page 11
(2)The organization of Production
Military investment in technology may be restricted to capital-intensive
modes of production that are of little use to the majority of the population
living in the rural hinterland of LDCs.
(3)The sociopolitical structure
Military establishments, by their very nature, are often seen as conservative
institutions with rigid hierarchical structures, and their concern for stability
and maintenance of status quo may inhabit them from taking positive steps
in the transformation of society.
(4)External Relations
The military loyalty in LDCs is often to the imperial power with which there
are links and that the military creates conditions under which surplus can be
transformed out of the country and the foreign aid succeeded by the military
may be a mixed blessing, creating more problems than it solves.
These types of claims challenged the Benoit’s hypothesis of positive defence-
growth relationship and several studies supporting the Deger’s hypothesis of
negative defence-growth relationship were followed. Fredericksen & Looney
Khin Ma Ma Myo Page 12
(1983) reported a negative relationship between defence spending and economic
growth in resource-constrained LDCs. Lim (1983) also concluded that the negative
effects of military spending on economic growth were more obvious among the
poor countries in Africa. Smith (1980), Faini, Annez and Taylor (1984), Lebovi &
Ishaq (1987), Scheetz (1991), Ward & Davis (1992) supported the hypothesis that
military spending had a net negative impact on economic growth.
In addition, Alexander (1995) who studied the OECD countries for the period of
1966-88 claimed that the impact of defence spending on growth is negative but
small. Similarly, Dunne, Nikolaidou & Roux (2000) who studied South Africa for
the period of 1989-1996 reported that the impact is negative but coefficients have
low significance. For Galvin (2003) who studied 64 developing nations, defence
spending had a negative impact on growth and savings ratio. Also, Klein (2004)
and Karagol & Palaz (2004) who studied Peru and Turkey, respectively, claimed
similar results like Galvin.
Although there are a lot of claims regarding this negative impact, there is no
evidence that reducing defense spending would automatically raise an economic
growth rate in the real world. This is mainly because substitutability is the product
Khin Ma Ma Myo Page 13
of a political process, not an economic one and depends on the changes in the
political arrangements of the countries. (Kennedy, 1983: 199)
On the other hand, the third version of defence-growth relationship emerged as
Joerding (1986) stated as economic growth may be causally previous to defence
expenditures. He argued that the most important point to assess whether defence
spending promotes or deters growth is affected by the changes in the economy.
Although military spending may affect growth through various mechanisms, it is
plausible that economic growth may be causally prior to military expenditures. For
example, do increases in defence spending create a follow-on change in the
economy, or, do economic changes cause movements in defence expenditures?
(Karagol & Plaza, 2004)
Dakurah (2001) supported this claim by stating that a country with high growth
rates may wish to strengthen its external as well as internal security by increasing
defence spending and it is equally plausible that countries with high growth rates
may divert resources from defence to other more productive uses.
Khin Ma Ma Myo Page 14
Specifically, Kollias (2004) identified four possible outcomes of the causal
relationship between defence spending and economic growth such as
(1)bi-directional causality between the two time-series
(2)unidirectional causality from growth to defence expenditures
(3)unidirectional causality from defence spending to growth and
(4) the absence of any causal relationship
After the claim of no evidence that military spending causes growth by Joerding
(1986), several studies were followed to examine these causal relationships with
extensive empirical work. Huang & Mintz (1990, 1991) studied the United States
for the period of (1952-88) and claimed that there is no defense effect on growth.
Similarly, Alexander (1990) studied 9 developed countries for the period of 1974-
1985 and concluded that there is no defense effect on growth. The same results
occurred in LDCs for the period of 1974-86 as studied by Alexander (1990).
Similar hypothesis is supported by Mintz & Stevenson (1993) who studied 103
countries with multiple intervals.
Khin Ma Ma Myo Page 15
Among the post-1995 literature, studies such as Madden & Haslehurst (1995),
Kollias (1997) and Kollias & Makrydakis (2000) showed there is no causal
ordering in either direction between military spending and economic growth. Also,
Al- Yousif, who studied Arab Gulf (1975-1998), claimed that the defence
spending- economic growth relationship cannot be generalized across countries.
However, Kollias, Naxakis & Zarangas (2004), who studied Cyprus (1964-1999),
reported that there is an instantaneous bi-directional causality between defence and
growth.
So it is clear that there has not been a convincing support for all three hypotheses
of the defence- growth relationship. Nevertheless, one important thing is that
defence spending may have the supply-side effects (diversion of resources from
other productive resources, reduction in private savings and investment, inefficient
of allocation resources, human resources development, improved infrastructure,
increased technological know-how, etc.) and the demand- side effects (inflationary
if resources are fully utilized, positive impact on aggregate demand if there is
unemployment, etc.) on the economy whether the effects may be positive or
negative.
Khin Ma Ma Myo Page 16
Thus, the purpose of this study is to analyze the defence-growth relation to identify
whether defence spending can promote or retard economic growth in Asian
countries during the period of 1985- 2000. Although military expenditures in Asian
countries represent one of the highest figures in the world, no previous studies of
defence-growth relationship concerning Asian counties were found in the defence
economics literature. In this paper, the relationship between military expenditures
and economic growth in 18 Asian countries is investigated by using the
simultaneous equation models and OLS estimation techniques for the time period
under consideration.
Military Balance in Asian Countries
Nation states are represented as rational agents that maximize a welfare function
for their citizens depending on the security and economic situations and subject to
budget constraint in the standard neoclassical model (Smith, 1995: 71). So the
competing for resources should be not only the military sectors but also the social
sectors. The purpose of military spending is to provide the military defence of,
principally, a country’s national security (both its state interest and territory) and,
ultimately, security of its citizens. For social sector, the purpose of social
Khin Ma Ma Myo Page 17
expenditure s to provide social services to the citizens of a country (SIPRI,
2007:272)
Throughout the history, most countries try to increase the military power as an
instrument in a variety of goals. These include prevention of an invader from
seizing one’s territory and taking away a part of one’s territory, taking away part of
the territory of another country and conquering another country (Payne, 1989:61)
During the Cold World, the national security agenda was based only on high
politics which emphasized on the issues of war and nuclear deterrence. However,
the world military balance trend declined with the fall of the Berlin Wall and the
trend in military strategy and national security agenda has been changed from high
political issues to low politics which emphasized on the issues of economic
development, environment and natural resources.
In a period (1986- 2000) under consideration, there was a downward trend in
overall military expenditures. But, in Asia, military spending has shown an
increasing trend. Before the Asian financial crisis in 1997-1998, the military
expenditures of Asia countries were increasing rapidly. Even after the financial
crisis, only slightly moderated but resumed procurement deals again in 2000.
Khin Ma Ma Myo Page 18
For security concerns, Asia has an increasing danger place. As Blackwill (2003)
pointed out, Asia has returned to the central stage in international system after five
hundred years and is driven by the crucial factors of
• The long peace among the major Asian powers in the last quarter of the 20th
century, underpinned by the security presence of the United States in Asia,
created political conditions for economic prosperity;
• The success of the liberal international economic order permitted many
Asian states to increase their economic growth rates far beyond the global
historical norm; and,
• The presence of enlightened leadership in key Asian countries produced
national strategies focused on economic development, expanded trade, and
increased prosperity. (Blackwill, 2003)
Despite of rapid economic prosperity, Asian countries find themselves beset with
many security issues, both in traditional and non-traditional terms. As the Institute
of Defence studies and Analyses (IDSA) notes, Centrifugal tendencies continue to
simmer in some states, many of these owing to socio-economic disparities. As a
result, common interests in economic prosperity have reduced but not completely
eliminated the potential for inter-state conflicts. Contentious issues such as the
volatility of energy supplies and threats to their dislocation, the safety of sea lines
Khin Ma Ma Myo Page 19
of communication, possible decline of tourism over terror threats, have emerged as
well. (IDSA, 2003)
Moreover, Asia is susceptible to acute instability. Different categories of conflicts
such as civil wars, insurgencies, ethnic conflicts, irregular wars and terrorism have
broken out between states and non-state players. Along with these, the
accentuation of geo-political fault- lines has severe security ramifications for the
region in general. Along a broad arc of volatility that stretches from the
Middle East and Persian Gulf (e.g. Iraq) to Northeast Asia (e.g. North
Korea), the region contains a hazardous mix of rising and declining regional
influential, prosperous and failing states, status quo and revisionist
nations, and responsible and rogue governments. (Blackwill, 2003)
For Asian governments, armed forces play an important role to maintaining
internal security. In most cases, states have made a steady transition to mature
democracies; however, it could not negate the possibility of interstate war and
conflict as politicians sometimes exacerbate ethnic, religious and social
inequalities leading to instability and insecurity. Due to this changing political and
economic environment, there has been a search for new military missions, not only
to justify budgets, but also to find a replacement for the lack of external threats
including combating transnational security threats, such as narcotics trafficking,
Khin Ma Ma Myo Page 20
illegal migration, or environmental degradation and other humanitarian and
peacekeeping operations. (Smith & Peterman, 2000)
As a result, political instability, internal security and external threats to states have
helped justify allocating rare resources for military expenditures rather than for
social expenditures. So it is important to analyze the growth effects of military
spending.
The following figures present comparative analyses of the military spending of 18
Asian countries for the period (1985- 2000). Figure 1 shows the total military
expenditures in terms of US$ millions while figure 2 shows the military burdens as
percentages of GDP within this period.
Khin Ma Ma Myo Page 21
(Source Data: International Institute for Strategic Studies, Military Balance, various editions)
Khin Ma Ma Myo Page 22
(Source Data: International Institute for Strategic Studies, Military Balance,
various editions)
Khin Ma Ma Myo Page 23
The above figures clearly show that the military expenditures in Asian countries
have continuously rising despite of the downward trend in the world. These also
reflect the impact of the financial crisis in 1997. Moreover, figure (2) indicates that
there is a little correlation between military burden and country size. In fact, the
rise of military expenditure depends on various factors such as escalation of
conflicts, wars, revolutions and ideologies.
After 15 years, Bangladesh military spending has tripled from 217 to 691 US$
millions, however, its military burden as a percentage of GDP is never more than
2%. Strategically, it lies at the strategic crossroads of South and Southeast Asia
and located near the India-China disputed frontier in the north. Military has been
regarded traditionally as the only institution capable of providing the nation with
efficient and effective administration. In addition to the defense roles, military
provided support to civil authorities for disaster relief and international security. Its
troops participated in 1991 Gulf War and in numerous UN peacekeeping
operations.
For the period of 1985-2000, military spending in India has doubled with average 3
percent defence burden of GDP. During the late 1990s, India forces were involved
Khin Ma Ma Myo Page 24
in two regional peace operations in Sri Lanka and Maldives. Moreover, they
involved in UN Peacekeeping operations. In fact, India was grappling with three
separate insurgencies in three states of Assam, Jammu and Kashmir, and Punjab. In
addition to insurgencies, India faced a lot of national security challenges including
political assertiveness and the proliferation of nuclear capabilities. Indeed, India
has involved in a three-way arms race in the region involving India, Pakistan and
China. (Ganguley, 1995)
For the period under consideration, military expenditures in Nepal had risen
threefold, especially in 2000. Geopolitically, its frontiers are regarded by India and
China as international boundaries; however, it was located as a geostrategic
position between China’s Tibetan population and India’s heartland that can lead to
a vulnerable situation (Makeig, 1991).The army has participated in aid- to civil-
power duties including disaster relief. As it is one of the poorest countries in the
world, Nepal had no enough provision for military. But, it still had a modest
military burden of average one percent of GDP.
Similarly, military expenditures in Pakistan has risen twofold until 1999, but had a
downward trend after that. It is a nation with a gaping external and internal security
Khin Ma Ma Myo Page 25
deficit. In the early 1990s, it engaged in a missile development program although
its nuclear program is shrouded in secrecy (Thornton, 1994). Pakistan contributed
in peacekeeping efforts in Bosnia, Herzegovina and Somalia. For internal security,
Pakistan had subversion and civil unrest problems, which are rooted in its own
polity and society. As a result, it leads to repeated political collapse, corruption,
failure to meet people’s needs and lack of religious and ethnic identities. Despite of
its increasing military expenditures, the military burden decreased from 7% to 4%.
For the period 1985-2000, military expenditures in Sri Lanka had more than
threefold with various fluctuations. Most of the threats to national security were
internal rather than external. Insurgency is the most serious problem in Sri Lanka.
The growing problem of civil unrest rooted not only from ethnic conflicts but also
from general economic problems (Levy, 1998). The intervention of peacekeeping
efforts decreased the defense expenditures; however, the military burden was very
high. It is mainly exacerbated by the fighting between the military and the
Liberation Tigers of Tamil Eelam.
For China, its military spending significantly decreased during the late 1990s, but,
rose rapidly after 1997. Although there are several reasons for this large increase,
Khin Ma Ma Myo Page 26
the most frequently offered official explanation is that military salaries have
needed to rise to stay in line with non-military pay levels (Information office of the
State Council of the People’s Republic of China: 2006) With the military
modernization program, the shift in resources have become in favor of economic
development; however, it represented the biggest spender in the region. For
national security concerns, China viewed Soviet Union as a major external threat.
Moreover, despite of its claim over non-existence of ethnic conflicts, it had Tibetan
problems as an internal threat. However, China defence White Paper did not
discuss on how the military plans did not relate to these threats.
For Indonesia, defense spending increased dramatically but decreased during the
late years of twentieth century. Mostly, it gives low priority to military
expenditures. Indonesia’s army had endorsed the principle that scarce domestic
resources and foreign aid could not be diverted for military use without slowing the
progress of national development (Haseman, 1992)
For Japan, the military spending has traditionally been capped at 1 per cent of
GDP. However, as the economy was so large that its military expenditure was the
biggest in Asia and Oceania. This is partly due to the involvement in peacekeeping
Khin Ma Ma Myo Page 27
operations and perceived increased threat from China and North Korea. The
absolute level of defense spending has been concerns for most of its neighbors.
Despite of this, Japanese defense industry contributed to high levels of economic
growth with the production of highly sophisticated weapons including F-15
fighters and E-2C early warning airborne system. Japanese industrialists and
defense planners seem to be inclined to be self sufficient with respect to future
weapons research. (Dolan, 1994)
Among the Asian countries, North Korean represents the highest military burden
despite of a downward trend in military expenditures. This is mainly due to its
ideological concept of chuch’e that emphasized on a self-sufficient state extended
to military industry and sustainability. (Arrigoni, 1993) With this concept, North
Korea engaged in nuclear weapons program and other forms of chemical and
biological weapons development.
In contrast to North Korea, South Korea tried to maintain the military burden on an
average of 3 percent. But with the growing economy, the military expenditure in
South Korea was increasing dramatically. To neutralize the threat of North Korean
weapons, South Korean defence planners tried to establish an independent
Khin Ma Ma Myo Page 28
reconnaissance system with intelligence satellites and early warning aircraft as
well as the surface-to-air and tactical surface-to-surface missiles.
For the period under consideration, military budget in Laos is the lowest in
Southeast Asian region, but it is one of the poorest countries in the world. After the
loss of military aids by the Vietnamese and Soviets in the early 1990s, its defense
budget slightly increased but this trend decreased after the Asian financial crisis.
For Mongolia, its military expenditures increased during the early 1990s but
decreased rapidly from to 15 US$ millions. Mongolia had an external threat
concern over China because of the traditional distrust of Beijing. But its distrust
level decreased after signing of a Mongolian- China border treaty. For internal
security, it was only maintained by the police force.
For Myanmar, the military regime increased defense spending from 171 to over
2000 US$ millions during that period. At the same time, the government reduced
the national budgets allocations on health and education. It had a serious internal
Khin Ma Ma Myo Page 29
conflict arising from the insurgencies that were rooted in ethnic political assertions
and different forms of ideologies.
For the same period, military spending in Malaysia increased from 2667 to 3158
US$ millions. However, its military burden had a downward trend as a percentage
of GDP. Until mid-1997, Malaysia was in the process of defence modernization
program. But, the economic turmoil that struck the region in the second half of
1997 led Malaysia to reduce its defense budget. It contributed in peace operations
and observer missions of the United Nations.
For the period under consideration, military expenditure in Philippines had
doublefolded, despite of its maintenance on the two percent average military
burden rate. For national security concerns, the internal threat of the active
communist regime rooted in the national history of Peasant rebellion was the main
problem. Although there was no serious threat of external aggression in this period,
there were some territorial disputes leading to security implications concerning
with Kalayaan fishing area and Malaysian state of Sabah.
Khin Ma Ma Myo Page 30
For Singapore, its defence spending increased rapidly from 1796 to over 4000 US$
millions with 5 percent military burden of GDP. In response to the economic
recession in 1985, the government instituted the five-year freeze on the size of
armed forces; however, it did not affect the acquisition of weapons as part of the
modernization program (Katz, 1989). It used the total defence concept which
means the capability of the nation to deter or overcome aggression by maintaining
small, well-equipped regular armed forces backed up by a large, well-trained
military reserve and a civil sector that could be quickly mobilized to provide
support to the armed forces.
For 15 years, defense spending in Thailand increased dramatically despite of a
downward trend in military burden. This may be due to its rapid economic growth
rate. By the late 1980s, Thailand improved its defense modernization program
aided by the western banks’ loans. Thailand's unconventional approach to its
defense needs was aided by its generally high credit rating among the world's
private banks and the judgment of most bankers that the money would be used for
the country's own defense rather than for purposes of aggression (Haseman, 1987).
For national security concerns, it faced with various threats along the border
resulting from the insurgencies by separatist groups against the neighbor countries.
Khin Ma Ma Myo Page 31
During the late 1980s, defence budget in Taiwan was reduced annually but
increased again in 1992 and rose rapidly after that. The main reasons contribute the
defence modernization program and the possible security threats of China. Taiwan
was expected to build its national defense capability to emphasize quality and
power over quantity by fielding a C4ISR system and by acquiring defensive
weapons.
Overall, the military balance in Asian countries were had an upward trend due to
internal and external security threats, arms racing, insurgencies, interstate and
intra-state conflicts and modernization programs. Figure (3) represents the trends
of total military expenditures in Asia during the period of 1985- 2000.
Khin Ma Ma Myo Page 32
Khin Ma Ma Myo Page 33
Model and Estimation method
The economic models of the relationship between defence spending and economic
growth were based on supply-side effects and demand-side factors. Among them,
most of the studies accounted only for either demand or supply that may produce
biased results. Generally, demand-side models predict a negative impact through
crowding-out effects, while supply-side models predict a positive impact of
military spending through externalities including spin-offs (Hartley, 2006)
Feder (1983) studied the effects of exports on growth in developing countries, then
Biswas and Ram (1986) adapted this Feder’s model on the study of defence-
growth relationship. The model considers only two sectors that can affect on
economic growth such as the government sector and civilian sector. In this model,
the military sector is considered as only a part of the government sector and this is
the factor that criticisms were emerged. Critics argued that Ram’s study failed to
account for any independent effect that the military sector may have on economic
growth. (Carr, 1989 & Rao, 1989)
Mintz and Huang (1980, 1991) have overcome this limitation of Ram’s model by
extending to a three sector economy including the government sector, the military
Khin Ma Ma Myo Page 34
sector and the civilian sector. They consider not only the overall effects of the
military sector on growth but also the externality effects of military expenditures.
The equations in the supply-side models have been estimated by using different
types of data such as cross-country data (eg. Biswas and Ram, 1986); time series
data for individual countries (eg. Huang and Mintz, 1991; Ward et al., 1993;
Sezgin, 1997; Antonakis, 1999; Batchelor et al. 2000) and pooled cross-section
time-series data (eg. Murdoch et al., 1997) as Dunne et. al, 2005 pointed out.
Studies using supply-side models show the positive effects of military spending on
economic growth. Morales- Ramos (2002) argued that the results can be sustained
under the assumptions such as
• Supply-models only measure the direct effects of defence on the economy
and
• Supply-models may produce positive results since military spending is an
additional spending which produces higher utilization rates of available
capacity.
Khin Ma Ma Myo Page 35
For demand-side models, the most widely used one is the Keynesian aggregate
demand model. In this model, actual output or potential output is assumed to be the
sum of consumption, investment, military expenditures and the current account
balance of payments. The main difference between actual output and potential
output is that when the sources of demand are expressed as a share of potential
output, crowding-out is likely to show up from the way in which empirical test is
formulated. In contrast, if shares are computed based on actual output, then
crowding-out would be automatic and the exercise would be tautological. (Sandler
& Hartley, 1995)
Several studies such as Smith (1980), Fanni, Annez & Taylor (1984), Stewart
(1991) and Gold (1997) used this model and concluded that the defence spending
had a negative impact on economic growth. It is clear that military spending
would have a negative impact on growth when regressed on investment shares if
both demands are in competition for the same resource pool and comprises the
components of actual outputs.
Alternatively, there are other types of models for defence-growth relationship
including augmented Solow model, Barro model and Granger testing. Mankiw et.
al (1992) and Knight et al. (1996) developed an augmented Solow model. The
underlying assumption in this model is that the military spending share m: = M/Y
affects factor productivity via a level effect on the efficiency parameter that
Khin Ma Ma Myo Page 36
controls labor-augmenting technical change (Dunne et al., 2005) It is a one sector
model unlike the Feder-Ram model. However, this model is rarely used outside
defence literature because the theory is so tight with ad-hoc error term and testable
restrictions on the estimated coefficients.
For Barro’s (1990) growth model, it explicitly allows for forms of government
expenditure, financed by taxes, which can influence output through the production
function and has an explicit utility function for the representative agent so that they
do not get explicit parametric restrictions as like in the augmented Solow model. It
is innovated by Aizeman & Glick (2003) and they claimed that military
expenditure induced by external threats should increased output by increasing
security; while military expenditure induced by rent seeking and corruption should
reduce growth by displacing productive activities. (Dunne et al., 2005)
The other estimation technique widely used in defence economic literature for
defence-growth relationship is the Granger’s (1969) definition of causality between
two variables in a time series context. The technique commonly used for
implementing the Granger test include the cross-correlation function of Pierce and
Haugh (1977), the one- sided distributed lag approach of Granger (1969) and the
two- sided distributed lag approach of Sims (1972) (Chowdhury, 1991) Several
studies followed to identify the causality relationship between military expenditure
and economic growth. The underlying concept implies that given an information
Khin Ma Ma Myo Page 37
set, X causes Y if the past values of X and Y can be used to predict Y more
accurately than simply using the past values of Y.
Nevertheless, it is clear that the relationship between military spending and
economic growth produce the divergent results that reflect the use of different
econometric methods, different combinations of variables, different time-periods
and heterogeneous set of countries.
In this paper, I would like to use the model that consider both demand-side and
supply-side influences because it can give more accurate analysis of the impact of
military spending on economic growth. One of the widely-used models which
studied both demand and supply-side influences is the Deger model firstly
introduced by Deger and Sen( 1983) and Deger and Smith (1983) and further
developed by Deger (1986).
Deger (1983) argued that the econometric model should allow for
1. a direct effect of military expenditure on growth through the resource
mobilization and modernization effect
Khin Ma Ma Myo Page 38
2. an indirect effect through the savings ratio, and
3. the endogeneity of military expenditure
By using these assumptions, Deger developed a three- question simultaneous
system to examine the interaction of growth, savings and military expenditure. The
complete model developed by Deger can be shown as follows.
g = - (α0δ – α4) + α0 v1s + α0v2a + α1p + α2m – α3y + α5 r
s = (1- β0) + β1 g + β2 yg – (1- β3 ) m – β4 a + β5 p˙
m = γ0 + γ1 y + γ2 (q-y) + γ3 N + γ4 D1 + γ5 D2
The variables represent as follows:
g : average annual growth rate of real GDP
s : national savings ratio
v : output capita ratio
Khin Ma Ma Myo Page 39
δ : proportional depreciation rate
a : net foreign capital flows as a percentage of GDP
m : share of military expenditure in GDP
y : level of per capita income
p : rate of growth in population
q : per capita income at purchasing power parity
N : total population
D2 : Dummy variable for war
D1 : Dummy variable for oil
The model in this paper resembles the above version derived by Deger & Smith
(1983) and developed from Galvin (2003) which considers the simple determinants
of defence expenditure and reduce the ad hoc considerations of Deger model.
For growth equation, it is derived from the standard Cobb-Douglas production
function with technology embedded in both capital and labor. Therefore, the
Khin Ma Ma Myo Page 40
growth rate is a function of capital growth, labor growth, military expenditure as a
share of GDP, per capita GDP and inflation rate. Capital growth is represented by
both savings – income ratio (s) and the current account balance as a percentage of
GDP (b). Labor growth rate is determined by the rate of labor force growth (l) and
military expenditure as a share of GDP (me) is an obvious candidate for inclusion
and per capita income (y) is employed to capture any catch-up effects. Deger
(1983) claimed that the higher per capita come, the smaller the gap between
domestic technology and world technology and the lower scope for rapid growth
through imported technology, however, the strength of this effect in low income
countries may be problematic. In addition, the GDP deflator as a measure of rate of
inflation (P) is included. Therefore, the growth equation can be written as
g = α0 + α1 s + α2 b + α3 l + α4 me + α5 y + α6 P (1)
According to the economic theory, the variables (s), (b) and (l) should have a
positive coefficient and the variable (y) should have a negative coefficient. The
effect of variable (P) cannot be identified a priori. The variable (me) determine the
results of this paper whether military spending may have crowding out effects or
Khin Ma Ma Myo Page 41
spill-over effects on the economy. This equation exactly represents the
specification used by Galvin (2003) but a significant departure from Deger (1983).
For savings equation, it can be derived from the consumption function and life-
cycle effects. Therefore, it is a function of military expenditures, the capital growth
rate and output-growth rate weighted by per capita income. The military
expenditure (me) represents the role of military in new resources investment. The
GDP deflator as a measure of inflation rate (P) is also incorporated. The current
account balance as a percentage of GDP (b) is included as a proxy foreign savings.
The growth rate (g) is included in accordance with the life-cycle hypothesis.
Moreover, the output-growth rate weighted by per capita income (gy) is included
as the growth effect on saving behavior is positively related to per capita income.
Therefore the equation will be written as
s = β0 + β1me + β2 P + β3 g + β4 b + β5 gy (2)
Economic theory suggests that variables (b) and (g) should have a positive
coefficient, however, variable (P) depends on whether the inflation is expected or
Khin Ma Ma Myo Page 42
not. Overall, this equation exactly represents the specification used by Deger
(1986) and Galvin (2003).
For defence equation, the variables reflecting the income, total population and
dummy variables for civil & external wars and oil are incorporated. Per capita
income (y) is included as it rises, military spending can be increased. The current
account balance as a percentage of GDP (b) is also included as a proxy for the
openness of the economy. The population (N) is also included as defence has
elements of a public good and the share spent on it might be expected to increase
with the population (Deger, 1983). Moreover, two dummy variables, one for oil-
producing countries (Doil ) and one for the countries engaging in civil wars and
external armed conflicts (Dcew). So the equation can be written as
me = γ0 + γ1 y + γ2 b + γ3 N + γ4 Doil + γ5 Dcew (3)
There is less economic theory providing the specification of the equation for
military expenditure but previous studies can be used as a guide. This equation
Khin Ma Ma Myo Page 43
represents the similar specification used by Deger, however, a clear departure from
Klein (2004) and Galvin (2003).
The above equations are estimated using the OLS method. However, there is a
limitation that these types of simultaneous equation regression models can create
simultaneity and identification problems, hence; they violate one of the OLS
assumptions. Due to this, there may produce biased and inconsistent estimates
(Gujarati, 1999).
Khin Ma Ma Myo Page 44
Empirical Results
It is necessary to spell out an econometric model in empirical work. The estimation
technique of Ordinary Least Squares will be used because it can give the best
estimated regression line that minimizes the sum of error terms by using the values
for coefficient estimates. (Halcoussis, 2005)
To evaluate the regression results, economic criteria and statistical criteria are
used. For economic criteria, the sign and size of the estimate parameters
(coefficients) are used. For statistical criteria, tests are used to find out the
existence of statistical evidence against or/ in favour of inclusions of each
regressors (coefficient of determination R2, t-test, F-test, etc.)
As Deger (1986) and Kusi (1994) argued, it is known that inter-country cross-
section analysis can produce the adverse effect of a variable across countries. To
reduce this impact, regression results were evaluated for the whole sample and
those for low, middle and high income countries separately.
Khin Ma Ma Myo Page 45
The empirical results are presented in Table 1-15 which show results for the whole
estimation, plus those for low, low-middle, upper- middle and high income
countries as follows. The tables show the results of the least square analyses of the
dependent variables against the independent variables. The coefficients allow us to
address the impact of the variables on the appropriate equation. The other columns
show the standard errors that provide measures of the dispersion of the estimates
and t-statistics to test the significance of the parameters.
(i) Growth equation
The growth equation used here is
g = α0 + α1 s + α2 b + α3 l + α4 me + α5 y + α6 P (1)
For all estimations, the effects of savings have positive correlations with growth as
economic theory expected. However, the current account balance as a percentage
of GDP is less consistent for the whole sample due to its negative signs. It takes the
expected positive signs for low income countries and upper-middle income
countries. The labor growth variable is not statistically significant for all samples
despite of its positive signs. Per capita GDP is positive for the whole sample and
less consistent with the expected results. When these take negative signs in other
samples, they were less statistically significant. GDP deflators are negative and not
Khin Ma Ma Myo Page 46
significant for the whole sample and low income countries but positive and more
statistically significant for the countries with greater initial wealth.
For the whole sample, the effect of military burden shows positive sign but not
statistically significant. It has a significant positive coefficient for low-middle
income countries, however, a negative sign for upper-middle income countries. It
is not statistically significant for low-income countries and high- income countries.
Overall, it cannot produce a clear-cut result.
Table 1: Whole estimation
Dependent Variable: G
Method: Least Squares
Date: 05/16/08 Time: 13:37
Sample: 1 288
Included observations: 280
Coefficient
Std. Error t-Statistic Prob.
S 0.152795 0.022396 6.822287 0.0000
B -6.33E-11 1.47E-11 -4.321685 0.0000
L 0.370169 0.099333 3.726550 0.0002
ME 0.142229 0.046826 3.037381 0.0026
Y 5.62E-05 4.54E-05 1.238783 0.2165
P -0.001322 0.001684 -0.784826 0.4332
C 0.925858 0.643425 1.438952 0.1513
R-squared 0.264292 Mean dependent var 5.414286
Adjusted R-squared 0.248122 S.D. dependent var 3.688869
Khin Ma Ma Myo Page 47
S.E. of regression 3.198650 Akaike info criterion 5.188017
Sum squared resid 2793.162 Schwarz criterion 5.278887
Log likelihood -719.3224 Hannan-Quinn criter. 5.224465
F-statistic 16.34518 Durbin-Watson stat 1.222064
Prob(F-statistic) 0.000000
Table 2: Low-income economies
Dependent Variable: G
Method: Least Squares
Date: 05/16/08 Time: 15:32
Sample (adjusted): 1 127
Included observations: 119
Coefficient
Std. Error t-Statistic Prob.
S 0.201396 0.059693 3.373852 0.0010
B 2.27E-11 1.69E-10 0.134559 0.8932
L 0.541106 0.165887 3.261889 0.0015
ME 0.156492 0.053760 2.910947 0.0043
Y -0.002192 0.001851 -1.184257 0.2388
P 0.023954 0.017846 1.342248 0.1822
C -1.695398 2.033517 -0.833727 0.4062
R-squared 0.206725 Mean dependent var 4.774790
Adjusted R-squared 0.164228 S.D. dependent var 2.910857
S.E. of regression 2.661122 Akaike info criterion 4.852395
Sum squared resid 793.1358 Schwarz criterion 5.015873
Log likelihood -281.7175 Hannan-Quinn criter. 4.918778
Khin Ma Ma Myo Page 48
F-statistic 4.864471 Durbin-Watson stat 1.035841
Prob(F-statistic) 0.000188
Table 3: Low-middle income economies
Dependent Variable: G
Method: Least Squares
Date: 05/16/08 Time: 14:56
Sample (adjusted): 1 80
Included observations: 80
Coefficient
Std. Error t-Statistic Prob.
S 0.329300 0.047756 6.895500 0.0000
B -1.68E-10 4.85E-11 -3.455701 0.0009
L -0.073450 0.159483 -0.460551 0.6465
ME 0.644662 0.229935 2.803671 0.0065
Y -0.001947 0.000740 -2.632509 0.0103
P 0.003170 0.022476 0.141047 0.8882
C -2.647698 2.632793 -1.005661 0.3179
R-squared 0.454854 Mean dependent var 6.147500
Adjusted R-squared 0.410047 S.D. dependent var 4.236878
S.E. of regression 3.254277 Akaike info criterion 5.281250
Sum squared resid 773.0933 Schwarz criterion 5.489678
Log likelihood -204.2500 Hannan-Quinn criter. 5.364815
F-statistic 10.15151 Durbin-Watson stat 1.635208
Prob(F-statistic) 0.000000
Khin Ma Ma Myo Page 49
Table 4: Upper-middle income economies
Dependent Variable: G
Method: Least Squares
Date: 05/16/08 Time: 15:21
Sample (adjusted): 1 16
Included observations: 16
Coefficient
Std. Error t-Statistic Prob.
S 0.830896 0.679594 2.694102 0.0246
B 3.39E-10 5.06E-10 0.670075 0.5196
L 0.414067 0.634071 0.653029 0.5301
ME -0.821531 2.438556 -0.336892 0.7439
Y 0.003742 0.006284 0.595470 0.5662
P 0.141269 0.516414 0.273557 0.7906
C 43.58835 37.36417 1.166582 0.2734
R-squared 0.626688 Mean dependent var 6.606250
Adjusted R-squared 0.377813 S.D. dependent var 4.964201
S.E. of regression 3.915703 Akaike info criterion 5.867503
Sum squared resid 137.9946 Schwarz criterion 6.205510
Log likelihood -39.94002 Hannan-Quinn criter. 5.884812
F-statistic 2.518086 Durbin-Watson stat 1.869403
Prob(F-statistic) 0.103004
Table 5: High income economies
Dependent Variable: G
Method: Least Squares
Date: 05/16/08 Time: 15:27
Khin Ma Ma Myo Page 50
Sample (adjusted): 1 64
Included observations: 64
Coefficient
Std. Error t-Statistic Prob.
S 0.126032 0.073943 1.704444 0.0937
B -1.64E-11 1.38E-11 -1.193170 0.2377
L 2.025489 0.198636 10.19699 0.0000
ME 0.221064 0.273878 0.807160 0.4229
Y -1.72E-05 3.58E-05 -0.479732 0.6333
P 4.51E-05 0.001024 0.043978 0.9651
C -2.613689 3.259780 -0.801799 0.4260
R-squared 0.782035 Mean dependent var 5.396875
Adjusted R-squared 0.759091 S.D. dependent var 3.767571
S.E. of regression 1.849218 Akaike info criterion 4.170321
Sum squared resid 194.9176 Schwarz criterion 4.406449
Log likelihood -126.4503 Hannan-Quinn criter. 4.263343
F-statistic 34.08491 Durbin-Watson stat 1.849620
Prob(F-statistic) 0.000000
(ii) Saving equation
The saving equation used here is
s = β0 + β1me + β2 P + β3 g + β4 b + β5 gy (2)
Khin Ma Ma Myo Page 51
For the whole estimation and low-middle income countries, the results of current
account balance and the growth rate show positive signs so that these are
consistence with the theory as we expected. However, these show some variations
for other sample groups. The growth rate has a negative impact on the saving rate
for upper-middle income countries although the current account balance shows a
positive sign. In contrast, the current account balance has a negative impact on the
saving rate for high income countries while the growth rate shows a negative sign.
For low income countries, both show negative signs and less consistent. The effect
of GDP deflator is not statistically significant for all sample groups.
The coefficients on the output growth rate weighted by per capita GDP also give
various results for different sample groups. These are statistically significant for
the whole sample and higher income countries, but less significant for low- income
countries. The impact of military spending shows negative coefficient in all cases.
The coefficients are highly significant and it clearly states that the indirect effect of
military spending on growth via saving rate is negative, as Deger found.
Khin Ma Ma Myo Page 52
Table 6: Whole estimation
Dependent Variable: S
Method: Least Squares
Date: 05/16/08 Time: 13:47
Sample: 1 288
Included observations: 280
Coefficient
Std. Error t-Statistic Prob.
ME -0.664206 0.113185 -5.868298 0.0000
P 0.005279 0.004236 1.246186 0.2138
G 0.848822 0.147188 5.766911 0.0000
B 1.18E-10 2.29E-11 5.125262 0.0000
GY 4.34E-05 1.32E-05 3.277584 0.0012
C 18.47051 1.138486 16.22375 0.0000
R-squared 0.339784 Mean dependent var 22.13789
Adjusted R-squared 0.327736 S.D. dependent var 9.842202
S.E. of regression 8.069789 Akaike info criterion 7.035327
Sum squared resid 17843.29 Schwarz criterion 7.113216
Log likelihood -978.9458 Hannan-Quinn criter. 7.066569
F-statistic 28.20311 Durbin-Watson stat 0.435694
Prob(F-statistic) 0.000000
Table 7: low-income economies
Dependent Variable: S
Khin Ma Ma Myo Page 53
Method: Least Squares
Date: 05/16/08 Time: 15:34
Sample (adjusted): 1 127
Included observations: 119
Coefficient
Std. Error t-Statistic Prob.
ME -0.518189 0.074763 -6.931108 0.0000
P -0.068114 0.026294 -2.590451 0.0108
G -0.145189 0.169795 -0.855081 0.3943
B -9.44E-10 2.29E-10 -4.118961 0.0001
GY 0.002334 0.000555 4.202466 0.0001
C 19.06079 2.667598 7.145303 0.0000
R-squared 0.469386 Mean dependent var 13.71301
Adjusted R-squared 0.445907 S.D. dependent var 5.291130
S.E. of regression 3.938580 Akaike info criterion 5.628622
Sum squared resid 1752.903 Schwarz criterion 5.768746
Log likelihood -328.9030 Hannan-Quinn criter. 5.685522
F-statistic 19.99215 Durbin-Watson stat 0.838460
Prob(F-statistic) 0.000000
Table 8: Low-middle income economies
Dependent Variable: S
Method: Least Squares
Date: 05/16/08 Time: 14:57
Sample (adjusted): 1 80
Khin Ma Ma Myo Page 54
Included observations: 80
Coefficient
Std. Error t-Statistic Prob.
ME -1.390499 0.469940 -2.958885 0.0041
P 0.002436 0.047198 0.051620 0.9590
G 1.026791 0.269145 3.815011 0.0003
B 3.65E-10 1.04E-10 3.495946 0.0008
GY 0.000234 0.000190 1.233592 0.2213
C 21.81184 5.281221 4.130075 0.0001
R-squared 0.406317 Mean dependent var 25.24115
Adjusted R-squared 0.366203 S.D. dependent var 8.860876
S.E. of regression 7.054265 Akaike info criterion 6.817180
Sum squared resid 3682.436 Schwarz criterion 6.995832
Log likelihood -266.6872 Hannan-Quinn criter. 6.888807
F-statistic 10.12912 Durbin-Watson stat 0.721259
Prob(F-statistic) 0.000000
Table 9: Upper-middle income economies
Dependent Variable: S
Method: Least Squares
Date: 05/16/08 Time: 15:23
Sample (adjusted): 1 16
Included observations: 16
Khin Ma Ma Myo Page 55
Coefficient
Std. Error t-Statistic Prob.
ME -1.168916 0.563840 -2.073136 0.0649
P 0.171664 0.079293 2.164937 0.0556
G -0.505252 0.314817 -1.604909 0.1396
B 3.71E-10 9.66E-11 3.844440 0.0032
GY 9.18E-05 0.000112 0.817803 0.4325
C 21.49529 8.226464 2.612944 0.0259
R-squared 0.869978 Mean dependent var 33.62340
Adjusted R-squared 0.804967 S.D. dependent var 3.246924
S.E. of regression 1.433924 Akaike info criterion 3.838703
Sum squared resid 20.56138 Schwarz criterion 4.128424
Log likelihood -24.70962 Hannan-Quinn criter. 3.853539
F-statistic 13.38202 Durbin-Watson stat 1.723373
Prob(F-statistic) 0.000367
Table 10: High income economies
Dependent Variable: S
Method: Least Squares
Date: 05/16/08 Time: 15:28
Sample (adjusted): 1 64
Included observations: 64
Coefficient
Std. Error t-Statistic Prob.
Khin Ma Ma Myo Page 56
ME -2.116840 0.386090 -5.482758 0.0000
P 0.001401 0.001726 0.811601 0.4203
G 0.425266 0.171364 2.481648 0.0160
B -4.51E-11 1.92E-11 -2.348224 0.0223
GY -1.73E-05 8.16E-06 -2.115218 0.0387
C 39.13919 2.214468 17.67431 0.0000
R-squared 0.409229 Mean dependent var 31.03741
Adjusted R-squared 0.358300 S.D. dependent var 3.913138
S.E. of regression 3.134665 Akaike info criterion 5.211982
Sum squared resid 569.9152 Schwarz criterion 5.414377
Log likelihood -160.7834 Hannan-Quinn criter. 5.291715
F-statistic 8.035352 Durbin-Watson stat 0.659388
Prob(F-statistic) 0.000008
(iii) Defence equation
The defence equation used here is
me = γ0 + γ1 y + γ2 b + γ3 N + γ4 Doil + γ5 Dcew (3)
For the current account balance, it produce positive results and highly statistically
significant for all sample groups, except low-income groups. It generates same
results as in studies by Galvin (2003) that imply that wealthier nations are more
Khin Ma Ma Myo Page 57
likely to spend the gains in foreign exchange on importing military equipment.
Population shows negative signs in all cases. It is a clear departure from previous
studies that were insignificant. So the effects of public goods seem important in
these cases. GDP per capita shows positive results and statistically significant as
expected. It also shows that a conflict has a positive and significant impact on
military spending and it is highly significant for low income countries that are
engaging in civil wars and external threats. The effects of oil production have
positive results for low income countries as in previous studies and not significant
in high-income economies. Overall, the military equation generates most of the
similar results as in the studies by Deger & Smith (1983), Sen (1983), Dunne &
Nikolaidou (2001) and Galvin (2003).
Table 11: whole estimation
Dependent Variable: ME
Method: Least Squares
Date: 05/16/08 Time: 13:55
Sample (adjusted): 1 272
Included observations: 248
Coefficient
Std. Error t-Statistic Prob.
Y 4.69E-05 7.20E-05 0.651570 0.5153
Khin Ma Ma Myo Page 58
B 2.91E-11 4.47E-11 0.651007 0.5157
N -2.56E-10 9.61E-10 -0.266428 0.7901
DOIL -0.077090 0.762774 -0.101066 0.9196
DCEW 2.396086 0.656716 3.648590 0.0003
C 3.725153 0.521092 7.148750 0.0000
R-squared 0.065444 Mean dependent var 4.655645
Adjusted R-squared 0.046135 S.D. dependent var 4.519966
S.E. of regression 4.414470 Akaike info criterion 5.831549
Sum squared resid 4715.986 Schwarz criterion 5.916551
Log likelihood -717.1121 Hannan-Quinn criter. 5.865768
F-statistic 3.389299 Durbin-Watson stat 0.226424
Prob(F-statistic) 0.005599
Table 12: Low-middle-income economies
Dependent Variable: ME
Method: Least Squares
Date: 05/16/08 Time: 14:59
Sample (adjusted): 1 80
Included observations: 80
Coefficient
Std. Error t-Statistic Prob.
Y 0.000361 0.000320 1.128081 0.2629
B 5.98E-11 2.08E-11 2.875457 0.0053
N -1.74E-08 2.57E-09 -6.773762 0.0000
Khin Ma Ma Myo Page 59
DOIL 21.27602 2.919017 7.288762 0.0000
DCEW 2.049380 0.420525 4.873378 0.0000
C 3.062214 0.486869 6.289606 0.0000
R-squared 0.504844 Mean dependent var 3.245000
Adjusted R-squared 0.471388 S.D. dependent var 1.844657
S.E. of regression 1.341172 Akaike info criterion 3.497003
Sum squared resid 133.1068 Schwarz criterion 3.675655
Log likelihood -133.8801 Hannan-Quinn criter. 3.568629
F-statistic 15.08957 Durbin-Watson stat 0.856890
Prob(F-statistic) 0.000000
Table 13: Upper-middle income countries
Dependent Variable: ME
Method: Least Squares
Date: 05/16/08 Time: 15:25
Sample (adjusted): 1 16
Included observations: 16
Coefficient
Std. Error t-Statistic Prob.
Y 0.001387 0.000569 2.439408 0.0312
B 9.14E-11 5.65E-11 1.616938 0.1319
N -7.32E-07 2.44E-07 -3.003931 0.0110
C 13.93491 3.030427 4.598333 0.0006
R-squared 0.600493 Mean dependent var 4.081250
Khin Ma Ma Myo Page 60
Adjusted R-squared 0.500617 S.D. dependent var 0.741367
S.E. of regression 0.523902 Akaike info criterion 1.757295
Sum squared resid 3.293683 Schwarz criterion 1.950442
Log likelihood -10.05836 Hannan-Quinn criter. 1.767185
F-statistic 6.012349 Durbin-Watson stat 2.322666
Prob(F-statistic) 0.009662
Table 14: High income countries
Dependent Variable: ME
Method: Least Squares
Date: 05/16/08 Time: 15:30
Sample (adjusted): 1 48
Included observations: 48
Coefficient
Std. Error t-Statistic Prob.
Y -3.49E-05 1.49E-05 -2.342349 0.0238
B 7.05E-12 5.56E-12 1.268736 0.2112
N -3.70E-08 3.70E-09 -9.997502 0.0000
C 5.919158 0.237211 24.95311 0.0000
R-squared 0.897955 Mean dependent var 3.435625
Adjusted R-squared 0.890997 S.D. dependent var 1.951122
Khin Ma Ma Myo Page 61
S.E. of regression 0.644174 Akaike info criterion 2.037958
Sum squared resid 18.25822 Schwarz criterion 2.193891
Log likelihood -44.91099 Hannan-Quinn criter. 2.096885
F-statistic 129.0608 Durbin-Watson stat 0.937151
Prob(F-statistic) 0.000000
Table 15: Low-income countries
Dependent Variable: ME
Method: Least Squares
Date: 05/16/08 Time: 15:35
Sample (adjusted): 1 127
Included observations: 119
Coefficient
Std. Error t-Statistic Prob.
Y 0.022504 0.003180 7.077090 0.0000
B -2.65E-10 4.60E-10 -0.575542 0.5661
N -1.14E-09 2.65E-09 -0.428196 0.6693
DOIL 1.174397 1.572299 0.746930 0.4567
DCEW 5.737561 1.111210 5.163343 0.0000
C -5.407609 1.574839 -3.433753 0.0008
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R-squared 0.400187 Mean dependent var 5.708403
Adjusted R-squared 0.373647 S.D. dependent var 6.124590
S.E. of regression 4.847152 Akaike info criterion 6.043765
Sum squared resid 2654.922 Schwarz criterion 6.183888
Log likelihood -353.6040 Hannan-Quinn criter. 6.100664
F-statistic 15.07843 Durbin-Watson stat 0.400083
Prob(F-statistic) 0.000000
Khin Ma Ma Myo Page 63
Conclusion
The study has investigated the effects of military spending on economic growth in
Asian countries by using a Deger-type supply and demand model. The direct effect
as externalities on growth rate is no clear-cut. But the indirect effect of the military
burden on the savings rate was found as a negative impact. The results also
indicate that the military and economic strategic factors play a significant role for
low- income countries. These general results are similar to the research studies by
Deger & Smith (1983) and Galvin (2003).
These findings are, however, subject to some limitations. The first limitation is the
model itself because the specification of the Deger model displays several
weaknesses related to the equations. For the growth equation, it is systematically
derived from a theoretical framework. But the other equations are developed from
ad hoc elements and the defence equation is the weakest point with various
determinants. Therefore, further research can be extended to devise alternative
variables for the equations of saving and military burden.
Khin Ma Ma Myo Page 64
The second limitation is the quality of the data because there are some constraints
on the reliability of military expenditure due to the purposes of security and
censorship. Therefore, further research can be extended to use alternative data
sources.
The third concern is raised by the choice of sample groups because countries differ
in social, political and economic structures. Therefore, further research can be
extended to different groups based on similar structures.
Moreover, the fourth limitation concerns with the estimation method because least
square estimation methods can generate unbiased estimates. Moreover, all the
diagnostic tests (e.g. Durbin-Watson test, etc.) are not valid in simultaneous
equation models. Further research can be extended to longitudinal analysis and
ridge regression analysis to break multi-collinearity.
In addition, the fifth limitation is raised by the choice of models because most of
the findings are amazingly consistent in demand-side models (negative results),
supply-side models (positive results) and combined demand-side and supply-side
Khin Ma Ma Myo Page 65
models (various results). Hartley (2005) proposed further research to focus on
Augmented Solow and Barro models.
Unless new evidence is found, the policy advice to be derived from this study is
that in Asian countries, the defence burden has no clear-cut effect on growth and
negative effect on savings rate.
Khin Ma Ma Myo
University of Aberdeen
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