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)

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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.

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Khin Ma Ma Myo

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)

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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.

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(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)

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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)

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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

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(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.

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(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

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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.

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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

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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.

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(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

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(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

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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.

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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.

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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.

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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

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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.

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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

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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,

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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.

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(Source Data: International Institute for Strategic Studies, Military Balance, various editions)

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(Source Data: International Institute for Strategic Studies, Military Balance,

various editions)

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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

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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

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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,

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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

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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

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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

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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.

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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.

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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.

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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

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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.

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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

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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

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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

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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

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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

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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

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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

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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

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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

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.

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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

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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

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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



Date: 05/16/08 Time: 15:32

Sample (adjusted): 1 127


Coefficient


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






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Table 3: Low-middle income economies



Date: 05/16/08 Time: 14:56



Coefficient


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








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Table 4: Upper-middle income economies



Date: 05/16/08 Time: 15:21



Coefficient


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








Table 5: High income economies



Date: 05/16/08 Time: 15:27

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Coefficient


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








(ii) Saving equation

The saving equation used here is

s = β0 + β1me + β2 P + β3 g + β4 b + β5 gy (2)

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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.

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Table 6: Whole estimation

Dependent Variable: S


Date: 05/16/08 Time: 13:47

Sample: 1 288


Coefficient


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








Table 7: low-income economies


Khin Ma Ma Myo


Date: 05/16/08 Time: 15:34



Coefficient


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








Table 8: Low-middle income economies



Date: 05/16/08 Time: 14:57


Khin Ma Ma Myo


Coefficient


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








Table 9: Upper-middle income economies



Date: 05/16/08 Time: 15:23



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Coefficient


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








Table 10: High income economies



Date: 05/16/08 Time: 15:28



Coefficient


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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








(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

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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


Date: 05/16/08 Time: 13:55



Coefficient


Y 4.69E-05 7.20E-05 0.651570 0.5153

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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








Table 12: Low-middle-income economies



Date: 05/16/08 Time: 14:59



Coefficient


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

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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








Table 13: Upper-middle income countries



Date: 05/16/08 Time: 15:25



Coefficient


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


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Table 14: High income countries



Date: 05/16/08 Time: 15:30



Coefficient


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



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Table 15: Low-income countries



Date: 05/16/08 Time: 15:35



Coefficient


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

Khin Ma Ma Myo








Khin Ma Ma Myo

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

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

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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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