Research Paper 3-1

Terry Chaney 1Econ 497Research Paper

An Econometric Study of Global Defense Spending


EXECUTIVE SUMMARY

The focus of this paper is to develop an econometric model that helps describe an

individual country’s defense spending as a percentage of annual GDP. More specifically,

the purpose is to identify which factors might contribute to countries that dedicate a large,

perhaps disproportionate percentage of their GDP on military expenditures. And this

would then increase conflict in the entire region. Understanding these factors would be

useful in discovering what drives global demand for weapons and facilitate conflict

resolution strategies. For example, increased demand for vital resources by developing

countries can create hotspots where a potential conflict is more likely to occur. The

importance of being able to anticipate potential hotspots and preventing unnecessary

bloodshed should be a concern to the developing world, whose defense contractors are

the beneficiaries of this global arms trade.1

The model was chosen to encompass various economic, geographic and

demographic characteristics of a country, which may help explain why one country

spends most of its resources on weapons and another does not. Intuitively, the

expectation was that if a country has a relatively young, disenfranchised population that

is ruled by an autocratic regime and also happens to be resource-rich that country

probably spends more arming itself against its neighbors and rival factions within its own

1 The author also takes it as a given that any country has the right to defend itself from outside aggressors.


country. And an OLS regression of the data does seem to support this thesis to some

degree. For example, unemployment proved to be a positive significant factor. Median

age, literacy and inflation, while having a negative effect as expected were not

significant. Of the various resource variables that I used oil production was positively

significant related to defense spending. Zinc, nickel and diamonds had a positive but not

a significant relationship within the model; while tin, gold and uranium were negative

predictors with no significant effect. A democracy and transparency ranking was applied

to each country and oddly enough, democracy was significant and transparency was not.

As far as geographic location is concerned, each region had a positive effect on defense

spending (in 2007) with only the Middle East dummy variable having a significant effect.

BACKGROUND DISCUSSION

On a daily basis households are faced with choices regarding how to allocate

resources. Some are trivial: how much should I spend on lunch? Others are more

difficult: how much should I save for retirement? Governments too must decide how to

allocate their country’s scarce resources. For example, they need to decide how much of

the years tax revenues will be used for things like: health care, education and national

defense. In

Terry Chaney 4Econ 497Research Papertheory anyway, these decisions are made based on the wants and needs of various interest

groups. A country like the U.S, with a GDP of over $13 trillion will have much more to

work with. And even though the U.S. has by far, the largest military budget on the

planet, it amounts to roughly 4% of GDP annually (this is assuming that the Pentagon is

accurately reporting their budget, which is unlikely). Defense spending varies from

country to country, but globally it is big business. In 2007, the world spent an estimated

$1.2 Trillion arming itself and preparing for war—some of the highest levels since the

Cold War.

Much of the existing academic literature uses defense spending as the explanatory

variable, and then studies how it affects variables such as economic growth, health care

spending, etc. The goal here on the other hand, is to discover which factors would

explain a country’s defense budget. A reasonable model should include variables that

take into consideration a country’s population, geography, government structure and

access to resources. The hypothesis to be tested, briefly stated, is that if a country’s

population is relatively young and unemployed then that country would be more likely to

organize their citizens militarily. This may serve fundamental social and economic

functions and it may also be a rather natural process of development that most nation-

states experience on their way to maturity—whatever that might be.2 In addition to this,

one would also expect that less developed and less democratic counties would fit this

profile. The assumption is that more democratic countries wouldn’t tolerate a

2 . For example, this was the situation in the U.S. during the 60’s: the baby boomers who are now preparing to upset the country’s economic stability with retirement were upsetting Johnson and Nixon with their civil disobedience—ah, to be bored and young.

Terry Chaney 5Econ 497Research Paperdisproportionate percentage of their wealth to be funneled into guns rather than butter.

Furthermore, if one country is arming itself and that same country’s population is

increasing rapidly, that country’s neighbors would likely follow suit. Thus, the data

should reveal regional patterns of high military spending. Finally, a country that meets

the other criteria and is also resource rich would create an environment that was ripe for

conflict—not to mention exploitation from within or without. These factors would then

be reflected in a large percentage of a country’s GDP being spent on defense related

items.3

This section examines how some of these factors may contribute to a region’s

defense budget and risk of conflict. It is reasonable to expect country X’s neighbors to

increase their defense budget if they observe X growing rapidly and buying tanks and

jets. One could argue that this is exactly what has happened in the Middle East over the

last fifty years. Some of this can be explained by the large amount of oil reserves under

the sand. But other factors are at work here as well. For example, many of these

countries, such as Saudi Arabia have only recently gained independence from colonial

rule. And though the oil-rich nation’s economy seems to rise and fall with the oil market

the House Of Saud remains in power. The kingdom is notorious for its brutality,

corruption and its arbitrary approach to due process. In addition to this there is the

problem of income

3 There does seem to be a hidden assumption in the following discussion that high defense spending implies increased conflict. The relationship between conflict and defense spending was not tested, but the assumption is that greater defense spending increases the likelihood of military conflict.

Terry Chaney 6Econ 497Research Paperinequality. According to an article in, Middle East Report, “In 1981, US and Saudi

Arabian per capita income levels were equivalent at roughly $18,000 per year. In the 20

years since, while the US level has grown to $36,000, the average Saudi Arabian

household income plummeted, now hovering around $7,500” (Jones, p.43). The

country’s population is young (median age is 21) growing rapidly and unemployment is

around 13%. Saudi Arabia also spends a large percentage of their oil revenues on

weapons—most of which are purchased with petro-dollars.

The significance of oil to the global economy and the conflict this creates has

already been written about extensively. And while the existence of large oil reserves

should not be overstated, it would be foolish to exclude it from the equation. According

to the hypothesis, oil production should have a positive effect on defense spending. The

effect of oil production on defense spending may be more indirect. In an article for,

American Journal of Political Science, Benjamin Smith argues that “oil wealth is

robustly associated with more durable regimes and significantly related to lower levels of

protest and civil war” (Smith, p.232). Smith’s study did not find that oil wealth was used

as a tool of repression but that leaders in oil-rich states “invested their windfall revenues

in building state institutions and political organizations that could carry them through the

hard times”(Smith, p.232).4 Smith suggests that the boom and bust cycles of the oil

market do not seem to affect the longevity of authoritarian regimes. For example, he

observes “the collapse of oil prices in 1986 exerted no significant negative effect on

4 How these repressive regimes maintain their power for as long as they do is not clear. It may be that there are cultural differences at work here; and thus, it may not be appropriate to apply western standards of democracy to the Middle East.

Terry Chaney 7Econ 497Research Paperregime viability or civil conflict among oil exporters” (Smith, p.232).5 Moreover, Smith

found that overall democracy was positively related to incidents of civil war—which is

rather unexpected. However, “location in the Middle East and North Africa increased the

likelihood of civil war” (Smith, p.240). Thus, even if oil wealth does have a stabilizing

effect within a given country, it appears to have a destabilizing effect within the region.

In the last fifteen years large oil reserves have been discovered in the Caspian

Sea region.6 And since the collapse of the Soviet Union countries like Kazakhstan have

become important players in the geopolitical energy game. Klare discusses how the

relative importance of the Caspian Sea region was revealed as a shift in the U.S. national

security strategy during the 90’s. Klare discusses Operation CENTRAZBAT-97, which

was the first deployment of U.S. combat troops to that particular region. The operation

began September 15, 1997, when “five hundred paratroopers from the army’s 82nd

Airborne Division jumped into an arid battle zone in southern Kazakhstan.7 Their

assigned mission: to link up with friendly forces from Kazakhstan, Kyrgyzstan, and

Uzbekistan and engage in simulated combat against renegade forces opposed to a

regional peace agreement” (Klare, pp. 1).

5 One could argue that this is precisely what Hugo Chavez’s project is in Venezuela.

6 And in terms of gaining independence these are the youngest countries.7 Relations with Uzbekistan have cooled since then, in 2005 President Karimov ordered U.S. troops to leave the country.


The end of the Cold War and the opening of the Caspian Sea to increased foreign

investment has done little however to nurture democratic institutions in this region—

despite Borat’s best efforts. For example, Uzbekistan and Kazakhstan are both ruled by

former Communist Party bosses and have proven that the new boss is not much different

from the old boss.8 Most of the countries of this region, so far, (in terms of dollars spent)

do not present much of a military threat. However, the population in this region, like

many of the Middle Eastern countries is young and unemployed.9 And as NATO

continues its expansion into this region and threatens Russia with a missile defense

system in Turkey, the possibility for a highly militarized “Eurasian Corridor” increases

dramatically. There is evidence that Russia has not only adopted a new security strategy,

but also a new theoretic framework, to address this perceived aggression into its sphere of

influence. And in addition to NATO, China is also considered a very real national

security threat. (Jackson, p.386).

It has often been said that the wars of the future will be fought over water rather

than oil (something fun to look forward to). The total amount of water reserves however,

in this model was neither positive nor significant. And there could be a number of

reasons for this. For example, if the (desert) countries of the Middle East have the

strongest effect on the model’s results then water reserves would not appear to fit

particularly well. On the other hand, there are historical examples of water disputes in

the Jordan, Tigris-Euphrates

8 Parade.com ranks Uzbekistan’s President Karimov the #5 worst dictator in the world—right behind Hu Jintao of China.9 The median age in the U.S. is 36, Uzbekistan and Turkmenistan is 22. And unemployment in Turkmenistan is around 60%, which is the highest of the “stans” including Afghanistan.

Terry Chaney 9Econ 497Research Paperand Indus River Basins. The Tigris and Euphrates Rivers, for example, are vital to the

economies of the bordering countries. As Klare points out “Syria obtains about 85

percent of its total renewable water supply from the Euphrates, while Iraq obtains nearly

100 percent of its supply from the two rivers combined” (Klare, p.175). The population

is increasing rapidly in this region, which increases the risk of future water disputes.

Africa’s history over the last fifty years has also been turbulent and chaotic as

(overt) colonial powers have receded (although they still exercise control behind the

scenes to some extent). For example, during the Cold War the U.S. and Russia were both

arming different factions within Angola, with the goal of gaining access to the country’s

valuable mineral and petroleum resources. This competition for resources by foreigners

aggravated discord between factions within the country as well. The Soviet-backed

MPLA and the U.S.-backed UNITA were engaged in a bloody civil war that lasted

several decades after the Portuguese withdrew from the country. Unfortunately, the end

of the Cold War did not mean the end of conflict on the continent. For example, the rich

diamond wealth of Sierra Leone proved to be an enticing target for the insurgent Liberian

leader Charles Taylor. Like the Congolese dictator Mobutu, Taylor realized that having

access to mineral wealth is the key to maintaining power.

According to author Michael Klare, “the illicit diamond trade in Angola generates

an estimated $700 million per year, and sales from Sierra Leone are thought to be worth

at least half as much. In Congo, royalties from copper and uranium are thought to have

netted long-term dictator Mobutu Sese Seko and his close associates several hundred

Terry Chaney 10Econ 497Research Papermillion dollars per year” (Klare, p.192). Klare also discusses the increasing use of

private military companies, such as Executive Outcomes and Sandline International10,

which are often used to protect large mining and petroleum operations in “unstable”

regions. And while the use of mercenaries is not a recent development, not only does

their presence not seek to reduce conflict “their interests are best served by allowing the

fighting to continue as long as possible”. He then observes that, “these multiple factors—

the violent pursuit of resource wealth in poor and divided countries, the lack of an

effective international response, the willingness of many resource firms to traffic with

warlords and rebels, and the prominent role of PMC’s—have combined to increase the

intensity, lethality, and duration of the internal conflicts of the post-Cold War era”(Klare,

p.195).

If undemocratic countries spend more on defense spending does the converse

hold: do democratic countries spend less on defense related budget items? In a 2001

article for the The Journal of Conflict Resolution, James H Lebovic, argues that spending

priorities among Latin American democracies were shifted away from military spending

by 12% between 1988 and 1994. (Lebovic, p.427). Similar to Africa, Latin America was

also used as a virtual chessboard during the Cold War. And it would be fair to argue that

Latin America produced some of the most brutal dictators of the twentieth century (some

were even trained with U.S. tax dollars).11 Therefore, if Lebovic is correct, then it is

worth asking what is (or is not) happening in Latin America that isn’t happening in the

10 These two particular companies folded in 1999 and 2004 respectively, but the Iraq War especially has drawn attention to the role of PMCs like Blackwater, DynCorp and KBR.11 And thus, it would be interesting to see if Latin American countries were spending more than say the Middle East during the 60’s and 70’s.The CIA Factbook 2007, has only 3 Latin American countries in the top 50 for military spending (% of GDP): Honduras , Cuba and Ecuador.

Terry Chaney 11Econ 497Research PaperMiddle East? Lebovic begins by discussing how democratic institutions may affect the

budgetary process in general.12 And his regression results did reveal that the level of

democracy does have a positive and significant effect on the change in civilian spending

relative to military spending. Also, he found that budget growth had a positive and

significant effect on civilian spending and he suggests that perhaps “a bigger government

budget favors civilian spending and a smaller one favors military spending. Because

Latin American budgets tend, in general, to grow (not shrink), civilian budgets mainly

benefit from this effect” (Lebovic, p. 441). One unexpected result of Lebovic’s model

however, was that in one sample age had a negative effect on social spending, which

suggest that an older population spends less on social programs. Lebovic’s assumption is

that a younger, more democratic demographic would exert political pressure to increase

social spending for programs like education.13He speculates that perhaps an older

population would demand less education spending—but then again, a sufficiently large

older population may demand increases in health care rather than education.

DATA DESCRIPTION

12 Lebovic uses a civil and political rights index from Freedom House, which is slightly different from the 2 that I used.13 Again, echoes of the Civil Rights movement of the 60’s: a younger populace exerting political pressure for less guns more butter.


The independent variable used for the study was defense spending as a percentage

of annual GDP for one-hundred and sixty-four countries during 2007.14 The decision to

measure defense spending as a percentage of GDP (rather than total dollars spent) makes

it easier to compare how each country prioritizes its military expenditures relative to

other national interests and to other countries. For example, the United States is the

highest ranked based on total military expenditures, but ranks twenty-first based on its

percentage of GDP spent on defense compared to other priorities. One obvious problem

with this percentage is that it could easily be falsely reported, exaggerated or

underestimated.15

The following explanatory variables were also included in the model for the year

2007:

Unemployment rate: This measures the percent of the labor force that is without a job.

A high rate of unemployment should have a positive impact on defense

spending.http://72.14.205.104/search?sourceid=navclient-ff&ie=UTF-8&q=cache%3Ahttp%3A%2F%2Fwww.photius.com

%2Frankings%2Feconomy%2Funemployment_rate_2007_0.html

Median Age: This is the halfway point in each country where half of the population is

older and half is younger. Since the assumption is that a country with a younger

population will spend more on defense the model should reveal a negative effect on

defense spending. http://www.photius.com/rankings/population/median_age_total_2007_0.html

14 http://www.photius.com/rankings/military/military_expenditures_percent_of_gdp_2007_0.html15 For example, this wouldn’t include “black budget” items or projects—only annual expenditures directly related to military goods and services.

Terry Chaney 13Econ 497Research PaperOil - production: The total oil produced in barrels per day (bbl/day). Due to its

importance to the global economy this should be a positive predictor in the model.

http://www.photius.com/rankings/economy/oil_production_2007_0.html

Literacy: The (best estimate of the) percentage of the total population that can read and

write. High literacy is expected to be a negative predictor of military spending.

http://www.photius.com/rankings/population/literacy_total_2007_0.html

Democracy Index: The Economist’s Democracy Index ranked from one (best) to one

hundred sixty-seven (worst); and also divided into four categories: full democracies,

flawed democracies, hybrid regimes and authoritarian regimes.16

A ranking, with 1 being the highest, of each country’s democratic participation (courtesy

of The Economist). The assumption is that the lower the ranking, or the more

democratic, the less percentage of the overall budget will be spent on defense. Thus, the

effect should be positive.http://www.economist.com/media/pdf/DEMOCRACY_INDEX_2007_v3.pdf

Transparency Index: This index was compiled courtesy of Transparency International.

It ranks government corruption from 0 to 10 (10 being the best or least corrupt). Since a

lower ranking indicates a more corrupt regime, this variable should be a negative

predictor.http://www.transparency.org/news_room/in_focus/2006/cpi_2006__1/cpi_table

16 The Economist Intelligence Unit’s democracy index is based on five categories: electoral process and pluralism;civil liberties; the functioning of government; political participation; and political culture. The five categories are interrelated and form a coherent conceptualwhole. The condition of having free and fair competitive elections, and satisfying related aspects of political freedom, is clearly the basic requirement of all definitions.

http://www.transparency.org/news_room/in_focus/2006/cpi_2006__1/cpi_table

http://www.economist.com/media/pdf/DEMOCRACY_INDEX_2007_v3.pdf

Terry Chaney 14Econ 497Research PaperRegional Indicator: A dummy variable for each region. A value of 1 indicates whether

a country is located in: Africa, The Middle East, Asia, Europe or North-South America.

Mineral Resource Indicator: A dummy variable that indicates if a country has reserves

of various mineral commodities. A value of 1 indicates that a country has measurable

reserves of: Uranium, Diamonds, Gold, Nickel, Tin or Zinc. Resource wealth should

have a positive effect on a defense budget.

http://minerals.usgs.gov/minerals/pubs/country/

Water Reserves: This is a measure of how much renewable freshwater a particular

country has access to, measured in cubic kilometers per year. Similar to the other

resource variables, water reserves should be positive predictors.

http://www.worldwater.org/data.html

Inflation rate: A measure of the annual percentage change in consumer prices. The

expectation is that higher inflation rates would be another indicator of civil unrest which

would positively effect military spending.

http://www.photius.com/rankings/economy/inflation_rate_2007_0.html

MODEL AND RESULTS




There are a few things from the results of the regression analysis that seem

noteworthy. With respect to the regional indicators, all of the regional dummies had a

positive effect on defense spending. The Middle East dummy variable however, was the

only significant predictor. Which suggests that, all else being equal a Middle Eastern

country will spend a larger percentage of their GDP on military expenditures. And

considering the region’s chaotic history—at least during the last fifty years—this is not

shocking news.17 One surprising result from the regression analysis was that the African

dummy variable was not a significant predictor. This was unexpected considering the

number of hotspots in that region and also its geographic and demographic resemblance

to the Middle East. A second test was then executed, which isolated the African dummy

variable.18 And there were a few noticeable changes in the results. For example, the R-

Square value increased considerably despite the fact that there were fewer variables. But

most of the variables that had been significant in the model with all of the regional

dummies were no longer significant, with the exception of unemployment. The literacy

variable however, stayed negative and was significant at a 90% level. It would be

difficult to draw any meaningful conclusions from this, due to the small number of

observations.

Despite the evidence of these so-called resource wars over most of the resource

variables in this particular model did not lend support to the thesis. The effect of water

17 According to the CIA Factbook, six out of the ten highest ranked countries in this category are located in the Middle East, the other four are African. (http://www.photius.com/rankings/military/military_expenditures_percent_of_gdp_2007_0.html)18 This same test was run with the other regional dummies, but there were not enough observations to generate any output.

Terry Chaney 16Econ 497Research Paperreserves was neither positive nor significant, which was unexpected. It is possible that

water does not belong alongside the other variables due to the difference in its marginal

utility.19 Also, as a wise person pointed out, it could be simply that water becomes more

valuable when it is in short supply—and this would explain its negative effect.20

Diamonds, nickel and zinc were positive factors but not significantly so.21 Uranium, gold

and tin were negative factors which was unexpected.22 This could be due to the fact that a

dummy variable was used instead of the actual amounts in thousands of tons. The

hypothesis was that if any given country, regardless of the magnitude of their respective

reserves, collected enough of these variables it would have a positive effect within the

model. Thus, there is the possibility that this is an excluded variable issue, i.e., that there

simply were not enough resource variables included in the model.

Oil production, however was a positive and significant factor in this model as

expected. This may signify that oil is still one of the global economy’s most significant

resources relative to the various mineral resources in the model. Another possibility is

that the defense industry itself is petroleum- intensive (as opposed to nickel or tin) and

this could be driving defense spending to some degree.

Unemployment is also a positive and significant predictor in the model. And

there are several obvious reasons that governments faced with high unemployment would

ratchet up their military. People without jobs and opportunities will blame those in charge

19 What I had in mind was the Diamonds -Water paradox.20 In some of the models that I discarded, Gold had a very negative and significant effect as well.21 Nickel was the most significant at a 90% level.22 The uranium and tin dummy variables had a positive effect on the model, which included only the African dummy variable.—see appendix.

Terry Chaney 17Econ 497Research Paperand will often seek alternatives to their present situation. Thus, the government will use

military force to stay in power; and will try to channel the energy of its (angry and

unemployed) populace into military endeavors. And a sufficiently Machiavellian leader

will then look for a “dangerous” neighbor/enemy to turn the focus away from his own

malfeasance.

Median age did have a negative effect on defense spending but was not a strong

predictor, despite the very young, growing populations in some of the countries that have

been discussed. Similarly, as expected high literacy rates negatively effect defense

spending but not significantly so. And there could be a few reasons that explain this. It

could be that there is some excluded variable, say that measures poverty, which may

improve the explanatory power of the model. For example, Niger which has the lowest

literacy rate (16.7%) is also near the bottom in terms of annual GDP (ranks 180th). Thus,

it may be the case that a threshold of some kind exists in order to have any military at all.

In other words, some countries may be too poverty and disease stricken to sustain any

kind of military infrastructure. There might also be a simpler explanation, such as

discrepancies in how literacy is defined and reported. A country’s rate of inflation also

had a negative and insignificant relationship within the model which was not expected.

But there are probably reasonable explanations for this. Perhaps a country with a high

inflationary rate simply cannot reach the appropriate level of investment necessary to

build a strong military.


Regarding democratic participation, the hypothesis was that the less democratic

countries would have a higher level of defense spending—and this was reflected in the

results. The Democracy Index had a positive and significant effect on annual defense

spending. There are however, some obvious subjective difficulties in defining

‘democracy’. For example, if the Economist were published in Riyadh, instead of the

UK the list would be much different—and the Economist acknowledges this.23 The model

also tested a country’s openness or transparency. Transparency’s value to the model was

significant,24 but it had a positive effect which was unexpected, considering that the

Transparency Index ranks a country from 0 to 10.25 There could be several reasons for

this. The Democracy Index is a ranking from 1 to 167 and as expected had a positive

effect, i.e., less democratic countries have a higher ranking number, and thus spend more

on defense. And while the Democracy Index gauges democratic participation the

Transparency Index rates a country 0 to 10 on things such as, the frequency of incidents

of bribery, government corruption and freedom of the press. (And in fact, many of the

highest ranked countries on both lists are the same). These characteristics often do go

hand in hand, and a test did reveal the existence of collinearity

between the Democracy and Transparency variables.26 And of course, the subjective

nature of the concept of Transparency would be subject to the same criticisms as the

concept of Democracy.

23 http://www.economist.com/media/pdf/DEMOCRACY_INDEX_2007_v3.pdf24 http://www.transparency.org/news_room/in_focus/2006/cpi_2006__1/cpi_table

25 Thus, the effect should be negative since a highly rated country is considered to be more transparent. 26 See correlation results that are in the appendix.

http://www.transparency.org/news_room/in_focus/2006/cpi_2006__1/cpi_table



DISCUSSION OF RESULTS

The results of the regression analysis did reveal some interesting relationships.

For example, the geographic location does seem to matter when it comes to defense

spending. It appears as though Middle Eastern countries can expect to direct more of their

country’s budget towards defense related items. This suggests that the citizens in those

countries will have to settle for less of something else. The fact that the results did

change with respect to the African dummy variable suggests that there may be different

factors driving defense spending on that continent.27 It would be difficult to say at this

point, since the data for this model covered only one budget cycle. It would be

interesting to test whether these regions have changed over time and how this may have

changed before or after the Cold War. In other words, one could ask: has defense

spending declined in Southeast Asia? Has there been a marked decrease in armed

conflict and increased democratic participation? Lebovic’s study suggests that this may

already be happening in Latin America. And though there may be subtle cultural

differences, it is still worth asking: what is working here that isn’t working there?

The fact that mineral wealth was not a stronger predictor of military spending was

unexpected. Again, a model that includes more observations over decades may reveal

more robust results. One idea for a future research project would be to study if specific

27 Another test might be to divide Africa into regions and see if there are differences.

Terry Chaney 20Econ 497Research Paperresources in specific regions over time seem to predict higher levels of military spending

and conflict. It would also be interesting to test whether the global economy demanded

some of these resources during certain time periods. Alternatively, a more

comprehensive approach to this model would be to collect data for the most sought after

elements in the global economy: iron ore, coal, bauxite, timber, etc; and then see if the

results improve significantly.

Oil turned out to be the only resource variable that was a positive and significant

predictor. Most of the reasons for this have already been discussed. And because of oil’s

importance to global economic growth, it would be fair to ask if is this is even an

interesting result. After all is it really surprising that oil production is influencing

military spending? And on some level the relationship between oil, guns and war has

become so politicized, that the discussion only seems to take place on bumper stickers.

The relationship between oil and defense spending, it appears is more subtle and indirect.

The more interesting relationship perhaps, as in Smith’s study, is how oil revenues may

contribute to regime stabilization (or destabilization) at different stages of the boom and

bust cycle. Also, a potential future project would be to test if other energy inputs like

coal or natural gas would be strong predictors.

Democratic participation was a significant factor in the model and the fact that it

did prove to be a strong predictor of defense spending suggests that this might be an

important area of study in the future. Along the lines of Lebovic’s research, which

focuses on Latin America, it is interesting to study how spending priorities are shifted as

Terry Chaney 21Econ 497Research Papera nation evolves, or “matures”. Does a mature democratic nation eventually spend more

on domestic programs like health care and education? Does the overall standard of living

improve significantly—and if not, why? Some may even question if this would even be a

desirable strategy in the Middle East. Depending on the party’s interest, some may prefer

a more militarized Middle East, because it does seem to create a balance of power

dynamic. Thus, including regime type in the model does seem justified.

The hypothesis of a young and unemployed population spending more on defense

was reflected in the regression results, although not as initially predicted. Recall that

median age was a negative predictor of defense spending, which supports the hypothesis

that a younger population is spending more—or at the very least that an older population

is spending less. However, since its effect was not very significant it would be premature

to draw any meaningful conclusions. A better model should compare different regions

over time. Unemployment was a strong predictor in both the model with all of the regions

included and the model which only included the African dummy variable. And therefore

it should be used in any future studies of military sending. How it may affect defense

spending is not entirely clear, but there were a few ideas offered earlier. Again, if the

model does offer any guidance about a nation’s stage of development it would be

important to try and determine why a country with high unemployment seeks military

solutions. And this may be more of a question for Sociology than for Economics.

The effect of inflation within the model is somewhat questionable, and the results

were previously discussed. Initially, it was assumed that high inflation combined with a

Terry Chaney 22Econ 497Research Paperyounger, unemployed populace would create an environment that required a “military

solution”, that would be preferred to civil unrest. And this would then be reflected in a

higher than normal defense budget. It had a negative effect which was not anticipated and

it is possible that the significance of inflation does stifle investment in several budget

categories—including defense spending. It is possible that this is an excluded variable

issue. Or perhaps, patterns of inflationary effects on defense spending would show up

over time. Thus a more complex model could reveal the more subtle effects of inflation

on defense spending. There is evidence that inflation leads to civil unrest. In an article

for International Journal of Middle East Studies, author Larbi Sadiki discusses how

inflation had sparked “bread riots” in several Middle Eastern countries during the 80’s

and 90’s. (Sadiki, p.75). Sadiki considers these protests in places like Sudan and Jordan,

as a positive sign of democratic change that is specific to the Arab world. Sadiki argues

that “deductions made from the experience of mature democracies are of doubtful

relevance for states that are only beginning the process of democratization” (p.88).

Similar to Toby Jones’ article, Sadiki suggests that a social contract in the Arab world

will have to take into consideration the cultural and religious beliefs that are unique to

that region.

WORKS CITED

Jackson, William D. Autumn, 2002. Encircled Again: Russia's Military Assesses Threats in a Post-Soviet World. Political Science Quarterly, Vol. 117, No. 3. (), pp. 373-400.

Terry Chaney 23Econ 497Research Paper Jones, Toby. Autumn, 2003. Seeking a "Social Contract" for Saudi Arabia. Middle East Report, No. 228, pp. 42-48 Published by: Middle East Research and Information Project.

Klare, Michael T. Resource Wars: The New Landscape Of Global Conflict.New York: Metropolitan Books, 2001.

Lebovic, James H. Aug., 2001. Spending Priorities and Democratic Rule in Latin America. The Journal of Conflict Resolution, Vol. 45, No. 4. pp. 427-452.

Sadiki, Larbi. Feb., 2000. Popular Uprisings and Arab Democratization International. Journal of Middle East Studies, Vol. 32, No. 1, (), pp. 71-95 Published by: Cambridge University Press.

Smith, Benjamin. Apr., 2004. Oil Wealth and Regime Survival in the Developing World, 1960-1999. American Journal of Political Science, Vol. 48, No. 2, pp. 232-246 Published by: Midwest Political Science Association

ONLINE SOURCES

http://www.photius.com/rankings/spreadsheets_2007/


http://www.transparency.org/



APPENDIX

Correlation Africa



http://www.transparency.org/



Correlations

1 -.757**.000

49 45-.757** 1.000

45 47

Pearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)N

TRANSPARENCY

DEMOCRACY INDEX

TRANSPARENCY

DEMOCRACYINDEX

Correlation is significant at the 0.01 level (2-tailed).**.

Correlation Rest of World

Correlations

1 -.715**.000

176 160-.715** 1.000160 166

Pearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)N

TRANSPARENCY

DEMOCRACY INDEX

TRANSPARENCY

DEMOCRACYINDEX

Correlation is significant at the 0.01 level (2-tailed).**.


20.015.010.05.00.0

MilitaryexpenditurespercentofGDP

60

40

20

0

Freq

uenc

y

Mean =2.591Std. Dev. =2.3838

N =164


100806040200

UnemploymentRate

60

50

40

30

20

10

0

Freq

uenc

y

Mean =13.68Std. Dev. =15.016

N =200


50.045.040.035.030.025.020.015.0

Medianagetotal

25

20

15

10

5

0

Freq

uenc

y

Mean =27.598Std. Dev. =8.3559

N =221


Defense Spending As Percentage of GDP: 20071 2

Rest Of World AfricaObservations 130 26R-Squared 0.48 0.682Literacy -0.003 -0.07

0.837 0.068Median Age -0.012 0.101

0.802 0.594Oil Production 2.87E-07 1.18E-06

0.037 0.119Transparency 0.313 0.306

0.015 0.697Democracy Index 0.014 0.013

0.025 0.4African Dummy 0.224 NA

0.788 NAAsian Dummy 0.974 NA

0.189 NAN. & S. American Dummy 0.76 NA

0.327 NAEuropean Dummy 0.747 NA

0.311 NAMiddle East Dummy 2.775 NA

0 NACopper Dummy 0.798 1.691

0.1 0.244Gold Dummy -0.519 -0.253

0.237 0.851Nickel Dummy 0.879 NA

0.139 NATin Dummy -0.458 NA

0.497 NAZinc Dummy 0.398 0.234

0.426 0.907Diamond Dummy 0.555 0.365

0.457 0.703Silver Dummy -0.329 NA

0.531 NAUranium Dummy -0.621 0.01

0.376 0.996Water Reserves 0 0

0.586 0.937Unemployment 0.041 0.089

0.004 0.006Inflation -0.001 -0.003


0.547 0.289

Research Paper 3-1

Documents

Transcript of Research Paper 3-1