Armed Forces & Society

Armed Forces & Society http://afs.sagepub.com/

Major Armed Conflicts, Militarization, and Life Chances: A Pooled Time-Series Analysis Steve Carlton-Ford Armed Forces & Society 2010 36: 864 originally published online 24 September 2009 DOI: 10.1177/0095327X09335946 The online version of this article can be found at: http://afs.sagepub.com/content/36/5/864

Published by: http://www.sagepublications.com

On behalf of: Inter-University Seminar on Armed Forces and Society

Additional services and information for Armed Forces & Society can be found at: Email Alerts: http://afs.sagepub.com/cgi/alerts Subscriptions: http://afs.sagepub.com/subscriptions Reprints: http://www.sagepub.com/journalsReprints.nav Permissions: http://www.sagepub.com/journalsPermissions.nav Citations: http://afs.sagepub.com/content/36/5/864.refs.html

Downloaded from afs.sagepub.com at UNIV OF CINCINNATI on October 25, 2010

Major Armed Conflicts, Militarization, and Life Chances: A Pooled TimeSeries Analysis

Armed Forces & Society 36(5) 864-889 ª The Author(s) 2010 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0095327X09335946 http://afs.sagepub.com

Steve Carlton-Ford1

Abstract Armed conflict typically worsens civilian life chances. The effects of social militarization (maintenance of armed forces) and economic militarization (military expenditures) on civilian life chances are disputed, and the joint effect of armed conflict and militarization on civilian life chances has not previously been examined. This study examines the joint effects of three types of major armed conflicts and two types of militarization on civilian life chances, using a fixed-effects negative binomial cross-national panel analysis (1985-1998) of data from 175 countries with populations larger than two hundred thousand. General economic development, political regime, and country-specific effects are controlled. Armed conflict and militarization interact in affecting civilian life chances. Armed conflict results in higher levels of civilian mortality; militarization interacts with armed conflict, producing the best civilian life chances at either medium-low or medium-high levels of militarization. Keywords armed conflict, militarization, child mortality, civil war, military participation

To fight armed conflicts, countries must militarize both socially (by recruiting and maintaining armed forces) and economically (by supporting the armed forces as well as buying and maintaining weapons systems). Major armed conflicts depress national economies and degrade many aspects of social life, lowering civilian life chances. In

1

University of Cincinnati

Corresponding Author: Steve Carlton-Ford, 1018, Crosley Tower Cincinnati OH, 45221-0378 513-556-4716 Email: [email protected]


Carlton-Ford

865

contrast, social militarization1 (maintaining armed forces) appears indirectly to improve the life chances of civilians. To the extent that economic militarization (spending on the military) affects civilian life chances, it appears to reduce spending in the areas of the economy that should improve civilian life chances. In addition, the military’s impact on social and economic development and, ultimately, on civilian life chances probably differs, depending on whether a country ever experiences a major armed conflict and whether that conflict is active. In the sections below, I discuss how major armed conflict, social militarization, and conomic militarization should affect civilian life chances. After discussing data and methodology, I examine the impact of armed conflict and militarization on young children’s mortality rates, a key indicator of civilian life chances that is unlikely to be directly affected by combat.

Major Armed Conflict and Civilian Life Chances After WWII, the number of major armed conflicts increased steadily, peaking in the late 1980s with nearly forty major armed conflicts; the number then declined to a low of nineteen in 1996 before increasing again in the late 1990s.2 Rather than attempting to control territory, the tactics of contemporary armed conflicts are generally designed to disrupt ongoing day-to-day life; by thus undermining the government in power, insurgents hope to gain political control.3 Such disruptions may affect transportation (road, rail, or air), the supply of electricity and fuel, the production and distribution of food, the provision of education and health services (either through the harassment of teachers and medical professionals or through the destruction of school buildings and hospitals or clinics), and commerce in general.4 Typically, research examining the impact of armed conflict5 (e.g., civil war) on social and economic development finds demonstrable adverse effects. Civil wars and other wars degrade economies and destroy educational and health infrastructures.6 Often the dynamics of armed conflict polarize populations, as people contend for increasingly rare and expensive stocks of food.7 As wars eliminate both production of and access to food, malnutrition increases.8 With infrastructures destroyed, access to safe water and medical treatment decreases. Ultimately, the mortality rates of civilian noncombatants increase; this is particularly the case for young children.9 These adverse effects are not, however, inevitable. For example, Iraq’s child mortality rates rose dramatically during the Gulf War; but during the civil war in Nicaragua, child mortality rates did not rise; during Sri Lanka’s civil war, child mortality rates decreased.10 In general, however, armed conflict should adversely affect children’s life chances, leading to my first hypothesis: Hypothesis 1: At least prior to controlling for potentially intervening factors, major armed conflict should increase child mortality rates. Regardless of the outcome, to fight armed conflicts, nations have to recruit, maintain, and equip armed forces—they have to militarize. Both international wars and civil


866

Armed Forces & Society 36(5)

wars (as well as external and internal threats) lead to an increase in military spending.11 In the aggregate, military spending was high during years with higher numbers of armed conflicts; military spending dropped during the years that armed conflicts were on the decline.12 In addition, civil wars led to about an 80 percent increase—from 2.8 percent of GDP to 5 percent of GDP—in military spending,13 although military spending appears not to deter rebellion.14 Similarly, countries with larger armies are more likely to be involved in international wars.15 Although detailed analyses linking armed conflict and the size of armed forces appear not to be available, it seems likely that armed forces would also swell during armed conflicts.

Militarization and Life Chances Rival theories linking militarization and national development argue either (1) that militarization harms the general population by drawing resources from more productive uses or, alternatively, (2) that militarization indirectly improves the general quality of life, since the resources devoted to creating and sustaining armed forces have side benefits for the general population. This second approach contends that if these resources were not devoted to the military, they would often otherwise be siphoned off for nonproductive uses. Although militarization research has often produced contradictory results,16 the impact of militarization appears to depend both on the aspect of militarization and on the aspect of national development being examined. Militarization theories, and associated research, typically focus either on economic militarization or on social militarization. Economic militarization. To the extent that nations must formulate and pursue competing and potentially incompatible national priorities with limited budgets, economic militarization should reduce spending in other areas, such as targeted development projects (e.g., safe water, health services, or education) that would benefit the general population of those countries.17 Research provides some support for this approach. Economic militarization appears to create both direct economic benefits and indirect economic disincentives, which together produce a small net negative effect on the general economy.18 Research on developed nations indicates that countries with large armed forces make relatively smaller investments in social welfare, such as ‘‘benefits for social insurance, public assistance, family stipends, health, and employment-related sickness and injuries.’’19 The same effect appears to occur in developing nations, with economic militarization generating an overall decrease in the overall quality of life for the general population (including a decrease in infant survival rates).20 Given the strong impact of both general and targeted economic development on population well-being,21 the second hypothesis is clear Hypothesis 2: In general, military spending should lead to poorer life chances (e.g., higher child mortality rates) for the general population.


Carlton-Ford

867

Social militarization. In contrast to theorists of economic militarization, theorists of social militarization argue that it will have beneficial effects for the general population. They argue that if funds were taken from military budgets, they probably would not be transferred to targeted development projects. Instead, money taken from the military would, for example, be siphoned off due to corrupt practices, a particularly serious problem in poor countries with weak political structures.22 The likelihood of corruption if funds were reallocated to civilian use, combined with the beneficial effects of military development projects, makes investment in armed forces the best—though less than ideal—avenue for national development in many countries. Since reallocation is not a realistic alternative, theorists of social militarization argue that what matters is the use to which military budgets are put. These theorists argue that social militarization—developing armed forces— requires nation-building, which leads to positive social and economic change.23 They contend that investments in armed forces—in troops rather than weapons—ultimately foster social and economic developments that benefit civilian populations. This can happen two different ways: (1) across the board, researchers argue that the military instills discipline and promotes adherence to commands, both of which are characteristics that should translate into a more effective workforce and economic growth; and (2) to maintain effective armed forces, a nation must be able to house, feed, arm, educate, and move its troops.24 This requires a strong general economy, a strong agricultural sector, an institutionalized educational system, developed transportation networks, as well as a health and medical infrastructure. In fact, armed forces may be directly involved in building infrastructures such as roads, waterways, communications networks, and water systems. All of these infrastructure developments have been shown to be associated with lower levels of poverty and lower levels of child mortality.25 The advocates of the benefits of social militarization argue that the armed forces promote (either directly or indirectly) modernization projects that ultimately benefit the civilian population. In short, Hypothesis 3: Social militarization should lead to social improvements that ultimately increase civilian life chances (e.g., lower child mortality rates). Although this position has not been not been universally endorsed (with other scholars arguing that militaries are unlikely either to have enough administrative capacity or to involve a large enough proportion of the population to have much effect26), the research on developing nations typically finds beneficial effects of social militarization, even when controlling for economic militarization (but not vice versa). Social militarization tends to promote national development and population well-being, resulting in both higher levels of economic development and lower levels of child and infant mortality,27 an effect that is likely to be particularly pronounced in less economically developed countries.28 Although social militarization may not be the most desirable way to enhance national development, it does appear to improve life chances.


868


Armed Conflict and Militarization Whether a country develops its military in an attempt to forestall armed conflict or develops it in response to armed conflict, the impact of both armed conflict and militarization on national development ought to be examined simultaneously. As discussed above, there is a considerable body of theory and research about each topic, yet no previous research has explored the joint effect of armed conflict and both social militarization and economic militarization on the well-being of civilian populations. Since war and other major armed conflict appear to drive up the size both of military expenditures and of armed forces, the relative impact of armed conflict and militarization needs to be carefully considered. To the extent that both economic militarization and armed conflict adversely affect civilian life chances, they stand as potentially redundant explanations. Any apparent negative impact of armed conflict might be the result of increased economic militarization; any apparent negative effect of economic militarization might arise from higher levels of armed conflict. In contrast, if social militarization theory is right, increases in the size of armed forces should have beneficial effects. If they are considered individually, social militarization and armed conflict may mask each other’s effects, leading us to underestimate the importance of each. If the standard accounts of the effects of armed conflict and militarization are correct, considering them simultaneously should reveal stronger beneficial effects of social militarization as well as stronger adverse effects of armed conflict. Rather than having the additive effects found in previous research, armed conflict and militarization could interact, either affecting life chances differently in countries with no armed conflict than in countries that do have armed conflicts or exhibiting different effects during years of active conflict. Since countries with armed conflicts are generally quite poor, militarization (either social or economic) during peaceful times might help promote development and help ensure life chances;29 although relatively large forces may be needed to effectively counter an insurgency,30 rapidly increasing the armed forces during active conflict could result in poorly trained troops attempting to quell conflict with detrimental side effects for the civilian population.31 In contrast, although economic militarization (over and above the costs of social militarization) might prove generally harmful to civilian life chances during peace time, it might provide resources needed to enable the military to carry out its operations during times of conflict.32 Alternatively, the strain of paying for both arms and personnel and also fighting an armed conflict might produce particularly adverse effects. There is no interaction hypothesis with clear support, but the potential for the effects of militarization to differ, depending on whether a country is involved in a major armed conflict, needs to be explored, leading to the fourth hypothesis: Hypothesis 4: Militarization will affect civilian life chances differently in more peaceful countries and years than in countries and years with armed conflicts.


Carlton-Ford

869

Alternative Explanations Other potentially consequential changes will undoubtedly occur in conjunction with major armed conflict and militarization.33 Researchers should explicitly consider two key potential confounding variables—regime type and economic development. Each is a rival explanation for the expected effects of armed conflict and militarization discussed above. Democracies (compared to other polities) are less likely to become engaged in armed conflicts and more likely both to come to an earlier resolution of conflict and to have lower levels of battle-related casualties. Democracies are expected to be more peaceful, in part, because they tend to place responsibility for involvement in war on the civilian population, because politicians in democratic regimes usually tend to be more ‘‘pacific,’’ and because democratic norms tend to oppose the use of violence.34 Democracies appear to avoid international wars because they have a propensity to settle disputes through nonviolent means.35 Autocracies are between two to four times more likely to be involved in international wars than democracies, a result that holds independent of the effects of the size of armed forces, militarization, and economic development.36 Yet both autocratic and democratic regimes are less likely to experience civil wars37 than are regimes in transition, which have the highest probability of major armed conflict. The relative stability of autocracies and democracies appears to hinge on their level of economic development, with poor autocracies and relatively rich democracies being the most stable.38 The ability to avoid war does not necessarily indicate that democracies are better at providing for their citizens than are other forms of government. Although a long tradition of research indicates that democracies make better provisions for the poor than other regime types, much of this research has been based on samples that underrepresent successful autocratic regimes. Although democracies may channel proportionately more funds into social services, they often respond more to the demands of the middle and upper classes. As a result, increased social service spending does not necessarily translate into better overall outcomes for poorer citizens.39 Although there is no particularly well-developed theory about why rich (or poor) nations should be more likely to go to war,40 changes in economic development might provide an alternative explanation for any effects of militarization. Decreases in economic development from armed conflict would lead to increases in child mortality, elaborating the process through which armed conflict affects civilian populations. Social militarization’s and economic militarization’s effects on the civilian population through economic development, in contrast, are less clear. To the extent that militarization is related to armed conflict, to political regime, to economic development, and to civilian life chances, all should be considered simultaneously.

Methods Data Set This study uses the ‘‘War and Children’s Life Chances’’ data set to conduct a cross-national negative binomial panel analysis, covering the years from 1985 through


870


1998, of the impact of armed conflict and militarization on life chances.41 The data set contains information from 175 countries with populations of two hundred thousand or larger (see Appendix A). The data are unbalanced, with the number of country-years of data depending on the number of years the country was in existence. As a result, the maximum number of country-years is 1,996 (not 2,450 ¼ 14 years 175 countries).

Dependent and Independent Variables Child mortality (U5M). The under-5 mortality rate—the number of children per thousand births who are expected to die prior to their fifth birthdays—is the indicator of civilian mortality. The under-5 mortality rate is unlikely to be directly affected by combat but, instead, by indirect effects on health42 and has been used previously as an indicator of the general well-being of civilian populations. The child mortality data are from UNICEF’s ‘‘State of the World’s Children’’ for 1985 through 1998. Although conceptually a rate (number per thousand), child mortality figures are reported as counts with integer values ranging from 4 to 329. The data distribution is quite skewed. The untransformed data are appropriately analyzed using the approach described below in the section describing the analysis plan. Major armed conflict (MAC1, MAC2, MAC3, MAC4). Information on major armed conflict from 1985 through 1998 comes from version 3 of the Oslo International Peace Research Institute’s (PRIO) data set.43 During these years, there were three types of conflicts: (1) international conflicts, which involve at least two states; (2) internal conflicts, which involve a state and at least one oppositional nonstate actor; and (3) internationalized internal conflicts, which involve a focal state, an oppositional nonstate actor, and one or more other states. For each type of conflict, each country-year of data was originally coded either as having no conflict (fewer than twenty-five battle-related deaths), minor armed conflict (more than twenty-five but fewer than one thousand battle-related deaths over the course of the conflict), intermediate armed conflict (twenty-five or more battle-related dead in a particular year and one thousand or more dead over the course of the conflict), or war (one thousand or more battle-related dead in a given year). Analyses (not shown) indicated that intermediate armed conflicts have effects similar in magnitude and direction to those of wars. Each type of conflict was dichotomized to contrast major armed conflicts (i.e., intermediate conflicts and war) with lower levels of conflict (no conflict and minor conflicts). This information was used to create four conflict variables. Using the country-year information described just below, a variable (MAC1) was created that contrasts countries with no major armed conflicts from 1985 through 1998 (coded 0) with those that had some major armed conflict during that time (coded 1). Previous research indicates that countries at war but without the war on their territory may actually benefit economically from the war.44 So both international and internationalized internal MACs (MAC2 and MAC4) were coded so that noncontiguous states in international armed


Carlton-Ford

871

conflicts are categorized as not being involved in armed conflict. This applies primarily to states (e.g., the United States) that were involved in the First Gulf War but were not within range of Iraq’s missile systems, as well as some sub-Saharan countries. Then each type of conflict in each country-year was coded to indicate whether the conflict was active. This yields three other variables: active international major armed conflict (MAC2, e.g., Iran and Iraq 1985-1988), active internal major armed conflict (MAC3, e.g., Liberia 1990-1995), and active internationalized internal major armed conflict (MAC4, e.g., Democratic Republic of the Congo 1997-1998). Militarization. First, social militarization is indexed by the World Bank’s measure of military personnel as a percentage of the total labor force, typically referred to as the military participation ratio (MPR). As indicated below, univariate results are in the original metric, but in the bivariate and multivariate analyses this indicator is logged. Second, economic militarization is indexed by the World Bank’s measure of military expenditures as a percent of GDP (M%$). The highest value of military expenditure is found for Kuwait in 1991. Univariate results are presented in the original metric, but in the bivariate and multivariate analyses this indicator is logged; when used in an interaction term, these variables are mean-centered. Political regime. I use Gleditsch’s country-year data set that contains the 21-point measure of regime type (polity2).45 Regimes are scored –10 if they are totally autocratic and þ10 if they are totally democratic. Countries in the middle range contain a mix of autocratic and democratic characteristics. Economic development. The measure of economic development is the gross national product per capita (1985-1998), taken from UNICEF’s yearly publication ‘‘State of the World’s Children.’’ As is typical in development research, I use a logged version, which normalizes the cross-national income distribution. Time. Time trends (from 1985 through 1998) are controlled by including an explicit indicator of time. This variable is coded 0 for the starting year (1985) and increases by one for each successive year. As a result of this coding, intercepts in multivariate analyses represent the value of the dependent variable in 1985 adjusted for the effects of the time trend and for other variables in the model. Country-specific controls. Multivariate analyses reported below include a dummy variable for each country except two: a country at the average under-5 mortality rate for countries with no major armed conflict and a country at the average under-5 mortality rate for countries that have armed conflict. With more than one country-year of data for each country, country-specific effects can be estimated by including dummy variables to represent constant country effects (see analysis plan below). Because they are not substantively informative, the country-specific effects are not reported in the analyses.


872


Analysis Plan and Methodological Checks Analyses employ a fixed-effects negative binomial panel model using generalized estimation equations. This approach, which is appropriate for skewed count data collected over time,46 arrays the data as country-years—a separate record for each country for each year it is represented in the data set. Country-specific effects are estimated using dummy variables without creating problems of multicollinearity.47 With the country-specific effects estimated, the intercept in the analysis represents the under-5 mortality rate for the omitted country without major armed conflicts; the effect for the country-level measure of armed conflict (MAC1) represents the difference between the average under-5 mortality rate for countries without major armed conflicts (the intercept) and the average for countries with major armed conflicts (adjusted for any other variables in the model). With the inclusion of an explicit variable controlling for time trends, this approach to panel analysis estimates the effects of time-varying characteristics of countries (e.g., militarization) as well as events (e.g., armed conflicts) on change in the dependent variable.48 Each analysis presents results based on data available for a limited range of years in an available subsample of countries (that sometimes is nearly as large as the population of countries). Uncertainty in the estimates results from sources of variation other than sampling. A large effect relative to its standard error indicates a consistent outcome. With panel data, ideally one corrects standard errors for clustering. Unfortunately, cluster-corrected standard errors are not available for negative binomial panel regressions. Instead, I used a skewed corrected version of the dependent variable so that I could estimate the same panel models using a routine (STATA’s xtreg) that does compute standard errors which have been corrected for clustering. The same pattern of significant results emerged. An examination of bivariate correlations (shown in Appendix B) showed only small selection effects (primarily for armed conflict). Since the largest amounts of missing data are associated with the two militarization variables, a Heckman selection model was estimated using time and a dummy variable for each country as predictors of missing data on these variables. Inclusion of the predicted probability in preliminary analyses left the results for internal armed conflict virtually unchanged; effects of internationalized internal conflict were heightened 40 to 50 percent. At every step in these preliminary analyses, controlling for additional variables produced approximately the same percentage reduction in effects as is reported below. In addition, specifying an autoregressive error structure yields results that were highly similar to the reported results. The reported results are robust to the inclusion of additional control variables; supplementary analyses controlling alternatively for population, population density, childhood immunizations, young adult literacy, battle deaths, and food availability left the findings unchanged. Analyses reported below include interaction terms, the effects of which are not the result of particularly influential individual countries or country-years of data. Regression coefficients are combined and exponentiated to estimate predicted levels of child mortality.49


Carlton-Ford

873

Results Table 1 presents the basic statistics for all substantive variables included in the analyses; the variables indexing time, interaction terms, and country-specific dummy variables are not listed. Across all countries and all years, an average of nearly eightysix children per thousand died before they reached their fifth birthdays. Roughly 37 percent of the countries in the sample experienced some form of major armed conflict at some time from 1985 through 1998. Approximately 2 percent of the country-years involved international armed conflicts, 15 percent of the country-years involved internal armed conflicts (e.g., civil wars), and about 4 percent of the country-years involved internationalized internal armed conflicts. Military participation rates averaged less than 2 percent, with a low of 0 percent and a high of nearly 30 percent (i.e., Iraq in 1990). Military expenditures averaged slightly more than 4 percent of GDP, but varied widely. Some countries (e.g., Austria, Bolivia) report no military expenditures for specific years; at the other extreme, in 1991, Kuwait spent 101.9 percent of GDP, averaging about 24 percent during the period). For each militarization variable, a logged version corrects for skewness. Gross national product per capita averaged just over $4,620, with a low of $60 and high of more than $45,000. The logged version corrects for skewness. Political regime varies from complete autocracy (–10) to complete democracy (þ10), with an average (1.14) indicating slightly more country-years with more democratic regimes. Coded values in the middle range indicate unstable governments. Table 2 presents three multivariate negative binomial panel analyses. Since country-specific fixed effects (not shown) are controlled in each analysis, coefficients represent effects on change in the under-5 mortality rate. The bottom three rows report the goodness-of-fit statistics first for the models as estimated, then with the substantive variables only, and then only the fixed effects. Comparisons within each model show that the full models always fit better than either of the reduced models. Fit statistics cannot be compared across models, since they are based on different numbers of cases. Comparisons of each reported model to its baseline model from the previous step estimated on the same cases (Appendix C) indicate that, at each step, adding substantive variables improves the fit. The top rows in Table 2 results show (1) the time trend for under-5 mortality rates, (2) the initial level of under-5 mortality in countries that never have a major armed conflict during the years of the study, (3) the difference (in 1985) between countries that have major armed conflicts and those that do not, and (4) the impact of active conflict for each of the three different types of major armed conflict. Model 1. Model 1 indicates that child mortality declines at about 4 percent per year (b ¼ –.042) from 1985 through 1998. Countries with no major armed conflicts begin with a child mortality rate of 84.4 children per thousand (eb|b ¼ 4.436) in 1985. Countries that have major armed conflicts at some time from 1985 through 1998 begin with


874


Table 1. Basic Statistics for Under-5 Mortality, Major Armed Conflict, Militarization, and Other Variables

Mean Under-5 mortality rate 85.75 (per thousand children) Major armed conflict MAC1: Conflict country .37 (0 ¼ no; 1 ¼ yes) MAC2: Active international .02 conflict MAC3: Active internal .15 conflict year .04 MAC4: Active internationalized internal conflict Militarization Social militarization (MPR 1.77 [percentage of workforce]) Social militarization: log10 .36 normalized Economic militarization (M$% 4.16 [of GDP]) Economic militarization: .60 log10 normalized Economic development 4,620.78 (GNP/c) Economic development: 3.16 log10 normalized Political regime (autocratic to 1.14 democratic)

Standard Deviation Minimum Maximum

Number of CountryYears

78.29

4

329

1,991

.48

0

1

1,996

.14

0

1

1,986

.36

0

1

1,986

.18

0

1

1,988

2.47

0

29.57

1,711

.24

0

1.49

1,711

6.04

0

101.9

1,613

.27

0

2.01

1,613

7,648.55

60

45,360.00

1,951

4.66

1,951

10

1,941

.67 7.34

1.78 –10

under-5 mortality rates that average 146.5 per thousand (eb|b ¼ 4.436 þ .551), just under 75 percent higher. Years in which international armed conflicts are active appear to have virtually the same child mortality rates (b ¼ .004); in contrast, years with internal armed conflicts (b ¼ .048) or with internationalized internal armed conflicts (b ¼ .066) have marginally higher child mortality, with rates of 153.7 (eb|b ¼ 4.436 þ .551 þ .048) and 156.5 (eb|b ¼ 4.436 þ .551 þ .066), respectively. Model 2. Model 2 introduces controls for both social and economic militarization as well as the interactions of these two variables with two armed conflict variables. The two armed conflict variables are (1) the variable that contrasts countries that do not have any armed conflict with countries that do (MAC1) and (2) the variable


Carlton-Ford

875

Table 2. Negative Binomial Fixed-Effect Panel Regressions of Child Mortality Rates on Armed Conflict, Militarization, Economic Development, and Political Regime Model 1

Model 2

b

b

Sig.

Sig.

Model 3 b

Time trend (1985-1998) –.042 .000 –.050 .000 –.048 Countries with no major armed conflicts (intercept) 4.436 .000 4.402 .000 4.345 Countries with major armed conflicts (MAC1) .551 .000 .626 .000 .610 Active international conflict (MAC2) .004 .945 –.007 .877 –.031 Active internal conflict (MAC3) .048 .173 .031 .364 .020 Active internationalized internal conflict (MAC4) .066 .139 .056 .252 .087 Social militarization (MPR) .181 .500 .207 Interaction with MAC1 –.577 .104 –.489 Interaction with MAC4 .435 .001 .406 Economic militarization (M$%) –.342 .045 –.154 Interaction with MAC1 .426 .036 .262 Interaction with MAC4 –.205 .075 –.234 Economic development (GNP/c) –.278 Political regime (autocratic to democratic) .009 N of countries 175 160 152 N of country years 1,981 1,571 1,531 Goodness of fit (QIC): Substantive and fixed effects 64.97 45.49 41.95 Substantive effects only 1,987.23 1,277.63 436.26 Fixed effects only 117.24 89.96 88.43

Sig. .000 .000 .000 .528 .564 .071 .411 .170 .000 .266 .131 .030 .008 .001

Note: For all models, the country-specific fixed effects are estimated via dummy variables. The dummy variables for two countries are omitted: (1) one for the country closest to the mean of the dependent variable for countries that never have an armed conflict and (2) one for the country closest to the mean of the dependent variable for countries that do have armed conflicts. As a result, the armed conflict contrast variable (MAC1) estimates the difference between the average for countries that do not have a major armed conflict and the average for the countries that do. Significant interactions are not the result of inclusion of influential countries (e.g., Iraq, Iran, or Kuwait). Results specifying an autoregressive error structure yield highly similar results. Except for not being able to estimate the mean difference between the two groups of countries (the contrast estimated by MAC1) or the significance of interaction effects, analyses run within groups of countries yield the same pattern of results.

that contrasts years of active internationalized conflict to years in those countries when the conflict was not active (MAC4). The two sets of interactions consistently produced substantial effects; no other interactions did (details available from the author). Since there are significant interaction effects, the coefficients in the rows labeled ‘‘social militarization’’ and ‘‘economic militarization’’ represent the effects of those variables on under-5 mortality only in countries that never have any major armed conflicts. These effects serve as a statistical baseline against which interaction terms are assessed. The interaction of each of the militarization variables with MAC1, the indicator of whether a country has a major armed conflict or not, represents the difference between the baseline effect (described at the beginning of this paragraph) and the


876


effect of militarization in countries that do have major armed conflicts at some time during the study, but only during the years when conflict is not active. The interactions of the militarization variables with MAC4, the variable that indicates whether an internationalized internal conflict is active in a particular year, estimate—for countries that do have major armed conflicts—the additional difference in the effect of militarization that occurs during the years when conflict is active. With the interaction effects in the model, the coefficients for the armed conflict variables (MAC1, MAC2, MAC3, and MAC4) represent direct effects estimated at mean levels of the militarization variables. Introducing controls for militarization and the interactions described above produced little, if any, change in the effects of the armed conflict variables at average levels of militarization. Countries without major armed conflict begin with an under-5 mortality rate of 81.6 per thousand that decreases by about 5 percent per year. Countries with armed conflicts start with a mortality rate that is nearly 90 percent higher. Years of active international conflict made little difference to the mortality rate (b ¼ –.007), but years of internal armed conflict raised the mortality rate by about 3 percent to 157.4 per thousand; at average levels of militarization, internationalized internal armed conflict raised the under-5 mortality rate by about 6 percent to 161.4 per thousand. Although the effects of both social and economic militarization were in their expected directions prior to controlling for country-specific effects and armed conflict (analyses not shown), they have much more complex relationships in the reported analyses. Social militarization has a positive coefficient (b ¼ .181) in countries with no armed conflict, exerting an adverse effect on child mortality; in countries that did have active armed conflicts at some time between 1985 and 1998, social militarization had a significantly and substantially different effect (b ¼ –.577). Adding the two effects together, the baseline plus the interaction, indicates that social militarization provided a net benefit for the civilian population during the years when conflict was not active (overall b ¼ –.396 [–.577 þ .181]). In years with active internationalized internal conflicts, this beneficial effect is all but eliminated (overall b ¼ .039 [–.577 þ .181 þ .435]). Economic militarization also showed a pattern of significant interactions. In countries with no major armed conflicts, economic militarization produced strong reductions in the under-5 mortality rate (b ¼ –.342); in countries that had armed conflicts at some time during the study, economic militarization produced no net improvement in under-5 mortality (overall b ¼ .084 [–.342 þ .426]); during years with active internationalized internal conflict, additional military spending did appear to provide some protection for children (overall b ¼ –.121 [–.342 þ .426 – .205]). Militarization clearly exerts a strong, if complex, impact on under-5 mortality rates, an issue that is addressed in more detail after considering (in model 3) the effect of controlling for economic development and political regime changes. Model 3. Model 3 introduces controls for both economic development and political regime. These controls do not eliminate the effects of armed conflict or of


Carlton-Ford

877

militarization. Countries with armed conflict start with under-5 mortality rates that are nearly 85 percent higher than countries with no armed conflict (77.1 per thousand versus 141.9 per thousand). Years of active international armed conflict are associated with slightly lower rates of under-5 mortality (137.6 per thousand), while years of active internal conflict are associated with slightly higher levels of child mortality (144.8 per thousand). At average levels of militarization, internationalized internal conflict appears to produce higher levels of child mortality: 154.8 per thousand. Social militarization continues to increase (b ¼ .207) and economic militarization to decrease (b ¼ –.154) under-5 mortality in countries that do not have armed conflict. Countries with armed conflicts exhibit the opposite pattern; social militarization decreases under-5 mortality (overall b ¼ –.282 [.207 – .489]), while economic militarization increases under-5 mortality (overall b ¼ .108 [–.154 þ .262]). Years of active internationalized internal conflict tend to reverse these effects. During years of active internationalized internal conflict, the overall impact of social militarization increases under-5 mortality (overall b ¼ .124 [.207 – .489 þ .406]), and the overall impact of economic militarization decreases child mortality (overall b ¼ –.126 [–.154 þ .262 – .234]). Supplementary analyses (not shown) that remove the nonsignificant interactions of militarization with the conflict country contrast variable (MAC1) reveal the same pattern of interactions of militarization with active internationalized internal conflict, yielding the same general conclusions: during years of conflict, increases in social militarization lead to marginally higher under-5 mortality rates, while increases in economic militarization lead to marginally lower child mortality rates. As expected, increases in economic development are associated with lower under-5 mortality rates (b ¼ –.278), and democratization appears to lead to somewhat higher levels of under-5 mortality (b ¼ .009). There were no interactions of nonlinear effects involving economic development or political regime. Given the complex pattern of offsetting interaction effects, the overall joint effects of militarization and armed conflict on under-5 mortality are difficult to assess; the interactive effects of militarization and armed conflict must be considered simultaneously across differing levels of conflict and differing levels of militarization. Because of the complex offsetting interactive effects of militarization, the lowest levels of under-5 mortality (55.4 children per thousand and 52.7 children per thousand) are found at mediumlow (e.g., 25th percentile) and at medium-high (e.g., the 75th percentile) levels of militarization, respectively (see Appendix D for more estimates). Even in years when conflict is not active, countries that have internationalized internal armed conflicts (middle row of estimates) have consistently higher under-5 mortality rates than countries that do not have armed conflicts (top row of estimates), with years of active internationalized internal armed conflict exhibiting still higher levels of under-5 mortality.

Discussion and Conclusion Countries militarize to fight armed conflicts; both militarization and armed conflict affect civilian life chances. Armed conflict adversely affects civilian life chances.


878


Although previous research has produced mixed results, theories of economic militarization predict that military expenditures will worsen civilian life chances; in contrast, theories of social militarization expect better civilian life chances. Yet despite their being intertwined, previous research had examined neither the simultaneous nor the joint impact of armed conflict and militarization. This article fills this gap by addressing four questions: (1) Does major armed conflict adversely affect civilian well-being, once militarization and other potentially confounding influences have been considered? (2) Does economic militarization adversely affect civilian well-being? (3) Does social militarization improve civilian life chances? and (4) Do the joint effects of militarization and armed conflict interact to produce a distinctive pattern of civilian life chances? I provide answers to these questions by estimating fixed-effect panel models of the effects of militarization and armed conflict on children’s mortality rates in more than 150 countries from 1985 through 1998. This study is not without limitations. The available data vary both by country and year, with the data on militarization particularly vulnerable to this problem. In contrast, data on major armed conflicts are available consistently, although the process of determining whether a country is involved in a major armed conflict is error-prone.50 Selection effects created by militarization data make the reported results for armed conflict somewhat conservative. As is the case in all crossnational research, similar problems arise in determining political regime, mortality rates, and economic development. The use of country-specific controls precludes the possibility of directly and explicitly examining the impact of constant national characteristics (e.g., history of colonization, history of previous conflict, world system position) that might have important long-term effects. Keeping these limitations in mind, the research presented above provides strong evidence about the impact of armed conflict and militarization on civilian life chances. The use of the fixedeffects negative binomial panel regressions ensures estimates that have been purged of the effects of most, if not all, extraneous influences. As has been found in previous research,51 countries with major armed conflicts start with poorer life chances (in this case, child mortality rates); years of active conflict raise these rates by 5 to 7 percent. But social and economic militarization both interact with armed conflict to influence civilian life chances in a complex pattern of offsetting effects. Social militarization—maintaining armed forces—produced higher child mortality rates in countries with no armed conflict. Consistent with the implications of previous research, social militarization lowered mortality rates in countries that did have armed conflict, but only during the years the conflicts were not active. When conflict was active, the beneficial effects of social militarization were largely eliminated. Perhaps increasing the size of armed forces during years of conflict introduces poorly trained troops who are ineffective in quelling violence, who resort to more terroristic attempts to intimidate opposition forces.52 In contrast, economic militarization—military spending—proved beneficial to civilian life chances in countries that did not have any major armed conflict. This effect was erased in countries that did experience major armed conflict, although


Carlton-Ford

879

economic militarization did appear to help lower child mortality somewhat during years of active conflict. These results suggest that in the more highly developed nations (those without major armed conflict), economic militarization, perhaps by spurring economic activity, produces benefits for the general population. In nations with armed conflict, lower levels of child mortality associated with economic militarization during years of active conflict might result from using those funds either to co-opt the opposition by currying favor with civilians, as was done during the Lebanese civil war,53 or to more effectively arm and train existing troops. Additional controls for changes in general economic development and for political regime (autocracy to democracy) had little additional effect on the general pattern of results. Cross-national research will consistently mislead policy makers, researchers, and theorists if it fails to take account of the complex ways in which armed conflict and militarization affect civilian populations. These results are exploratory, and their interpretation is somewhat speculative. Nonetheless, future research on armed conflict and militarization needs to address the joint impact of armed conflict to see if these results can be reproduced. Development-oriented theory and research need to account for the effects of major armed conflict and militarization. The effects of militarization on civilian life chances are as large as, or larger than, those for economic development more generally; the effects of militarization were much larger than for either armed conflict or democratization. The current war in Iraq provides a particularly stark example of the complex relationships between war, regime, militarization, and economic development, but it is only one example among approximately seventeen major armed conflicts currently active. Although in recent years the number of major armed conflict has stabilized, there is little indication that armed conflict will disappear. Future research—both large-sample and case-study—needs to specify more completely the dimensions of militarization that profoundly affect civilian populations. What aspects of military organization are particularly salient? Through what specific processes does militarization affect population well-being? Does the internal organization of militaries influence their impact on civilian life? For example, Praetorian militaries have been thought to be particularly inimical to the well-being of civilian populations.54 But little research has addressed this issue even indirectly. With the rise of international concern over human rights, the military’s impact on civilian populations has become an important national security issue; theory and research must attempt to determine the answers to these questions. To the extent that particular levels of social and economic militarization promote civilian life chances, while other levels reduce life chances, a nation must carefully balance both how much national wealth to expend on the military as well as how to allocate that spending to enhance both national security and the well-being of its population.


880


Appendix A Countries Included in Analyses No Major Armed Conflict (1985-1998)a Albania Argentina Australia Austria Bahamas, The Bahrain Barbados Belarus Belgium Belize Benin Bhutan Bolivia Botswana Brazil Brunei Bulgaria Burkina Faso Cameroon Canada Cape Verde Central African Rep. Chile Comoros Costa Rica Cote d’Ivoire Croatia Cuba Cyprus Czech Rep. Czechoslovakia Denmark Djibouti Dominican Rep. Ecuador Egypt, Arab Rep. Equatorial Guinea Estonia

Gabon Gambia, The Germany Germany Federation Germany, Dem. Rep. Ghana Greece Guyana

Namibia Nepal Netherlands New Zealand Niger Nigeria Norway Oman

Haiti Honduras Hungary Iceland Ireland Italy

Panama Papua New Guinea Paraguay Poland Portugal Qatar

Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kyrgyz Rep. Latvia Lesotho Lithuania Luxembourg Macedonia, FYR Madagascar Malawi Malaysia Maldives Mali Malta Mauritania Mauritius Mexico Moldova

Romania Singapore Slovak Rep. Slovenia Solomon Islands Spain Suriname Swaziland Sweden Switzerland Tanzania Thailand Togo Trinidad and Tobago Tunisia Turkmenistan Ukraine United Arab Emirates United States Uruguay Venezuela (continued)


Carlton-Ford

881

Appendix. (continued) Fiji Finland France

Mongolia

Major Armed Conflict (At Some Time Afghanistan Algeria Angola Armenia Azerbaijan

1985-1998)b India Indonesia Iran, Islamic Rep. Iraq Israel

Bangladesh Bosnia and Herzegovina Burundi

Kuwait

Cambodia Chad China Colombia Congo, Dem. Rep. Congo, Rep. El Salvador Eritrea Ethiopia Georgia Guatemala Guinea-Bissau Guinea

Lao PDR Lebanon Liberia Libya Morocco Mozambique Myanmar

Yemen Zambia Zimbabwe

Saudi Arabia Senegal Sierra Leone Somalia South Africa Soviet Union Sri Lanka Sudan Syrian Arab Rep. Tajikistan Turkey Uganda United Kingdom Uzbekistan

Nicaragua Vietnam Pakistan Peru Philippines

Yemen, Dem. Rep. Yemen, Rep. Yugoslavia, FR (Serbia/Montenegro)

Russian Federation Rwanda

a. Not a country with an international major armed conflict on its territory; not a country with an internal major armed conflict; not a country with an internationalized internal major armed conflict on its territory, and not a contiguous or nearby state involved in such a conflict. b. A country with an international major armed conflict on its territory; or a country with an internal major armed conflict; or a country with an internationalized internal major armed conflict on its territory or a contiguous or nearby state involved in such a conflict.


882


— –.157*** .327*** .047* .168*** .135*** –.317*** –.005 –.768*** –.472***

–.146*** — –.031 –.058** –.051* –.085*** –.098*** –.157*** .062** .192***

TIME

.328*** –.005 — .184*** .549*** .252*** .115*** .289*** –.348*** –.305***

MAC1a .054* –.063** .192*** — .118*** .053* .109*** .211*** –.066** – .043*

MAC2 .159*** –.056* .582*** .115*** — –.049** .094*** .165*** –.199*** –.051*

MAC3 .136*** –.029 .188*** .053* –.044 — .111*** .139*** –.089*** –.158***

MAC4

M$% .005 –.132*** .290*** .205*** .179*** .139*** .700*** — .045*** –.371***

MPR – .334*** –.083*** .084*** .105*** .097*** .057* — .698*** .324*** –.167***

–.763*** .056* –.349*** –.065** –.188*** –.109*** .340*** .055* — .483***

GNP/c

.485*** .149*** –.304*** –.047 –.056* –.156*** –.142*** –.369*** .488*** —

–

Regime

Note: The minimum pairwise n is 1,579 for military personnel with military expenditures; excepting correlations with time, the maximum pairwise n is 1,991 for MAC1 with U5M. The n for the listwise deletion is 1,531. b. MAC1 represents a contrast between countries that have no major armed conflict (0) and countries that have a major armed conflict at some point during the study (1). MAC2 is country-year specific international major armed conflict (PRIO type 2); MAC3 is country-year specific internal major armed conflict (PRIO type 3); MAC4 is country-year specific internationalized internal major armed conflict (PRIO type 4). *p .05. **p .01. ***p .001 (are one-tailed tests).

U5M TIME MAC1 MAC2 MAC3 MAC4 MPR M$% GNP/c Regime

U5M

Appendix B. Bivariate Pearson Correlations between Under-5 Mortality, Major Armed Conflict, Militarization, and Other Variables (Listwise Deletion above the Diagonal; Pairwise Deletion below the Diagonal)


883

.173 .139

.945

.000 .000 .000

175 1,981 64.97 1,987.23 117.24

.048 .066

.004

–.042 4.436 .551

Sig.

Sig.

.415 .349

.982

.000 .000 .000

160 1,571 45.84 1,592.09 89.96

.029 .056

.001

–.048 4.465 .563

b

Model 1a Sig.

.364 .252 .500 .104 .001 .045 .036 .075

.877

.000 .000 .000

160 1,571 45.49 1,277.63 89.96

.031 .056 .181 –.577 .435 –.342 .426 –.205

–.007

–.050 4.402 .626

b

Model 2 Sig.

.409 .154 .395 .074 .000 .051 .041 .116

.427

.000 .000 .000

152 1,531 44.02 1,255.99 88.43

.029 .078 .214 –.641 .464 –.314 .410 –.305

–.034

–.051 4.417 .611

b

Model 2a

152 1,531 41.95 436.26 88.43

.020 .087 .207 –.489 .406 –.154 .262 –.234 –.278 .009

–.031

–.048 4.345 .610

b

Sig.

.564 .071 .411 .170 .000 .266 .131 .030 .008 .001

.528

.000 .000 .000

Model 3

Note: For all models, the country-specific fixed effects are estimated via dummy variables. The dummy variables for two countries are omitted: (1) one for the country closest to the mean of the dependent variable for countries that never have an armed conflict and (2) one for the country closest to the mean of the dependent variable for countries that do have armed conflicts. As a result, the armed conflict contrast variable (MAC1) estimates the difference between the average for countries that do not have a major armed conflict and the average for the countries that do. Significant interactions are not the result of inclusion of influential countries (e.g., Iraq, Iran, or Kuwait). Results specifying an autoregressive error structure yield highly similar results. Except for not being able to estimate the mean difference between the two groups of countries (the contrast estimated by MAC1) or the significance of interaction effects, analyses run within groups of countries yield the same pattern of results.

Active internal conflict (MAC3) Active internationalized internal conflict (MAC4) Social militarization (MPR) Interaction with MAC1 Interaction with MAC4 Economic militarization (M$%) Interaction with MAC1 Interaction with MAC4 Economic development (GNP/c) Political regime (autocratic to democratic) N of countries N of country-years Goodness of fit (QIC): Substantive and fixed effects Substantive effects only Fixed effects only

Active international conflict (MAC2)

Time trend (1985-1998) Countries with no major armed conflicts (intercept) Countries with major armed conflicts (MAC1)

b

Model 1

Appendix C. Negative Binomial Fixed-Effect Panel Regressions of Child Mortality Rates on Armed Conflict, Militarization, Economic Development, and Political Regime

884


Appendix D Predicted Under-5 Mortality Rate by Level of Militarization and Major Internationalized Internal Armed Conflict

Predicted Under-5 Mortality Rate by Level of Militarizationa 25th Percentile

Mean

75th Percentile

Countries With

Minimum

No major armed conflict Major internationalized internal conflict Years with no active conflict Years with active conflict

94.0

55.4

81.6

167.2 171.2

106.3 136.2

152.6 97.0 161.4 133.0

52.7

Maximum 61.9

109.7 142.3

a. All estimates are based on model 2 presented in Table 2. For each estimate of under-5 mortality, both social militarization and economic militarization were recoded so that the zero point corresponds to the level described above. For example, for estimates at the mean level of militarization each variable was centered on its own mean; the computation of the estimates of under-5 mortality at this level of militarization is shown in the text discussion of model 2.

Author’s Note This research received generous support from the American Sociological Association’s Fund for the Advancement of the Discipline and the Charles Phelps Taft Fund. The McMicken College of Arts & Sciences and the Department of Sociology, both at the University of Cincinnati, also provided important support. Many thanks to Andrea Hunt for conducting background research, to Donielle Boop for conducting additional research and supplementary analyses, to Cindy Carlton-Ford for editorial advice, to Nicolas Williams for advice on panel analysis, and to Morten Ender and Louis Hicks for encouragement and feedback as I have developed my ideas. Finally, thanks to the editor and anonymous reviewers for constructive criticism that substantially improved this article. An earlier version of this article was presented at the Biennial Meeting of the Inter-University Seminar on Armed Forces and Society, Chicago, October 27, 2007. Declaration of Conflicting Interests The author declared no potential conflicts of interests with respect to the authorship and/or publication of this article. Funding The author received no financial support for the research and/or authorship of this article.


Carlton-Ford

885

Notes 1. Three meanings can clearly be distinguished: (1) militarization, ‘‘the quantity and proportion of resources a society devotes to military affairs’’; (2) cultural militarism, the attitudes and behaviors of individuals, groups, and organizations; and (3) national policy, ‘‘governmental actions.’’ My use of militarization is the first one: ‘‘the quantity and proportion of resources a society devotes to military affairs’’; no positive or negative connotations are intended. See Herbert P. Van Tuyll, ‘‘Militarism, the United States, and the Cold War,’’ Armed Forces & Society 20 (1994): 519-30. My use of the term is consistent with its use in much of the sociological literature. For example, see Brad Bullock and Glenn Firebaugh, ‘‘Guns and Butter? The Effect of Militarization on Economic and Social Development in the Third World,’’ Journal of Political and Military Sociology 18 (1990): 231-66. 2. Nils Petter Gleditsch, Peter Wallensteen, Mikael Eriksson, Margareta Sollenberg, and Havard Strand, ‘‘Armed Conflict 1946 to 2001: A New Dataset,’’ Journal of Peace Research 39 (2002): 615-37. 3. Ian Roxborough, ‘‘Learning and Diffusing the Lessons of Counterinsurgency: The U.S. Military from Vietnam to Iraq,’’ Sociological Focus 39 (2006): 319-46; and Ian Roxborough, ‘‘Counterinsurgency,’’ Contexts 6 (2007): 15-21. 4. Paul Collier, Lani Elliot, Havard Hegre, Anke Hoeffler, Marta Reynol-Querol, and Nicholas Sambanis, Breaking the Conflict Trap: Civil War and Development Policy (Washington, DC: International Bank for Reconstruction and Development/World Bank, 2003). 5. The literature on the effects of armed conflict often glosses over the distinctions among internal conflicts (i.e., civil conflicts), international conflicts, and internationalized internal conflicts when assessing the effects of conflict. For example, see Frances Stewart, Valpy FitzGerald, and Associates, War and Underdevelopment, 2 vols. (Oxford: Oxford University Press, 2001), particularly vol. 1, chap. 4. As a result, I do not attempt to always make these distinctions in the literature review or when formulating hypotheses. I do, however, distinguish among these types of conflict in the analyses. 6. Brian Lai and Clayton Thyne, ‘‘The Effect of Civil War on Education, 1980-97,’’ Journal of Peace Research 44 (2007): 277-92; and Paul Collier and Nicholas Sambanis, Understanding Civil War: Evidence and Analysis, 2 vols. (Washington, DC: International Bank for Reconstruction and Development/World Bank, 2005). 7. Anthony Oberschall and Michael Seidman, ‘‘Food Coercion in Revolution and Civil War: Who Wins and How They Do It,’’ Comparative Studies in Society & History 47 (2005): 372-402. 8. J. Craig Jenkins, Stephen J. Scanlan, and Lindsey Peterson, ‘‘Military Famine, Human Rights, and Child Hunger: A Cross-National Analysis, 1990-2000,’’ Journal of Conflict Resolution 51 (2007): 823-47. 9. Steve Carlton-Ford, ‘‘The Impact of War, Adult HIV/AIDS, and Militarization on Young Children’s Mortality,’’ in Sociological Studies of Children and Youth, vol. 10, Special International Volume, ed. Loretta Bass (San Diego, CA: Elsevier, 2005), 231-55; Steve Carlton-Ford, Ann Hamill, and Paula Houston, ‘‘War and Children’s Mortality,’’


886

10. 11. 12.

13. 14. 15. 16. 17.

18.

19.

20. 21. 22. 23. 24.


Childhood 7 (2000): 401-19; and Debarati Guha-Sapir and Wilem Gijsbert van Panhuis, ‘‘Conflict-Related Mortality: An Analysis of 37 Datasets,’’ Disasters 28 (2004): 418-28. Stewart, FitzGerald, and Associates, War and Underdevelopment. Paul Collier, ‘‘War and Military Expenditure in Developing Countries and Their Consequences for Development,’’ Economics of Peace and Security Journal 1 (2006): 10-13. Gleditsch et al., ‘‘Armed Conflict 1946 to 2001’’; and Stockholm International Peace Research Institute (SIPRI), ‘‘World and Regional Military Expenditure Estimates: 19882006’’ (2007), http://www.sipri.org/contents/milap/milex/mex_wnr_table.html (accessed August 24, 2007). Collier et al., Breaking the Conflict Trap. Paul Collier and Anke Hoeffler, ‘‘Unintended Consequences: Does Aid Promote Arms Races?’’ Oxford Bulletin of Economics and Statistics 69 (2006): 1-27. Kenneth Benoit, ‘‘Democracies Really Are More Pacific (in General): Reexamining Regime Type and War Involvement,’’ Journal of Conflict Resolution 40 (1996): 636-57. William J. Dixon and Bruce E. Moon, ‘‘The Military Burden and Basic Human Needs,’’ Journal of Conflict Resolution 30 (1986): 660-84. Saadet Deger, ‘‘Economic Development and Defense Expenditure,’’ Economic Development and Cultural Change 35 (1986): 179-96; and Alvin Birdi and J. Paul Dunne, ‘‘South Africa: An Econometric Analysis of Military Spending and Economic Growth,’’ in Arming the South: The Economics of Military Expenditure, Arms Production, and Arms Trade in Developing Countries, ed. Jurgen Brauer and J. Paul Dunne (New York: Palgrave, 2002), 221-33. See Emile Benoit, ‘‘Growth and Defense in Developing Countries,’’ Economic Development and Cultural Change 26 (1978): 271-80, for a more mixed assessment. Francis O. Adeola, ‘‘Military Expenditures, Health, and Education: Bedfellows or Antagonists in Third World Development?’’ Armed Forces & Society 22 (1996): 441-67; and Deger, ‘‘Economic Development and Defense Expenditure.’’ Brian Gifford, ‘‘Why No Trade-Off between ‘Guns and Butter’? Armed Forces and Social Spending in the Advanced Industrial Democracies, 1960-1993,’’ American Journal of Sociology 112 (2006): 473-509. The quoted material can be found on page 481. Adeola, ‘‘Military Expenditures, Health, and Education.’’ Lant Pritchett and Lawrence H. Summers, ‘‘Wealthier Is Healthier,’’ Journal of Human Resources 31 (1996): 841-68. Gabriella R. Montinola and Robert W. Jackman, ‘‘Sources of Corruption: A Cross-Country Study,’’ British Journal of Political Science 32 (2002): 147-70. John J. Johnson, ed., The Role of the Military in Underdeveloped Countries (Santa Monica, CA: Rand Corporation, 1962; reprint, Westport, CT: Greenwood, 1981). For example, see Bullock and Firebaugh, ‘‘Guns and Butter?’’; Dixon and Moon, ‘‘The Military Burden and Basic Human Needs;’’ Edward L. Kick, Byron L. Davis, David M. Kiefer, and Thomas J. Burns, ‘‘A Cross-National Analysis of Militarization and WellBeing Relationships in Developing Countries,’’ Social Science Research 27 (1998): 35170; Edward L. Kick, Randa Nasser, Byron L. Davis, and Lee Bean, ‘‘Militarization and Infant Mortality in the Third World,’’ Journal of Political and Military Sociology 18 (1990): 285305; and Erich Weede, ‘‘Military Participation Ratios, Human Capital Formation, and


Carlton-Ford

25.

26.

27.

28.

29.

30. 31.

32. 33. 34.

887

Economic Growth: A Cross-National Analysis,’’ Journal of Political and Military Sociology 11 (1983): 11-19. For a concise discussion of development, poverty, and infant mortality, see Coralie Bryant and Christina Kappaz, Reducing Poverty, Building Peace (Bloomfield, CT: Kumarian, 2005), esp. chap. 1. Morris Janowitz, The Military in the Political Development of New Nations (Chicago: University of Chicago Press, 1964); and Brian S. Macdonald, Military Spending in Developing Countries: How Much Is Too Much? (Ottawa, Canada: Carleton University Press, 1994). Bullock and Firebaugh, ‘‘Guns and Butter?’’; Carlton-Ford, ‘‘The Impact of War, Adult HIV/AIDS, and Militarization on Young Children’s Mortality’’; Dixon and Moon, ‘‘The Military Burden and Basic Human Needs;’’ Kick et al., ‘‘A Cross-National Analysis of Militarization and Well-Being Relationships in Developing Countries’’; and Kick et al., ‘‘Militarization and Infant Mortality in the Third World.’’ Erich Weede, ‘‘The Impact of Military Participation on Economic Growth and Income Inequality: Some New Evidence,’’ Journal of Political and Military Sociology 21 (1993): 241-58. For social militarization, see ibid.; for economic militarization, see Alex Mintz and Randolph T. Stevenson, ‘‘Defense Expenditures, Economic Growth, and the ‘Peace Dividend’: A Longitudinal Analysis of 103 Countries,’’ Journal of Conflict Resolution 39 (1995): 283-305. David H. Petraeus, James F. Amos, and John A. Nagl, The U.S. Army & Marine Corps Counterinsurgency Field Manual (Chicago: University of Chicago Press, 2007). Jeffery Herbst, ‘‘African Militaries and Rebellion: The Political Economy of Threat and Combat Effectiveness,’’ Journal of Peace Research 41 (2004): 357-69; Stathis N. Kalyvas, ‘‘The Paradox of Violence in Civil War,’’ Journal of Ethics 8 (2004): 97-138; and Roxborough, ‘‘Counterinsurgency,’’ 15-21. Petraeus, Amos, and Nagl, The U.S. Army & Marine Corps Counterinsurgency Field Manual. Stewart, FitzGerald, and Associates, War and Underdevelopment. That democracies are less likely to be involved in international wars and internal conflicts has been well documented as an empirical fact. Researchers and theorists still dispute the reason for this regularity. Some argue that it is the result of democratic norms, others that the decentralization of power in democracies is crucial. See Benoit, ‘‘Democracies Really Are More Pacific (in General)’’; William Dixon, ‘‘Democracy and the Peaceful Settlement of International Conflict,’’ American Political Science Review 88 (1994): 14-32; Bruce Bueno de Mesquita, Michael T. Koch, and Randolph M. Siverson, ‘‘Testing Competing Institutional Explanations of the Democratic Peace: The Case of Dispute Duration,’’ Conflict Management and Peace Science 21 (2004): 255-67; David A. Lake, ‘‘Powerful Pacifists: Democratic States and War,’’ American Political Science Review 86 (1992): 24-37; and R. J. Rummel, ‘‘Democracy, Power, Genocide, and Mass Murder,’’ Journal of Conflict Resolution 39 (1995): 3-26. For a review of theoretical disputes and a list of additional sources, see David Kinsella, ‘‘No Rest for the Democratic Peace,’’ American Political Science Review 99 (2005): 453-72.


888


35. Dixon, ‘‘Democracy and the Peaceful Settlement of International Conflict.’’ 36. Benoit, ‘‘Democracies Really Are More Pacific (in General).’’ 37. J. Joseph Hewitt, Jonathan Wilkenfeld, and Ted Robert Gurr, Peace and Conflict 2008 (Boulder, CO: Paradigm, 2008); and Edward D. Mansfield and Jack Snyder, ‘‘Incomplete Democratization and the Outbreak of Military Disputes,’’ International Studies Quarterly 46 (2002): 529-49. 38. Collier et al., Breaking the Conflict Trap. 39. For research that finds beneficial effects of democracy, see Bruce E. Moon and William J. Dixon, ‘‘Politics, the State, and Basic Human Needs: A Cross-National Study,’’ American Journal of Political Science 29 (1985): 661-93; and Thomas D. Zweifel and Patricio Navia, ‘‘Democracy, Dictatorship, and Infant Mortality,’’ Journal of Democracy 11 (2000): 99114. For the selection effect argument, see Michael Ross, ‘‘Is Democracy Good for the Poor?’’ American Journal of Political Science 50 (2006): 860-74. 40. Benoit, ‘‘Democracies Really Are More Pacific (in General).’’ 41. World Bank data concerning the armed forces and military expenditures are available starting only in 1985. 42. A. Reza, J. A. Mercy, and E. Krug, ‘‘Epidemiology of Violent Deaths in the World,’’ Injury Prevention 7 (2001): 104-11. 43. Ha˚vard Strand, Lars Wilhelmsen, and Nils Petter Gleditsch, ‘‘Armed Conflict Dataset Codebook Version 3.0,’’ (2004), http://www.prio.no/sptrans/-1938717918/codebook_v3_0.pdf. 44. Stewart, FitzGerald, and Associates. War and Underdevelopment. 45. Kristian Skrede Gleditsch, ‘‘Modified Polity P4 and P4D Data, Version 1.0’’ (2003), http:// weber.ucsd.edu/~kgledits/Polity.html (accessed June 14, 2007). 46. J. Scott Long, Regression Models for Categorical and Limited Dependent Variables (Thousand Oaks, CA: Sage, 1997), chap. 8. For types of data appropriately analyzed as counts (including variables, such as the number of smoked cigarettes per day, that are expressed as number per time period), see Badi H. Baltagi, Econometric Analysis of Panel Data, 4th ed. (Chichester, UK: John Wiley, 2008), 226-35. 47. Paul D. Allison, ‘‘Using Panel Data to Estimate the Effects of Events,’’ Sociological Methods and Research 23 (1994): 174-99; and Charles N. Halaby, ‘‘Panel Models in Sociological Research: Theory into Practice,’’ Annual Review of Sociology 30 (2004): 507-44. 48. Allison, ‘‘Using Panel Data to Estimate the Effects of Events.’’ 49. Long, Regression Models for Categorical and Limited Dependent Variables, chap. 8. 50. Gleditsch et al., ‘‘Armed Conflict 1946 to 2001.’’ 51. Carlton-Ford, ‘‘The Impact of War, Adult HIV/AIDS, and Militarization on Young Children’s Mortality’’; and Carlton-Ford, Hamill, and Houston, ‘‘War and Children’s Mortality.’’ 52. Kalyvas, ‘‘The Paradox of Violence in Civil War.’’ 53. Samir Makdisi and Richard Sadaka, ‘‘The Lebanese Civil War, 1975-90,’’ in Collier and Sambanis, Understanding Civil War, vol. 2. 54. Stanislav Andreski, Military Organization and Society, 2nd ed. (Berkeley: University of California Press, 1968), Postscript to the Second Edition; Kirk Bowman, Militarization, Democracy, and Development: The Perils of Praetorianism in Latin America (University


Carlton-Ford

889

Park: University of Pennsylvania Press, 2002), chap. 6; and Amos Perlmutter, The Military and Politics in Modern Times (New Haven, CT: Yale University Press, 1977).

Bio Steve Carlton-Ford is an associate professor of sociology at the University of Cincinnati. His research centers on the well-being of children and adolescents. His most recent research focuses on the effect of armed conflict on both the life chances of children and the psychological wellbeing of adolescents. His research has been published in Child Development, Childhood, the Journal of Adolescence, the Journal of Health and Social Behavior, Peace Review, Sociological Focus, The Sociological Quarterly, and Sociological Studies of Children and Youth.
