Changes in military expenditure as a share of gross domestic product (MIL/GDP) and of total expenditure (MIL/EX) during IMF-supported programs are examined for two subsamples, broadly divided according to fiscal tightening and fiscal accommodation. Under fiscal tightening, the evidence suggests that MIL/GDP decreases during Fund-supported programs, but that MIL/EX increases, revealing resilience to budgetary adjustments. Under fiscal accommodation, as total government expenditure tends to increase, so does military expenditure; the ratio MIL/EX declines, however, because fewer additional resources are allocated to the military.

Abstract

Changes in military expenditure as a share of gross domestic product (MIL/GDP) and of total expenditure (MIL/EX) during IMF-supported programs are examined for two subsamples, broadly divided according to fiscal tightening and fiscal accommodation. Under fiscal tightening, the evidence suggests that MIL/GDP decreases during Fund-supported programs, but that MIL/EX increases, revealing resilience to budgetary adjustments. Under fiscal accommodation, as total government expenditure tends to increase, so does military expenditure; the ratio MIL/EX declines, however, because fewer additional resources are allocated to the military.

Devloping countries have more than quintupled their military spending in real terms since the 1960s, almost tripling their share of worldwide military spending. These developments have often significantly affected both the balance of payments and the government budget, and possibly the rate of economic growth (Lebovic and Ishaq (1987)). To the extent that Fund-supported adjustment programs have stressed the control and rationalization of government expenditure or cutbacks in government outlays, military spending is a potentially important policy issue. Even though the Fund has rarely mandated specific actions in this area, government authorities can be expected to review all categories of public expenditures during an adjustment program. The main objective of this paper is to examine, from the limited data available, how total military spending has evolved during Fund-supported programs and to assess when military expenditures have been, or could be expected to be, resilient to adjustments in overall expenditure.

One must initially consider that expenditure restraint is not necessarily the central aspect of all Fund-supported adjustment programs. Although all Fund programs may stress the importance of efficient and productive government expenditure, and some the need for cutbacks in expenditure, others may provide for sometimes significant increases in government outlays. This is particularly likely to be true of programs that emphasize economic rehabilitation owing to increased domestic or external resources. The structure of this paper will of necessity reflect this duality.

The effect of fiscal policy adjustment on military spending is likely to reflect, in addition to the constraints on the availability of resources, objective and subjective considerations related to security requirements and social preferences, as well as broader and more complex political, strategic, and indirect economic considerations that could pressure governments to maintain allocations to the military sector. For example, a country that is under intense threat at its border and faces, in addition, political instability may find it virtually impossible to reduce military spending and may be forced to cut its budget in other areas.

Section I first reviews overall military spending trends in the developing countries over the past two and a half decades and highlights the uneven distribution of military expenditure among regions and even among countries within a region. It then discusses several inherent problems with data on military outlays that render research in this area particularly difficult.

Section II develops a conceptual framework that will serve as a blueprint for the subsequent empirical study. It emphasizes the choices faced by the authorities in the absence and presence of a Fund-supported program and whether the program constrains or accommodates expenditure. It also reviews objective variables that may affect the level of, and potential for adjustments in. military spending. An empirical methodology is suggested that consists, in particular, in looking at the changes, before and during a Fund-supported program, in military expenditure as a share of gross domestic product (MIL/GDP) and as a share of total expenditure (MIL/EX) for an overall sample and then for two sub-samples of Fund-supported programs, broadly divided according to fiscal tightening and fiscal accommodation.

Under fiscal tightening, the data suggest that countries’ MIL/GDP ratio decreased during Fund-supported programs, but that the MIL/EX ratio increased. The latter finding will be interpreted as evidence that the military expenditure tended to be “resilient” to the budgetary adjustments that needed to be made. For those countries experiencing fiscal accommodation, the evidence indicates that as total government expenditure tended to increase during Fund-supported programs, military expenditure also increased. The data show rather conclusively, however, that a higher proportion of countries also showed declines in the MIL/EX ratio. Hence, in an environment of fiscal accommodation, a smaller proportion of additional resources was allocated to the military sector than to other sectors, in contrast with the results obtained under fiscal tightening.

The latter part of Section II focuses on fiscal tightening and tries to establish links between specific characteristics of countries and their observed military spending, including the resilience of that spending. The main, albeit weak, result that emerges is that if a country has a below-average preprogram level of MIL/EX (or MIL/GDP), its military spending is likely to exhibit resilience. Hence, resilience appears to be inversely related to the objective variables that explain a high initial level of military expenditure. Brief conclusions are drawn in Section III.

I. Military Spending in Developing Countries

Overall trends in, and the distribution of, military expenditures in developing countries are reviewed in this section. Problems with data on military spending are also examined.

Trends in Military Spending

Military spending in developing countries has increased substantially in real terms over the past two and a half decades. Spending surged in the 1960s and then again in the 1970s (Sivard (1987)). Military spending in developing countries during 1960–86 grew on average almost three times as fast as in the industrial countries and quintupled in real terms during the period (Table 1). Developing countries now account for a much larger proportion of worldwide military spending. Their share of such spending in 1986 was almost three times as great as in 1960 (Table 2).

Table 1

Percentage Change in Real Military Expenditures

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Source: Sivard (1987, p. 42).Note: Percentage changes are based on data expressed in 1984 prices and (in general) converted to U.S. dollars using three-year average exchange rates (1982–84).
Table 2.

Military Expenditures in Developing Countries as a Percentage of World Military Expenditure

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Source: Sivard (1987, p. 42).Note: Percentages are based on data expressed in 1984 prices and (in general) converted to U.S. dollars using three-year average exchange rates (1982–84).

It has been suggested that this rise in developing country military expenditures can be explained in part by the increase in external conflicts in developing regions, by the amount of protection necessary for the domestic ruling elites, by the influence of the military in the political realm, and by the increase in the cost and maintenance of weapons systems and the armed forces (Ball (1986)). Also contributing to the explanation is the near tripling of the number of independent states in the developing world since the 1950s. Many of these countries, and especially those in Africa, lacked military establishments at the time of independence. As each new country allocated resources to create its armed forces, military spending for developing countries surged. The decline in industrial countries’ military grants to developing countries that began in the late 1960s could also help to explain this rise in recorded military spending. To the extent that military aid went previously unrecorded in the budgets of recipient countries, the cessation of aid forced these countries not only to finance their own military outlays but also to record more clearly these expenditures in their budgets.

The growth in military spending by developing countries has been distributed unevenly, both across regions and in countries within regions. Table 3 displays regional differences in the growth of military spending.1 The jump in Middle Eastern expenditures in nominal terms during 1970–75 is striking; spending increased by 152 percent, outpacing the average rate of growth in developing country military spending by 112 percentage points. This development was, however, reversed during 1975–80, as the rate of growth of military spending of Middle Eastern countries dropped off sharply to less than 10 percent, or below the average developing country rate of growth in military outlays.

Table 3.

Percentage Change in Real Military Spending by Region, 1965–85

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Source: U.S. Arms Control and Disarmament Agency, ACDA (1988).Note: Percentage changes are based on data in U.S. dollars. Note that for 1965–70 data are in 1973 prices and are converted from local currencies to U.S. dollars using 1973 exchange rates. Data for 1970–75 are in constant 1978 U.S. dollars and are converted from local currencies using 1978 exchange rates. The data for 1975–85 are in constant 1984 prices, converted from local currencies to U.S. dollars based on 1984 exchange rates.

For 1965–70, data are for the Organization of Petroleum Exporting Countries rather than for the Middle East region as a whole.

Even within regions, military spending has not been evenly distributed among countries. Africa is especially characterized by uneven spending patterns across countries. For the continent as a whole, military expenditures increased in real terms by less than 50 percent on average between 1965 and 1980, but military spending rose by some 300 percent in a subset of 14 African countries (Ball (1986)). For several of these countries, earnings from oil exports provided additional resources that were allocated to the military; for others, internal or external threats or conflicts resulted in greater military spending (Ball (1986)).

Data Sources and Problems

The preceding discussion of trends in military spending is based on several sources of military data often criticized for their unreliability and inconsistency. Because we will use these data sources in Section II to analyze how military spending has evolved during Fund-supported adjustment programs, it is appropriate to briefly review some of these criticisms.

Researchers have expressed skepticism about military data because they suspect that national governments have reason to hide the true figures. For example, foreign governments may interpret the news of another country’s increase in military spending as a threat, while the country’s own citizens may protest that government resources should be allocated to social policy programs.2

Practices that have led to discrepancies between actual and reported data include3

  • Double bookkeeping: governments may keep two sets of budget accounts, one for internal purposes, the other for external purposes

  • Extrabudgetary accounts: military spending is funded by sources that are omitted from the national government budgets, as are the outlays they finance

  • Highly aggregated budget categories that include military spending: military-related outlays can be easily hidden in other budget categories and may not be traceable

  • Military assistance: particularly when military budgets are highly aggregated, military aid to and from foreign governments is not necessarily reported in expenditure and financing accounts

  • Foreign exchange manipulation; a portion of foreign exchange that is earned by a country through exporting is not reported in the budget; these funds can then be used to purchase goods, such as military items, that would go unreported.

Researchers have tended to rely on data published by the following organizations: the U.S. Arms Control and Disarmament Agency (ACDA), the Stockholm International Peace Research Institute (SIPRI), the International Institute for Strategic Studies (IISS), and the Fund (in its Government Finance Statistics, GFS). Even though these organizations attempt to be reliable, the data they provide can be only as reliable as those released to them by national governments. One should bear this in mind when assessing the robustness of any empirical results, especially in such a delicate area of government expenditure.

In the analysis in Section II we use three of the four sources of data: ACDA, GFS, and SIPRI. By using various data sets, we are able to verify the sensitivity of qualitative results and judgments on military expenditure to data set variations. Each source tends, however, to define military expenditure in a slightly different way and produces the data in a slightly different format, and one should also keep this in mind when reviewing the empirical results. The Appendix provides detailed descriptions of the various definitions of military expenditure.4

II. Characterizing Military Expenditures During Fund-Supported Programs

Fund-supported stabilization programs in the form of stand-by arrangements or extended Fund facilities primarily focus on achieving medium-term balance of payments viability. To the extent that nonsus-tainable external current account deficits tend to reflect fiscal imbalances, in general they involve reducing the government’s budget deficit, often through expenditure restraint, given limits on the feasibility and desirability of increased taxes.

Even though stabilizing fiscal policy, including expenditure restraint, is central to many Fund-supported adjustment programs, it is not central to all. Particularly when a country has experienced disequilibria for long periods of time, as well as a greatly overvalued exchange rate and the quasi-disappearance of foreign financing, a forced and disorderly adjustment of government expenditures may have occurred long before the Fund’s involvement. In such cases, Fund-supported adjustment programs are likely to emphasize adjusting relative prices, restructuring production, and rehabilitating the administrative and economic infrastructure, which, in addition to promoting domestic activity, will spur new foreign investment from bilateral, multilateral, and private sources. Under such catalytic programs, both government expenditure and the deficit could temporarily rise, reflecting the greater availability of foreign financing and, possibly, additional domestic resources.

If governments must restrain spending to achieve balance of payments objectives, however, there is unlikely to be any obvious economically, socially, and politically optimal way of implementing such a policy. On the one hand, limiting capital, rather than current, expenditure is often expedient but could prove detrimental to long-term growth. On the other hand, some current expenditures may be more ‘‘productive” than many capital projects, particularly if (in the case of maintenance expenditures) curtailment today could contribute to the future deterioration of the economic infrastructure.

The above discussion underscores how difficult it is to evaluate the impact of Fund-supported programs on government military spending. Indeed, evaluating the implications of Fund-supported programs for public expenditure in general is a complicated issue likely to involve a broad range of considerations and particular circumstances. Yet we seek to explore the question one step further; to the extent that Fund-supported adjustment policies affect government spending, how have they influenced military spending? In the following subsection, a formal conceptual framework is developed to guide the subsequent empirical analysis.

A Conceptual Framework

We will assume that, in the short run, the government can be viewed as having a preference ordering between “security,” y1, “other public services,” y2, and “burden on private sector,” occasioned by inflationary finance or crowding out, for which the size of domestic (bank and non-bank) financing, Dd, is a reasonable proxy.5 This preference ordering results in a utility function,

U(y1,y2,Dd),(1)

with the following partial derivatives: U1 > 0, U2 > 0, U3 < 0. An increase in Dd is viewed as bad and. hence, lessens welfare.

A complex interaction of political, economic, and strategic considerations is likely to contribute to the amount a country chooses to spend on the military. All interact with each other at the national, regional, and global levels. These considerations may include such factors as the perceived or actual domestic or external security risk,6 the nature of the political regime (military or quasi-military rule versus civilian government, a repressive versus liberal regime),7 the existence of a local arms industry, the existence and degree of regional conflicts or insecurity, and adherence to a global power bloc. The level of development could also be a significant factor (to the extent that increased per capita wealth may require greater protection from external and domestic threats), as could the degree of urbanization. Indeed, the protection requirements of a country appear to be related directly to the level of infrastructural development associated with large cities. Furthermore, urbanization contributes to a country’s potential for external and domestic conflict, and hence to protection needs, both because it introduces greater complexity in individuals’ interactions and because it renders existing inequalities among socioeconomic groups more transparent and visible.

For the purpose of the model we assume that “security,” y1, will, for any given level of defense expenditure undertaken, x1, be inversely related to the vector of variables,S¯, indicated above. Hence, assuming for simplicity a one-to-one correspondence between “other public services,” y2, as it appears in the utility function (1) and actual expenditure, x2, on such goods, the relationships (2a)–(2c) are postulated:

y1=f(x1(+),S¯,)()(2a)
y2=x2(2b)
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x1+x2=R+Df+Dd.(2c)

Expression (2a) can he viewed as a “production function.” The signs of partial derivatives (indicated in parentheses) imply that, other things being equal, more defense expenditures, x1 yield higher security, y1 For a given level of defense expenditures, however, the security obtained depends negatively on the variables in S¯; that is, on the extent of the security threat, the level of income per head, the degree of urbanization, and so forth (Maizels and Nissanke (1986)). Expression (2c) is the government budget constraint, where revenue, R, and foreign financing, Df are for the moment assumed to be exogenous.

In the absence of a Fund-supported program, the variables x1, x2 and Dd, can be viewed as endogenously determined in that they are objects of policy choice. After y1 and y2 in utility function (1) are replaced by their expressions from equations (2a)–(2b), utility maximization subject to equation (2c) is postulated to yield a set of expenditure functions such as8

x1=x1*(S¯,(+)R+(+)Df)(3a)
x2=x2*(S¯,()R+(+)Df)(3b)

and a domestic financing choice function.

Dd=Dd*(S¯,(+)R+()Df)(3c)

implying, given equation (2c), an aggregate expenditure function

x=x1+x2=R+Df+Dd*(S¯,R+Df).(3d)

Again, the signs of partial derivatives are indicated in parentheses; note, in particular, that higher values of S¯ imply both an increase in military and total expenditure, but a decline in other government spending, and that higher revenue or foreign financing (or both) should lessen the demand for domestic financing. Aggregate government expenditure demand, however, should be positively related to R + Df; that is,

1+Dd*R+df>0.

The government’s expenditure choice in the presence of a Fund-supported program is often affected by the fact that domestic financing Dd (especially, but not exclusively, in the form of domestic bank resources) is no longer a choice variable, but rather exogenously constrained at some binding level D¯d<Dd*. 9 In this case utility maximization, along the lines detailed earlier, yields

x1=x1(S¯(+),R+Df+(+)D¯d)(4a)
x2=x2(S¯(),R+Df+(+)D¯d)(4b)
Dd=D¯d(4c)
x=x1+x2=R+Df+D¯d.(4d)

Note that the system of equations (4a)–(4d) can always be approximated around the unconstrained case, equations (3a)–(3d) to find, in particular,

x1=x1*(S¯,R+Df)x1D¯d[Dd*()D¯d](5a)
x=R+Df+Dd*(S¯,R+Df)[Dd*()D¯d].(5b)

The above rewriting of constrained demand functions in the presence of a Fund-supported program clearly illustrates the link between the two regimes: total expenditure will be reduced by the full difference between Dd* () and D¯d, but the impact of defense expenditure will depend on the size of the partial derivative x1/D¯d, which is a measure of how defense expenditures would share in the adjustment imposed by D¯d<Dd* (). A low value for x1/D¯d would imply resilience in the sense that x1 remains close to its unconstrained level x1* (), and accordingly, that the ratio of military over total expenditure, x1/x, would tend to rise.

The foregoing discussion implicitly assumes that developments in revenue and foreign financing can be viewed as independent of whether a Fund-supported program is in effect. Clearly, they are often not independent. Even as a share of GDP, government revenue could tend to increase systematically under a Fund-supported adjustment program either because of specific revenue mobilization efforts or because of the positive effect that macroeconomic policies pursued in the context of the program could have on government revenue. Perhaps, more important (and as indicated earlier), the availability of foreign financing could be strongly correlated with the implementation of a Fund-supported adjustment program, particularly catalytic programs that stress economic rehabilitation. This concomitance would relieve the constraint on expenditures imposed by D¯d<Dd* () in equations (5a) and (5b) in the sense that R + Df in equations (5) would actually turn out to be larger than in equations (3), and it would allow total and military expenditure to expand: at the limit, the effect of these additional nondomestic financing resources could be dominant.

The conceptual framework described here suggests that both the structure of government expenditure functions and their stability are likely to be critically affected not only by whether an adjustment program is in effect, but also by the nature of this program, particularly its implications for government revenue and external resources. Thus, simple econometric specifications are not likely to perform well, whereas with more complex ones, the limited numher of time-series or cross-section observations becomes a problem. Accordingly, we propose an alternative methodological approach in the next subsection, which nevertheless follows the spirit of the conceptual framework developed here.

One might also add that other characteristics of military expenditures may make them less susceptible to sudden changes, particularly within the sometimes short duration of adjustment programs. Military expenditures involve acquisition of new and relatively expensive weapons systems and technologies as well as the training of new personnel. Both activities may require a long period of implementation. Military supply pipelines, especially when they are in the form of purchases from one of the major national suppliers of arms, are often quite long. Training schedules may be very complex and prolonged, for technical and political reasons. This applies particularly to the more advanced technologies or forms of equipment that are either highly complicated to operate or politically sensitive. Once committed to such expenditures, countries may find it difficult to reverse decisions. Finally, developing countries are often not in a position to dictate either the terms or timing of military purchases. As a result, there is often a mistiming of events (for example, the emergence of a current account deficit and the arrival of a large military package).

In any analysis of resilience, these factors particular to the military sector may need to be considered in understanding the observed results, with the recognition, however, that other nonmilitary outlays are also subject to factors that limit a government’s flexibility for adjustment.

Empirical Methodology

Using the complete sample of countries for which data are available, we first investigate how the share of overall military expenditure in GDP (MIL/GDP) and in total expenditure (MIL/EX) behaved before and during Fund-supported adjustment programs. In terms of the earlier conceptual framework, it amounts to analyzing the behavior of x1 and x1/x as in equations (5a) and (5b) versus equations (3a) and (3d), where the variables x1, x2, Dd, R, and Df must now be interpreted as a share of GDP. As previously indicated, we use three different data sources—ACDA, GFS, and SIPRI—to check for consistency among the different data sources as well as to address the problem of limited country coverage in some sources. We also examine the percentage change in armed forces during Fund-supported programs.10 The results confirm the need to distinguish between cases of fiscal tightening and fiscal accommodation, as anticipated earlier. Fiscal tightening will be defined as coinciding with a decrease of total expenditure as a share of GDP, fiscal accommodation with an increase.

Next, we reconsider in more detail the behavior of MIL/GDP, MIL/EX, and the percentage change in armed forces in each of the two subsamples of Fund-supported programs. As indicated earlier, “resilience” will describe a situation in which, despite budgetary spending restraint, the share of military expenditure in total expenditure, MIL/EX, actually increased during the Fund-supported program. Again, in terms of the conceptual framework introduced earlier, this will occur when the adjustment coefficient x1/D¯d in equation (5a) is sufficiently small, implying that x1/x will tend to rise.

Finally, the discussion will specifically focus on those countries that experienced fiscal tightening during Fund-supported programs to see if resilience can be related to some of the variables, or proxies to them, identified in the formal framework as likely to be key determinants of military spending in the first place. Formally, we investigate whether the size of the adjustment coefficient x1/D¯d in equation (5a) can be systematically related to variables that explain defense expenditures themselves. Thus, we seek to formulate a profile of characteristics that could assist in clarifying the resilience of military expenditure in specific countries. In particular, we try to establish whether, relative to the sample average levels, resilient countries tend (1) to have higher preprogram levels of MIL/GDP and MIL/EX, (2) to have higher per capita GDP, (3) to be more highly urbanized, and (4) to have a larger percentage of the population in the military. The explanatory variable in item 1 could be viewed as synthetic for all others, while the variable in item 4 could be viewed as a proxy to the index of security risk indicated earlier, for which no comprehensive satisfactory time series data could be found (and which, in any case, may not be amenable to objective quantification).

Data Preparation

The first task in preparing the military data for analysis is to determine for which calendar years a country was involved with a Fund-supported program, so that program periods can be established for each country. This is not entirely straightforward because many stand-by arrangements and extended Fund facilities did not coincide with the calendar year, sometimes succeeded one another in the same calendar year, became ineffective, or were canceled at some point in the year. Nevertheless, we have attempted to establish for each country the time periods during which a Fund-supported program was in effect (Table 13 contains a list of the countries and the associated calendar year coverage of programs).11 This approach, however, has an inherent problem: we only recognize as ending those programs that either formally expired or were formally canceled. Yet some programs simply became ineffective, with the result that not all scheduled “purchases” (disbursements or drawings from the Fund) were made. If programs became ineffective because of nonperformance (overperformance) with program targets, which may include fiscal targets, one runs the risk of understating (overstating) the intended impact of the Fund-supported program in these countries.

To identity possible changes in military spending during Fund-supported adjustment programs, we compare data for the period before the program was implemented and the average value of these data for the years during the program for each country.12 The preprogram period has been defined in two different ways: first, as the calendar year before the Fund-supported program was implemented; second, as an average of the three years before the Fund-supported program was implemented. Averaging should smooth out any temporary fluctuations in spending unique to a particular year.13

The above methodology for analyzing the data has some drawbacks and, possibly, distortionary effects.

First, as indicated above, the duration of Fund-supported programs varies greatly across countries. Although a program may become ineffective or be canceled at any time, stand-by arrangements are designed to last from less than one year to over two years, and extended Fund facilities are designed to last three years. Therefore, a cross-country comparison of averages over the so-called Fund-supported program period must be viewed with caution, since for every country a different time period and a different sequence of programs may be involved.

Second, analyzing the data as described above also obscures trends in military spending that might help to explain how military expenditure changes before and during a program period. For example, this methodology obscures whether military spending was increasing for a prolonged period before the implementation of the Fund-supported program. Also, information on trends in overall government expenditure, as well as cycles and trends in GDP, is ignored.

Overall Behavior

To provide an overall picture of how military spending behaved before and during Fund-supported adjustment programs, Table 4 compares data on trends in military spending before and during the program period, as a share of GDP, as a share of total expenditure, and as the percentage change in the size of armed forces. The original sample of countries included all those that had either a stand-by arrangement or an extended Fund facility during 1978–84, regardless of the fiscal policy stance they adopted in the context of the program. In the top panel, preprogram is defined as equal to the calendar year before the Fund-supported program was implemented. In the bottom panel, preprogram is defined as the average of the three years before implementation.

Table 4.

Military Indicators During Fund-Supported Programs: All Countries

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See the Appendix. ACDA, U.S. Arms Control and Disarmament Agency (1988); SIPRI, Stockholm International Peace Research Institute (1986); GFS. the Fund’s Government Finance Statistics Yearbook (1987).

Increase also includes those countries in which there was no change.

In the top panel, the ACDA and GFS data reveal that slightly more countries experienced a decrease in MIL/GDP during their program period than experienced an increase in MIL/GDP. The SIPRI data, however, indicate that more countries experienced an increased or stable than a decreased MIL/GDP. These results are consistent with those displayed in the lower panel of the table under the alternative definition of preprogram period.

The indicator MIL/EX reveals less consistent results with regard to data sources and definition of preprogram period. When the preprogram period is defined as one year, the following results are obtained. The ACDA data suggest that more countries experienced a decrease in MIL/EX than experienced an increased or steady ratio combined. In contrast, the GFS data indicate that as many countries experienced a decline in MIL/EX as experienced increased or steady ratios. Finally, the SIPRI data indicate that more countries experienced an increased or steady ratio than a decrease. When the preprogram period is defined as a three-year average, the results from all three data sources indicate that more countries exhibited a decrease in MIL/EX over the program period than exhibited an increased or a stable ratio.

For the percentage change in armed forces, the results uniformly indicate that more countries exhibited either a constant or increasing rate of change than a decreasing one.

Fiscal Tightening and Fiscal Accommodation

Although the preceding description provides an overview of how military spending in developing countries has evolved in the context of Fund-supported programs, it has not taken account of the diversity of fiscal policy stances among countries with Fund-supported programs. This may explain the very mixed and ambiguous results obtained so far. As suggested in the conceptual framework described earlier, when the rehabilitation and restructuring aspects of the Fund-supported program are overriding and are likely to be accompanied by larger domestic revenue and, especially, external resources, the constraints imposed on government expenditure through the binding constraint on domestic financing are likely to be relaxed and possibly offset. Because changes in overall government expenditure patterns are reflected in military spending, it is natural to examine the data in a way that highlights the different fiscal policy stances of programs. Therefore, we split the sample of countries into those that exhibited what we refer to as fiscal tightening and those that exhibited fiscal accommodation during the program years. As mentioned earlier, fiscal tightening is associated with a decrease in the ratio of total government expenditure to GDP during the program period compared with the preprogram period, whereas fiscal accommodation is associated with an increase.14

On the basis of the above criterion, 26 out of 60 countries for which data on total government expenditure as a share of GDP were available experienced fiscal tightening during their respective Fund-supported programs, whereas 34 experienced fiscal accommodation when the preprogram period is defined as the year before implementation. When the preprogram period is defined as a three-year average, 23 out of the 60 countries experienced fiscal tightening, whereas 37 experienced fiscal accommodation.

Consider first the military spending data for those countries identified as having experienced fiscal tightening. Table 5 describes the military indicators in this environment of overall budget restraint. If the preprogram period is defined as one year, all three data sources indicate that a higher proportion of countries exhibited a decrease in MIL/GDP.

Table 5.

Military Indicators During Fund-Supported Programs: Fiscal Tightening

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See the Appendix and Table 4.

Increase also includes those countries in which there was no change.

When the preprogram period is defined as a three-year average, the ACDA and GFS data confirm these results, whereas the results from the SIPRI data are reversed. In general, when expenditures as a percent of GDP are tightened, military spending appears vulnerable to such tightening as well.

As detailed earlier, in this environment of overall budget restraint, the indicator MIL/EX can be interpreted as reflecting the budget allocation choice the authorities make when a tightening of expenditure is necessary. Military spending reveals resilience, if, in relative terms, it escapes the budgetary cutbacks that affect other categories of expenditures.

To a certain extent, the data confirm this resilience. As noted in the top panel of Table 5, when preprogram is defined as the one year before program implementation, all data sources indicate that a larger proportion of countries exhibited higher or stable MIL/EX. For example, the GFS data indicate that 72 percent of the countries exhibit resilience in military spending, whereas the ACDA and SIPRI data indicate that 57 percent and 67 percent, respectively, of the countries exhibit resilience.

When the preprogram period is defined as a three-year average, these strong results are confirmed by two of the data sources but are contradicted by one. The GFS and SIPRI data indicate that 56 percent and 75 percent, respectively, of countries exhibited resilience in military spending during Fund-supported programs. The ACDA data, however, suggest that a higher percentage of countries, 58 percent, decreased military spending as a share of total expenditure during Fund-supported programs.

The indicator of percentage change in armed forces also lends some support to the notion of resilience. In Table 5, both preprogram definitions indicate that a significantly greater proportion of countries experienced a sustained or an increased rate of growth in their armed forces during Fund-supported programs. This is especially noteworthy given that these countries all experienced fiscal restraint, and a majority also experienced a decrease in the MIL/GDP ratio during the Fund-supported program period.

Data describing military spending for those countries that experienced fiscal accommodation during the program years are displayed in Table 6. As we discussed earlier, these are countries in which total government expenditure as a share of GDP increased during Fund-supported programs. In terms of the conceptual framework described earlier in Section II, the presumption is that higher resources (R + Df) have tended to offset the impact of the constraint on domestic financing, with the result that overall expenditure, and probably military expenditure, could expand. Accordingly, one would expect to see a rise in MIL/GDP; how ever, in terms of the budget allocation choice, there is no reason to expect that MIL/EX will move in any particular direction. Indeed, although military spending as a share of the total may resist the magnitude of expenditure adjustments imposed in other sectors during times of expenditure restraint, when the budget constraint is loosened it is not clear whether military spending as a share of total expenditure would experience a disproportionate increase or decrease.

Table 6.

Military Indicators During Fund-Supported Programs: Fiscal Accommodation

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See the Appendix and Table 4.

Increase also includes those countries in which there was no change.

The results for countries displaying fiscal accommodation during the Fund-supported program are consistent across the two definitions of the preprogram period. For the indicator MIL/GDP, all three data sources confirm that a larger proportion of countries displayed an increasing or stable ratio during Fund-supported programs.

In terms of the budget allocation choice regarding military spending that is made by the authorities in these countries, the data show conclusively that, in a higher proportion of countries, the MIL/EX ratio declined during Fund-supported programs. This suggests that, in an environment of fiscal accommodation, fewer additional resources are allocated to the military sector than to other sectors. This is in direct contrast to the evidence derived from those countries that have experienced fiscal tightening. Hence, when budgets are tightened, military spending as a share of total expenditure for a majority of countries is protected relative to other sectors. However, when additional resources become available, the military sector does not benefit more than other sectors. One possible explanation for this relates to the nature of additional resources obtained under fiscal accommodation; to the extent that they consist of project- or expenditure-tied external assistance, the expenditures that they finance are not, in general, military in nature. Admittedly, some amendments would need to be introduced to the conceptual framework detailed earlier to reflect this nonfungibility of resources.

The percentage change in armed forces during Fund-supported programs for this group of countries also shows that a higher proportion of countries experience an increase in, or stable rates of, growth. As mentioned above, this result also occurs for those countries characterized as experiencing fiscal tightening; for the group of countries considered here, however, the behavior is consistent with the observation that military expenditure in general increases as a percentage of GDP.

To summarize the major findings of this section, we observe that a majority of countries exhibit an increase in MIL/EX and a decrease in MIL/GDP during periods of fiscal restraint, and a decrease in MIL/EX and an increase in MIL/GDP during periods of fiscal accommodation.

Focus on Fiscal Tightening

So far, we have discussed the diverse patterns of military spending among Fund-supported program countries without focusing on specific explanatory variables, except to emphasize the importance of the fiscal policy stance adopted under the program. The following set of exercises attempts to establish links between specific characteristics of countries and their observed military spending, concentrating on those countries that have experienced fiscal tightening during Fund-supported program years.

As indicated earlier in Section II, several variables can explain why one country is likely to spend relatively more than another on defense as measured, for instance, by MIL/GDP and MIL/EX. These same variables could play a role in determining why countries react differently to adjusting their military expenditures under Fund-supported programs and, in particular, why some countries display greater resilience. Not all these variables can easily be quantified. Even for those that can be quantified, data are not always readily available (as in the case of the security risk index referred to earlier). Accordingly, a first exercise consists in establishing whether countries that display above-average shares of MIL/EX before a Fund-supported program, compared with the sample mean for all countries, tend to exhibit resilience or, on the contrary, greater flexibility when expenditure constraints become more effective in the context of Fund-supported programs. With reference to the formal framework earlier in the section, this exercise may be viewed as testing whether the size of the adjustment coefficient x1()/D¯d is negatively or positively related to the set of variables, S¯, that tends in general to explain higher military spending.15

Turning to the empirical evidence, we calculate the average preprogram value of MIL/EX over the entire sample of countries for each of three data sources using both preprogram definitions. We then compute the preprogram year MIL/EX for each country in which fiscal restraint occurred during the Fund-supported program and rank the countries according to whether they are above or below the sample average. Subsequently, we look at how many countries in each group exhibited resilience during a Fund-supported program in the sense that MIL/EX increased.

The results of this exercise, reported in Table 7, are somewhat ambiguous, varying over preprogram period definition as well as data sources. Where the preprogram level of MIL/EX is greater than the sample average for all countries, the results indicate that during Fund-supported programs almost an equal number of countries exhibited increases in this ratio—that is, resilience—as exhibited decreases. (When the preprogram period is defined as a three-year average, slightly more countries experienced an increase in MIL/EX during the Fund-supported program.)

For the countries in which the relative preprogram level of MIL/EX is below the sample average, the results of this exercise are somewhat more informative. When the preprogram period is equal to one year, all data sources indicate that a majority of countries experience an increase in MIL/EX—that is, resilience. When the preprogram period is equal to an average of three years, however, only the SIPRI data confirm this result. The ACDA data suggest that more countries exhibit a decrease, whereas the GFS data are split evenly between increases and decreases in MIL/EX.

Table 7.

Relationship Between Preprogram Level of MIL/EX Relative to Sample Average and Behavior of MIL/EX During Fund-Supported Programs

(with Fiscal Restraint)

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Source: See the Appendix.

The result that emerges, albeit weak, is that if a country has a below-average level of MIL/EX during the preprogram period, its military spending is likely to exhibit resilience. We also explored how the behavior of MIL/EX during Fund-supported programs relates to the preprogram level of MIL/GDP relative to the sample average. The results are quite similar to those presented above and are displayed in Table 8.

A Closer Look at Resilience

On the basis of the results in the previous subsection, we were able to conclude tentatively that countries with below-average preprogram MIL/EX or MIL/GDP relative to other countries are likely to exhibit resilience during a period of fiscal tightening. In this subsection, we further quantify that relationship and analyze whether the country-specific characteristics that would explain lower or higher military expenditure could also, individually, explain greater or lesser resilience.

Tables 9, 10 and 11, 12 list those countries that have exhibited resilience in military spending during Fund-supported programs, with the preprogram period defined as one year and a three-year average, respectively.16 Again, in line with our discussion on the determinants of military spending and given the availability of data, the following limited sample of preprogram variables is considered for each country exhibiting resilience in military spending and is compared with the sample average for all countries: armed forces as a percentage of total population, urban population as a percentage of total, and per capita GNP. For the reasons already indicated, military expenditure is expected to be positively related to each one of these variables.

In Tables 9 and 11, columns 1 and 2 report values of MIL/EX before and during program periods for each country. They quantify the extent to which MIL/EX has actually increased and therefore how resilient is military spending in each of these countries actually. MIL/EX and MIL/GDP relative to (that is, as a ratio of) sample averages in columns 3 and 4 reveal what was previously suggested about the relationship between resilience and each of these variables. In Table 9 (where the preprogram period equals one year), the pooling of the three data sources yields 38 observations. Of the 38 observations. 25 indicate values of MIL/EX below the respective sample average, whereas 13 are above. In Table 11 (where the preprogram period equals a three-year average), the pooling of data sources yields 29 observations. Of the 29, 18 indicate a value of MIL/EX below average, whereas 11 are above. With regard to MIL/GDP, in Table 9, pooling the three data sources yields 36 observations, of which 23 are below their respective sample average and 13 are above. In Table 11, pooling the three data sources yields 29 observations, of which 19 are below their sample average and only 10 are above. These results seem to confirm that countries exhibiting resilience are dominated by below-average MIL/EX and MIL/GDP before a Fund-supported program.

Table 8.

Relationship Between Preprogram Level of MIL/GDP Relative to Sample Average and Behavior of MIL/EX During Fund-Supported Programs

(with Fiscal Restraint)

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Source: See the Appendix.
Table 9.

Resilient Countries: Preprogram Levels Relative to Sample Average, Preprogram Period of One Year

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Source: For MIL/EX and MIL/GDP, see the Appendix.
Table 10.

Resilient Countries: Preprogram Levels Relative to Sample Average, Demographic Factors, Preprogram Period of One Year

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Sources: For armed forces as percentage of total population, see the Appendix. Data on urban population as a percentage of total population and on GNP per capita are from the World Bank ((1983–84) and (1980), respectively); both of these variables are for 1978 rather than the preprogram period as defined elsewhere.

As displayed in Table 10 for armed forces as a percentage of population, 12 of the 17 available observations for resilient countries are below the sample average. This result is confirmed in Table 12; of the 14 observations there. 10 are below the average. The data support the claim that countries with resilient military expenditure are characterized as having a below-average level of armed forces as a percentage of the total population.

Table 11.

Resilient Countries: Preprogram Levels Relative to Sample Average, Preprogram Period of Three Years

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Source: For MIL/EX and MIL/GDP, see the Appendix.
Table 12.

Resilient Countries: Preprogram Levels Relative to Sample Average, Demographic Factors, Preprogram Period of Three Years

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Sources: For armed forces as percentage of total population, see the Appendix. Data on urban population as a percentage of total population and on GNP per capita are from World Bank ((1983–84) and (1980), respectively); both of these variables are for 1978 rather than the preprogram period as defined elsewhere.

The other variables—urban population as a percentage of total population and GNP per capita—yield notably mixed results. For both variables, approximately half of the available observations lie above the sample average and half below, irrespective of the definition of preprogram period.

III. Concluding Remarks

The strongest results of this study relate to the evidence that military spending in developing countries has tended to exhibit resilience during adjustment programs that have emphasized fiscal tightening, particularly in cases where the preprogram levels of expenditure were below average. In adjustment programs that were accompanied by fiscal accommodation, the evidence suggests that the nonmilitary sector tends to be given priority in the allocation of additional resources. Both the scarcity and uncertain quality of data, however, mean that the above conclusions must be interpreted with great caution. To go beyond the broad conclusions reached in this paper, specific country studies would need to be undertaken. Such case studies might consider data on disaggregated expenditures and foreign financing and take into account the particular domestic and external political and strategic environment faced by these countries.

APPENDIX

Data Sources and Program Coverage

This Appendix identifies the data sources used and the extent of Fund program coverage.

Military Expenditure Data

In Section II of this study, we used three sources of military expenditure data:17

  • U.S. Arms Control and Disarmament Agency, ACDA (1988)

  • Stockholm International Peace Research Institute, SIPRI (1986)

  • International Monetary Fund. Government Finance Statistics Yearbook, (GFS; 1987).

Each source uses a different definition of military expenditure; therefore the data are not directly comparable. ACDA and SIPRI definitions of military expenditure are different but both in large part are based on the North Atlantic Treaty Organization (NATO) definition (see ACDA (1986, p. 156)):

  • Civilian-type expenditures of each NATO defense ministry are excluded, and military-type expenditures of other ministries are included.

  • Grant military assistance is included in the expenditures of the donor country.

  • Purchases of military equipment for credit are included at the time the debt is incurred, and not at the time of payment.

For countries not belonging to NATO, the ACDA data are based on the expenditure of each country’s ministry of defense. If these data include expenditures on internal security, then an attempt is made to eliminate these expenditures. Ministry of defense data, however, could also include expenditures on flood control, space research, civil defense, stockpiling of industrial materials, pensions, and medical services. The SIPRI data for non-NATO countries do not include any adjustments for the discrepancy in the definitions, as do the ACDA data.

The Fund’s (GFS) definition of military expenditure is detailed but based on the NATO definition as well. Member countries are asked to calculate their defense outlays using Fund categories as a guideline. The Fund data are considered to be the most reliable and are often used by ACDA and SIPRI as a basis for estimates.

Other Data

Gross domestic product (GDP) data were taken from the Fund’s GFS (1986). Data for the armed forces as a percentage of total population were taken from ACDA (1988).

Fund Program Coverage

Coverage of Fund programs, including stand-by arrangements and extended Fund facilities, is indicated in Table 13 for selected developing countries during calendar years 1978–84.

Table 13.

Fund Program Coverage in Selected Developing Countries, 1978–84

(Calendar years)

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Note: Fund programs include stand-by arrangements and extended facilities.

REFERENCES and FURTHER READING

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*

Ms. De Masi is a doctoral candidate at Harvard University and was an intern in the Fiscal Affairs Department during the summer of 1987. Mr. Lorie is a Senior Economist in the Government Expenditure Analysis Division of the Fiscal Affairs Department. He is a graduate of the University of Louvain (Belgium) and Northwestern University.

1

The figures for world average percentage change in real military spending given in Table 3 differ somewhat from those reported in Table 1 because of different data sources.

2

For an extensive discussion of why countries would have an incentive to manipulate their military spending figures, see Brzoska (1981).

3

See Ball (1984a) for detailed insight into the problems that plague data on military spending.

4

The ACDA and SIPRI collect data from the individual country’s defense ministry and are therefore unable to impose any cross-country consistency on how military expenditure is defined. GFS data are based on a standardized reporting format to which all countries are supposed to adhere. Other explanations for the differences among these data sources are related to timing procedures (whether the data are recorded on the basis of fiscal or calendar year), deflation methods, and currency conversion methods. These are fully described, for instance, in Brzoska (1981).

5

Foreign financing is assumed to be determined for the most part exogenously and, hence, is not a direct object of choice for the government (it does not mean, however, that foreign financing is independent of the macroeconomic policies pursued by the government). That assumption appears reasonable for many developing countries. Nevertheless, for those with easier access to international financial markets, external debt strategy may be a genuine choice. In this case, foreign financing Df, in addition to Dd, could enter the utility function (1) with a negative sign, to reflect the burden of the external debt (particularly on future generations).

6

See Lebovic and Ishaq’s efforts to develop a “security needs index” (Lebovic and Ishaq (1987)).

7

Some empirical studies have, however, questioned whether the political regime per se exerts a definite influence on military spending. See Tannahill (1975), McKinlay and Cohan (1975), and Maizels and Nissanke (1986).

8

A specific example that yields demand functions with the properties postulated below can be worked out using the following functional forms for U() and f(): U=y1αy2β(HDd)γ;

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f={max[0,(x1S¯)]}θ
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where α, β, γ, and θ are elasticity parameters, H is a constant, and S¯
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is here taken to be a scaler variable. Note that the production function f embodies the notion that given a positive S¯
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, a “core” amount of defense expenditures are needed to produce a minimum level of security.

9

There is relatively good evidence that Fund-supported programs tend systematically to reduce domestic financing of the government deficit, even if one compares behavior before versus during a Fund-supported program; see, for instance, Kelly (1982). The relevant question is, however, what would have happened. Observations that indicate an increase in domestic financing under a Fund-supported program could nevertheless reflect a constrained behavior in the sense of equations (4a)–(4d).

10

Ideally, we would like to investigate how fiscal policy changes during Fund-supported programs translated into changes in several disaggregated variables, such as the level and structure of wages and salaries, in addition to the number of military personnel, purchases of locally produced versus imported military equipment, pure consumption outlays versus durable goods expenditure, and so forth. Unfortunately, the lack of disaggregated data on military spending in developing countries precludes such a detailed analysis and has forced us to adopt an aggregate view.

11

There is necessarily some arbitrariness in establishing the calendar years of program coverage. The following “rules” were followed: (1) if a program became effective in a month after July, consider it as belonging to the next calendar year; (2) if a program (one year) is split evenly over two calendar years, consider it as belonging to the first year; (3) if a program (one year) is split over two calendar years, consider it as belonging to the year in which it existed for the longest time; (4) if a program extended for more than a year, consider it as belonging to the next calendar year as well only if it extended more than five months into the second year; (5) if we know that a program was formally canceled, then we acknowledge this.

12

As suggested by the data in Table 13, for most countries it is rather easy to define a specific and rather continuous period of involvement with Fund-supported programs.

13

For example, in financing major pieces of military equipment, funds may be appropriated and spent in a single year.

14

Fiscal tightening or accommodation was determined on the basis of the GFS data, when available, for total expenditure as a share of GDP, and on the basis of ACDA data for total expenditure as a share of gross national product (GNP) when GFS data were not available.

15

Before focusing on the statistical analysis, and referring now to the specific example in footnote 8 above, we note that x1()/D¯d

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would in that example be a constant independent of the variable S¯d
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as long as the parameter θ itself is a constant. However, should θ increase with S¯
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, x1()/D¯d
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would be positively related to the variable S¯
article image
. This means that the likelihood of resiliency would be inversely related to S¯
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, and thus to the level of military expenditure prevailing before the Fund-supported program, since equations (5a) and (5b) suggest that the smaller is x1()/D¯d
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the closer would x1 be to its unconstrained level.

16

Because of the scarcity of data, all countries that exhibited resilience on the basis of any data source were included in this subsample.

17

For an excellent survey and evaluation of military expenditure data and issues, see Ball (1984b).