Domestic and international violence : A forecasting approach

Domestic and International Violtmce

DOMESTIC

477

AND

INTERNATIONAL

VIOLENCE

:

A forecasting approach Herman

M. Weil

This article is directed at the need for the development of forecasting techniques for non-environmental issues, especially political and military concerns. It describes a major research project in this area completed by Dr Weil and his colleagues at Consolidated Analysis Centers, Inc. The article defines the concepts and operational measures forecast, describes the development of a regression-based forecasting model and simulation experiments performed on that model, and presents selected long-range forecasts of significant political, economic, military, and social variables for the European region.

IN a recent issue of this publication Yehezkel Dror lamented that futures studies are too often directed towards environmental concerns to the exclusion of other important issues, particularly poIitic~-military matters1 He suggested several possible reasons for this deficiency. These include a rejection of war and violence as a legitimate study subject, a desire to engage in wishful thinking on the part of futurists, a faith in the adaptability of man to the nuclear age, and a desire to avoid controversial and divisive subjects in futures studies. Unfortunately, these positions may actually enhance the likelihood of war and other forms of violence. Avoiding these issues means failing to understand, and perhaps control, forces that can destroy the human species. As Dror notes, The main social functions of futures studies include awareness of critical problems and help in their handling through anticipatory recognition, analysis, and prescription. To fuIf3 this social mission, futures studies must devote much more high quality attention to the hard issues of war and violence.2

Of course, these efforts will be of interest to any “military-industrial complex”, and might be used in a rather counter-productive manner. But ensuring that Dr Weil is with Consolidated Analysis Centers, Inc, 1815 North Fort Myer Drive, Arlington, Virginia 22209. This article was developed from work pursued in collaboration with Dr G. Robert France and others.

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military and political leaders can avoid war and other forms of violence requires knowledge about the causes of violence and about the likelihood of future violence. Finally, some would argue that the prevention of violence also inhibits needed social change and preserves an undesirable social order. We would suggest, however, that preventing violence forces the search for less destructive avenues of social change. A case study We report here on an effort to forecast systematically a series of political, economic, military, and social variables that bear upon the likelihood of war or domestic violence.3 The research performed was intended to assist in creative and wide-ranging long-range planning. The regional focus of this study is Europe. On the basis of relevance to planners and the regional context, five broad concepts were selected for analysis: national power base o domestic unrest l dyadic trade 0 international alignment l international conflict. l

National power base refers to the resources at a nation’s disposal for use in influencing other nations. This concept was divided into two sub-concepts, economic power base and military power base. Economic power base was measured by gross national product, population, energy consumption, and GNP per capita while military power base was measured by defence spending, military manpower, and defence expenditures per man. Similarly, domestic unrest was divided into two sub-concepts, turmoil and revolt, reflecting internal disturbances of fundamentally different intensities.4 Domestic unrest was measdemonstrations, armed attacks ured by reports of riots, anti-government against public institutions, and deaths associated with those events, Dyadic trade simply refers to the value of goods and services moving between nations included in the study. We differentiated between international alignment patterns and formal alliances among nations. Alignments are neither as permanent nor as global as alliances, but refer to the tendency of nations to behave in similar ways towards specified objects over specified issues. 5 Consistent with our European focus, we regard alignments with the USA and the USSR as most significant for understanding the future political-military context of the region. Rather than employing a one-dimensional alignment scheme, however, two alignment variables were developed. The first, ALIGN&, taps the tendency of nations to align with one or both major powers while the second, ALIGN@, divides that tendency between the USA and USSR. Thus, strongly pro-Soviet nations like East Germany can be differentiated from strongly pro-US nations like West Germany on the basis of their ALIGN0 scores. Then, the ALIGNR scores allow multi-aligned countries like Finland and Yugoslavia to be distinguished from essentially non-aligned nations like Switzerland.6 These alignment concepts were measured by UN voting patterns and mutual security pacts.

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Finally, international conflict refers to the patterns of hostile verbal and physical behaviour among the nations included in the study. Conflict was measured by reports of interactions between countries drawn from the World Event/Interaction Survey (WEIS).’ Table 1 shows how each of the five major concepts was divided into sub-concepts and variables that were actually forecast in this effort. TABLE

1. COi’lCEPTS

FOR THE

EUROPEAN

MODEL

Major concepts

Sub-concepts

Forecast

National

Economic

GNP Population Energy consumption

power base

Military

Domestic

unrest

power base (EPB)

power base (MPB)

Defence expenditures (DEFEX) Military manpower (MANPOW)

Turmoil

Riots and anti-government demonstrations

Revolt

Armed

Trade

Dyadic trade flows

Imports

International alignment

Extent of alignment Distribution of alignment

ALIGNR ALIGN0

Monadic conflict Dyadic conflict

Negative Directed

International

conflict

Table 2 shows how the forecast tional measures of the sub-concepts. focus on the sub-concept level. TABLE

2 OPERATIONAL

Sub-concept i)

MPB (Country

i)

attacks and deaths of i from j

WEIS events negative WEIS events

variables were combined to construct operaThe forecast results presented in this paper

MEASUREMENT

Operational

EPB (Country

variables

OF SUB-CONCEPTS

measurement

C MANPOWt

)I

DEFEXi x MANPUWi

Turmoil

[log (RIOTS

Revolt

[log (ARMED

ATTACKS

ALIGN/?

1/(ALlGN,,)’

+ (ALIGNs7J2

ALIGN0

ALIGNJALIGNR

+ DEMOS + I)] + I)]

x [log (DEATHS

+ IO)]

Dyadic trade

Conflict where: Xij = Scale score of jth event nation, and Frj = frequency of jth event nation

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December 1974

involving

the ith

involving

the

ith

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The forecasting

Violence

model

The forecasting model developed in this effort was based upon three sets of theoretical frameworks: substantive social science theory, statistical theory, and cybernetic theory. The assumptions of the model, or the relationships among variables within it, were subjected to validation against each of these three sets of theoretical frameworks. The result was a set of 12 equations that describe the relationships among forecast variables over time and relate those variables to exogenous predictors. Economic, demographic, sociological, and political science theory were used to establish the structure of the forecasting model and to identify the structure of the 12 equations stating relationships among the variables being forecast. Then, regression techniques were used to estimate the exact nature and strength of those relationships from actual data for the European nations from 1950 to 1970. In that process, estimates were developed of the degree to which the model produced accurate predictions for the 1950-1970 period. The model was about 95% accurate for the power base variables and international trade variable, about 80% accurate for the international alignment variables, and approximately 60% accurate for the domestic unrest and international conflict variables. Finally, a computer simulation of the forecasting model was developed to aid in isolating and removing destabilising feedback loops from the model. Given the goals of this effort, destabilising feedbacks have at least two major disadvantages. First, they tend to produce wildly unrealistic forecasts which are implausible from a planner’s standpoint. Second, and probably more important, a forecast must suggest some means of controlling the environment and minimising undesirable developments. In this respect, feedback controls enhance the usefulness of a forecast for making public policy. An important goal of forecasting, after all, is to illustrate to policy makers that actions taken today can have important effects in the long-range future. The simulation allows assessment of the implications of alternative model structures and alternative estimates of model parameters in terms of resulting forecasts. When policies can be represented in terms of model structure and model parameters, planners can quickly and easily ascertain the long-range effects of different actions. The assumptions upon which the forecasts are based can be summarised as follows : 1. A nation’s power base can be viewed as having two dimensions: economic and military. The economic dimension, measured by population, GNP, and energy consumption, is largely self-contained; economic variables are, by and large, influenced by other economic variables. Defence spending, however, contributes to growth in GNP while domestic unrest inhibits economic growth. The military dimension is much more sensitive to the international conditions a nation experiences; both defence spending and military manpower are affected by international conflict. In addition, a nation’s military establishment responds to domestic conditions; both measures ofmilitary power base respond to changes in the level of income, or GNP, and to changes in domestic unrest. 2. A nation’s international trade is best viewed as a component of its general level of economic activity. Large and wealthy countries are consistently the FUTURES

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world’s most extensive traders. As levels of GNP increase, also increases.

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trade

3. International alignment patterns are rather stable and persistent over time. Nations’ levels of wealth and their patterns of international trade affect their alignments with the major powers. Finally, nations with large military establishments tend to be most strongly aligned with the major powers. 4. In contrast to alignment patterns, domestic unrest is heavily influenced by peculiar situations and personalities. Nonetheless, there are some rather potent determinants of the potential for unrest within nations. International trade and strong international alignments both reduce the potential for unrest within nations. As nations become more closely tied economically and politically, they tend to reinforce the legitimacy of one another’s governments. Moreover, as nations’ military establishments increase in size and sophistication, their ability to suppress domestic unrest is enhanced. Domestic unrest decreases when suppression capabilities are very high. High levels of international conflict, especially persisting over time, contribute to strife within nations. Unrest within countries is in part a reaction to the strains created by continued high levels of conflict between nations. Finally, patterns of behaviour within nations are, to a limited extent, consistent over time. Some nations typically experience unrest during times of strain while others resolve difficulties by more formal means. Knowledge about the past patterns of behaviour in a country and expected future conditions within that country can be used to forecast effectively the potential for unrest. 5. Finally, international conflict, like domestic unrest, depends in part upon unique situations and personalities. The potential for high levels of international conflict, however, is affected by other international and domestic processes. Nations that are large and wealthy and that traditionally have been active in international politics have the greatest potential for conflict. However, as the size and sophistication of those nations’ military establishments increase, they exhibit restraint in their international interactions, and the intensity of their conflict experiences decreases. The potential for destruction acts as a moderating force in international affairs. These assumptions form the heart of the 12-equation forecasting model which was simulated on a year-by-year basis from 1971-1990. Actual data for 1970 were used to start the simulation, which produced year-by-year values for each of the variables in the model based on the previous year’s values or the present year’s values for each predictor variable. 8 Thus, the “bootstrapping” process continued for 25 iterations to produce forecasts for 1971-1990. Thus the forecasting model was initially a set of 12 non-recursive equations with parameters estimated by a standard technique. A computer simulation of the equations was then iterated through 25 cycles to produce a set of forecasts. These results were then analysed for destabilising loops and, where appropriate, equation structures and parameters were adjusted. This experimental process continued until the final model had the desired feedback qualities. The specifications of that final model are essentially summarised in the five sets of assumptions above.

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Two general points should be made about the model as finally specified. First, as a process model it neither explicitly predicts nor takes account of the impact of major events, such as the oil crisis, a potential food crisis, or a major nuclear war. In no way, then, can the model be considered a “crystal ball”. Nonetheless, it can provide useful information about the configuration of our future environment and, at a minimum, a baseline of expectations against which to assess the impact of significant events. Second, the variables within the model are used to predict one another on the basis of a fixed set of relationships among them. Clearly, value changes, such as a renunciation of armaments on the part of the world’s nations, will alter those relationships. In most cases, we argue that major value shifts are unlikely and, in any event, unpredictable. Moreover, as is the case with major events, the effects of value changes can only be assessed by comparing them with expectations generated in their absence. Thus, the model might prove peripherally useful for examining the effects of cultural and value changes precisely because it does not explicitly include them. Some long-range

forecasts

In this section we present selected long-range forecasts for the political and military environment of Europe. For brevity, these forecasts are presented for three groups of nations-NATO members, Warsaw Pact members, and nonmembers of either alliance. Table 3 shows economic and military power base forecasts for 1985, 1990, and 1995. It should be kept in mind that the USA and Canada are excluded from the mean NATO scores; the gap between Warsaw Pact and NATO scores, then, reflects the inclusion of the USSR in the former and the exclusion of the USA from the latter. And although in absolute terms this gap grows larger between 1985 and 1995 for both economic and military power base, in relative terms NATO countries’ economic and military power bases grow faster. During the IO-year period Warsaw Pact countries’ mean economic power base TABLE 3. MEAN POWER 1985 Warsaw Pact NATO Non-members

342 142 63

BASE FORECASTS’

Economic 1990 1995 401 178 83

% 92

1995 Y’kYY

1995

1355 435 147

1924 810 300

1563 587 204

grows at an annual rate of 4.3% while that of NATO nations grows at an annual rate of 6.0%. The difference in growth in military power is even more striking; a 4.2% annual rate for Warsaw Pact countries and a lO*Oo/0rate for NATO nations. Of course, American leaders have argued for some time that European NATO members have not accepted responsibility for common defence commensurate with their increasing economic capabilities, and must begin to compensate during the next 20 years. Our results suggest that they will. Table 4 shows domestic unrest (TURMOIL + REVOLT) forecasts for 1985, 1990, and 1995. Domestic unrest is forecast to decrease for all three

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groups during the lo-year-period, primarily because of better economic conditions and greater suppressive capabilities by the regimes in power. TABLE 4. MEAN DOMESTIC

Warsaw Pact NATO Non-members

UNREST

1985 0.67 0.61 0.51

1990 0.58 0.40 o-43

FORECASTSI“ 1995 0.39 0.32 0.28

On an annual basis, moreover, the percentage decrease is nearly equal for all three alliance groups. We might note that much of the domestic unrest within NATO nations is expected to be concentrated in Turkey, Greece, and Portugal, and that these nations are expected to shift their alignment patterns. Excluding these three countries, the internal strife scores for the NATO nations are much lower and decrease at a faster rate. By and large, nations that have historically traded very heavily and that are forecast to have large economic power bases are forecast to have high levels of trade. The UK retains its leadership in international trade and among the European countries, depending on imports for most raw materials and foodstuffs and on exports for balance of trade. Other large members of the European Community-France, West Germany, and Belgium-also trade extensively. Generally, the smaller and poorer nations are forecast to have the lowest levels of trade. Bulgaria, Romania, Greece, and Turkey have among the lowest levels, and Iceland, the smallest of the European nations examined here, consistently ranks last in trade. Forecasts of international alignment patterns show some of the more interesting, but least surprising, changes from the present environmental configuration. By 1995, the presently bipolar European political milieu is forecast to be composed of four clusters of nations. The first, including the UK, France, West Germany, and Italy is very strongly aligned with the USA. A second cluster shows much weaker, yet distinct, ties to the USA. This group is composed of Iceland, the Netherlands, Belgium, Luxembourg, Ireland, Norway, Switzerland, Denmark, and Sweden. A third group of countries, Czechoslovakia, East Germany, Poland, Romania, Hungary, and Bulgaria, is expected to remain primarily aligned with the USSR, but the strength of their political ties to the USSR is forecast to diminish significantly. The most significant changes in alignment patterns, however, are found in the fourth group, the multi-aligned countries. By 1995, no nation can be considered truly non-aligned and fully seven countries are forecast to evidence moderately strong ties to both the USA and the USSR. These include Yugoslavia and Finland, two nations already multi-aligned, and Spain, Turkey, Greece, Austria, and Portugal. Three of these nations, Greece, Turkey, and Portugal, are presently NATO members. Perhaps the most significant of the variables forecast here is international conflict. Generally speaking, international tension in Europe is expected to reach its low point in the early to mid-1970s. From then until the early 1990s tension is forecast to climb steadily, reaching a peak in the mid-1990s. As expected, alliance group non-members are forecast to engage in the least

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amount of conflict. Of the two alliance groups, the Warsaw Pact nations are expected to experience the most extensive international conflict. Of conflict emanating from the Warsaw Pact nations, most is forecast to be directed at the NATO countries; but between 1985 and 1995, an increasing share is forecast to be directed at alliance group non-members and indeed at other Warsaw Pact nations. Conflict from NATO nations to Warsaw Pact countries and alliance group non-members remains relatively constant during that lo-year period, while intra-NATO conflict increases substantially. Of the NATO countries, the largest and most powerful, West Germany, the UK, and France, are expected to be the highest conflictors. Conclusion We have reported on an effort to develop systematic and credible forecasting techniques for important economic, political, social, and military variables. We have not, of course, tried to forecast all such variables, and perhaps not even the most important of them, but merely to select subjects for examination that are of broad interest within the forecasting, planning, and policy-making communities. It is our hope that by openly reporting these results this perception can be countered, and that those results might become available and useful to all who promote peaceful goals. As Dror noted, an understanding of war and other forms of violence is crucial to the survival of mankind, and should come under the purview of serious futurists as well as other researchers. Our effort here is a step in that direction.

References 1. Yehezkel Dror, “War, Violence and Futures Studies”, Futures, Vol 6, No 1, February 1974, pages 2-3 2. Ibid, page 3 3. This is part of a larger study entitled “Quantitative Methods for Long-Range sponsored by the Advanced Research Projects Environmental Forecasting,” Agency of the US Department of Defense, Contract No DAHC15-7 l-C-0201, Modification Nos PO001 1 and POO013. The views expressed here are solely those of the author and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the Advanced Research Projects Agency or any other agency of the US Government. 4. A number of theorists have used the terms turmoil and revolt, or very similar terms to differentiate domestic unrest by intensity. See, eg, Ted Robert Gurr, Why Men Rebel (Princeton, NJ, Princeton University Press, 1970) and R. J. Rummel, “Dimensions of Conflict Behavior Within Nations, 1946-59,” Journal of ConJict Resolution, Vol 10, 1966. Unfortunately, these theorists are not as consistent in their distinctions at the operational level as they are at the conceptual level so that our choice of measures for turmoil and revolt can be viewed as rather arbitrary. 5. See John D. Sullivan, “The Dimensions of United States Alignments in the Third World”, paper presented at the International Studies Association meetings, Pittsburgh, Pennsylvania, April 1970 6. Imagine a two-dimensional space on which one dimension represents alignment

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with the USA and the other alignment with the USSR. Any given nation, X, can be located on the space by measures on these two dimensions. Then, the length of the vector originating at the origin of the space and ending at X’s coordinates measures the tendency to align with these powers, ALIGN& while the cosine of the angle of that vector, ALIGNS, measures the distribution of that tendency between the USA and the USSR. 7. For a more detailed description of the conceptualisation and measurement of these economic, political, and military variables, and the development of the forecasting model, see Quantitative Methods for Long-Range Environmental Forecasting, Interim Technical Report No 4 (CACI, Inc, 1974), Chapters 2-6 8. The forecast simulation generated here is of the same form as that developed by Milstein and Mitchell for the Vietnam war. See Jeffrey S. Milstein and “Dynamics of the Vietnam Conflict: A Quantitative William C. Mitchell, Analysis and Predictive Computer Simulation,” in Walter Isard, ed, Vietnam: Issues and Alternatives (Cambridge, Mass, Schenkman Publishing Company, 1969) 9. The economic power base index is computed according to the formula, EPB

= (%GNP

while the military MPB

+ %POP

+ %ENCON)/3

power base formula

= (%DEFEX

x GNP/POP,

is

+ %MANPOW)

12 x DEFEX/MANPOW.

To compute economic and military power base, then, a nation’s percentage shares of the region’s GNP, population, energy consumption, and so forth are averaged and multiplied by GNP/POP or DEFEX/MANPOW respectively. 10. The actual numbers shown here do not correspond to any observable real-world phenomena, but rather are weighted indices of domestic strife events. Thus, they should be interpreted comparatively, eg, Warsaw Pact nations are expected to experience more domestic unrest than NATO countries.

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