Thursday, July 26, 2007
How Strong is the Connection between Foreign Influence and Military Coups d'Etat in Africa? A Meta Analysis
Abdul Karim Bangura
Abstract
Employing a meta-analytical approach, this essay examines the connection between foreign influence and military intervention in Africa through coups d’état. Accordingly, the study begins with a look at the major differences and similarities between studies—both qualitative and quantitative—which are relevant in understanding the findings. The study then presents a statistical analysis of the pertinent quantitative studies that have dealt with the issue. The substantive findings from the systematic analysis of the available works on the topic seem to suggest that foreign influence does have a medium effect in enhancing the military’s position vis-à-vis civilian institutions in Africa, thereby satisfying the military’s corporate interests. This situation, in turn, is a recipe for regime instability.
Introduction
While scholars who have studied the connection between foreign influence and military intervention in Africa through coups d’état do agree that the connection does exist, they, nevertheless, part company when it comes to the question of how strong the connection is. Some authors (e.g., First 1970) have asserted that the connection is minimal, while others (e.g., Assensoh and Alex-Assensoh 2002) have demonstrated that the connection is strong. Consequently, the major question investigated in this essay is quite straightforward: How strong is the connection between foreign influence and military coup d’état in Africa?
This essay, which employs a meta-analytic methodology, applies statistical procedures to collections of empirical findings from individual quantitative studies that have examined the connection between foreign influence and military intervention in Africa through coups d’état for the purpose of integrating, synthesizing, and making sense of them. This helps in discovering underlying trends and principles developed from the accumulation and refinement of this body of studies. But before this is accomplished, a combined review of qualitative and quantitative studies on the issue is done first in order to allow for the description of interesting, worthwhile studies that are not included in the statistical analysis. Thus, the rest of the essay is divided into various sections that (a) deal with the major differences and similarities between studies which are relevant for understanding the findings, and (b) present a statistical analysis of the pertinent quantitative studies that have dealt with foreign influence as a cause of military intervention in Africa through coups d’état.
Comparison of Studies
In this section, an attempt is made to delineate the differences and similarities between studies. This will help the reader to understand those relevant factors that may underlie the different findings in the studies.
Number, Types and Sources
A literature search on foreign influence and military intervention in Africa yielded 26 works. They include books, academic journal articles, and unpublished studies (a doctoral dissertation and an Orkand Corporation report). Each of these media, of course, calls for different ways of presenting findings. For example, whereas a book may be targeted at a wider audience and, thus, its author may soften its technical aspects, a journal article may not sacrifice technical aspects but may have to reduce details because of space limitation.
The studies were written by African, North American, and European researchers. They were also published in these continents. The cultural biases of these investigators may in some way underlie the measurements used and, consequently, the findings in the studies.
Methodologies
The studies that dealt with the connection between foreign influence and military intervention in Africa can be divided into two methodological groups. One of these groups can be referred to as the Qualitative. This group comprises those researchers who emphasize words to generate descriptions of and explanations for the connection between foreign influence and coups d’état. The 16 (62%) qualitative investigations include studies by Apter (1969), Assensoh and Alex-Assensoh (2002), Baynham (1980), Bebler (1973), David (1985), First (1970), Fisher (1969), Higgot and Fuglestad (1975), Liebnow (1981), Lofchie (1972), Souaré (2006), Terray (1964), Welch, Jr. (1967, 1970), Wolpin (1980), and Yannopoulus and Martin (1972).
The other group can be called the Quantitative. This group encompasses those researchers who conducted numerical representations and manipulations of observations in order to describe and explain the connection between foreign influence and military coups d’état in Africa. The 10 (38%) quantitative investigations include the studies by Johnson, Slater and McGowan (1984), McGowan (1975), McGowan and Johnson (1985), Orkand Corporation (1983), Thompson (1972, 1975), Wang (1998), Wells (1974), and Zimmermann (1979a, 1979b).
Consequently, the results of the preceding studies might have differed due to their different methods of inquiry. Whereas the qualitative studies are basically enumerative, the quantitative studies are more causally oriented. Thus, although the qualitative studies are as important as the quantitative studies, the quantitative studies are methodologically more complex than the qualitative studies.
It may appear, however, as if the difference between the qualitative and quantitative groups is a somewhat artificial dichotomy: each group combines both approaches in its underlying assumptions. This is because the quantitative approach calls for a great deal of qualitative description prior to counting (in order to empirically ground each category) as well as after counting (statistical tendencies have to be interpreted as to what they reveal about causal relations). And the qualitative approach has an implicit notion that ‘more is better’: that is to say, the more instances of a phenomenon to be found, the more a researcher can trust his/her interpretation of an underlying pattern.
Despite these underlying similarities, the qualitative and quantitative approaches used in the studies investigated here are different in some ways. In addition to some of the more obvious procedural differences (for example, quantitative studies categorize and count occurrences), the two types of approaches differ in their overall orientation toward inquiry: the qualitative focuses more on particularities and the quantitative focuses more on generalities.
Thus, the classification of works as qualitative and quantitative is important for the present essay because procedures employed in meta-analysis are geared toward quantitative reviews and syntheses of the research literature that address the issues involved. Meta-analysis calls for more technical and statistical approaches as opposed to unscientific and impressionistic ones. Nevertheless, although qualitative studies are not included in the statistical analysis, they are discussed in various sections of this study to help in comparing the underlying trends and principles developed in the large body of studies that have dealt with the connections between foreign influence and military intervention in Africa.
Research Designs
A number of different research designs were employed by researchers in their examinations of the connection between foreign influence and military intervention in Africa. All of the investigators listed under the rubric of the qualitative approach naturally used the Case Study design. These researchers looked at the issue in considerable detail, typically using personal interviews, observation, and document analysis as data collection procedures. Investigators who used the Case Study design undoubtedly contribute to the cumulative knowledge on military intervention in Africa in the sense that they were able to mix the specific and the general, the peculiar and the typical, the descriptive and the thematic.
Investigators listed under the rubric of the quantitative approach attempted to infer causal relationships from a variety of Pooled Cross-sectional Non-experimental research designs. The primary difference in these designs lies in the way the statistical and temporal dimensions are employed. A total of five different designs can be discerned: (1) Simple Pooled Cross-sectional, (2) Pooled Cross-sectional with Percent Scores, (3) Pooled Cross-sectional with Regression Analysis, (4) Pooled Time-lagged Cross-sectional with Regression and Discriminant Analysis, and (5) Event-count Analysis with Conventional Regression Techniques.
A Simple Pooled Cross-sectional design combines measures on variables for a number of countries for different years into a single analysis using correlational statistics. This design was employed by Thompson (1972). A major limitation with this design is that it cannot be used to measure change over time in any of the variables.
A Pooled Cross-sectional with Percent Scores design combines measures on variables for a number of countries for different years into a single analysis by using percentages to standardize frequency distributions. This design was used by Thompson (1975). Like the simple pooled cross-sectional design, the pooled cross-sectional with percent scores design does not permit the measurement of change over time in any of the variables. In addition, the percent does not necessarily express what it claims to do. While nothing is wrong with the percent itself, conclusions drawn from using it can be unwarranted for one reason or another.
The Pooled Cross-sectional with Regression Analysis design involves combining measures on variables for a number of countries for different years into a single analysis by using regression techniques to specify the nature of plausible relationships between the independent (and control) variables and the dependent variable(s). Investigators who used this design include Johnson, Slater and McGowan (1984), McGowan and Johnson (1985), Orkand Corporation (1983), Wells (1974), and Zimmermann (1979a, 1979b). Like the previous designs, the pooled cross-sectional with regression analysis design does not allow a researcher to measure change over time in any of the variables. While it is relatively stronger than the previous designs, it has two shortcomings when used to predict data (as is the case in predicting the causes of military coups d’état across many countries in Africa): (1) There is the problem toward the mean. This means that in a randomly distributed measure of military coups d’état, predictions from extreme values can be expected to be less extreme. (2) Regression cannot legitimately be used to predict beyond the range of the data.
A Pooled Time-lagged Cross-sectional with Regression and Discriminant Analysis design combines measures on variables for a number of countries for different years using regression techniques that relate current endogenous variables to past values of the exogenous and/or endogenous variables, and using discriminant techniques that form a linear function of the independent (and control) variables which maximizes the correct classification between countries which have had coups d’état and those which have not. This design was employed by McGowan (1975). The design, which also permits a researcher to measure change over time in the variables, is, nevertheless, marred by the same problems inherent in the pooled cross-sectional and time-series design. The major difference between the two designs is that while Ordinary Least Squares (OLS) and Generalized Least Squares (GLS) can be used to generate unbiased, relatively efficient and consistent estimates in a pooled time-lagged, cross-sectional with regression and discriminant analysis design, only GLS can be used in a pooled cross-sectional and time-series design. This is due to the fact that the latter is a special case in which the error variances of concurrent cross-sections may be unequal whereas their covariances equal zero, and error variances of successive cross-sections are equal whereas the covariances are of the same structure and are also time dependent.
An Event-count Analysis with Conventional Regression Techniques was employed by Wang (1998). The simplest specification of an event-count analysis is the exponential Poisson regression (EPR) model, which is used to estimate the vector of regression estimates in which each element represents the individual effect of a particular independent variable on the dependent variable or the observed event count. There are several challenges to event-count analysis. First, it is quite difficult to unitize: that is, to separate a stream of actions into discrete units. Second, it is impossible to capture the full universe of a phenomenon. Third, precise information about location and timing of events is not always available. Finally, there is the selection bias of event-count analysis.
In sum, the studies that have dealt with the connection between foreign influence and military intervention in Africa through coups d’état used a variety of research designs. The biases in the use of these different designs could have influenced the results of these studies.
Statistical Estimators
Expectedly, only those investigators who employed quantitative methodology used statistical estimators for the variables they utilized. The exception here is Zimmermann (1979a, 1979b) who reported other investigators’ statistical estimators but presented none for his own causal model. While some researchers used single statistical estimators, others employed multiple estimators.
Partial Correlation Coefficient was used by McGowan (1975). Standard Regression or Beta Coefficient was employed by Johnson, Slater and McGowan (1984), McGowan (1975), Orkand Corporation (1983), Wells (1974), and Wang (1998). Coefficient of Determination was employed by Johnson, Slater and McGowan (1984), McGowan (1975), and Orkand Corporation (1983). F Ratio was used by Johnson, Slater and McGowan (1984), and Orkand Corporation (1983). Percentile was utilized by Thompson (1975).
These studies, then, utilized a variety of statistical estimators. Again, it is not farfetched to expect, therefore, that the findings of some of these studies differ because of these different estimators.
Time Periods
A variety of time periods were utilized in the studies. These time periods range from the 1940s to the 2000s. While some researchers employed single years in their analyses, others used multiple years. For the sake of brevity, these time periods and the attendant studies have been segmented into 12 categories.
1. Single Years, 1960s. Research in this category includes the studies of Apter (1969), Terray (1964), and Wolpin (1980).
2. Single Years, 1970s. Investigations in this group comprise those of Baynham (1980), Higgott and Fuglestad (1975), and Lofchie (1972).
3. Single Years, 1980s. The one study here is by Liebnnow (1981).
4. Multiple Years, 1940s-1970s. Works in this group include those by Thompson (1972, 1975) and Zimmermann (1979a, 1979b).
5. Multiple Years, 1950s-1960s. Research in this category comprises those of First (1970) and Welch, Jr. (1967, 1970).
6. Multiple Years, 1950s-1980s. The following study can be placed here: McGowan and Johnson (1985).
7. Multiple Years, 1960s. The studies in this group comprise those of Fisher (1969) and McGowan (1975).
8. Multiple Years, 1960s-1970s. Research in this category includes the works of Bebler (1973), Wells (1974), and Yannopoulos and Martin (1972).
9. Multiple Years, 1960s-1980s. This category entails the studies of David (1985), Johnson, Slater and McGowan (1984), and Orkand Corporation (1983).
10. Multiple Years, 1980s-1990. The study of Wang (1998) is the only one here.
11. Multiple Years, 1900s. The only study here is that of Assensoh and Alex-Assensoh (2002).
12. Multiple Years, 1950s-2000s. The one study here is by Souaré (2006).
Clearly evident from the preceding categories is that while all the studies identified earlier as quantitative used multiple years in their analyses, those identified as qualitative used either single years or multiple years in their analyses. The great variation in the time periods analyzed in the studies means that their results were conditional on certain characteristics of the African societies at various points in time.
Sample Size and Composition
The numbers of African countries examined in the studies vary from one to 35. Researchers who examined single African countries comprise the largest group in terms of sample size and composition. These researchers, according to the countries they investigated, include:
1. Ghana: Apter (1969)
2. Uganda: First (1970), Lofchie (1972)
3. Liberia: Liebnow (1981)
4. Mali: Wolpin (1980)
5. Sierra Leone: Fisher (1969)
6. Equatorial Guinea: Baynham (1980)
7. Niger: Higgott and Fuglestad (1975)
The rest of the studies examined multiple countries with various sample sizes and compositions. For the sake of brevity, these studies have been divided into five categories (note that the number of countries examined in each of these studies within these categories varies from two to 35):
1. West African States: the studies in this group include those of Bebler (1973), Souaré (2006), and Welch, Jr. (1986).
2. Sub-Sahara African States: the investigations in this category include those by Assensoh and Alex-Assensoh (2002), Johnson, Slater and McGowan (1984), McGowan (1975), McGowan and Johnson (1985), Orkand Corporation (1983), Terray (1964), Wang (1999), Wells (1974), and Yannopoulos and Martin (1972).
3. Cross-Continental (Africa-wide) States: research in this category includes the studies of First (1970) and Welch, Jr. (1967, 1970).
4. Developing States Including Some in Africa: the only study here is that by David (1985).
5. Worldwide Including Some African States: the works in this category comprise those of Thompson (1972, 1975) and Zimmermann (1979a, 1979b).
Clearly obvious from the preceding discussion is that all the studies that were identified earlier as quantitative examined multiple African states in their analyses. Those studies classified under the rubric of qualitative methodology used either single or multiple African states in their analyses. Great variation, thus, exists between studies in terms of sample size and composition. Any one study viewed in isolation presents problems of scope and generalizability.
Conceptualization of the Dependent and Independent Variables
There is a great consensus among the studies in terms of the way the dependent variable, coup d’état, is conceptualized within the general rubric of military intervention: that is, a bid for government power, normally by a sudden seizure of strategic points of power in a state by the removal of the ruler and his government. This means that it is likely to be—and most often is—an act of the military or a segment of it. As David (1985) noted, the military is behind virtually every coup attempt. By virtue of its superior organization, discipline, centralized command and monopoly of arms, the military is the most powerful institution in developing countries.
There also is great consensus among the scholars in terms of their definitions of the independent variable, foreign influence. It is generally defined as any form of perceived or real external effect from military intervention presence, military aid, economic aid, trade, ideology, values, and veto power.
Measurement of Variables
As can be expected, only those studies classified earlier under the rubric of quantitative methodology measured the variables they used. The measurement of coups d’état is generally couched within the prism of military involvement. It was measured by its users in a number of ways.
Wang (1998) and Zimmermann (1979a, 1979b) employed frequency counts; they counted both successful and unsuccessful coups d’état, because they believed that they represent a “structural propensity” of military intervention. Thompson’s (1972, 1975) index for coup d’état proneness involved counting the number of years of coups d'état.
Wells (1974) used a coup rate index for coup d’état which involved a weighing method. Successful coups were scored 10 points each, overt attempts that failed were scored three points each, and uncovered plots were scored one point each. The sums were then divided by number of years of independence.
Total Military Involvement was employed by Johnson, Slater and McGowan (1984), McGowan and Johnson (1985), and Orkand Corporation (1983). It was measured by using the following weighing method: successful coups d'état were scored five points each, attempted coups d'état were weighed three points each, and reported plots were weighed one point each.
Elite Instability was utilized by McGowan (1975) as follows: coups d’état were scored five points each, attempted coups d’état were scored three points each, and plots were scored one point each. Thus, this measurement is similar to that used by Johnson, Slater and McGowan (1984), McGowan (1984), McGowan and Johnson (1985), and Orkand Corporation (1983).
Communal Instability was used by McGowan (1975) by developing a weighted index in the following manner: civil wars were scored five points each, rebellions were scored four points each, irredentist events were scored three points each, and ethnic violence was scored one point. These were then summed for each state.
The independent variable, foreign influence, was also measured in a number of ways. Johnson, Slater and McGowan (1984), McGowan and Johnson (1985), and Orkand Corporation (1983) measured foreign influence in terms of international economic dependence utilizing two indicators: (1) the ratio of exports-imports to GNP for 1965 and (2) the percentage increase in export commodity concentration for 1960-1965. In his 1975 study, McGowan measured foreign influence in terms of the average annual per capita total foreign aid from 1967 to 1969 and the per capita foreign aid from the ex-metropole in 1969.
In his 1972 study, Thompson employed the amount of foreign aid a country received. For his 1975 study, he used the level of dependence of a country upon the fluctuations of world trade measured by commodity ratio 1, commodity ratio 2, and partner concentration.
Wang (1998) measured foreign influence in terms of international transfers of military equipment by means of grants, credits, or cash. Wells (1974) measured foreign influence by the amount of total loans and credits a country received from the United States as of June 1968.
Thus, it appears at this juncture that the studies by Johnson, Slater and McGowan (1984), McGowan (1975), McGowan and Johnson (1985), Orkand Corporation (1983), Wang (1998) and Wells (1974) are the most likely candidates for the statistical analysis of this essay. These studies entail similar measurements for the connections between foreign involvement and military intervention in Africa through coups d’état.
Results
On the one hand, since researchers who used the qualitative method intermeshed the conceptualizations of their variables with the results of their investigations, the suggested relationships between independent and dependent variables in those works are consequently confirmed. Thus, it suffices to refer the reader to the earlier discussion on the conceptualization of the independent and dependent variables. Researchers who used the quantitative method, on the other hand, began by delineating a number of variables from the available literature and then performed statistical tests to determine which variables are related. Thus, the discussion that follows is exclusively on the results from those quantitative studies.
Since the quantitative studies were done by individuals and smaller groups of researchers with different interests and foci, grouping their results is a very difficult task. What follows, therefore, is a discussion of how best to make sense of those results without losing their substance.
Johnson, Slater and McGowan (1984) and Orkand Corporation (1983) found that African states with relatively dynamic economies that were not mobilized before independence and had maintained or restored some degree of political participation and pluralism while keeping their military forces small and non-political had been the most stable in terms of military coups d’état and associated forms of military intervention in politics. The alternative is true for countries that had the opposite set of characteristics.
McGowan’s inquiry (1975) yielded four categories of findings. First, African states with large and influential military forces and extensive ethnic pluralism and social mobilization had extensive communal instability. African states in which government policy was achieving some degree of success in promoting national integration and economic development, as well as flows of foreign aid to them, had a low likelihood of communal instability. Second, African states that had fragmented party systems and increasing degrees of social mobilization were most likely to experience elite instability. Those states that were making progress in the areas of national integration, economic growth, and foreign assistance flows were less likely to have military coups d’état and other related elite instability phenomena. Third, five factors were statistically related to coups d'état. These included social mobilization, political party disunity, interest group size, government economic success, and external support. Finally, countries that had coups d’état through the end of 1969 exhibited greater levels of social mobilization, larger urban interest groups, worse economic performance, less political party unity, and less metropole foreign aid per capita than did the non-coup countries. In their 1985 study, McGowan and Johnson found that length of independence, increasing number of independent states, colonial heritage, regional factor, and the lack of industrialization were causes for military intervention in Africa.
Wang (1998) discovered that arms transfers serve to meet the military’s corporate interest and have a long-term, direct effect on reducing the likelihood of coups d’état. By enhancing the military’s position in relationship to civilian institutions, however, arms transfers indirectly contribute to regime instability. Wells (1974) found that the overall structure of the military and the socio-economic setting in which it operates relate to coups d’état activity.
In sum, the most agreed upon explanations for coups d’état outcomes include economic condition, institutional structure, military’s corporate or personal interest, domestic environment for participation, pluralism, social mobilization, and foreign influence. Since the focus of this chapter is on the connection between foreign influence and coups d’état, the following section deals only with these two variables.
Statistical Analysis
The analysis that follows is twofold. First, since the selected studies employed correlation coefficients or other statistics that can be easily converted into correlation coefficients, the correlational relationship between the independent variable, foreign influence, and the dependent variable, coup d’état/military intervention, is determined first by calculating their raw (unadjusted) statistical results. Second, weighted statistical results are computed to empirically examine the impact of sample size (number of countries included in the analysis of each study).
A simple method for synthesizing correlational results essentially involves obtaining the average of the correlation between two variables. This is typically done by averaging the raw Pearson correlation coefficients (r) using formula one.
r’= Σr [ 1 ]
n
where r is Pearson correlation from each study, and n is the number of correlation coefficients combined. The r’ (mean r) is then used and reported as the effect size indicator (Wolf 1986). To determine the impact of sample size, formula two is utilized.
(ws)r’ = Σ(ws)r [ 2 ]
n
where (ws) is weighted sample size, r is Pearson correlation from each study, and n is the number of correlation coefficients combined.
The issues surrounding the interpretation of what constitutes either a small, medium, or large effect for correlational analysis is beyond the scope of the present essay. In the absence of a single agreed-upon standard, Cohen’s guidelines for small (r = .10), medium (r = .30), and large (r = .50) effect sizes are utilized here because they have been widely employed in meta-analytical studies (Cohen 1977).
The selected studies that used foreign influence to explain military intervention/coup d’état outcomes and their attendant statistics are as follows:
(a) Johnson, Slater and McGowan (1984): r = -.30
(b) McGowan (1975): r = -.23
(c) McGowan and Johnson (1985): r = -.30
(d) Orkand Corporation (1983): r = -.30
(e) Wang (1998): r = -1.34
(f) Wells (1974): r = .32
Using formula one, these statistics are calculated as follows:
r’ = -.30 - .23 -.30 - .30 -1.34 +.32 = -.35 [ 3]
6
An r’ of -.35 suggests that foreign influence has a negative and medium effect on coup d’état outcomes. Weighing for sample size, formula two is employed as follows:
(sw)r’= 35)(-.30)+(32)(-.23)+(35)(-.30)+(35)(-.30)+(35)(-1.34)+(35)(.32)= -.06
(207)6 [ 4 ]
The weighted r’ here is -.06. This means that foreign influence still has a negative, albeit very small, effect on coup d’état outcomes. Sample size, however, appears to explain a great deal of the effect delineated above. In sum, it appears that foreign influence does have a medium effect in enhancing the military’s position vis-à-vis civilian institutions in Africa, thereby satisfying the military’s corporate interests. This situation, in turn, is a recipe for regime instability.
Conclusion
The available works that have dealt with the connection between foreign influence and military intervention in Africa through coups d’état have followed a tradition of reviewing previous studies on the subject by dividing them into what are frequently referred to as the two major schools of thought: the “systemic” and the “praetorian.” The former is said to hold the view that the military intervenes in politics because of systemic ills in a country and, thus, seeks to protect the political and institutional structures of society. The latter is said to purport the notion that the military intervenes in politics because it seeks to preserve and/or extend its corporate interests. While this approach has certain merits, it does not, however, tell readers about the methods, techniques, and type of data various researchers used to arrive at their conclusions. It also does not account for those studies that employ both “systemic” and “praetorian” variables in their analyses.
The present essay, which employs a meta-analytic method, views the research activity on the connection between foreign influence and military intervention in Africa as the accumulation and refinement of information and knowledge. This approach is a small step toward establishing guidelines for reliable and valid reviews, integrations, and syntheses for future research on military intervention in Africa. Given the enormous amount of data that must be gathered, processed, and synthesized from many disciplines, it is true that the exercise is a difficult one. But it behooves social scientists to make the effort, if the traditional approach of reviewing literature in an unscientific, impressionistic fashion is to be abandoned.
References
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Assensoh, A. B. and Y. Alex-Assensoh. 2002. African Military History and Politics: Ideological Coups and Incursions, 1900-Present. New York: Palgrave Macmillan.
Baynham, S. 1980. “Equatorial Guinea: The Terror and the Coup!” The World Today. February.
Bebler, A. 1972. Military Rule in Africa: Dahomey, Ghana, Sierra Leone and Mali. New York: Praeger.
Cohen, J. 1977. Statistical Power Analysis for the Behavioral Science. Hillsdale: Erlbaum.
David, S. R. 1985. Defending Third World Regimes from Coups d’État. Lanham, MD: University Press of America.
First, R. 1970. Power in Africa. New York: Pantheon Books.
Fisher, H. J. 1969. “Elections and Coups in Sierra Leone, 1967.” The Journal of Modern African Studies. December.
Higgot, R. A. and F. Fuglestad. 1975. “The 1964 Coup d'Etat in Niger: Towards an Explanation.” The Journal of Modern African Studies. Vol. 13.
Liebnow, J. G. 1981. “The Liberian Coup in Perspective.” Current History. March.
Lofchie, M. 1972. “The Uganda Coup—Class Action by the Military.” The Journal of Modern African Studies. May.
Johnson, T. H., R. O. Slater and P. McGowan. 1984. “Explaining African Military Coups d’État, 1960-1982.” American Political Science Review. Vol. 78.
McGowan, P. 1975. “Predicting Political Instability in Tropical Africa.” In M. K. O’Leary and W. D, Coplin, eds. Quantitative Techniques in Foreign Policy Analysis and Forecasting. New York: Praeger.
McGowan, P. and T. H. Johnson. 1985. “Forecasting African Coups d’État.” The South African Journal of Political Science. Vol. 12, No. 2.
Orkand Corporation. 1983. Analysis of the Causes of Coups d’État in Sub-Saharan Africa, 1960-1982. Silver Spring, MD: Orkand Corporation.
Souaré, Issaka K. 2006. Civil wars and Coups d’État in West Africa: An Attempte to Understand the Roots and Prescribe Possible Solutions. Lanham, MD: University Press of America.
Terray, E. 1964. “Les Revolutions Congolese et Dahomeens de 1963: Essai d’Interpretations.” Revue Française de Science Politique. Vol. 14.
Thompson, W. R. 1972. “Explanations of the Military Coup.” Unpublished Doctoral Dissertation, University of Washington.
Thompson, W. R. 1975. “Regime Vulnerability and the Military Coup.” Comparative Politics. Vol. 7.
Wang, T. Y. 1998. “Arms Transfers and Coups d’État: A Study on Sub-Saharan Africa.” Journal of Peace Research. 35, 6.
Welch, Jr., C. E. 1967. “Soldier and State in Africa.” The Journal of Modern African Studies. Vol. 5.
Welch, Jr., ed, 1970. Soldier and State in Africa: A Comparative Analysis of Military Intervention and Political Change. Evanston: Northwestern University Press.
Wells, A. 1974. “The Coups d’État in Theory and Practice: Independent Black Africa in the 1960s.” American Journal of Sociology. 79, 4.
Wolf, F. M. 1986. Meta-Analysis. Thousand Oaks: Sage Publications.
Wolpin, M. D. 1980. “Legitimizing State Capitalization: Malian Militarism in Third-World Perspective.” The Journal of Modern African Studies. Vol. 18.
Yannopoulos, T. and D. Martin. 1972. “Regimes Militaires et Classes Sociales en Afrique Noire.” Revue Française de Science Politique. Vol. 79.
Zimmerman, E. 1979a. “Toward a Causal Model of Military Coups d’État.” Armed Forces and Society. Vol. 5.
Zimmerman, E. 1979b. “Explaining Military Coups d’État: Towards the Development of a Complex Causal Model.” Quality and Quantity. Vol. 13.
Abstract
Employing a meta-analytical approach, this essay examines the connection between foreign influence and military intervention in Africa through coups d’état. Accordingly, the study begins with a look at the major differences and similarities between studies—both qualitative and quantitative—which are relevant in understanding the findings. The study then presents a statistical analysis of the pertinent quantitative studies that have dealt with the issue. The substantive findings from the systematic analysis of the available works on the topic seem to suggest that foreign influence does have a medium effect in enhancing the military’s position vis-à-vis civilian institutions in Africa, thereby satisfying the military’s corporate interests. This situation, in turn, is a recipe for regime instability.
Introduction
While scholars who have studied the connection between foreign influence and military intervention in Africa through coups d’état do agree that the connection does exist, they, nevertheless, part company when it comes to the question of how strong the connection is. Some authors (e.g., First 1970) have asserted that the connection is minimal, while others (e.g., Assensoh and Alex-Assensoh 2002) have demonstrated that the connection is strong. Consequently, the major question investigated in this essay is quite straightforward: How strong is the connection between foreign influence and military coup d’état in Africa?
This essay, which employs a meta-analytic methodology, applies statistical procedures to collections of empirical findings from individual quantitative studies that have examined the connection between foreign influence and military intervention in Africa through coups d’état for the purpose of integrating, synthesizing, and making sense of them. This helps in discovering underlying trends and principles developed from the accumulation and refinement of this body of studies. But before this is accomplished, a combined review of qualitative and quantitative studies on the issue is done first in order to allow for the description of interesting, worthwhile studies that are not included in the statistical analysis. Thus, the rest of the essay is divided into various sections that (a) deal with the major differences and similarities between studies which are relevant for understanding the findings, and (b) present a statistical analysis of the pertinent quantitative studies that have dealt with foreign influence as a cause of military intervention in Africa through coups d’état.
Comparison of Studies
In this section, an attempt is made to delineate the differences and similarities between studies. This will help the reader to understand those relevant factors that may underlie the different findings in the studies.
Number, Types and Sources
A literature search on foreign influence and military intervention in Africa yielded 26 works. They include books, academic journal articles, and unpublished studies (a doctoral dissertation and an Orkand Corporation report). Each of these media, of course, calls for different ways of presenting findings. For example, whereas a book may be targeted at a wider audience and, thus, its author may soften its technical aspects, a journal article may not sacrifice technical aspects but may have to reduce details because of space limitation.
The studies were written by African, North American, and European researchers. They were also published in these continents. The cultural biases of these investigators may in some way underlie the measurements used and, consequently, the findings in the studies.
Methodologies
The studies that dealt with the connection between foreign influence and military intervention in Africa can be divided into two methodological groups. One of these groups can be referred to as the Qualitative. This group comprises those researchers who emphasize words to generate descriptions of and explanations for the connection between foreign influence and coups d’état. The 16 (62%) qualitative investigations include studies by Apter (1969), Assensoh and Alex-Assensoh (2002), Baynham (1980), Bebler (1973), David (1985), First (1970), Fisher (1969), Higgot and Fuglestad (1975), Liebnow (1981), Lofchie (1972), Souaré (2006), Terray (1964), Welch, Jr. (1967, 1970), Wolpin (1980), and Yannopoulus and Martin (1972).
The other group can be called the Quantitative. This group encompasses those researchers who conducted numerical representations and manipulations of observations in order to describe and explain the connection between foreign influence and military coups d’état in Africa. The 10 (38%) quantitative investigations include the studies by Johnson, Slater and McGowan (1984), McGowan (1975), McGowan and Johnson (1985), Orkand Corporation (1983), Thompson (1972, 1975), Wang (1998), Wells (1974), and Zimmermann (1979a, 1979b).
Consequently, the results of the preceding studies might have differed due to their different methods of inquiry. Whereas the qualitative studies are basically enumerative, the quantitative studies are more causally oriented. Thus, although the qualitative studies are as important as the quantitative studies, the quantitative studies are methodologically more complex than the qualitative studies.
It may appear, however, as if the difference between the qualitative and quantitative groups is a somewhat artificial dichotomy: each group combines both approaches in its underlying assumptions. This is because the quantitative approach calls for a great deal of qualitative description prior to counting (in order to empirically ground each category) as well as after counting (statistical tendencies have to be interpreted as to what they reveal about causal relations). And the qualitative approach has an implicit notion that ‘more is better’: that is to say, the more instances of a phenomenon to be found, the more a researcher can trust his/her interpretation of an underlying pattern.
Despite these underlying similarities, the qualitative and quantitative approaches used in the studies investigated here are different in some ways. In addition to some of the more obvious procedural differences (for example, quantitative studies categorize and count occurrences), the two types of approaches differ in their overall orientation toward inquiry: the qualitative focuses more on particularities and the quantitative focuses more on generalities.
Thus, the classification of works as qualitative and quantitative is important for the present essay because procedures employed in meta-analysis are geared toward quantitative reviews and syntheses of the research literature that address the issues involved. Meta-analysis calls for more technical and statistical approaches as opposed to unscientific and impressionistic ones. Nevertheless, although qualitative studies are not included in the statistical analysis, they are discussed in various sections of this study to help in comparing the underlying trends and principles developed in the large body of studies that have dealt with the connections between foreign influence and military intervention in Africa.
Research Designs
A number of different research designs were employed by researchers in their examinations of the connection between foreign influence and military intervention in Africa. All of the investigators listed under the rubric of the qualitative approach naturally used the Case Study design. These researchers looked at the issue in considerable detail, typically using personal interviews, observation, and document analysis as data collection procedures. Investigators who used the Case Study design undoubtedly contribute to the cumulative knowledge on military intervention in Africa in the sense that they were able to mix the specific and the general, the peculiar and the typical, the descriptive and the thematic.
Investigators listed under the rubric of the quantitative approach attempted to infer causal relationships from a variety of Pooled Cross-sectional Non-experimental research designs. The primary difference in these designs lies in the way the statistical and temporal dimensions are employed. A total of five different designs can be discerned: (1) Simple Pooled Cross-sectional, (2) Pooled Cross-sectional with Percent Scores, (3) Pooled Cross-sectional with Regression Analysis, (4) Pooled Time-lagged Cross-sectional with Regression and Discriminant Analysis, and (5) Event-count Analysis with Conventional Regression Techniques.
A Simple Pooled Cross-sectional design combines measures on variables for a number of countries for different years into a single analysis using correlational statistics. This design was employed by Thompson (1972). A major limitation with this design is that it cannot be used to measure change over time in any of the variables.
A Pooled Cross-sectional with Percent Scores design combines measures on variables for a number of countries for different years into a single analysis by using percentages to standardize frequency distributions. This design was used by Thompson (1975). Like the simple pooled cross-sectional design, the pooled cross-sectional with percent scores design does not permit the measurement of change over time in any of the variables. In addition, the percent does not necessarily express what it claims to do. While nothing is wrong with the percent itself, conclusions drawn from using it can be unwarranted for one reason or another.
The Pooled Cross-sectional with Regression Analysis design involves combining measures on variables for a number of countries for different years into a single analysis by using regression techniques to specify the nature of plausible relationships between the independent (and control) variables and the dependent variable(s). Investigators who used this design include Johnson, Slater and McGowan (1984), McGowan and Johnson (1985), Orkand Corporation (1983), Wells (1974), and Zimmermann (1979a, 1979b). Like the previous designs, the pooled cross-sectional with regression analysis design does not allow a researcher to measure change over time in any of the variables. While it is relatively stronger than the previous designs, it has two shortcomings when used to predict data (as is the case in predicting the causes of military coups d’état across many countries in Africa): (1) There is the problem toward the mean. This means that in a randomly distributed measure of military coups d’état, predictions from extreme values can be expected to be less extreme. (2) Regression cannot legitimately be used to predict beyond the range of the data.
A Pooled Time-lagged Cross-sectional with Regression and Discriminant Analysis design combines measures on variables for a number of countries for different years using regression techniques that relate current endogenous variables to past values of the exogenous and/or endogenous variables, and using discriminant techniques that form a linear function of the independent (and control) variables which maximizes the correct classification between countries which have had coups d’état and those which have not. This design was employed by McGowan (1975). The design, which also permits a researcher to measure change over time in the variables, is, nevertheless, marred by the same problems inherent in the pooled cross-sectional and time-series design. The major difference between the two designs is that while Ordinary Least Squares (OLS) and Generalized Least Squares (GLS) can be used to generate unbiased, relatively efficient and consistent estimates in a pooled time-lagged, cross-sectional with regression and discriminant analysis design, only GLS can be used in a pooled cross-sectional and time-series design. This is due to the fact that the latter is a special case in which the error variances of concurrent cross-sections may be unequal whereas their covariances equal zero, and error variances of successive cross-sections are equal whereas the covariances are of the same structure and are also time dependent.
An Event-count Analysis with Conventional Regression Techniques was employed by Wang (1998). The simplest specification of an event-count analysis is the exponential Poisson regression (EPR) model, which is used to estimate the vector of regression estimates in which each element represents the individual effect of a particular independent variable on the dependent variable or the observed event count. There are several challenges to event-count analysis. First, it is quite difficult to unitize: that is, to separate a stream of actions into discrete units. Second, it is impossible to capture the full universe of a phenomenon. Third, precise information about location and timing of events is not always available. Finally, there is the selection bias of event-count analysis.
In sum, the studies that have dealt with the connection between foreign influence and military intervention in Africa through coups d’état used a variety of research designs. The biases in the use of these different designs could have influenced the results of these studies.
Statistical Estimators
Expectedly, only those investigators who employed quantitative methodology used statistical estimators for the variables they utilized. The exception here is Zimmermann (1979a, 1979b) who reported other investigators’ statistical estimators but presented none for his own causal model. While some researchers used single statistical estimators, others employed multiple estimators.
Partial Correlation Coefficient was used by McGowan (1975). Standard Regression or Beta Coefficient was employed by Johnson, Slater and McGowan (1984), McGowan (1975), Orkand Corporation (1983), Wells (1974), and Wang (1998). Coefficient of Determination was employed by Johnson, Slater and McGowan (1984), McGowan (1975), and Orkand Corporation (1983). F Ratio was used by Johnson, Slater and McGowan (1984), and Orkand Corporation (1983). Percentile was utilized by Thompson (1975).
These studies, then, utilized a variety of statistical estimators. Again, it is not farfetched to expect, therefore, that the findings of some of these studies differ because of these different estimators.
Time Periods
A variety of time periods were utilized in the studies. These time periods range from the 1940s to the 2000s. While some researchers employed single years in their analyses, others used multiple years. For the sake of brevity, these time periods and the attendant studies have been segmented into 12 categories.
1. Single Years, 1960s. Research in this category includes the studies of Apter (1969), Terray (1964), and Wolpin (1980).
2. Single Years, 1970s. Investigations in this group comprise those of Baynham (1980), Higgott and Fuglestad (1975), and Lofchie (1972).
3. Single Years, 1980s. The one study here is by Liebnnow (1981).
4. Multiple Years, 1940s-1970s. Works in this group include those by Thompson (1972, 1975) and Zimmermann (1979a, 1979b).
5. Multiple Years, 1950s-1960s. Research in this category comprises those of First (1970) and Welch, Jr. (1967, 1970).
6. Multiple Years, 1950s-1980s. The following study can be placed here: McGowan and Johnson (1985).
7. Multiple Years, 1960s. The studies in this group comprise those of Fisher (1969) and McGowan (1975).
8. Multiple Years, 1960s-1970s. Research in this category includes the works of Bebler (1973), Wells (1974), and Yannopoulos and Martin (1972).
9. Multiple Years, 1960s-1980s. This category entails the studies of David (1985), Johnson, Slater and McGowan (1984), and Orkand Corporation (1983).
10. Multiple Years, 1980s-1990. The study of Wang (1998) is the only one here.
11. Multiple Years, 1900s. The only study here is that of Assensoh and Alex-Assensoh (2002).
12. Multiple Years, 1950s-2000s. The one study here is by Souaré (2006).
Clearly evident from the preceding categories is that while all the studies identified earlier as quantitative used multiple years in their analyses, those identified as qualitative used either single years or multiple years in their analyses. The great variation in the time periods analyzed in the studies means that their results were conditional on certain characteristics of the African societies at various points in time.
Sample Size and Composition
The numbers of African countries examined in the studies vary from one to 35. Researchers who examined single African countries comprise the largest group in terms of sample size and composition. These researchers, according to the countries they investigated, include:
1. Ghana: Apter (1969)
2. Uganda: First (1970), Lofchie (1972)
3. Liberia: Liebnow (1981)
4. Mali: Wolpin (1980)
5. Sierra Leone: Fisher (1969)
6. Equatorial Guinea: Baynham (1980)
7. Niger: Higgott and Fuglestad (1975)
The rest of the studies examined multiple countries with various sample sizes and compositions. For the sake of brevity, these studies have been divided into five categories (note that the number of countries examined in each of these studies within these categories varies from two to 35):
1. West African States: the studies in this group include those of Bebler (1973), Souaré (2006), and Welch, Jr. (1986).
2. Sub-Sahara African States: the investigations in this category include those by Assensoh and Alex-Assensoh (2002), Johnson, Slater and McGowan (1984), McGowan (1975), McGowan and Johnson (1985), Orkand Corporation (1983), Terray (1964), Wang (1999), Wells (1974), and Yannopoulos and Martin (1972).
3. Cross-Continental (Africa-wide) States: research in this category includes the studies of First (1970) and Welch, Jr. (1967, 1970).
4. Developing States Including Some in Africa: the only study here is that by David (1985).
5. Worldwide Including Some African States: the works in this category comprise those of Thompson (1972, 1975) and Zimmermann (1979a, 1979b).
Clearly obvious from the preceding discussion is that all the studies that were identified earlier as quantitative examined multiple African states in their analyses. Those studies classified under the rubric of qualitative methodology used either single or multiple African states in their analyses. Great variation, thus, exists between studies in terms of sample size and composition. Any one study viewed in isolation presents problems of scope and generalizability.
Conceptualization of the Dependent and Independent Variables
There is a great consensus among the studies in terms of the way the dependent variable, coup d’état, is conceptualized within the general rubric of military intervention: that is, a bid for government power, normally by a sudden seizure of strategic points of power in a state by the removal of the ruler and his government. This means that it is likely to be—and most often is—an act of the military or a segment of it. As David (1985) noted, the military is behind virtually every coup attempt. By virtue of its superior organization, discipline, centralized command and monopoly of arms, the military is the most powerful institution in developing countries.
There also is great consensus among the scholars in terms of their definitions of the independent variable, foreign influence. It is generally defined as any form of perceived or real external effect from military intervention presence, military aid, economic aid, trade, ideology, values, and veto power.
Measurement of Variables
As can be expected, only those studies classified earlier under the rubric of quantitative methodology measured the variables they used. The measurement of coups d’état is generally couched within the prism of military involvement. It was measured by its users in a number of ways.
Wang (1998) and Zimmermann (1979a, 1979b) employed frequency counts; they counted both successful and unsuccessful coups d’état, because they believed that they represent a “structural propensity” of military intervention. Thompson’s (1972, 1975) index for coup d’état proneness involved counting the number of years of coups d'état.
Wells (1974) used a coup rate index for coup d’état which involved a weighing method. Successful coups were scored 10 points each, overt attempts that failed were scored three points each, and uncovered plots were scored one point each. The sums were then divided by number of years of independence.
Total Military Involvement was employed by Johnson, Slater and McGowan (1984), McGowan and Johnson (1985), and Orkand Corporation (1983). It was measured by using the following weighing method: successful coups d'état were scored five points each, attempted coups d'état were weighed three points each, and reported plots were weighed one point each.
Elite Instability was utilized by McGowan (1975) as follows: coups d’état were scored five points each, attempted coups d’état were scored three points each, and plots were scored one point each. Thus, this measurement is similar to that used by Johnson, Slater and McGowan (1984), McGowan (1984), McGowan and Johnson (1985), and Orkand Corporation (1983).
Communal Instability was used by McGowan (1975) by developing a weighted index in the following manner: civil wars were scored five points each, rebellions were scored four points each, irredentist events were scored three points each, and ethnic violence was scored one point. These were then summed for each state.
The independent variable, foreign influence, was also measured in a number of ways. Johnson, Slater and McGowan (1984), McGowan and Johnson (1985), and Orkand Corporation (1983) measured foreign influence in terms of international economic dependence utilizing two indicators: (1) the ratio of exports-imports to GNP for 1965 and (2) the percentage increase in export commodity concentration for 1960-1965. In his 1975 study, McGowan measured foreign influence in terms of the average annual per capita total foreign aid from 1967 to 1969 and the per capita foreign aid from the ex-metropole in 1969.
In his 1972 study, Thompson employed the amount of foreign aid a country received. For his 1975 study, he used the level of dependence of a country upon the fluctuations of world trade measured by commodity ratio 1, commodity ratio 2, and partner concentration.
Wang (1998) measured foreign influence in terms of international transfers of military equipment by means of grants, credits, or cash. Wells (1974) measured foreign influence by the amount of total loans and credits a country received from the United States as of June 1968.
Thus, it appears at this juncture that the studies by Johnson, Slater and McGowan (1984), McGowan (1975), McGowan and Johnson (1985), Orkand Corporation (1983), Wang (1998) and Wells (1974) are the most likely candidates for the statistical analysis of this essay. These studies entail similar measurements for the connections between foreign involvement and military intervention in Africa through coups d’état.
Results
On the one hand, since researchers who used the qualitative method intermeshed the conceptualizations of their variables with the results of their investigations, the suggested relationships between independent and dependent variables in those works are consequently confirmed. Thus, it suffices to refer the reader to the earlier discussion on the conceptualization of the independent and dependent variables. Researchers who used the quantitative method, on the other hand, began by delineating a number of variables from the available literature and then performed statistical tests to determine which variables are related. Thus, the discussion that follows is exclusively on the results from those quantitative studies.
Since the quantitative studies were done by individuals and smaller groups of researchers with different interests and foci, grouping their results is a very difficult task. What follows, therefore, is a discussion of how best to make sense of those results without losing their substance.
Johnson, Slater and McGowan (1984) and Orkand Corporation (1983) found that African states with relatively dynamic economies that were not mobilized before independence and had maintained or restored some degree of political participation and pluralism while keeping their military forces small and non-political had been the most stable in terms of military coups d’état and associated forms of military intervention in politics. The alternative is true for countries that had the opposite set of characteristics.
McGowan’s inquiry (1975) yielded four categories of findings. First, African states with large and influential military forces and extensive ethnic pluralism and social mobilization had extensive communal instability. African states in which government policy was achieving some degree of success in promoting national integration and economic development, as well as flows of foreign aid to them, had a low likelihood of communal instability. Second, African states that had fragmented party systems and increasing degrees of social mobilization were most likely to experience elite instability. Those states that were making progress in the areas of national integration, economic growth, and foreign assistance flows were less likely to have military coups d’état and other related elite instability phenomena. Third, five factors were statistically related to coups d'état. These included social mobilization, political party disunity, interest group size, government economic success, and external support. Finally, countries that had coups d’état through the end of 1969 exhibited greater levels of social mobilization, larger urban interest groups, worse economic performance, less political party unity, and less metropole foreign aid per capita than did the non-coup countries. In their 1985 study, McGowan and Johnson found that length of independence, increasing number of independent states, colonial heritage, regional factor, and the lack of industrialization were causes for military intervention in Africa.
Wang (1998) discovered that arms transfers serve to meet the military’s corporate interest and have a long-term, direct effect on reducing the likelihood of coups d’état. By enhancing the military’s position in relationship to civilian institutions, however, arms transfers indirectly contribute to regime instability. Wells (1974) found that the overall structure of the military and the socio-economic setting in which it operates relate to coups d’état activity.
In sum, the most agreed upon explanations for coups d’état outcomes include economic condition, institutional structure, military’s corporate or personal interest, domestic environment for participation, pluralism, social mobilization, and foreign influence. Since the focus of this chapter is on the connection between foreign influence and coups d’état, the following section deals only with these two variables.
Statistical Analysis
The analysis that follows is twofold. First, since the selected studies employed correlation coefficients or other statistics that can be easily converted into correlation coefficients, the correlational relationship between the independent variable, foreign influence, and the dependent variable, coup d’état/military intervention, is determined first by calculating their raw (unadjusted) statistical results. Second, weighted statistical results are computed to empirically examine the impact of sample size (number of countries included in the analysis of each study).
A simple method for synthesizing correlational results essentially involves obtaining the average of the correlation between two variables. This is typically done by averaging the raw Pearson correlation coefficients (r) using formula one.
r’= Σr [ 1 ]
n
where r is Pearson correlation from each study, and n is the number of correlation coefficients combined. The r’ (mean r) is then used and reported as the effect size indicator (Wolf 1986). To determine the impact of sample size, formula two is utilized.
(ws)r’ = Σ(ws)r [ 2 ]
n
where (ws) is weighted sample size, r is Pearson correlation from each study, and n is the number of correlation coefficients combined.
The issues surrounding the interpretation of what constitutes either a small, medium, or large effect for correlational analysis is beyond the scope of the present essay. In the absence of a single agreed-upon standard, Cohen’s guidelines for small (r = .10), medium (r = .30), and large (r = .50) effect sizes are utilized here because they have been widely employed in meta-analytical studies (Cohen 1977).
The selected studies that used foreign influence to explain military intervention/coup d’état outcomes and their attendant statistics are as follows:
(a) Johnson, Slater and McGowan (1984): r = -.30
(b) McGowan (1975): r = -.23
(c) McGowan and Johnson (1985): r = -.30
(d) Orkand Corporation (1983): r = -.30
(e) Wang (1998): r = -1.34
(f) Wells (1974): r = .32
Using formula one, these statistics are calculated as follows:
r’ = -.30 - .23 -.30 - .30 -1.34 +.32 = -.35 [ 3]
6
An r’ of -.35 suggests that foreign influence has a negative and medium effect on coup d’état outcomes. Weighing for sample size, formula two is employed as follows:
(sw)r’= 35)(-.30)+(32)(-.23)+(35)(-.30)+(35)(-.30)+(35)(-1.34)+(35)(.32)= -.06
(207)6 [ 4 ]
The weighted r’ here is -.06. This means that foreign influence still has a negative, albeit very small, effect on coup d’état outcomes. Sample size, however, appears to explain a great deal of the effect delineated above. In sum, it appears that foreign influence does have a medium effect in enhancing the military’s position vis-à-vis civilian institutions in Africa, thereby satisfying the military’s corporate interests. This situation, in turn, is a recipe for regime instability.
Conclusion
The available works that have dealt with the connection between foreign influence and military intervention in Africa through coups d’état have followed a tradition of reviewing previous studies on the subject by dividing them into what are frequently referred to as the two major schools of thought: the “systemic” and the “praetorian.” The former is said to hold the view that the military intervenes in politics because of systemic ills in a country and, thus, seeks to protect the political and institutional structures of society. The latter is said to purport the notion that the military intervenes in politics because it seeks to preserve and/or extend its corporate interests. While this approach has certain merits, it does not, however, tell readers about the methods, techniques, and type of data various researchers used to arrive at their conclusions. It also does not account for those studies that employ both “systemic” and “praetorian” variables in their analyses.
The present essay, which employs a meta-analytic method, views the research activity on the connection between foreign influence and military intervention in Africa as the accumulation and refinement of information and knowledge. This approach is a small step toward establishing guidelines for reliable and valid reviews, integrations, and syntheses for future research on military intervention in Africa. Given the enormous amount of data that must be gathered, processed, and synthesized from many disciplines, it is true that the exercise is a difficult one. But it behooves social scientists to make the effort, if the traditional approach of reviewing literature in an unscientific, impressionistic fashion is to be abandoned.
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