Freedom, Economic Development and Crime in the former Soviet Republic

Huntington has called the recent wave of democratization throughout the world "The Third Wave." This wave began approximately in 1974 and has continued into the 1990s. Many scholars such as Huntington have tried to explain this wave of democracy. One explanation forwarded for this rise in democratic governments since the late 1950s has been that increased socioeconomic development in these nations created a stable political environment that help to promote democracy. As the literature review below will reveal, many scholars have found a positive relationship between the growth in socioeconomic development and the establishment of democratic governments. However, none of these studies have examined if this explanation has any relevance in explaining which Soviet Republics have been most successful in establishing democratic governments. This study attempts to examine this relationship.

Literature Review

Ever since Seymour Martin Lipset’s cross national study in 1959, many scholars have examined the relationship between economic development and democracy. Lipset found a positive relationship between economic development and democracy. However, many scholars have criticized his study for its limitations. For example, the study only examined the countries in Europe, North America, Australia, New Zealand and Latin America for one period. Moreover, Lipset’s study established correlation between democracy and economics and not causality. Diamond has criticized the study for not controlling for other variables. Even with its shortcomings, the Lipset study was a cornerstone piece of research that has inspired many studies to examine the relationship between economic development and democracy.

Lipset developed the theory of modernization to explain the positive relationship he found between socioeconomic development and democracy. According to modernization theory, Lipset argued that the empowerment of the middle class and the spread of education in society helped to weaken the power of the ruling elites in authoritarian nations. As a result, the middle class obtained enough economic and political power to demand democracy. In his work, Lipset argued that "..since the more well-to-do and better educated a man is, the more likely he is to belong to voluntary organizations, the propensity to form such groups seems to be a function of level of income and opportunities for leisure within given nations." At least, Lipset concludes, the chance of survival for democracy is higher in the more developed countries than in the poor countries given the complex structure of developed countries.

Modernization theory has had no shortage of its critics. Several development theories which include dependency theory, critical theory and contingency theories, have contested the legitimacy of modernization theory. One critic, Barrington Moore, claimed that the Western capitalist route to democracy was only one among many. Several countries did modernize without democracy as in the example of Germany and Japan. It was, Moore argued, the contingent circumstances that made possible democracy in some places and fascism, or communism, in other places. He argues that the reaction of the landed upper classes and the peasants to commercial agriculture was the determinant of certain political outcome. The outcome in a certain context was communism for which the peasants played a critical role, and fascism in another one, the engine of which was the landlord class. Such different paths to modernization, often accompanied by revolutionary violence, suggest that the gradual process toward democracy, an assumption borrowed from modernization theory, is nothing but an exception, and it loses its power in terms of its applicability to each case of political development.

Since Lipset’s study, many empirical studies have examined the relationship between socioeconomic development and democracy. Beginning with Cutright and Wiley many multivariate studies found a casual relationship with economic development causing democracy. Cutright and Wiley examined countries that were continuously self-governing from 1927 to 1966. Their study divided the 40 years into four successive decades and applied a cross-lagged correlational test. In addition, they found that countries with low levels of social security and literacy had a high degree of changes in democracy. This finding hinted that the relationship between economic development and democracy may not be a linear relationship and gave some validity to modernization theory.

Cutright and Wiley’s study encouraged other scholars to pursue the possibility of establishing a casual relationship between economic development and democracy. Many studies since have created linear and curvlinear models that establish a relationship where economic development appears to cause democracy. Many of these studies found intervening variables between economic development and democracy were important in explaining the exact dynamics of this relationship. These variables included urbanization, education, communication media, per capita energy consumption, and ethnic pluralism. Depending on the study, these intervening variables varied in their importance on explaining the relationship between democracy and economic development. Their importance depended on the period studied and countries used in the individual study’s sample. As a result, no conclusive evidence supports the modernization theory.

In fact, some studies seem to contradict modernization theory. Hannan and Carroll have found that high levels of development seemed to prevent regime change among democracies as well as other forms of governments. Also, Hannan and Carroll found that modernization variables such as education and urbanization did not affect democracy. The findings in this study may be time bound since the authors conducted the research before the fall of communism in 1989. Another study conducted before the fall of communism, Thomas, Ramirez, Meyer, and Golbart agreed with the results of the Hannan and Carroll study concerning modernizing experiences having little effect on democracy.

In addition, some studies have called into question whether there is even a positive correlation between development and democracy. Arat suggests that higher levels of economic development do not predict more democracy even among less developed nations. Gonick and Rosh agree with this conclusion. However, Burkhart and Lewis-Beck points out that both studies used Banks’ measure for democracy which Bollen showed had considerable measurement error. Also, Burkhart and Lewis-Beck criticize these studies because they do not examine causality or use the full range of statistical tools available for pooled time series data. In their study Burkhart and Lewis-Beck attempt to test the casual direction of development and democracy through a time series analysis on freedom house civil and political rights indexes measured for each year from 1972-1989. They found a strong relationship with energy consumption per capita (the measure used for economic development), controlling for how democratic a nation was the year previously. Democracy, controlled by the amount of development in the previous year, however does not predict democracy. They conclude "economic development causes...democracy, but democracy does not cause economic development."

More recently, Vincent and McCluskie attempted to examine the casual relationship between quality of life indicators and freedom house data. They replicated a 1987 Vincent study that worked with cross-time difference variables across the 1970s for the 1980s. In essence, the study would examine a variable such as literacy rates and take its rate at the beginning of the decade from the rate at the end of the decade. The 1970s study found that nations that had increases in quality of life became more democratic and nations that had declines in quality of life became less democratic. These results could not be replicated for the 1980s. The main reason was that there was not very much shifting in quality of life variables throughout the 1980s. The main conclusion from this study is that the relationship between democracy and development may be time based. This conclusion may be extended to all of the other studies previewed here since all of them examined the relationship between economic development and democracy after World War II. As a result, it is not guaranteed that these findings will occur in the future.

Besides the issue of causality and the validity of modernization theory, scholars have also attempted to discover at what level of economic development do nations start to become more democratic. In his discussion of the "third wave" of democratization, Huntington suggested that "a social scientist in the mid 1970’s who wished to predict future democratizations, in short, would have done reasonably well if he had simply fingered the non-democratic countries in the $1,000-$3,000 transition zone." More recently, a comprehensive study by Lipset, Seong and Torres found that economic development was the best predictor of political democracy when controlling for other variables. In examining nonlinear models on developing nations, Lipset, et al. report that the best fit models were N-curve relationships. These relationships suggest that economic development increased the likelihood of democracy up to a lower-middle level of per capita GNP, then decreases the odds in a middle range (between $2,346 and $5,000 in 1980), while stabilizing the chances of democracy at a very high probability in the higher-income range.

As with other results of studies, some scholars still express doubt that a level of development has been found that can predict when democracy will likely occur. For example, Przeworski and Limongi argued that the causal power of economic development in feeding democratization and bringing down authoritarian governments appears "paltry." They argue that even if democratization is related to economic development, there is no exact line when that occurs. On the other hand, Przeworski and Limongi contend that the level of economic development can promote the survival of democracy once established: democracies are more likely to become successful in rich countries than in the poor ones.

Of all the above studies, none have examined how the relationship of socioeconomic development and democracy has evolved in the Soviet Union after its break up in 1991. All these countries have attempted to create liberal economies with democratic governments. However, the results have varied among nations. This study examines whether the Soviet Republics with the highest socioeconomic development have been more successful than less developed nations in creating democratic forms of government. These nations provide a forum in which scholars can clearly observe the barriers to creating a liberal economic and democratic political system.

Examining the former Soviet republics is difficult because of the lack of reliable data. This problem is twofold. First, there is little data for each individual republic before 1991. Second, the data for some republics after 1991 is either nonexistent or highly unreliable. Thus, the available data has directed the project in terms of formulating the hypotheses and testing them. Since the report published by the Commonwealth of Independent States (CIS) center in Moscow, Russia, has provided the only detailed data, the research remained limited to the CIS countries. It does not include the countries of Estonia, Latvia, Lithuania and Georgia. The study examines the years 1985, 1990, 1992 and 1994. These years were chosen to measure the countries before, during and after the nation’s became independent.

To measure socioeconomic development, the variables used were the nations’ national income, infant mortality rate and crime rate. A particular interesting variable used is the crime rate of countries. This variable has been rarely used in measuring the level of socioeconomic development. However, it is an important variable because it examines a problem that has been common among new democracies that are coming from an authoritarian tradition. The measurement examines how much crime occurs in these newly emerging democracies. A problem that is well-documented in case study literature among emerging democracies. Scholars point out that this problem occurs because many of these countries’ police forces are ill equipped to handle the crime problems associated with market-based democracies. In the previous regimes, the police forces’ main task was to repress the population which is very different from preventing crimes in a free society. Finally, the study controlled for nations that were in Central Asia (Kazakstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan) to examine whether their particular Islamic histories have caused them to have unique results.

In the first step, factor analysis was used to measure the commonality of the indicators of socioeconomic development. The independent variables of national income, infant mortality rate, and crime rate were included in the statistical analysis. For these variables, two groups of factors were extracted as the result of initial factor analysis. As Table 1 shows, the first two factors are able to explain 92.5 % of the variation.

By using these factors, a factor analysis with varimax rotation was performed on the original variables. The correlations of the original variables with the factors extracted are shown in Table 2. According to these results, we can name the factors depending on the loadings that the original variables score on the factors. Factor 1 signifies high loadings for the infant mortality rate variable; thus, we named it the quality of life variable. Also, Factor 2 represents how much crime is associated with the level of socioeconomic development.

We can interpret the results of the factor analysis by comparing factor scores and the values on the original variables for each individual country. In this respect, a state scoring high on the factors is quite likely to carry high values on the original variable, infant mortality rate or crime rate. For example, Belarus received a score of -1.27140 on Factor 1, the quality of life variable, as opposed to Tajikistan with the score of 1.42970 on the same factor. Their values on the original variables conform to this variation: Tajikistan is one of the countries with high infant mortality rates among the CIS countries while Belarus not only has lower infant mortality rates of but also has a steady decline across time. Therefore, a nation scoring high on Factor 1 (the infant mortality rate) means that it has a low level of socioeconomic development.

The same relationship between factor scores and the values for the original variables can be found valid for the Factor 2 variation as well. We can assume that the states that have high scores on Factor 2 are likely to have high values on the variables pertaining to crime rates. Russia leads the way with its highest score of 2.000775 on Factor 2, which reflects its crime rates are the highest among the CIS countries. Uzbekistan, on the other hand, has a low score on Factor 2,

-.69243, in line with its low crime rates.

It should be noted that those countries with high scores on Factor 1, and thus, high values on the infant mortality rate tend to have low values on the crime variables. In other words, the lower the level of socioeconomic development, the lower the crime rates. Russia, for example, had scored -.22398 on Factor 1 corresponding low values on the original variable. Nevertheless, its score on Factor 2 was the highest while Uzbekistan had one of the lowest scores of the Factor 2 ( -.69243) with significantly low rates of crime.

While the states’ scores on the original variables have been found relevant to both factors, it was significant that Factor 1 tended to be more powerful in terms of explaining variation than Factor 2. This is confirmed by the finding that Factor 1 alone is able to explain 74.746 percent of the variation on the original variables whereas Factor 2 brings this percentage to the cumulative value of 92.352 percent (Eigenvalues: Factor 1=9.717, Factor 2=2.289). Also, as a general tendency, Central Asian countries have been found scoring high on Factor 1 and low on Factor 2 pointing out the high infant mortality rates and low crime rates.

After the reduction of the independent variables to the factors, we used discriminant function analysis to examine whether we can predict the level of freedom of the states from the scores on the two factors. Before doing that, we grouped the states under two categories according to their cumulative points on freedom level. The mean value of 43.5 was used to place the states into the groups. Under this method, four states those in Central Asia except Kyrgyzstan were classified as "more authoritarian," while the other seven states were listed as "less authoritarian." Then, we used discriminant analysis to predict these listings based on the factor variables, that is, the correlation between the quality of life and crime, and democracy.

The statistical analysis showed a significant relationship (Rao’s V= .0003). Table 2 shows the percentage of correctly classified group listings. According to these results, the discriminant analysis was able to predict all of the "less authoritarian" states, while this success was 85.7% in the case of "more authoritarian" states, which is still a significant prediction power. The analysis has also shown that Factor 1, quality of life variable, is more powerful than Factor 2, crime variable, in terms of increasing the level of prediction (when only Factor 2 was included in the discriminant analysis, the significance value, Rao’s V, was .0397, while the inclusion of the Factor 1 increased this value to .0003, which is highly significant).

Table 3.

Table 4 includes discriminant scores and the estimated group listings in relation to the actual group listings under the authoritarian dichotomy. Using the discriminant scores, it is possible to predict correctly how each state might score on the original variables. The scores show that nations that are likely to have higher discriminant scores will probably have lower values on the quality of life variable and have higher values on the crime variable. This means that less authoritarian states tend to have low infant mortality rates and high levels of crime. This model fits quite significantly to Russia. Its discriminant score is the highest, thus implying low values on the quality of life variable and high values on the crime variable. The actual scores for Russia are in fact in this direction: it has the lowest rate of infant mortality and the highest rate of crime. Thus, the inclusion of the quality of life variables in the analysis of democratization, and, to a much lesser extent, crime rates certainly increases the prediction power.

Among all the countries, Kyrgyzstan has been placed into the more authoritarian group, while it was less authoritarian according to the experts. One explanation for that is Kyrgyzstan’s unique experience of successful democratization in relation to other Central Asian countries: despite the absence of economic development and increased living standards, Kyrgyzstan is on the way to overcome the structural problems to more freedom. Thus, it is the only country that does not fit the theory to be explored through this analysis.

One interesting result of this analysis has been that crime rates vary with the level of freedom: the higher the level of freedom the higher the crime rates. This suggests that democracies are vulnerable to high levels of crime even though they are more likely to be more developed countries with increased living standards. The first notion could be that authoritative states are successful in discouraging tendencies in the society for crime. However, they fail to provide a satisfying level of quality of life to their populace. Thus, there is a need to further explanations in the face of the immediate disadvantage of democratization in the form of high crime rates.

Whether the variables taken as related to the level of freedom have the power to explain, the variation was the question that the research attempted to answer. As seen in the Table 3, the discriminant function analysis, by using these variables, could place ten countries out of eleven on their actual groups determined through the Freedom House reports. (The percentage of "cases" correctly classified is 90.91%.). This analysis shows that, by knowing the variation of the countries on the indicators of quality of life, we can predict their level of freedom in a significantly high rate. Even though the quality of life is not a perfect equivalent to the level of economic development, it can be concluded that the Soviet Republics like countries in other studies need a considerable amount of economic development to secure a certain degree of quality of life. Further research is needed to confirm whether this result occurs beyond the cases examined in this study. As the findings suggest with the Central Asian Republics, there could be other attributes that explain the differences on freedom, let it be cultural or social. The findings indicate that the movement from authoritarianism toward a democratic and free political system in some way needs to consider the implications of quality of life provided for people in these nations.

Finally, the study shows considerable evidence that these nations have obtained increased levels of democracy with a cost. This cost being increased crime levels. This finding should concern domestic policy markers since their governments’ inability to control their crime rates may undermine the public support for the economic and political reforms. As a matter of policy for Western nations trying to encourage democracy in these nations, it may be wise for them to develop programs in conjunction with the host countries to prevent and control crime.

Footnotes

1. Samuel Huntington, The Third Wave (Norman: University of Oklahoma Press, 1991).

2. Larry Diamond, ‘Economic Development and Democracy Reconsidered’, American Behavioral Scientist, Vol. 35 (1992), p. 451.

3. Seymour Martin Lipset, Political Man (New York: Double Day & Company, 1959), p. 67.

4. Barrington Moore, Social Origins of Dictatorship and Democracy (Boston: Beacon Press, 1993), p. xxii-xxiii.

5. The following are bivariate studies that showed a positive correlations between socioeconomic development and democracy using cross-tabulations: James. S. Coleman, ‘Conclusion: The Political Systems of Developing Areas’, in Gabriel. A. Almond and James. S. Coleman (eds). The Politics of Developing Areas (Princeton, NJ: Princeton University Press, 1960); Phillips Cutright, ‘National Political Development Measurement and Analysis’, American Sociological Review, Vol. No. 28 (1963); Samuel Huntington, ‘Will More Countries Become Democracies?’, Political Science Quarterly, Vol. 99 (1984); Seymour Martin Lipset, Political Man: The Social Bases of Politics (Baltimore: Johns Hopkins University Press, 1981); M. E. Olsen, ‘Multivariate Analysis of National Political Development’, American Sociological Review, Vol. 35 (1968); Bruce M. Russet, Trends in World Politics (New York: Macmillian, 1965).

6. Phillips Cutright and James A. Wiley, ‘Modernization and Political Representation: 1927-1966', Studies in Comparative International Development, Vol. 5 (1969).

7. Kenneth A. Bollen, ‘Political Democracy and the Timing of Development’, American Sociological Review, Vol. 44 (1979); Kenneth A. Bollen, ‘World System Position, Dependency and Democracy: The Cross-National Evidence’, American Sociological Review, Vol. 48 (1983); Kenneth A. Bollen and Robert W. Jackman ‘Political Democracy and the Size Distribution of Income’, American Sociological Review, Vol. 50 (1985); Gregory G. Brunk, Gregory A. Calderia and Michael S. Lewis-Beck ‘Capitalism, Socialism, and Democracy: An Empirical Inquiry’, European Journal of Political Research, Vol. 15 (1987); Robert W. Jackman, ‘On the Relationship of Economic Development and Political Performance’, American Journal of Political Science, Vol. 17 (1973).

8. M. T. Hannan and G. R. Carroll, ‘Dynamics of Formal Political Structure: An Event History Analysis’, American Sociological Review, Vol. 46 (1981).

9. M. T. Hannan and G. R. Carroll.

10. G. M. Thomas, F. Ramirez, J. W. Meyer and J. G. Gobalet, ‘Maintaining National Boundaries in the World System: The Rise of Centralist Regimes’, In J. W. Meyer and Michael Hannan (eds.). National Development and the World System (Chicago: University of Chicago Press 1979).

11. Zehra F. Arat, ‘Democracy and Economic Development: Modernization Theory Revisited’, Comparative Politics, Vol. 21 (1988). Lev S. Gonick and Robert M. Rosh, ‘The Structural Constraints of the World-Economy on National Political Development’, Comparative Political Studies, Vol. 21 (1988).

12. Zehra F. Arat.

13. Lev S. Gonick and Robert M. Rosh.

14. Arthur Banks, Cross-National Time-Series Data Archive (Binghamton: State University of New York, 1979); Kenneth A. Bollen; Ross E. Burkhart and Michael S. Lewis-Beck, ‘Comparative Democracy: The Economic Development Thesis’, American Political Science Review, Vol. 88 (1994).

15. Ross E. Burkhart and Michael S. Lewis-Beck.

16. Ross E. Burkhart and Michael S. Lewis-Beck, p. 907.

17. Jack E. Vincent and Sean McCluskie, ‘Promoting Political Liberties Through Quality of Life’, International Journal of World Peace, Vol. 14 (1997).

18. Samuel Huntington, p. 63.

19. Seymour Martin Lipset, K. R. Seong and J. C. Torres, ‘A Comparative Analysis of Social Requisites of Democracy’, Unpublished Paper (Stanford University, Hoover Institution 1991), pp. 465-466 cited in Larry Diamond (1992).

20. Adam Przeworski and Fernando Limongi, ‘Modernization: Theories and Facts’, World Politics, Vol. 49 (1997).

21. Adam Przeworski and Fernando Limongi.

22. Grigory Tavlinsky, ‘Russia’s Phony Capitalism’, Foreign Affairs, Vol. 77 (1998); Kurt Weyland, ‘The Politics of Corruption in Latin America’, Journal of Democracy, Vol. 9 (1988).

23. Kurt Weyland.

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