The Diverging Economic Dynamics of Dictatorships: Enlightened Rule and Tyranny?[1]
Draft Working Paper, 2008. Department of Political Science, University of Oslo
Carl Henrik Knutsen
Abstract
This paper analyzes the question of why dictatorships diverge so much in their economic outcomes. First, the hypothesis of large economic divergence among dictatorships is investigated empirically, by looking at GDP per capita growth rates, and is found to be strongly supported by the data. Then, a theoretical model is constructed and analyzed, and the model points to some crucial mechanisms that might explain the result. Rational autocrats motivated by personal power engage in widely different strategies and conduct very different economic policies in different contexts. The central explanatory variable is the nature of the security threat facing the dictator and his regime. If the security threat is mainly external, for example a neighboring country and its army, the dictator will have incentives to conduct growth- and development enhancing policies. If the nature of the security threat is mainly internal, for example a rebel movement or a democracy movement, the dictator can have strong incentives to hinder economic development. The model also makes other predictions, like for example that a vast amount of natural resources in a country reduces the dictator’s incentives to develop the economy. Some statistical evidence and historical examples are presented to illuminate the relevance of the model. In particular, the history of how the Kuomintang switched from a predatory strategy when fighting the Communists in the Chinese civil war to a developmentalist strategy once it had established itself on Taiwan is treated. This historical “quasi-experiment”, involving the same actors in two different specified contexts, gives strong support to the validity of the model presented in the paper.
1. Introduction
In “Politics”, Aristotle wrote that the best possible form of government under ideal conditions was enlightened Monarchy, with the benevolent and knowledgeable monarch at the helm (Aristotle, 2000). Aristotle also describes how monarchy easily slides into a form of government he labeled “Tyranny”, for example when the Monarchy faces the unavoidable event of monarchic succession, with the death of the old king. Therefore, Aristotle concluded that other and more “balanced” forms of government like his “Politeia” would be more robust in the sense that they provide decent rule under different contexts. Aristotle based his analysis on observations of ancient Greek city states, but his analysis could perhaps also be used fruitfully in order to explain trajectories in the more recent history of dictatorial nation states. One key insight is how concentration of power in dictatorships brings about very divergent outcomes in different empirical settings. Aristotle however focused on the virtues of rulers. In this paper, I will show that even if all rulers are self-interested and motivated by power, some autocratic states will prosper economically, while others will face developmental disasters. The key claim is that rulers choose very different policies in different contexts, and what seems like “Enlightened Monarchs” to the outside observer might very well be self-interested dictators, who due to accident do things that have “good” consequences for their subjects.
Dictatorships exhibit far more variation in their empirical performances than democratic regimes (Rodrik, 2000). You have the present-day Chinas and the Singapores; the growth miracles that make the Lee-thesis (on the necessity of authoritarian rule for development) resonate with many academics and politicians. Then you have the North Koreas and the Zaïres; primary examples for the hypothetical course: “How to destroy your economy 101”. Adam Przeworski (2007) claims that “[W]e currently do not do a good job distinguishing one dictatorship from the next” and that “[D]ictatorships are by far the most understudied area in comparative politics. We need to start thinking about them”. As Robert Barro puts it, it is clear that we have two types of dictatorships when it comes to how they produce economic outcomes. However, the necessary theory for explaining why this is so is not yet fully developed (Barro, 1997:50). This paper seeks to provide such a theory and give explanations to the puzzle of how and why dictatorship produces so wildly diverging economic results. Why do some autocratic regimes become growth miracles whereas others turn out as growth disasters? The underlying assumption is that the actions and policies promoted by dictators explain a large share of the variation in growth and development performances. Social scientists studying growth have turned their focus towards institutions as a primary mover of developmental outcomes, and this is obviously important also for understanding how dictatorships work (Przeworski, 2007). However, institutions are endogenous, and can be affected by the actions taken by rulers and other important actors in a country, and this insight is crucial in the following paper. In this paper, rulers are portrayed as motivated mainly by the concern of staying in power. This motivation leads to very different strategies in different contexts, and thereby affects the overall economy in extremely different ways.
2. The modern empirical record: Dictatorship, democracy and variation in outcomes.
Before explaining the phenomenon of large economic variation among dictatorships, we have to set the record straight in terms of examining whether relatively autocratic regimes actually have had more disparate economic outcomes than more democratic regimes in general. Anecdotal evidence can be provided in abundance: Think of modern-day China compared with China under the Great Leap forward. Think of the Taiwanese and South Korean experiences and compare them with that of Pol Pot’s Cambodia or North Korea under Kim Jong Il. According to Mueller, “[T]he greatest advantage of democracy over dictatorship may not be that democracies outperform dictatorships on average, but that democracies seldom sink to the depth of misery that one too often observes under dictators” (Mueller, 2003: 425).
Data on growth rates in GDP per capita (1970-2000) from the Penn World Tables (PWT) show that dictatorial countries figured heavily both among the best and worst performances. Table 1 shows that 11 out of the 15 best performances had an average score on the Freedom House Index (FHI) above 3,5, and the same was true for 14 of the 15 worst performers. Dictatorships dominate both among the best and the worst performing countries.
Table 1: Top and bottom fifteen growth performers.
Best performers / Worst performersCountry / Average annual growth 1970-2000 / Average FHI 1972-2000 / Country / Average annual growth 1970-2000 / Average FHI 1972-2000
Taiwan / 6,7 / 4,1 / Zaïre/Congo / -4,8 / 6,4
Singapore / 6,4 / 4,7 / Angola / -2,6 / 6,6
Botswana / 6,3 / 2,3 / Central Afr Rep / -2,6 / 5,6
South Korea / 6,1 / 3,7 / Nicaragua / -2,4 / 4,3
China / 5,2 / 6,6 / Sierra Leonne / -1,8 / 5,3
Thailand / 4,7 / 3,6 / Niger / -1,5 / 5,8
Cyprus / 4,4 / 1,9 / Mozambique / -1,5 / 5,6
Ireland / 4,4 / 1,1 / Comoros / -1,4 / 4,6
Mauritius / 4,3 / 2,0 / Venezuela / -1,4 / 2,1
Haiti / 4,3 / 5,9 / Zambia / -1,3 / 4,7
Indonesia / 4,2 / 5,3 / Togo / -1,2 / 6,0
Malaysia / 4,2 / 4,0 / Madagascar / -1,1 / 4,4
Cape Verde / 4,0 / 4,1 / Mauritania / -0,6 / 6,2
Seychelles / 3,7 / 4,7 / Nigeria / -0,6 / 4,9
Romania / 3,7 / 5,3 / Cote d´ Ivoire / -0,6 / 5,4
If we now look into the variances in growth performances among all recorded autocratic and democratic regimes on a decade-wise basis, there is reasonable evidence for the hypothesis that there is more variation among dictatorships than among democracies. Tables 3, 4 and 5, which are taken from Knutsen (2006), show the variance in national growth rates in different categories of regimes along the democracy-dictatorship continuum, based on the FHI. When using the dichotomous classification (classification-criteria are given in the table), F-tests (two-sided) show that the discrepancies in variances between the groups are significantly different from zero at the 5% level for all the decades, and it is significant even at the 0,1%-level in the 1970’s and 1990’s. When comparing the two extreme cases from the trichotomous classification, the p-value for the 1980’s statistic is 0,051, just above the 5% significance level, whereas the divergence in variance between the groups is significantly different from zero at the 1%-level for the 1970’s and 0,1%-level for the 1990’s. These tests provide convincing support for the hypothesis that dictatorships vary more in their economic growth performances than do democracies.
Table 2: Degree of democracy and variation in PWT growth rates in the 1970’s
Average FHI / Number / Variance growth / Average FHI / Number / Variance growth[1, 4) / 45 / 3,40 / [1, 3) / 35 / 3,95
[4, 7] / 68 / 8,92 / [3, 5] / 31 / 6,45
(5, 7] / 47 / 8,81
Table 3: Degree of democracy and variation in PWT-growth rates in the 1980’s
Average FHI / Number / Variance growth / Average FHI / Number / Variance growth[1, 4) / 61 / 4,81 / [1, 3) / 47 / 4,41
[4, 7] / 61 / 8,09 / [3, 5] / 29 / 6,98
(5, 7] / 46 / 7,15
Table 4: Degree of democracy and variation in PWT-growth rates in the 1990’s
Average FHI / Number / Variance growth / Average FHI / Number / Variance growth[1, 4) / 88 / 4,38 / [1, 3) / 66 / 3,42
[4, 7] / 56 / 15,00 / [3, 5] / 46 / 5,92
(5, 7] / 32 / 22,34
However, the results above might be driven by omitted variables that impact both the probability of having a specific regime type and the variation in growth performances. One such factor could be for example the prior level of development in a country. I therefore propose a better test methodologically for investigating the hypothesis related to variation; a so-called Goldfeld-Quandt test of heteroskedasticity (Greene, 2003:223). I want to look at how observations are spread along a regression line, derived from a regression model proposed in Knutsen (2008). The regression equation is given below, and the independent variables are PPP-adjusted GDP per capita, log of population, dummies for plurality religion, geographic region and colonizer, as well as the log of regime duration (+1), share of population in urban areas, energy production/GDP and a linear time trend:
The dependent variable, namely growth in GDP per capita, is now operationalized by using data from the World Development Indicators, and the data are from 1972 to 2005. I run OLS with Panel Corrected Standard Errors, with country-year as unit of analysis. The calculation procedure of the standard errors takes into account autocorrelation (AR1), contemporaneous correlation and heteroskedasticity between panels. I then subtract the predicted values from the actual values of economic growth per capita, and square this difference, to obtain the squared residuals. I then perform the Goldfeld-Quandt test to see if there is reason to reject a H0 of homoskedasticity when comparing the subgroups of observations classified after regime type. First I check the dichotomous classification used above, categorizing all observations with FHI larger than or equal to four as dictatorships, and the rest as democracies. The F-value is 2,54 (1390, 1572 degrees of freedom), and the hypothesis of equal variation can be rejected even at the 0,01%-level. I then compared the group with FHI above or equal to 5,5 on the FHI with those observations that had FHI less than or equal to 2,5 on the FHI. The F-value (789,1214 df) is 3,52, which is even higher than the F-value for the value based on the dichotomous classification, and the test shows that the hypothesis of equal variation can be rejected at the 0,01%-level[2].
From this analysis, there is good reason to reject the claim that there is similar spread along the regression line for both relatively democratic and relatively autocratic regimes. The evidence points in favor of the hypothesis presented above, namely that there is systematically higher variation among dictatorships, and this result holds even if we control for a host of other factors. The analysis points out that not only do dictatorships grow significantly less on average than democracies according to the model (Knutsen, 2008), but autocratic regimes are also scattered more widely around their model-predicted values; they show much more variation. This is the empirical fact that will be sought explained in this paper.
3. Concentration of power in dictatorships
It is hard to argue with Overland et al. in their statement that “[G]ood policy analysis should acknowledge the realities of dictatorships” (Overland et al., 2000:2). What is it about dictatorship that generates such vastly divergent economic outcomes? Some would automatically respond that it is the broadness of the concept and the lack of nuances in describing all non-democratic regimes as dictatorial, and to a certain extent this insight is a valid one. Dictatorships come in several forms or “types”, from absolute monarchies to one-party states to military regimes (Hadenius and Teorell, 2007). One interesting classification comes from Linz and Stepan (1996), who distinguishes between authoritarian, totalitarian, post-totalitarian and sultanistic regimes. These regimes might be institutionalized in widely different ways, and their political processes are driven by relatively different “logics”. Nevertheless, there are common denominators, and lack of general popular control over public decision making and lack of political equality are two of them (Beetham, 1999). Dictatorships are then often associated with a concentration of political power, when compared to democracies, even if the degree of power concentration varies also within the group of autocratic regimes. Often, in practice, dictatorship is associated with a lack of horizontal power dispersing institutional structures, like checks and balances. Additionally, the vertical accountability links, in the form of free and fair elections and freedom of speech and media, between populace and political elites are lacking. Political rights and civil liberties are often either weakly or selectively protected under autocratic rule.
It is among others in the areas of power concentration and lacking political accountability we have to look when seeking to understand the diverging economic dynamics in different dictatorships. When power is concentrated and accountability is lacking, the scope of possible policies the political elites can follow, if they wish, is much larger than in democracies, where power dispersion and institutional structures like free and fair elections put constraints on the possible policy choices of government. An autocrat bent on producing a high rate of economic growth, can with fewer political constraints than in a democracy, drive through tough economic reforms without fearing popular backlash in the next election and push for a high national savings rate through restricting private and public consumption. However, autocrats can also rampage the economy by stealing, looting and even killing off the human capital (as in Cambodia), without being thrown out of office or the palace. This very general point of power concentration increasing the policy scope is one of the key explanations for the high variation in autocratic economic performance. I will elaborate on the argument and specify potential mechanisms in the rest of the paper.
Institutions matter, but so do actors
I will in this study focus less on institutional structure and divergence in autocratic “types” than what is perhaps appropriate. There is no doubt that institutional structures have important real world effects, and that a complete understanding of the functioning and economic effects of dictatorships would need to entail this insight. However, I offer a very general theory on dictatorship and economic effects, where power concentration and survival strategies are core concepts. There are differences between different types of autocratic regimes, especially when it comes to the first. Some dictatorships are more personalized and some are more institutionalized with for example the party playing a crucial role. In the latter case, it is perhaps most appropriate to view the party, rather than the leading individual, as the actor in the model that will be presented. Intra-party dealings and their effects will then not be explained by the theory. However, it is wrong to believe in complete institutional determinism. The central actors in power can build, reshape or restructure institutions, at least in the long run, and my theory, as I will explain later, is best viewed as a theory of the long run. Haber (2006) claims that the “logic of organizational proliferation” is one of the three main survival strategies of autocrats, and he shows how building organizations that counter the influence and powers of existing ones can enhance the survival of the autocrat. It is however probably easier to crush the influence of a bureaucratic apparatus than to build a well-functioning one, and the “privatization” of states in Africa has been recognized in the Africanist literature, even though the bureaucratic structures that existed from the colonial-era were often little to cheer about. As Evans and Rauch (1999) show, a well-functioning and autonomous bureaucracy is an important factor in promoting economic development, but bureaucratic structures are not exogenously given (think about the differences between present day South and North Korea and how they diverge on this point), they can be restructured and strengthened or weakened (for example by refusing to pay high wages or assigning positions to the dictator’s closest friends) by the political elite in charge. My claim is that due to power concentration in dictatorships, institutional structures are not as difficult to change for dictators as they are for democratic government, but this does of course not mean that institutional structures are plastic in all dictatorships. In the model presented below, we will see that rational dictators engage in different survival strategies, including the shaping and reshaping of institutions as well as in more concrete promotion of specific economic policies. My argument is to a certain extent therefore classifiable as what Paul Pierson (2004) has labeled “actor-centered functionalism”: An actor sets up or alters (or destroys) an institution because the effects of the institutional change are viewed as beneficial for the actor. As Pierson notes, this requires rational behavior and a good understanding of how the institution works, and also a relatively long time horizon (which fits well with my claim that the model presented below is a long run model).
4. Previous research on rational dictators and the economy
Political economic research has generally been focused towards explaining the interrelations between politics and the economy in democracies. There are however credible exceptions, both among less formalized studies in political science and among more formalized studies from political scientists and economists. I will focus on the more formalized literature here.