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⁹ See Appendix 1 for descriptive statistics on polarization and growth. The EBRD's Transition Report 1999 notes laconically that growth rates in the region “can lack precision.” It also notes that some countries incorporate estimates of the size of the informal economy into their growth rates. The growth data presented here are likely the best available and have been widely used. European Bank for Reconstruction and Development, Transition Report (London: EBRD, 1999), 188Google Scholar. In the quantitative analysis, I introduce a correction to the growth data that attempts to account for the size of the informal economy. See fn. 60.

¹⁰ Schroeder, Gertrude, “Economic Transformation in the Post-Soviet Republics,” in Kaminski, Bartlomiej, ed., Economic Transition in Russia and the New States of Eurasia (Armonk, N.Y.: M. E. Sharpe, 1997)Google Scholar.

¹¹ Giovanni Sartori defines a polarized party system by the ideological distance between parties, but such precise measures are unavailable in the postcommunist world. Others measure polarization using indices of social cleavages, such as ethnic fractionalization. These indices assume that cleavages are politically salient, but many cleavages do not translate into political movements. The salience of the excommunist/anticommunist cleavage in the postcommunist cases seems to be quite high. Other types of cleavages, such as ethnic divisions, also do not translate readily into economic policy. For example, nationalist rhetoric aside, Prime Minister Meciar continued the construction of a market economy in Slovakia. Sartori, , Parties and Party Systems (New York: Cambridge University Press, 1976)Google Scholar; Easterly, William and Levine, Ross, “Africa's Growth Tragedy: Policies and Ethnic Divisions,” Quarterly Journal of Economics 82 (November 1997Google Scholar); Keefer, Philip and Knack, Stephen, “Polarization, Politics, and Property Rights” (Manuscript, World Bank, Washington, D.C., 2000)Google Scholar. For a critique of these indices, see Laitin, David and Posner, Daniel, “The Implications of Constructivism for Constructing Ethnic Frac-tionalization Indices,” APSA-CP Nevjsletterfor the Organized Section in Comparative Politics of the APSA 12 (Winter 2001)Google Scholar.

¹² Zyuganov, GennadyMy Russia: The Political Autobiography of Gennady Zyuganov, ed. Medish, Vadim (Armonk, N.Y.: M. E. Sharpe, 1997), pt. 4; Aslund (fn. 7)Google Scholar.

¹³ Ishiyama creates three categories of communist successor parties—standpatter, liberal, and democratic reformist—based on their policy positions in three areas: the economy, the communist past, and the value of democratic competition. Ishiyama, , “Communist Parties in Transition: Structures, Leaders, and Processes of Democratization in Eastern Europe,” Comparative Politics 27 (January 1995)CrossRefGoogle Scholar; idem, , “The Sickle or the Rose: Previous Regime Types and the Evolution of Ex-Communist Parties,” Comparative Political Studies 30 (June 1997)Google Scholar.

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¹⁵ Alesina and Drazen (fn. 4).

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¹⁷ More formally, two players bargain over an asset and choose to fight or not fight. If neither fights, each receives 0. Fighting is costly so each player must pay a cost, c, and the winner receives a prize, w. Each is uncertain about the costs the other side can bear. As long as w > 0 > c, each party prefers to fight and receive w-c, rather than not fight. Given these incentives, each chooses to fight in hopes of shifting the costs of transformation to their opponents. The result is a war of attrition.

¹⁸ Alesina and Drazen (fn. 4).

¹⁹ Hellman (fn. 3); Frye, Timothy, “Presidents, Parliaments and Democracy: Insights from the Post-communist World,” in Reynolds, Andrew, ed., The Architecture of Democracy: Constitutional Design, Conflict Management, and Democracy (New York: Oxford University Press, 2002).Google Scholar

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²¹ One anecdote highlights this dynamic. A Russian oligarch recounted to a journalist that in early February 1996 at the Davos meetings of the World Economic Forum, George Soros told him: “'Boys, your time is over. You've had a few good years but now your time is up.' His [Soros's] argument was diat the communists were definitely going to win. We Russian businessmen, he said, should be careful that we managed to get to our jets in time and not lose our lives.” Freeland, Chrystia, The Sale of the Century: Russia's Wild Ridefrom Communism to Capitalism (New York: Random House, 2000), 192.Google Scholar

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²⁴ Przeworski (fn. 1).

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²⁸ Here I treat a polarized country as having at least 20 percent of the seats held by a traditional ex-communist (anticommunist) party when the executive is held by an anticommunist (ex-communist) in a given year.

²⁹ Bresser-Perreira, , Maravall, , and Przeworski, , Economic Reforms in New Democracies: A Social-Democratic Approach (New York: Cambridge University Press, 1993)Google Scholar.

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³¹ This threshold, although a convention, is nonetheless somewhat arbitrary. I estimate model 1 after redefining the threshold for democracy as (a) 3 and lower, (b) 4 and lower. Doing so does not alter the results. Data are available at Freedom House, Annual Survey of Freedom Country Scores, 1972/73–1998/99 (www.Freedomhouse.org). Similar results are obtained using updated POLITY III scores for democracy, which are then treated as a dummy variable with the technique advocated by Jaggers, Keith and Gurr, Ted Robert; Jaggers, and Gurr, , “Tracking Democracy's Third Wave with the Polity III Data,” Journal of Peace Research 32 (November 1995)CrossRefGoogle Scholar.

³² Bresser-Pereira, Maravall, and Przeworski (fn. 29). That government spending as a portion of GDP is relatively high indicates nothing about the content or beneficiaries of that spending.

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³⁴ EBRD (fn. 9).

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³⁶ Aslund, Boone, and Johnson (fn. 6) argue that economic performance in the former Soviet republics may differ from that in other states in the region due to “different underlying structural factors, such as the greater reliance on military-industrial production, a longer history of communism, greater reliance on trade within the communist bloc, and membership in the ruble zone when control over money creation disintegrated.”

³⁷ Aghion and Howitt (fn. 33).

³⁸ Barro (fh. 35).

³⁹ Christopher Achen critiques this strategy for addressing temporal dependence, on the grounds that the lagged endogenous variable may substantially deflate the impact of other independent variables. The results of the argument are stronger when the lagged dependent variable is dropped. Achen, “Why Lagged Dependent Variables Can Suppress the Explanatory Power of Other Independent Variables” (Paper presented at the annual meeting of the Political Methodology Section of the American Political Science Association, Los Angeles, July 2000).

⁴⁰ The former Soviet countries enter the data set in 1992 after the fall of the Soviet Union.

⁴¹ Because the units outnumber the years in the data by more than 2:1, I do not employ the correction suggested by Beck, Nathaniel and Katz, Jonathan; Beck, and Katz, , “What to Do (and Not to Do) with Time-Series-Cross-Section Data in Comparative Politics,” American Political Science Review 89 (September 1995)CrossRefGoogle Scholar.

⁴² Long and Ervin show that in samples of fewer than 250 observations Ordinary Least Squares (OLS) regression may produce inconsistent standard errors. They propose a correction that is more appropriate for small samples. Results from this analysis are slightly stronger when opting for the more traditional approach of using robust standard errors with clustering on country. I am thankful to an anonymous reviewer for alerting me to this article. Long, and Ervin, , “Using Heteroscedasticity Consistent Standard Errors in the Linear Regression Model,” American Statistician 54 (August 2000)Google Scholar.

⁴³ Dropping this threshold to 15 percent does not alter the results presented in columns 3 and 4 in Table 2. The polarization measure retains its sign and significance with this new coding.

⁴⁴ Ishiyama (fn. 13).

⁴⁵ Haggard and Kaufman (fn. 14) consider a party system polarized if an antisystem or anticapitalist party has 15 percent of the seats in parliament.

⁴⁶ National elections here include parliamentary elections in a parliamentary system and presidential elections in a presidential system.

⁴⁷ Declining growth rates in parliamentary systems may hasten calls for an election, thus suggesting the potential endogeneity of growth and elections. However, it is notable that declining growth seems to have no effect on elections in nonpolarized countries.

⁴⁸ As Ross Levine and David Renelt note: “There does not exist a consensus theoretical framework to guide empirical work on growth, and existing models do not completely specify the variables that should be held constant while conducting statistical inference on the relationship between growth and the primary variables of interest.” See Levine, and Renelt, , “A Sensitivity Analysis of Cross-Country Growth Regressions,” American Economic Review 82 (September 1992), 943Google Scholar; Islam, Nazrul, “Growth Empirics: A Panel Data Approach,” Quarterly Journal of Economics 110 (November 1995)CrossRefGoogle Scholar.

⁴⁹ Shugart, and Carey, , Presidents and Assemblies: Constitutional Design and Electoral Dynamics (New YorkCambridge University Press, 1992)CrossRefGoogle Scholar; Timothy Frye, Joshua Tucker, and Joel Hellman, “Data-Base on Political Institutions in the Post-Communist World” (Data set, Columbus, Ohio, 2001). Herbert Kitschelt and Edward Malesky offer a conditional theory of the effects of presidential power on economic performance in the postcommunist world. They argue that countries with weak economic prospects choose strong presidencies, and thus the effect of presidential power is conditional upon initial prospects. Testing the argument would seem to require a model different from the one proposed here. See Kitschelt and Malesky, “Constitutional Design and Post-Communist Economic Reform” (Paper presented at the annual meeting of the Midwest Political Science Association, Chicago, April 2000).

⁵⁰ For a discussion of elite policy preferences based on their political base, see Geddes, Barbara, “Douglass C. North and Institutional Change in Contemporary Developing Countries,” in Alt, James E., Levi, Margaret, and Ostrom, Elinor, eds., Competition and Cooperation: Conversations with Nobelists about Economics and Political Science (New York: Russell Sage Foundation, 1999)Google Scholar.

⁵¹ For more detail on the definition of these and other variables, see Appendixes 2 and 3.

⁵² Roubini, and Sachs, , “Government Spending and Budget Deficits in the Industrial Countries,” Economic Policy 8 (April 1989)Google Scholar; and idem, , “Political and Economic Determinants of Budget Deficits in the Industrial Democracies,” European Economic Review 33 (1989)Google Scholar.

⁵³ Hellman (fn. 3); EBRD (fn. 9).

⁵⁴ The International Monetary Fund 2000 (www.Imf.org/external/np/tre/tad); Stone, Randall, Lending Credibility: The International Monetary Fund and the Post-Communist Transition (Princeton: Princeton University Press, 2002)CrossRefGoogle Scholar.

⁵⁵ DeMelo, Martha, Denizer, Cevdet, and Gelb, Alan, From Plan to Market: Patterns of Transition, World Bank Policy Research Paper (Washington, D.C., 1996)Google Scholar; Popov, Vladimir, “Shock Therapy versus Gradualism: The End of the Debate (Explaining the Magnitude of The Transformational Recession),” Comparative Economic Studies 42, no. 1 (2000)CrossRefGoogle Scholar.

⁵⁶ I had to drop the fixed effects for countries and years due to the small sample sizes in these estimations.

⁵⁷ Measures of corruption and institutional quality are not directly included in the model but are often correlated with the wealth of a country. In addition, polarization may foster corruption and weak institutions by heightening incentives to lobby to prevent changes in policy from affecting your firm.

⁵⁸ There is great debate about the inclusion of fixed effects—dummy variables for countries or years—in models such as this. Some argue that including fixed effects reduces the potential for omitted variable bias, while others argue that there is little theoretical basis to includefixedeffects and that the cure is usually worse than the disease. See Symposium on Research Design and Methods in International Relations, International Organization 55 (Spring 2001)Google Scholar.

⁵⁹ The dummy variable FSU_it is a rather crude indicator of the institutional legacy of a Soviet polity. Many aspects that set the former Soviet republics apart are captured in other variables, for example, GDP per capita, miles from Vienna, government spending, and so on. The effects of membership in the former Soviet Union should also be captured by the country-specific fixed effects. One problem with the FSU variable is that it is constant over time. A somewhat more refined measure includes a dummy variable for each year that countries are in the ruble zone. This variable is not significant when added to the base model.

⁶⁰ The size and significance of the results are essentially unchanged using a correction for growth rates that takes into account the size of the informal economy. Marcelo Selowsky and Ricardo Martin calculate growth rates after increasing the GDP by the fraction x_lt/3 (for FSU countries) or x_lt/10 (for other countries), where x_lt = the share of private sector output in GDP. They take their estimates for the size of the informal economy from the EBRD's Transition Report (fn. 9). See Selowsky, and Martin, , “Policy Performance and Output Growth in the Transition Economies,” American Economic Review Papers and Proceedings 87 (May 1997)Google Scholar.

⁶¹ To address the possibility of reverse causation further, I conducted an instrumental variable/two-stage least-squares regression analysis by estimating the following system of equations:

In the first stage I use a continuous variable for the size of the population and a dummy variable for the existence of a parliamentary regime as instruments for the continuous measure of polarization. In the second stage, I include variables commonly found in models of economic growth. The effect of political polarization on growth remains statistically significant in this analysis at the .10 level. Because (1) the number of cases is fairly small, (2) the determinants of growth and polarization are poorly understood, and (3) it is difficult to find proper instrumental variables, there is reason to be skeptical of this technique in this setting. Bartels, Larry, “Instrumental Variables and 'Quasi-Instrumental' Variables,” American Journal of Political Science 35 (August 1991)CrossRefGoogle Scholar; Kennedy, Peter, A Guide to Econometrics (Cambridge: MIT Press, 1993)Google Scholar.

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⁶⁴ The Liberalization Index includes two clear policy elements, liberalization in foreign trade and domestic prices. It also includes the size of the private sector, which is harder to classify as a policy element. Nonetheless, the index does include progress in privatization, which is an important policy measure. In addition, reassertions of state control over property—which would affect the size of the private sector—have been common following transitions of political power in polarized countries. Thus, it is important to include the size of the private sector in this index.

⁶⁵ See Appendix 1 for data on annual average changes in the World Bank Liberalization Index.

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⁶⁷ Roubini and Sachs (fn. 52); Frye, Hellman, and Tucker (fn. 49).

⁶⁸ Long and Ervin (fn. 42).

⁶⁹ Again the results are stronger using robust standard errors with clustering on country rather than the HCCM correction suggested by Long and Ervin (fn. 42).

⁷⁰ The relationship between oil and policy volatility is sensitive to the coding of polarization.

⁷¹ Democracy_it and Fragmentation_it are correlated at .45. Dropping either from the analysis individually does not change the results. These results are, however, sensitive to the coding of polarization.

⁷² The Liberalization Index experiences relatively few reversals. Nonetheless, these cases of backsliding seem to be important. Using the average year-on-year increase in the Liberalization Index—rather than the absolute value year-on-year change—as the dependent variable in the regression produces different results. For individual elements of the index, reversals occur ten times and take place in Russia, Ukraine, Romania, Bulgaria, Belarus, and Azerbaijan in years in which the political system is polarized.

⁷³ Timothy Frye, “Russian Privatization and the Limits of Credible Commitment,” in Weimer, David, ed., The Political Economy of Property Rights: Institutional Change and Credibility in the Reform of Centrally Planned Economies (New York: Cambridge University Press, 1997)Google Scholar.

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⁷⁵ Fish (fn. 5); Kopstein and Reilly (fn. 5).

⁷⁶ Aslund (fn. 7); Stiglitz (fn. 2); Mau (fn. 22).

⁷⁷ Nelson (fn. 30); Aslund, Boone, and Johnson (fn. 6).

⁷⁸ Hellman (fn. 3).

⁷⁹ The polarized countries also experience higher increases in income inequality than do nonpolar-ized countries. Data from seventeen countries collected by Branko Milanovich reveal that the average increase in income inequality between 1988 and 1994 was 46 percent in polarized countries and 31 percent in the nonpolarized countries. See Milanovich, , Income, Inequality, and Poverty during the Transition (Washington, D.C.: World Bank, 1998)Google Scholar.

⁸⁰ Shleifer and Treisman (fn. 7).

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