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Democracy and Economic Growth: A Historical Perspective

Published online by Cambridge University Press:  13 June 2011

John Gerring
Affiliation:
Boston University
Philip Bond
Affiliation:
University of Pennsylvania
William T. Barndt
Affiliation:
Princeton University
Carola Moreno
Affiliation:
Boston University

Abstract

Recent studies appear to show that democracy has no robust association with economic growth. Yet all such work assumes that the causal effect of democracy can be measured by a country's regime status in a particular year (T), which is correlated with its growth performance in a subsequent period (T+l). The authors argue that democracy must be understood as a stock, rather than a level, measure. That is, a country's growth performance is affected by the number of years it has been democratic, in addition to the degree of democracy experienced during that period. In this fashion, democracy is reconceptualized as a historical, rather than a contemporary, variable—with the assumption that long-run historical patterns may help scholars to understand present trends. The authors speculate that these secular-historical influences operate through four causal pathways, each of which may be understood as a type of capital: physical capital, human capital, social capital, and political capital. This argument is tested in a crosscountry analysis and is shown to be robust in a wide variety of specifications and formats.

Type
Research Article
Copyright
Copyright © Trustees of Princeton University 2005

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References

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49 Correlations between Polity2 and other democracy indices (introduced below in the text) are as follows: “Political Rights” (Freedom House) = -.85; “Liberal Democracy” (Bollen) =.92; “Democracy index” (Vanhanen) = .85.

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52 We see no reason to suppose that a longer period of measurement—which might, in principle, stretch back to 1850—would alter any of the findings presented here.

53 This recoding affects the following countries: Albania (1900–1912, Ottoman Empire), Andorra (1900-present, France), Armenia (1900–1990, Russia/USSR), Azerbaijan (1900–1990, Russia/USSR), Belarus (1900–1990, Russia/USSR), Bosnia-Herzegovina (1908–17, Austria-Hungary; Yugoslavia 1929–91), Croatia (1900–1917, Austria-Hungary; Yugoslavia, 1929–91), Czech Republic (1900–1917, Austria-Hungary), Slovakia (1900–1917, Austria-Hungary), Estonia (1900–1916 and 1941–90, Russia/USSR), Finland (1900–1916, Russia), Georgia (1900–1990, Russia/USSR), Iraq (1900–1917, Ottoman Empire), Palestine/Israel (1900–1917, Ottoman Empire), Kazakhstan (1900–1990, Russia/USSR), Kyrgyzstan (1900–1990, Russia/USSR), Latvia (1900–1917 and 1941–90, Russia/USSR), Lithuania (1900–1917 and 1941–90, Russia/USSR), Macedonia (1922–90, Yugoslavia), Moldova (1900–1945, Romania; 1946–90, USSR), Mongolia (1900–1920, China), Bangladesh (1947–71, Pakistan), Slovenia (1900–1917, Austria-Hungary; 1929–91, Yugoslavia), Syria (1900–1917, Ottoman Empire), Tajikistan (1900–1990, Russia/USSR), Turkmenistan (1900–1990, Russia/USSR), Ukraine (1900–1917 and 1920–90, Russia/USSR), Uzbekistan (1900–1990, Russia/USSR), and East Timor (1976–99, Indonesia).

54 In an alternative coding of this variable we assign a score of -10 (the lowest score on the Polity2 variable) to missing data from preindependence years (rather than the usual default score of 0). The historical variable constructed from this alternative coding procedure shows virtually identical results to those displayed in Table 1. Thus, in fixed-effect tests it does not matter what sort of coding procedure is used to fill in missing data from years prior to a country's independence. These scores, the reader will recall, matter only for the construction of the stock variable; they are not observations in the data analysis (no growth data is available for periods prior to independence).

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70 World Bank (fn. 56).

71 Ibid.

72 These variables are added together to form a composite index (construction by the authors). Monty Marshall, “Major Armed Conflicts and Conflict Regions, 1946–1997,” data set from CIDCM, University of Maryland (1999), obtained via the State Failure Task Force data set, http://gking.har-vard.edu/data.shtml (accessed April 25, 2005).

73 World Bank (fn. 56).

74 We interpolate missing values for illiteracy, life expectancy, and population growth in order to maintain a consistent sample (failing to do so would have significantly reduced the sample size and perhaps biased our results).

75 See Papaioannou and Siourounis (fn. 1); Przeworski et al. (fn. 1).

76 An additional test—not shown—divides the sample into (1) observations where a country registers a “positive” democratic stock (>0) and (2) observations where a country registers a “negative” democratic stock (<0). This tests the possibility that our aggregate results are being driven by influential groups of long-term democracies or long-term autocracies. Reassuringly, the coefficients and standard errors for our key variable, democracy stock, are virtually constant across these two subsamples, suggesting that there is a relatively consistent democratic growth effect for deep autocracies and deep democracies.

77 The number of years that a country growing at rate g takes to double its income is given by ln 2/ln

78 Temporal delays and nonlinear causal relationships are possible only if one moves beyond the realm of interests, opinions, and coercion tout court. For example, if a person does not fully realize his or her true interests then some delay between cause and effect might be anticipated.

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