¹ The earlier evidence is surveyed in Lipset, Seymour Martin, ‘Some Social Requisites of Democracy: Economic Development and Political Legitimacy’, American Political Science Review, 53 (1959), 69–105.CrossRefGoogle Scholar

² Many empirical studies of the effects of democracy on economic growth are reviewed in Sirowy, L. and Inkeles, A., ‘The Effects of Democracy on Economic Growth and Inequality: A Review’, Studies in Comparative International Development, 25 (1990), 126–57.CrossRefGoogle Scholar The extent to which the results depend on country-specific factors is emphasized in Haggard, S., Pathways from the Periphery: Tlte Politics of Growth in the Newly Industrializing Countries (Ithaca, NY: Cornell University Press, 1990), chap. 10.Google Scholar

³ The income measure used is real gross domestic product (GDP) per capita, converted at purchasing power parity exchange rates, using data compiled by national statistical agencies, with the collaboration of the United Nations and the OECD. The features of the Mark V release of the data used in Tables 1 and 2 are described in Summers, R. and Heston, A., ‘The Penn World Table (Mark 5): An Expanded Set of International Comparisons, 1950 to 1988’, Quarterly Journal of Economics, 106 (1991), 327–68.CrossRefGoogle Scholar

⁴ Lipset, , ‘Some Social Requisites of Democracy’, p. 75.Google Scholar

⁵ The data are described in Gastil, R. D., ‘The Comparative Survey of Freedom: Experiences and Suggestions’, Studies in Comparative International Development, 25 (1990), 25–50.CrossRefGoogle Scholar Gastil's separate indices for political rights and civil liberties are each on a scale from 1 to 7, with 1 representing the highest levels of rights, and 7 the lowest. Summing the two indices, as Gastil does in his more recent work, gives a measure that takes the value 2 for the most democratic and 14 for the least democratic systems. This is linearly transformed to make an index for the probability of freedom (PFR), ranging from 0 for no freedoms to 1.0 for fully democratic systems. If FR is the 2 to 14 index, then PFR = (14 – FR)/12.

⁶ These are Bahrain, the United Arab Emirates, Iran, Iraq, Kuwait and Saudi Arabia.

⁷ The R ² rises from 0.634 to 0.635 if the OECD has a separate slope rather than intercept in Equation 2. The coefficient on InGDP falls from 0.122 to 0.120, with an additional income effect of 0.037 for the OECD countries.

⁸ If the level and the square of per capita GDPs are used as explanatory variables, both are strongly significant, in a 125-country cross-sectional equation for the 1985 Gastil index, with the coefficients being positive for the level and negative for the quadratic term. However, if an artificial encompassing model is set up, containing these two variables and the logarithm of real per capita GDP (the variable that is used in the equations reported in Table 1), statistical tests show that there is no significant difference in explanatory power between the quadratic and the logarithmic models, with the data preferring the logarithmic model to the quadratic model. The P-value of the Wald chi-square test for excluding the two variables of the quadratic model is 0.25, while it is 0.21 for excluding the logarithmic variable, with the tests in both cases being of restricted versions of the encompassing equation. If the equation is augmented by adding the separate intercept for the Middle East oil producers, the preference for the logarithmic over the quadratic form is much stronger, with a P-value for the Wald test of excluding the quadratic variables being 0.43, compared to 0.03 for excluding the logarithmic variable. Since the peak of the quadratic is very near the top of the range of GDP per capita, at the levels of Sweden and Australia, the exponential and quadratic forms give very similar predicted values for most countries.

⁹ Dahl, R. A., Polyarchy: Participation and Opposition (New Haven, Conn.: Yale University Press, 1971), pp. 74–5.Google Scholar

¹⁰ This conclusion needs to be treated with some caution, as inclusion of the OECD variable in Equation 6 removes the significance of the education variable, evidence of the fairly high correlation between the two variables. Thus to some extent education and the complex of factors that define members of the OECD are competing for explanatory power, with the OECD variable adding to the equation by slightly more than the schooling variable.

¹¹ In surveying the issues, Bollen concludes that it is important not to confound political liberties and political rights with political stability. He argues that the former two comprise an appropriate measure of political democracy, while the latter is not. The Gastil measures accord with Bollen's preferences, by focusing on political rights and freedoms rather than political stability, and in providing measures whose changes might themselves provide an index of stability. Bollen's views and Gastil's measures both seem to embody key features of Dahl's Polyarchy dimensions of open competition and widespread participation, with individuals protected in their rights to express their political opinions, and free to form parties and to compete in binding elections by unintimidated voters. Both of Gastil's component indices seem relevant, since civil rights and political freedoms are in many respects mutually supportive. There is no evidence that either component has more influence than the other, as Gastil's two component indices give indistinguishable results when used separately. See Bollen, K. A., ‘Issues in the Comparative Measurement of Political Democracy’, American Sociological Review, 45 (1980), 370–90CrossRefGoogle Scholar; and Bollen, K. A., ‘Political Democracy: Conceptual and Measurement Traps’, Studies in Comparative International Development, 25 (1990), 7–24.CrossRefGoogle Scholar

¹² The biggest factor limiting the comparison is that the Gastil indices do not start before the mid-1970s, with the result that there is no overlap in the time periods covered by the Gastil and Bollen indices. In addition, the Bollen index for 1965 is only available for ninety of the ninety-eight countries for which full data are available from 1960 through 1985, and the 1960 index has several fewer observations. To provide as full as possible a sample of the state of democracy for the beginning of the growth period, 1965 values were used to fill out the 1960 sample to ninety countries.

¹³ Huntington reports that the number of democratic states fell from thirty-six in 1962 to thirty in 1973 and has since risen again, to fifty-eight in 1990. Measured as percentages of the total number of states, Huntington calculates that democracies fell from 32.4 percent in 1962 to 24.6 percent in 1973 and rose to 45 per cent in 1990. See Huntington, S., The Third Wave: Democratization in the Late Twentieth Century (Norman: University of Oklahoma Press, 1991).Google Scholar

¹⁴ There are also statistical grounds for being glad to have the unimodal Bollen index available to check the results that use the bi-modal Gastil index as a dependent variable. The Gastil index, like many of the dichotomous measures of democracy, is not normally distributed about its mean. In addition, both indices are bound in the range between zero and 1.0. To avoid the risks of biased standard errors that might arise from the implied non-normality, all OLS equations estimated with either of the democracy indices as the dependent variable makes use of H. White's procedure for estimating standard errors consistently in the presence of heteroskedastic residuals. See White, H., ‘A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity’, Econometrica, 48 (1980), 149–70.CrossRefGoogle Scholar

¹⁵ Although the estimated coefficient for schooling is much smaller for the Bollen equation, it is necessary to bear mind that the 1960 schooling variable is measured as a fraction of population of school age, while the education variable from the growth equation is measured as a fraction of the adult population. When this scale adjustment is made, the coefficients are insignificantly different from one another. If regional variables are added to Equations 1 and 2 of Table 2, they are not significant.

¹⁶ Instrumental variables regression is a single-equation procedure for removing simultaneous equations bias by employing instruments for each of the right-hand-side endogenous variables in the equation. Eligible instruments should be free of any correlation with the error terms in the equation being estimated, yet be closely correlated with the variable for which they are acting as an instrument. The instruments used in this study mainly comprised 1960 observations of a closely related variable. Thus Bollen 1960 was used as an instrument for Gastil 1976, 1960 schooling rates were used as an instrument for average 1960–85 schooling rates, and 1960 investment rates were used as instruments for average 1960–85 investment.

¹⁷ See Sirowy, and Inkeles, , ‘The Effects of Democracy on Economic Growth and Inequality’.Google Scholar

¹⁸ Three studies outside the range of their survey report some evidence of positive effects of democracy on growth; Pourgerami, Kormendi and Meguire, and Grier and Tullock. However, since their measures of democracy were taken late in the growth period under survey, these studies are open to the risk of reverse causation. Attempts to make appropriate adjustments will be reported later in this section and in Table 3. See Pourgerami, A., ‘The Political Economy of Development: A Cross-national Causality Test of the Development-democracy-growth Hypothesis’, Public Choice, 58 (1988), 123–41CrossRefGoogle Scholar; Kormendi, R. C. and Meguire, P. G., ‘Macroeconomic Determinants of Growth’, Journal of Monetary Economics, 16 (1985), 141–63CrossRefGoogle Scholar; and Grier, K. B. and Tullock, G., ‘An Empirical Analysis of Cross-National Economic Growth, 1951–1980’, Journal of Monetary Economics, 24 (1989), 259–76.CrossRefGoogle Scholar

¹⁹ See Solow, R. M., ‘A Contribution to the Theory of Economic Growth’, Quarterly Journal of Economics, 70 (1956), 65–94CrossRefGoogle Scholar, and ‘Technical Change and the Aggregate Production Function’, Review of Economics and Statistics, 39 (1957), 312–20.CrossRefGoogle Scholar

²⁰ See Mankiw, G., Romer, D. and Weil, D., ‘A Contribution to the Empirics of Economic Growth’, Quarterly Journal of Economics, 107 (1992), 407–37.CrossRefGoogle Scholar

²¹ The technology index A is none the less assumed to have the same exogenous growth rate in each country. Alternative convergence models assume that there is also convergence in the rates of growth of the efficiency indices, thus giving international transfers of knowledge a key role to play in the convergence process. Tests of equal versus converging growth rates for the efficiency indices strongly favour the latter, as reported by Helliwell, J. F. and Chung, A., ‘Macroeconomic Convergence: International Transmission of Growth and Technical Progress’, in Hooper, P. and Richardson, J. D., eds. International Economic Transactions: Issues in Measurement and Empirical Research (Chicago: University of Chicago Press, 1991), pp. 388–436.Google Scholar

²² Convergence of growth rates among the current industrial countries has also been shown by Abramovitz, Maddison, Dowrick and Nguyen, and Baumol, among others. The Baumol results were queried by De Long because of the possibility that the tests were likely to be biased by focusing only on the countries that ended up rich. This difficulty is largely avoided by the use of nearly complete samples of countries in subsequent studies, including Mankiw et al. and in this article. See Abramovitz, M., ‘The Catch-up Factor in Postwar Economic Growth’, Economic Inquiry, 28 (1990), 1–30CrossRefGoogle Scholar; Maddison, A., Phases of Capitalist Development (Oxford: Oxford University Press, 1982)Google Scholar; Dowrick, S. and Nguyen, D.-T., ‘OECD Comparative Economic Growth 1950–85’, American Economic Review, 79 (1989), 1010–30Google Scholar; Baumol, W., ‘Productivity Growth, Convergence and Welfare: What the Long-Run Data Show’, American Economic Review, 76 (1986), 1072–85Google Scholar; and De Long, J. B., ‘Productivity Growth, Convergence and Welfare: Comment’, American Economic Review, 78 (1988), 1138–54.Google Scholar

²³ Romer and Lucas, among others, have presented models assuming increasing returns at the national level. Alternative endogenous growth models by Grossman and Helpman assume economies of scale and knowledge spillovers mainly at the industry level, which need not imply returns to scale at the national level. See Romer, P. M., ‘Are Non-Convexities Important for Understanding Growth?’, American Economic Review, 80 (1990), 97–103Google Scholar; Lucas, R. E., ‘Why Doesn't Capital Flow from Rich to Poor Countries?’, American Economic Review, 80 (1990), 92–6Google Scholar; and Grossman, G. M. and Helpman, E., Innovation and Growth in the Global Economy (Cambridge, Mass.: MIT Press, 1991).Google Scholar

²⁴ The dependent variable is the logarithm of real GDP per adult in 1985 minus the logarithm of real income per adult in 1960, following Mankiw et al. The independent variables are the same as in Equation 4, using the logarithm of the gross investment rate to measure the fraction of output invested in physical capital and the logarithm of the percentage of the adult population in secondary school to proxy for the share of output devoted to investment in human capital. The results reported in Table 3 impose the coefficient restrictions implied by Equation 4 in the text, that the coefficient on the population growth term should be equal to the negative of the sum of the coefficients on the investment and education variables. Tests show that the restriction is easily accepted, leads to a slightly higher explanatory power (after taking account of the degree of freedom saved) and does not change any of the results materially, as reported by Mankiw et al. The income data are from the Mark IV version of the Summers and Heston data set. See Mankiw, et al. , ‘A Contribution to the Empirics of Economic Growth’Google Scholar, and Summers, R. and Heston, A., ‘A New Set of International Comparisons of Real Product and Prices: Estimates for 130 Countries, 1950 to 1985’, Review of Income and Wealth, 34 (1988), 1–25.CrossRefGoogle Scholar

²⁵ This is shown by the significant negative coefficients on the variable measuring initial real income per adult, which imply that countries with lower average incomes at the beginning of the growth period had faster growth rates in the subsequent twenty-five years, once account is taken of differences in the rates of investment in physical and human capital.

²⁶ The investment and education variables both have the expected positive sign, although the investment rate is not significant when instrumental variables estimation methods are used.

²⁷ This is shown by the positive coefficient on the variable measuring the average scale of each economy during the sample period. Subsidiary tests show that the result for economies of scale is based entirely on the experience of the OECD countries, and depends on the use of sample-average scale rather than initial scale in the equation. No evidence of scale economies appears when the experience of the developing countries is separately assessed.

²⁸ See Pourgerami, , ‘The Political Economy of Development’.Google Scholar

²⁹ See Sirowy, and Inkeles, , ‘The Effects of Democracy on Economic Growth and Inequality’, p. 137.Google Scholar

³⁰ See Kormendi, and Meguire, , ‘Macroeconomic Determinants of Growth’Google Scholar, and Grier, and Tullock, , ‘An Empirical Analysis of Cross-National Economic Growth, 1951–1980’.Google Scholar

³¹ There is a possibility that civil liberties and political rights have different effects on economic growth, with the former encouraging the movements of people and ideas likely to foster growth and the latter posing greater risks of short-term policy choices leading to instability of the type emphasized in Dombusch, R. and Edwards, S., eds. The Macroeconomics of Populism in Latin America (Chicago: University of Chicago Press, 1991).CrossRefGoogle Scholar However, when the difference between the 1976 civil liberties and political rights indices was added to the ninety-country growth equation of Table 3, it took an insignificant negative coefficient, casting doubt on the idea that civil rights are more growth-inducing than political rights.

³² Following Grier and Tullock, I used all countries with values equal to 6.0 or 7.0 for the Gastil index of civil rights in 1978. The analogous cutoff for the freedom index was 12.0 or more for the sum of the civil rights and political freedoms measures. In both cases, I constructed a Bollen dichotomous index covering the same number of countries. This involved a Bollen index of 0.49 or below for the twenty-two countries with the lowest values of civil rights, and 0.48 or below for the twenty-four countries with the lowest values for the combined Gastil index.

³³ See Huntington, , The Third Wave, p. 14.Google Scholar

³⁴ A similar conclusion is reported by Cooper, based on cases studies of eighteen major developing countries. See Cooper, R. N., Economic Stabilization in Developing Countries (New Haven, Conn.: Yale University Press, 1991), pp. 74–5.Google Scholar

³⁵ See Olson, Mancur jr, The Rise and Decline of Nations: Economic Growth, Stagflation and Rigidities (New Haven, Conn.: Yale University Press, 1982).Google Scholar

³⁶ The countries are Australia, Canada, Finland, Iceland, Ireland, New Zealand, Sweden, Switzerland, United Kingdom and the United States (see Huntington, , The Third Wave, p. 14).Google Scholar

³⁷ The coefficient on the dummy variable covering the ten rich democracies was – 0.065, with a t-value of – 0.4, and the adjusted R ² fell from 0.458 to 0.444.

³⁸ The investment effect is the product of the coefficient on investment in Equation 2 of Table 3 and the coefficient on the Bollen index in Equation 2 of Table 4. The schooling effect uses the schooling coefficient from Equation 2 of Table 3 and the Bollen coefficient from Equation 4 of Table 4.

³⁹ Studies have found a negative linkage between economic growth and the instability of government (Alesina et al.) and the frequency of assassinations and coups (Barro), although Londregan and Poole have found that the significance of the negative effect of coups on subsequent growth becomes slight when the two-way linkages between coups and economic growth are jointly estimated. The results of Alesina et al. suggest that the two-way linkages between political instability and economic growth are unaffected by the level of democracy as measured by a three-valued index of democracy. Using the 1960 values for their index in the Table 3 equation gives similar results to those using the 1960 Bollen index, although the negative effect is less significant using the Alesina et al. index. See Alesina, A., Ozler, S., Roubini, N. and Swagel, P., ‘Political Instability and Economic Growth’, NBER Working Paper, No. 4173 (Cambridge: National Bureau of Economic Research, 1992)Google Scholar; Barro, R. J., ‘Economic Growth in a Cross-Section of Countries’, Quarterly Journal of Economics, 106 (1991), 407–44CrossRefGoogle Scholar; Londregan, J. and Poole, K., ‘Poverty, the Coup Trap, and the Seizure of Executive Power’, World Politics, 42 (1990), 151–83.CrossRefGoogle Scholar

⁴⁰ See Alesina, A. and Rodrik, D., ‘Distributive Politics and Economic Growth’, CEPR Discussion Paper, No. 565 (London: Centre for Economic Policy Research, 1991).Google Scholar

⁴¹ Presumably it is important to make the distinction between pre-tax and post-tax distributions of income. One of the influential strands of thinking arguing that democracy will be bad for growth adopts the position that democratic governments will be more likely to undertake redistributive policies that lead to higher tax rates and otherwise discourage savings, labour supply and capital accumulation. For examples, see Bauer, P. T., Equality, the Third World, and Economic Delusion (London: Weidenfield & Nicholson, 1981)Google Scholar, Huntington, S. and Nelson, J., No Easy Choice: Political Participation in Developing Countries (Cambridge, Mass.: Harvard University Press, 1976)CrossRefGoogle Scholar and Weede, E., ‘The Impact of Democracy on Economic Growth: Some Evidence from Cross-National Analysis’, Kyklos, 36 (1983), 21–39.Google Scholar

⁴² See Huntington, , The Third Wave.Google Scholar

⁴³ This partial negative effect only appears if allowance is made for the positive effects of investment and openness, both of which may in turn be positively influenced by the level of democracy. Differences in education levels do not appear to help explain variations in growth rates among the Asian economies. See Helliwell, J. F., ‘International Growth Linkages: Evidence From Asia and the OECD’, in Ito, T. and Kreuger, A., eds, Macroeconomic Linkage: Saving, Exchange Rates and Capital Flows (Chicago: University of Chicago Press, 1993).Google Scholar

⁴⁴ See Mankiw, , Romer, and Weil, , ‘A Contribution to the Empirics of Economic Growth’Google Scholar; Summers, and Heston, , ‘A New Set of International Comparisons of Real Product and Prices’.Google Scholar

⁴⁵ See Summers, R. and Heston, A., ‘The Penn World Table (Mark 5): An Expanded Set of International Comparisons, 1950–1988’, Quarterly Journal of Economics, 106 (1991), 327–68.CrossRefGoogle Scholar