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Economic Growth in Culturally Diverse Nations

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Intercultural Economic Analysis

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Abstract

In existing literature relating to the determinants of economic growth, such explanatory variables as income inequality and cultural diversity have been treated separately. In this chapter, we try to discuss their joint effects. Evidence from a broad panel of nations reveals somewhat ambiguous results in that economic growth is quite independent from the variables of inequality and cultural (linguistic and religious) diversity. But for the post-Cold War era, there is also an indication that religious diversity tends to retard growth in high-inequality nations and to encourage growth in low-inequality places. Besides, we find some evidence that supports the view that inequality tends to encourage growth in low religious diversity nations, but not in high religious diversity places. The estimated results show that higher religious diversity could become a source of productive factors contributing to economic growth for low-inequality nations; but in nations with high degrees of religious diversity, high inequality could seriously affect economic growth. In nations with low degrees of religious diversity, income inequality could generate higher economic growth since there are very few, if any, intercultural barriers within each religiously homogeneous nation.

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Notes

  1. 1.

    Cited from Lian and Oneal (1997).

  2. 2.

    Similarly, Eckstein (1966) and Schattschneider (1960) propose that a two-party system is less stable than systems with more parties because decisions may appear to be zero-sum, straining the unity and peace of the society.

  3. 3.

    Theoretical surveys on the effects of income inequality on economic growth would include Benabou (1996), Aghion et al. (1999), and Barro (2000).

  4. 4.

    See Perotti (1993), Alesina and Rodrik (1994), Persson and Tabellini (1994) and Benabou (1996) for detailed analyses.

  5. 5.

    This effect arises if the economy is partly closed, so that domestic investment depends, to some extent, on desired national saving (Barro 2000, p. 8).

  6. 6.

    There is an indication in Barro’s (2000) study that growth tends to fall with greater inequality when per capita GDP is below around $2,000 (1985 US dollars) and to rise with inequality when per capita GDP is above $2,000.

  7. 7.

    For example, an economic shock that may feel like only a ripple to an enormous economy like the United States, or even to a large developing economy like China, is a tidal wave for an economy the size of Ghana or Bangladesh.

  8. 8.

    Cited from Alesina and Ferrara (2005).

  9. 9.

    Source: China Ethnic Statistical Yearbook (1997, pp. 299–300).

  10. 10.

    In the extreme case when c→® - ¥, the ranking of the corresponding GE is same as that of Rawls’ maximum criterion, i.e., to focus exclusively on the well-being of the worst-off province (Shorrocks 1980, pp. 613–25).

  11. 11.

    In the extreme cases, 0 corresponds to perfect equality (everyone has exactly the same income) and 1 corresponds to perfect inequality (where one person has all the income, while all the remaining persons have zero income).

  12. 12.

    See, for example, Holesovsky (1977), Hwang (1993), Carson (1996), Kohler (1996), Schnitzer (1997), Gregory and Stuart (1998), McMahon and Square (2003, eds), and Rodrik (2003, ed.).

  13. 13.

    Since 1999 is the latest year in which we have been able to assemble the panel data on all the variables employed, we have to reduce the starting year to 1980 in order to equalize the two periods (the Cold War and the post-Cold War) in length.

  14. 14.

    The estimation is by three-stage least squares. Instruments are the actual values of the schooling and terms-of-trade variables, lagged values of the other variables aside from inflation, and dummy variables for prior colonial status. Since some explanatory variables employed by Barro (such as a subjective index of the maintenance of the rule of law, a subjective for democracy, the ratio of inflation, the log of total fertility rate, and the growth rate of the terms of trade) could either be influenced by cultural diversity or their data are not available, we ignore their effects on growth rates when calculating the data.

  15. 15.

    Note that the only difference between the two panel data is that five nations (Mali, Nicaragua, Singapore, Yemen and Zambia) are missing in the 1990s’ sample.

  16. 16.

    We have also tested other forms of regressions (including those that include the interactive term of GINI and lnGDPPC), none of which has yielded statistically meaningful results.

  17. 17.

    Barro and McCleary (2003) find that economic growth responds positively to the extent of religious beliefs.

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  1. Regional Science Association of China at Peking University, Beijing, China

    Rongxing Guo

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Guo, R. (2009). Economic Growth in Culturally Diverse Nations. In: Intercultural Economic Analysis. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0849-0_5

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