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The autocratic gamble: evidence from robust variance tests

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Abstract

This paper examines whether autocracy is a gamble. Using robust variance tests and other analyses, we find that long-term growth varies more across autocracies than across democracies. This remains true even when richer countries are excluded from the sample. We also investigate channels, to see if the higher variance of growth outcomes across autocracies can be traced to a higher variance in investment ratios or productivity growth. Overall, the paper’s findings suggest that growth prospects are more uncertain for autocracies than democracies, and especially for closed autocracies. From the viewpoint of a domestic population, autocracy remains a gamble.

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Notes

  1. See, for example, Sah (1991) or Gandhi (2008, pp. 139–140). Related research includes (Knutsen 2015) and Sylwester (2015). Earlier work by Gasiorowski (2000) found that democracies grow more slowly; results may conflict because the cross-section variance of outcomes depends on regime type, which is the hypothesis we consider in this paper. An alternative argument is that long-term democracy is what matters; see (Gerring et al. 2005) and (Persson and Tabellini 2009).

  2. Note that, throughout the paper, we use the idea of an ‘autocratic gamble’ in this loose metaphorical sense, rather than as a well-defined decision problem for a specific set of decision-makers. In a similar spirit, Knutsen (2018) describes democracy as providing a ’safety net’ that makes the worst outcomes less likely.

  3. This is based on the V-Dem classification of autocracies, discussed later in the paper. The importance of discriminating between types of regime was stressed by Gandhi (2008), Gleditsch and Ward (1997) and Vreeland (2008). In future work, it might be especially interesting to ask whether the variance of outcomes depends on the strength of parties; see Bizzarro et al. (2018).

  4. It is possible that the number of decision-makers is smallest in closed autocracies, on average, but that is only a conjecture.

  5. See Chapter XI of Aristotle’s Politics: a Treatise on Government.

  6. The earlier empirical literature was inconclusive; see the meta-analysis in Doucouliagos and Ulubaşoğlu (2008).

  7. Of course, this does not rule out other sources of heterogeneity, such as transitions to highly imperfect democracies (for discussion see, for example, Haggard and Kaufman 2016) or which arise through a range of mechanisms, decisions, and events, including mistakes by autocrats (Treisman 2020).

  8. See also (Wright 2008) and (Wilson and Wright 2017). Haggard and Kaufman (2016) caution against the idea that an overarching theory will be achievable.

  9. We have also used classifications based on Polity V, Marshall et al. (2020). Those results, which are consistent with those reported here, are available on request.

  10. For discussions of democracy measurement, see (Treier and Jackman 2008; Cheibub et al. 2010; Boix et al. 2013) and (Gründler and Krieger 2019).

  11. Recently Anckar and Fredriksson (2019), building on Geddes et al. (2014), distinguish between party rule, personalist rule, military rule, absolute monarchy, and oligarchy.

  12. In the "Appendix" we provide results using data from Boix et al. (2013), Cheibub et al. (2010) and Anckar and Fredriksson (2019).

  13. Note that we are interested in the cross-section variance; we do not study growth rate volatility, but rather how distributions of long-term growth rates compare across different types of regime.

  14. As an historical aside, the fragility of simple tests for equal variances has been known to statisticians for almost a century, and a study by Box (1953) is often seen as the first use in statistics of the term ‘robustness’ in its modern sense. See (Stigler 2010) for a brief history.

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Acknowledgements

Corres. author: Fabio Monteforte. We are grateful to Paddy Carter, Adeel Malik, James Rockey, Nicolas Van de Sijpe and two anonymous referees for helpful comments, but the usual disclaimer applies. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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  1. Department of Economics, University of Messina, Via dei Verdi 75, 98122, Messina, Italy

    Fabio Monteforte

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  1. Fabio Monteforte
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Correspondence to Fabio Monteforte.

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Appendix

Appendix

In this appendix, we report robust variance tests using a range of datasets on political regimes.

See Tables 11, 12, 13, 14 and 15.

Table 11 Robust variance comparisons for growth rates—DD
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Table 12 Robust variance comparisons for growth rates—DD autocracy types
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Table 13 Robust variance comparisons for growth rates—Boix et al. 2013
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Table 14 Robust variance comparisons for growth rates—AF2019
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Table 15 Robust variance comparisons for growth rates—AF2019 autocracy types
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Monteforte, F., Temple, J.R.W. The autocratic gamble: evidence from robust variance tests. Econ Gov 21, 363–384 (2020). https://doi.org/10.1007/s10101-020-00245-4

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