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Democratic Institutions, Natural Resources, and Income Inequality

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Abstract

This paper examines how democratic institutions shape the nexus of natural resources and income inequality, under the hypothesis that democracy can help to alleviate the possible effects that resources may have on income inequality. Starting from a survey of the existing literature, we provide a cross-country regression analysis showing that the effect of natural resources on income inequality does indeed depend on democracy. Our results suggest that, if the level of democracy in a country is high, natural resources have the ability to lower inequality. This finding suggests several avenues for future research.

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Notes

  1. Boschini et al. (2007) arrive to a similar conclusion and argue that the positive or negative impact of natural resources on economic growth depends not only on institutional quality, but also on the type of natural resources. If institutional quality is good, mineral-rich countries are less likely to suffer from the negative consequences of natural resources as compared to countries rich in diamonds and precious metals.

  2. Libman (2013) extends this analysis for the case of Russian regions and shows that when institutions are efficient and non-corrupt, natural resource rents may enhance economic growth even in non-democracies. Also, Asiedu and Lien (2011) argue that democracy facilitates FDI in countries where the share of natural resources in total exports is low, but where exports are dominated by natural resource democracy can actually have a negative effect.

  3. In contrast, Haber and Menaldo (2011) suggest that resource rents are not associated with autocracy. Aslaksen and Torvik (2006) also provide a theoretical model and empirical evidence to show that high resource rents combined with low labor productivity increase the likelihood of civil conflict, while high labor productivity makes democracy more likely.

  4. Acemoglu et al. (2019) argue that in the long run, democratization leads to 20% increase in GDP per capita. Eberhardt (2019) reassesses this finding and suggests that the impact of democracy is more conservative though still sizeable (about 10%).

  5. Gerring et al. (2012) also posit that the amount of time under democracy matters for other human development indicators, suggesting that established democracies are better able to handle issues of social protection rather than new ones.

  6. Of course, in some transition countries such as Ukraine and Russia, the drivers of economic inequality were precisely a reliance on the state, as tentative moves toward democracy were accompanied by rent capture by elites. Thus, even the transition experience cannot be generalized into a more/less inequality relationship with democracy.

  7. The issue of income inequality data comparability and coverage has been extensively discussed in the literature (Atkinson and Brandolini 2001, 2009; Jenkins 2015; Solt 2016). Earlier versions of the SWIID database have also been criticized for imperfect imputation of missing data (Jenkins 2015). However, as detailed in Solt (2015, 2016), starting from the version 5.0 (October 2014), the SWIID data took into account the earlier critiques and were substantially updated. A comprehensive documentation regarding the SWIID methodology is provided in Solt (2016). To date, the SWIID database remains the most comprehensive source on income inequality data comparable across countries (Solt 2016).

  8. We are aware that these cut-off points are somewhat arbitrary, but further robustness tests conducted after our examination show that the results are unaffected even if we change the cut-off points upward or downward.

  9. According to our results, an average level of democracy with an average level of natural resource abundance reduces inequality. Within the average level of natural resource abundance, the turning point for democracy vis a vis inequality is a score of 0.36, which is, for example, Uganda or Vietnam in our sample. Thus, our results suggest that countries with a democracy score above 0.36 will be better situated to utilize natural resource discoveries to lower income inequality. However, given that this is a first attempt at exploring this relationship, we do not want to overemphasize the precision of the estimated coefficients and are more interested in the average effects.

  10. See their website at https://www.v-dem.net/en/.

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Acknowledgements

We thank Nauro Campos, Jan Mares, and an anonymous referee for helpful comments. Horvathova acknowledges support from the Grant Agency of the Czech Republic, Grant No. 17-16633S. Popova acknowledges support from Russian Science Foundation Grant No. 19-18-00262.

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Authors and Affiliations

  1. Bournemouth University, Dorset House D129, Dorset House, Talbot Campus, Fern Barrow, Poole, BH12 5BB, UK

    Christopher A. Hartwell

  2. Kozminski University, Warsaw, Poland

    Christopher A. Hartwell

  3. Charles University, Prague, Czech Republic

    Roman Horvath

  4. Global Change Research Institute, Czech Academy of Sciences, Prague, Czech Republic

    Eva Horvathova

  5. Leibniz Institute for East and Southeast European Studies (IOS), Regensburg, Germany

    Olga Popova

  6. CERGE-EI, Prague, Czech Republic

    Olga Popova

  7. Graduate School of Economics and Management, Ural Federal University, Yekaterinburg, Russian Federation

    Olga Popova

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Appendix

Appendix

See Tables 2 and 3.

Table 2 Data definitions and sources
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Table 3 Descriptive statistics
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Countries Included in the Regressions

Albania, Algeria, Argentina, Armenia, Australia, Azerbaijan, Bangladesh, Belarus, Brazil, Bulgaria, Burkina Faso, Canada, Colombia, Croatia, Cyprus, Czech Republic, Dominican Republic, Ecuador, Egypt, Estonia, Ethiopia, Finland, France, Germany, Ghana, Guatemala, Hong Kong, Hungary, Chile, China, India, Indonesia, Iran, Israel, Italy, Japan, Jordan, Kazakhstan, Korea South, Latvia, Lebanon, Lithuania, Malaysia, Mali, Mexico, Moldova, Morocco, Netherlands, New Zealand, Nigeria, Norway, Pakistan, Peru, Philippines, Poland, Russia, Singapore, Slovakia, Slovenia, South Africa, Spain, Sweden, Switzerland, Tanzania, Thailand, Trinidad and Tobago, Tunisia, Turkey, Uganda, Ukraine, UK, USA, Uruguay, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe.

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Hartwell, C.A., Horvath, R., Horvathova, E. et al. Democratic Institutions, Natural Resources, and Income Inequality. Comp Econ Stud 61, 531–550 (2019). https://doi.org/10.1057/s41294-019-00102-2

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