Abstract
We analyse the relationship between income volatility and inequality and the conditional role played by aid and remittances. Using a panel of 142 countries for the period 1973–2012, we confirm a well-established finding among the literature that income volatility has an adverse impact on inequality, and that the poorest people are the most exposed to these fluctuations. However, while aid and remittances do not seem to have a clear direct impact on inequality, we uncover robust evidence that suggests that aid helps dampen the negative effects of volatility on the distribution of income, while remittances do not.
Notes
Adding the lagged dependent variable on the right-hand side of the equation allows controlling for time persistence in income inequality which seems to be the case when looking at Figures S1 in the supplementary appendix. Serial autocorrelation is confirmed using Wooldridge tests which all suggest persistence in our various inequality measures. Results available upon request.
It is also worth mentioning the work of Solt (2016), who, building on the WIID, proposed an interpolated version of the dataset, the “Standardized World Income Inequality Database (SWIID)”. The SWIID provides comparable estimates of the Gini index for 174 countries from 1960 to 2012, as well as measures of absolute and relative redistribution. Data points are fully interpolated and should be used cautiously.
Measures based on consumption data reflect more accurately income distribution, but would restrict our sample too much.
When the aid variable is introduced without the interaction term aid × volatility, the coefficient of the aid variable is not significantly different from zero. Results available from the authors upon request.
Which can be seen with implausibly good p-values of 1.000.
The underlying idea is that when destination countries experience significant economic growth, the migrant’s diaspora is likely to benefit from this growth and therefore could send more remittances in their home country.
Cf. Table S2 in the supplementary appendix.
Channel 3 (impact of aid on inequality) is not significant.
The same pattern appears when education is removed from the effect of income per capita (i.e. when we use predicted educational outcomes with respect to countries’ income level).
Aid to social sectors is from the Creditor Reporting System (CRS) dataset and includes aid to education, for health of population, and water and sanitation. It is only available for 2002 onwards.
Note that when looking at the primary school enrolment rate the effect of macroeconomic volatility is also negative and statistically significant. Results not reported here to save space but available on request from the authors.
When using the primary instead of the secondary school enrolment rate, the interaction term between aid and macroeconomic volatility is still positive, but less significant (results not shown).
Not shown but available upon request.
Aid counter-cyclicality is measured using the correlation of the cycles of aid with the cycles of exports. When the correlation is negative, aid is assumed to be counter-cyclical. Aid and exports are measured in constant US dollars deflated by US unit import prices.
Results are also robust to the unweighted measure of exports volatility. Results available upon request.
References
Adams, R. H., & Page, J. (2005). Do international migration and remittances reduce poverty in developing countries? World Development, 33(10), 1645–1669.
Agénor, P.-R. (2002). Business cycles, economic crises and the poor: Testing for asymmetric effects. Journal of Policy Reform, 5, 145–160.
Agénor, P.-R. (2004). Macroeconomic adjustment and the poor: Analytical issues and cross-country evidence. Journal of Economic Surveys, 18(3), 351–408.
Atkinson, A. B., & Brandolini, A. (2001). Promise and pitfalls in the use of “secondary” data-sets: income inequality in OECD countries as a case study. Journal of Economic Literature, 34(3), 771–799.
Atkinson, A. B., & Brandolini, A. (2009). On data: A case study of the evolution of income inequality across time and across countries. Cambridge Journal of Economics, 33(3), 381–404.
Barham, B., & Boucher, S. (1998). Migration, remittances, and inequality: Estimating the net effects of migration on income distribution. Journal of Development Economics, 55(2), 307–331.
Bjornskov, C. (2010). Do elites benefit from democracy and foreign aid in developing countries? Journal of Development Economics, 92, 115–124.
Boone, P. (1996). Politics and the effectiveness of foreign aid. European Economic Review, 40, 289–329.
Bouoiyour, J., Selmi, R., & Miftah, A. (2016). What mitigates economic growth volatility in Morocco?: Remittances or FDI. Journal of Economic Integration, 31(1), 65–102.
Breen, R., & Garcia-Penalosa, C. (2005). Income inequality and macroeconomic volatility: an empirical investigation. Review of Development Economics, 9(3), 380–398.
Bugamelli, M., & Paternò, F. (2011). Output growth volatility and remittances. Economica, 78, 480–500.
Bulír, A., & Hamann, A. J. (2001). How volatile and unpredictable are aid flows, and what are the policy implications? IMF working paper 167, Washington, DC.
Bulír, Ales, & Hamann, A. Javier. (2008). Volatility of development aid: from the frying pan into the fire? World Development, 36(10), 2048–2066.
Calderón, C., Chong, A., & Gradstein, M. (2009). Can foreign aid reduce income inequality and poverty? Public Choice, 140, 59–84.
Calderón, C., & Levy Yeyati, E. L. (2009). Zooming. In From aggregate volatility to income distribution. Policy Research Working Paper, World Bank.
Chase-Dunn, C. (1975). The effects of international economic dependence on development and inequality: a cross-national study. American Sociological Review, 40, 720–738.
Chauvet, L., & Guillaumont, P. (2004). Aid and growth revisited: Policy, economic vulnerability and political instability. In B. Tungodden, N. Stern and I. Koldstad (Eds.), Towards pro-poor policies— aid, institutions and globalization. ABCDE 2003 annual World Bank conference on development economics Europe. New York, NY: Oxford University Press.
Chauvet, L., & Guillaumont, P. (2009). Aid, volatility and growth again. When aid volatility matters and when it does not. Review of Development Economics, 13(3), 452–463.
Chauvet, L., & Mesplé-Somps, S. (2007). Impact des financements internationaux sur les inégalités des pays en développement 2007/3. Revue Economique, 58, 735–744.
Chen, S., & Ravallion, M. (2008). The developing world is poorer than we thought, but no less successful in the fight against poverty. Poverty Research Paper 4703. Washington, DC: World Bank.
Combes, J.-L., Ebeke, C. H., & Ntsama Etoundi, M. (2014). Are remittances and foreign aid a hedge against food price shocks in developing countries? World Development, 54, 81–98.
De, S., Islamaj, E., Kose, M. A., & Yousefi, S. R. (2016). Remittances over the business cycle: Theory and evidence, CAMA Working Paper 13/2016.
Deininger, K., & Squire, L. (1996). A new data set measuring income inequality. World Bank Economic Review, 10(3), 565–591.
Dercon, S., & Krishnan, P. (2000). In sickness and in health: Risk sharing within households in rural Ethiopia. Journal of Political Economy, 108(4), 688–727.
Ebeke, C. H., & Le Goff, M. (2009). Why migrants’ remittances reduce income inequality in some countries and not in others? CERDI Etudes et documents, n° 19.
Guillaumont, P. (2006). Macro vulnerability in low income countries and aid responses. In F. Bourguignon, B. Pleskovic and J. van der Gaag (Eds.), Securing development in an unstable word. ABCDE Europe 2005, Word Bank, pp. 65–108.
Guillaumont, P. (2009). Caught in a trap. Identifying the least developed countries, Economica.
Guillaumont, P., & Chauvet, L. (2001). Aid and performance: A reassessment. Journal of Development Studies, 37(6), 66–92.
Guillaumont, P., Guillaumont Jeanneney, S., & Brun, J.-F. (1999). How instability lowers African growth. Journal of African Economies, 8(1), 87–107.
Guillaumont Jeanneney, S., & Kpodar, K. (2011). Financial development and poverty reduction: Can there be a benefit without a cost? Journal of Development Studies, Taylor and Francis Journals, 47(1), 143–163.
Guillaumont, P., & Le Goff, M. (2010). Aid and remittances: Their stabilizing impact compared, FERDI working paper n°12.
Guillaumont, P., & Wagner, L. (2012). Aid and growth accelerations: Vulnerability matters, Working Papers UNU-WIDER Research Paper, World Institute for Development Economic Research (UNU-WIDER).
Guillaumont, P., & Wagner, L. (2013). Aid effectiveness for poverty reduction: Macroeconomic overview and emerging issues. Revue d’Economie du Développement, 2(4), 115–164.
Hnatkovska, V., & Loayza, N. (2005). Volatility and growth. In J. Aizenmann & B. Pinto (Eds.), Managing volatility and crises: A practitioner’s guide. Cambridge: World Bank, Cambridge University Press.
Laursen, T., & Mahajan, S. (2005). Volatility, income distribution, and poverty. In J. Aizen- man and B. Pinto (Eds.), Managing volatility and crisis: A practitioner guide. The World Bank, Cambridge University Press.
Le Goff, M. (2010a). How remittances contribute to poverty reduction: A stabilizing effect, CERDI WP Etudes et documents, 2010 n° 8.
Le Goff, M. (2010b). Migrant remittances, foreign aid and development of recipient countries, these soutenue à l’Université d’Auvergne le 29/03/2012.
Milanovic, S. (2013). Description of all the Ginis dataset. Washington, DC: World Bank, Research Department.
Norrbin, S. C., & Pinar Yigit, F. (2005). The robustness of the link between volatility and growth of output. Review of World Economics, 141(2), 343–356.
Pallage, S., & Robe, M. A. (2001). Foreign aid and the business cycle. Review of International Economics, 9(4), 641–672.
Raddatz, C. (2007). Are external shocks responsible for the instability of output in low-income countries? Journal of Development Economics, 84, 155–187.
Ramey, G., & Ramey, V. A. (1995). Cross country evidence on the link between volatility and growth. American Economic Review, 85(5), 1138–1151.
Rapoport, H., & Docquier, B. (2006). The economics of migrants’ remittances, Handbook of the economics of giving, altruism and reciprocity. applications, Volume 2, 2006, Chapter 17, pp. 1135–1198.
Roodman, D. (2006). How to do xtabond2: An introduction to difference and system GMM in Stata. Center for Global Development working paper (103).
Solt, Frederick. (2016). The standardized world income inequality database. Social Science Quarterly, 97(5), 1267–1281.
Stark, O., Taylor, J. E., & Yitzhaki, S. (1988). Migration, remittances and inequality: A sensitivity analysis using the extended Gini index. Journal of Development Economics, 28(3), 309–322.
Tavares, J. (2003). Does foreign aid corrupt? Economics Letters, 79(1), 99–106.
Taylor, J. E. (1992). Remittances and inequality reconsidered: Direct, indirect, and intertemporal effects. Journal of Policy Modeling, 14(2), 187–208.
Thomas, D., Beegle, K., Frankenberg, E., Sikoki, B., Strauss, J., & Teruel, G. (2004). Education in a crisis. Journal of Development Economics, 74(1), 53–85.
Wagner, D. (2003). Aid and trade—an empirical study. Journal of Japanese International Economies, 17, 153–173.
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Special acknowledgments are due to Pierre-Richard Agenor and Kyriakos Neanidis and to participants at the BCEAO seminar held in Dakar on November 9, 2016 as well as to the anonymous referees for helpful comments and suggestions. The authors are grateful to Maddalena Agnoli and Sosso Feindouno for their assistance at the early stage of this work. Financial support from the DFID-ESRC Growth Research Programme, under Grant No. ES/L012022/1, is gratefully acknowledged. The views expressed in this paper are only those of the authors.
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Appendix
See Table 11.
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Chauvet, L., Ferry, M., Guillaumont, P. et al. Volatility widens inequality. Could aid and remittances help?. Rev World Econ 155, 71–104 (2019). https://doi.org/10.1007/s10290-018-0331-7
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DOI: https://doi.org/10.1007/s10290-018-0331-7