International Remittances and Income Inequality: An Empirical Investigation

Abstract

Using several cross‐sectional and panel data methodologies, this paper provides evidence of the existence of an inverted U‐shaped relationship between international remittances and income inequality in a cross section of 78 countries. Our analysis supports previous theoretical work that describes how, at the first stages of migration history, there is an inequality‐increasing effect of remittances on income inequality. Then, as the opportunity cost of migrating decreases due to this effect, remittances tend to lower inequality. We also show how education and the development of the financial sector can help countries reach faster the inequality‐decreasing section of the curve.

Key Words:

• Migration
• international remittances
• income distribution
• GMM‐IV

Jel Codes:

• O1
• O15
• J16

Acknowledgments

We greatly thank Alberto Chong for constant comments and advice on previous versions of the papers. We are also thankful to participants in seminars held in the Unviersidad del Pacifico, IADB, and in the XI meeting of the Latin American and the Caribbean Economics Association, who provided insightful comments and suggestions. Sebastian Ipince was particularly helpful on the initial stages of this research. The views and opinions in this paper should not be attributed to the Universidad del Pacifico, the Inter‐American Development Bank, or their corresponding executive directors. We express thanks to an anonymous referee.

Notes

1. Kapur (2004) also mentions these kind of financing for separatist movements in Sweden, Canada, and the United Kingdom.

2. Cross‐country evidence for the impact of remittances on poverty has been provided by Adams and Page (2003). For a sample of 74 countries, they found that international migration has a significant effect on poverty reduction. An increase of 10% in the number of migrants reduces the number of people living under the poverty line by about 1.9%.

3. Anecdotal evidence on the formation of migrant networks in the host country and their close ties with home communities has been reported recently by the Christian Science Monitor. The town of Indaparapeo in Mexico, for example, receives remittances from migrants who have settled in the United States. A portion of this money is collected through public activities, and its expenditure is being coordinated by the community and the State governor. At this point, the money is being used for a program that provides college scholarships for poor young people in the town. See Campbell (2006).

4. Many sociological studies provide evidence of the beneficial effects of the formation of migrant networks in foreign countries. For example, Espinosa and Massey (1997) emphasize the role of social networks in lowering the information costs and dangers of crossing the Mexican border on the way to the United States. These networks may provide useful information on techniques and routes for entering the United States; also they can arrange way to provide temporary housing and financial assistance once they have crossed the border. Munshi (2003) finds that individuals with larger networks are more likely to be employed and to hold higher‐paying jobs upon arrival in the United States.

5. Obviously, the Gini coefficient and similar indices also pose some problems. One is that the general coverage tends to be sparse and unbalanced. To minimize this problem, the data from the World Bank (2005) combines different sources. Still, the question is whether there is any better proxy than these indices for making broad cross‐country comparisons on inequality, and the answer is no.

6. The definition problems that can arise include whether the data is taken at the individual or household level; whether it correspond to income or expenditures; in the former case, whether it is net of taxes or not; or if it representative at the national or sub national levels. We only take into account data that is representative at the national level, based on income data and weighted to the individual level.

7. For example, Freund and Spatafora (2005) estimated that informal remittances are equivalent to between 35% and 70% of the amount of official remittances. This difference is explained by the development of the local financial sector.

8. See, for example, Ahluwalia (1976); Li et al. (1998); Papanek and Kyn (1986); Sudhir and Kanbur (1993); Milanovic (1996); and Kuznets (1955), among others.

9. The countries included in the analysis are the following: Algeria, Argentina, Austria, Burundi, Bangladesh, Bolivia, Botswana, Brazil, Central African Republic, Chile, China, Cameroon, Colombia, Costa Rica, Denmark, Dominican Republic, Ecuador, Egypt, El Salvador, Fiji, Finland, France, Gambia, Ghana, Guatemala, Guyana, Honduras, Hungary, India, Indonesia, Iran, Ireland, Iran, Israel, Italy, Jamaica, Japan, Jordan, Kenya, Korea, Lesotho, Liberia, Lesotho, Mali, Mauritania, Mauritius, Malawi, Malaysia, Mexico, Nepal, Nicaragua, Nigeria, Norway, New Zealand, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, the Philippines, Poland, Rwanda, Senegal, Sierra Leone, Singapore, South Africa, Sri Lanka, Swaziland, Sweden, Switzerland, Thailand, Trinidad and Tobago, Tunisia, Turkey, Uganda, Uruguay, United States, Venezuela, Zambia, and Zimbabwe.

10. In many countries there is not a single passport cost. Costs may differ for children and adults, for renewals, for expedited service, and even for duration and number of pages. Also, the justification for not dividing a 10‐year passport price in half is that potential migrants must pay the full cost of the passport upfront (McKenzie, 2005).

11. Chong and León (2006) show that the determinants of the barriers to exit a country (as proxied by the cost of obtaining a passport) do not vary with time. This supports our statement that the relative ranking of countries does not vary over time.

12. For space reasons, we do not show the summary statistics or the correlation matrix, but they are available upon request to the authors.

13. See Carrington et al. (1996).

14. Column 4 in Table 2 shows the results when including continental controls, although we also try including other variables similar to those shown and the coefficients and significance of remittances did not vary significantly. These results are available upon request to the authors.

15. Column 3 of Table 2 is taken as our benchmark specification since it is the one that most closely follows the specifications previously used in the literature.

16. A detailed explanation of these methods is available in a technical appendix, which will be happily provided by the authors upon request of the interested reader.

17. When testing the regression using continental dummies we obtain a significant coefficient for the interactive term, although these results are not as robust as those shown for the interactions between remittances and years of secondary schooling.