Hollowing out the middle? Remittances, poverty, and income inequality in Nigeria

ABSTRACT

This paper investigates the impact of remittances on poverty and inequality in Nigeria. In contrast to the existing literature, our methodology of instrumental variable quantile regression (IVQR) explicitly demonstrates the differential marginal impact of remittances for households at different levels of the conditional expenditure distribution. In tracing this heterogeneous impact, we are further able to address the effect of remittances on poverty and inequality simultaneously in one econometric model. Our results based on the Nigerian Migration Household Survey 2009 show that remittances reduce poverty by increasing household expenditures reveal a positive marginal impact of remittances at all but the highest quantiles of the conditional distribution of household expenditure, with the impact being the greatest up to the 12^th quantile. While this unambiguously supports the poverty alleviation role of remittances documented in the literature, the distributional impact is more nuanced: The marginal effect of remittances follows a U-shape over most of the household expenditure distribution, which suggests that remittances may ‘hollow out’ the middle class. Specifically, households lying between the 13^th to the 35^th quantile gain less from receiving remittances than households on either side of this range.

KEYWORDS:

• Poverty
• income inequality
• migration
• remittances
• quantile regression

JEL Codes:

• F22
• F24
• O15
• O55

Acknowledgements

We would like to thank an anonymous referee of this journal for constructive suggestions. Earlier versions of this paper were presented at the 13th Annual Conference on Economic Growth and Development (New Delhi, India, December 2017), at the 87th Southern Economic Association Conference (Tampa, FL, November 2017),at the David K Smith ‘42 Economics Symposium titled ‘Economics of Remittances’ (Middlebury, VT, April 2017), and at Inclusive and Sustainable Economic Growth. Challenges, Measures and Solutions (Transilvania University of Brasov, Romania, October 2017). An earlier draft of this paper was also circulated as IZA Discussion Paper No. 11438. We would like to thank panelists at these forums for very helpful feedback and Sanjay Wunnava for his valuable editorial assistance. The usual caveats apply.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. From the World Bank data on Annual Remittance Inflows by Country: http://www.worldbank.org/en/topic/migrationremittancesdiasporaissues/brief/migration-remittances-data.

2. According to the World Development Indicators (https://data.worldbank.org/indicator/SI.POV.NAHC), 46 percent of Nigerians lived below the national poverty line at its last measurement in 2009, which also happens to coincide with the date of the survey we use.

3. To the best of our knowledge, Bang et al. (2016) is the first study to use the method to analyze household level survey data from Kenya. IVQR has since been applied by Agwu et al. (2018) to the Senegalese context. Also see Bui and Imai (2018) for an application of quantile regression to the context of internal migration in Vietnam.

4. See Massey et al. (1993) for a critical review of this and other theories of migration.

5. See Mata-Codesal (2018) in the context of Ecuador.

6. Taylor and Wyatt (1996) provide the example of nontradableejido lands in Mexico which are communally owned but assigned to individual households for cultivation. While the household has property rights over the agricultural output it generates from the land, it cannot sell its right to cultivate that land to others. In other words, there is a separation of ownership and control rights.

7. There is increasing evidence that migrants are cognizant of and take steps to address informal asymmetries inherent in the utilization of remittance income. De Laat (2014), for example, documents an array of monitoring mechanisms employed by internal migrants in Kenya, including random visits, insistence on project proposals for the disposal of remittance income prior to sending any money, and arranging for monitoring household expenditure by friends and family who are not part of the immediate household and can be depended upon.

8. See Wouterse (2010) for a recent contribution focusing on Burkina Faso.

9. See Plaza et al. (2011) on the methodology and main findings. The survey is available as part of the World Bank Microdata Library at http://microdata.worldbank.org/index.php/catalog/402.

10. This last category was created to minimize the number of observations lost due to missing data.

11. Azam and Gubert (2006), for example, describe how relatively wealthier households in Africa tend to migrate, and show how this selection might have different impacts on incentives and outcomes due to the selection problem.

12. We calculate he LM statistic for underidentification for the means regression as 18.417 with a p-value of 0.0001 to confirm the strength of our instruments; the Sargan statistic for overidentification is 3.459 with a p-value of 0.0629, which fails to reject the null hypothesis that the excluded instruments are uncorrelated with expenditures and thus confirms validity.

13. Since we have taken logs of the expenditure variable, the coefficient represents a proportional change in expenditures for a given unit change (switch from no remittances to remittances):

$\frac{d\mathrm{l}\mathrm{n}\left(expend.p.c.\right)}{dremit}=\frac{\frac{dexpendp.c.}{expendp.c.}}{dremit}=\mathrm{7.156.}$

Additional information

Notes on contributors

James T. Bang

James T. Bang is Professor of Economics at St. Ambrose University, Davenport, Iowa, USA and Fellow at Global Labor Organization. He received his education at the University of Illinois at Urbana-Champaign with a Ph.D. in Economics. He specializes in development economics, international economics, and institutional economics. He has published a wide range of articles in scholarly journals on the topic of migration, remittances, conflict, terrorism, institutions, gender, economic growth, income inequality, and more recently health economics. Professor Bang has co-authored Remittances and the World Economy (Routledge, 2015), and two books on machine learning methods in economics: Predicting Hotspots: Using Machine Learning to Understand Civil Conflict (Lexington Books, 2018) and Machine-learning Techniques in Economics: New Tools for Predicting Economic Growth (Springer, 2018). He is also co-authoring a forthcoming book, Machine Learning Approach to Identifying the Complex Causes of Civil War (Palgrave MacMillan).

Aniruddha Mitra

Aniruddha Mitra is Associate Professor of Economics at Bard College, Annandale-on-Hudson, NY and Fellow of the Global Labor Organization. He received his doctorate in economics from the University of Illinois at Urbana-Champaign and has published extensively in the areas of his interest, namely, transnational migration and remittances, civil conflict, the economics of gender. His recent research explores the transformation of human and labor rights in developing countries induced by globalization and associated flows.

Phanindra V. Wunnava

Phanindra V. Wunnava is the David K. Smith '42 Chair in Applied Economics at Middlebury College, Middlebury, Vermont, USA, Research Fellow at IZA (Institute for the Study of Labor), Bonn, Germany, and Fellow at Global Labor Organization. He was trained under a noted labor economist Solomon Polachek of State University of New York-Binghamton, and received a Ph.D. in economics. His fields of interest are applied econometrics and labor economics. His articles appeared in wide range of scholarly journals covering the areas of life-cycle union non-union wage/benefit differentials, firm size effects, gender and racial wage differentials, efficiency wage models, charitable contributions towards higher education, disincentive effects of unemployment insurance, infant mortality, effect of net foreign investment on manufacturing productivity, time-series properties of the north American unemployment rates and Asian stock markets, the effect of political regimes on economic growth, fertility determinants, determinants of internet diffusion, the economics of optimal currency area, brain drain, linking globalization with ethnic division linking financial liberalization and remittances, and linking remittances with income inequality. Furthermore, Wunnava co-edited (i) New Approaches to Economic and Social Analyses of Discrimination (with Richard R. Cornwall) Praeger 1991, (ii) Immigrants and Immigration Policy: Individual Skills, Family Ties, and Group Identities (with Harriet Duleep) JAI Press 1996, and (iii) Changing Role of Unions: New Forms of Representation, M. E. Sharpe 2004 [has been recognized by the Industrial Relations Section of Princeton University as one of the twelve Noteworthy Books in Industrial Relations and Labor Economics for 2004]. He is co-author of a forthcoming book titled: New Look at Human Capital Investment: A History of Asian Immigrants and Their Family Ties (Palgrave Macmillan 2020).