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The impact of migrant remittances on economic development: empirical evidence from the developing world

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Abstract

Given the growing interest in the role of remittance inflows in economic development in developing countries, this study aims to explore the impact of migrant remittances on human capital, as measured by per capita health expenditures and gross secondary school enrollment, as well as on economic growth measured through real GDP per capita. The study utilizes pooled cross-country annual panel balanced data to investigate the role of remittances from 1995 to 2020 in 61 developing nations. The fixed-effects estimator is preferred over the random-effects estimator based on the Hausman test. Additionally, the two-step generalized method of moments is implemented for a robustness check. The empirical results reveal that remittance inflows have a significant impact on education and health despite positive impact of migrant remittances on economic growth, thereby confirming the positive contribution of migrant remittances to the economic development of developing economies. Migrant remittances have the greatest impact on health in upper–middle-income countries, followed by that in low-income and middle-income countries in the sub-sample analysis. The impact of remittances on education is the highest in low-income countries, followed by that in middle-income and upper–middle-income countries. These findings from a policy perspective suggest the allocation of remittance inflows into sectors that bolster economic development and improve social welfare. The study suggests developing economies to formulate effective policies for diverting remittances to productive sectors.

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Fig. 1

Source World Development Indicators (2023), the World Bank

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Data availability

Data used in this study for empirical examination have been obtained from the World Development Indicators (2022), the World Bank database.

Notes

  1. In the GMM approach, Eq. (2) is used appropriately, including the lagged regressand. In the cases, where per capita health spending (H) and gross secondary school enrollment (ED) are the regressands, this study used empirical models in the following forms: H = f (ED, Y, RM, FDI, P, T), and ED = f (Y, RM, FDI, AID). Moreover, these equations in the case of the GMM approach are used appropriately including the lagged regressand in the empirical models.

  2. See Valero-Gil 2008; De and Ratha 2012; Amega 2018; Azizi 2018.

  3. See De and Ratha 2012; Ngoma and Ismail 2013; Amakom and Iheoma 2014; Amega 2018.

  4. See Giuliano and Ruiz-Arranz 2005; Fayissa and Nsiah, 2010; Das and Chowdhury 2011; Cooray 2012; Bajra 2021; Bucevska 2022.

  5. See Ratha 2013; Sutradhar 2020.

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  1. Department of Economics, Faculty of Business & Economics, Abdul Wali Khan University Mardan, Mardan, Khyber Pakhtunkhwa, Pakistan

    Muhammad Azam Khan

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Table 9 Classification of countries based on 2011 GNI per capita.
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Khan, M. The impact of migrant remittances on economic development: empirical evidence from the developing world. J. Soc. Econ. Dev. (2024). https://doi.org/10.1007/s40847-024-00329-5

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