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Achieving the sustainable development goals in developing countries: The role of remittances and the mediating effect of financial inclusion

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  • Barkat, Karim
  • Mimouni, Karim
  • Alsamara, Mouyad
  • Mrabet, Zouhair

Abstract

This study investigates the pivotal role of remittances in advancing Sustainable Development Goals (SDGs) within developing countries. While previous literature has acknowledged the potential of remittances in fostering growth, empirical analyses on their impact on SDGs remain scant. Utilizing data from 109 developing countries spanning 2000 to 2022 and employing system GMM and the Lewbel's (2012) estimator to tackle endogeneity issues, we unveil significant positive effects of remittances on SDGs. Additionally, we identify financial inclusion as a mediating factor enhancing remittances' impacts on SDGs. Moreover, we show that remittances, international aid, and government spending exhibit complementary roles in SDGs attainment.

Suggested Citation

  • Barkat, Karim & Mimouni, Karim & Alsamara, Mouyad & Mrabet, Zouhair, 2024. "Achieving the sustainable development goals in developing countries: The role of remittances and the mediating effect of financial inclusion," International Review of Economics & Finance, Elsevier, vol. 95(C).
    • Handle: RePEc:eee:reveco:v:95:y:2024:i:c:s1059056024004520
    DOI: 10.1016/j.iref.2024.103460
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    More about this item

    Keywords

    Remittances; Sustainable development goals; Financial inclusion; Panel data;
    All these keywords.

    JEL classification:

    • F24 - International Economics - - International Factor Movements and International Business - - - Remittances
    • F63 - International Economics - - Economic Impacts of Globalization - - - Economic Development
    • G2 - Financial Economics - - Financial Institutions and Services
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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