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<p>This study examines the influence of pivotal macroeconomic determinants on unemployment across eight South Asian nations, utilizing a panel dataset spanning from 2001 to 2023 sourced from World Development Indicators. Through the application of Quantile Regression, this analysis unveils how the interplay between these economic variables varies across distinct unemployment quantiles. This methodological approach affords a comprehensive understanding of how macroeconomic factors exert divergent effects on both low and high unemployment rates in diverse national contexts. While global quantile regression studies examine post-industrial economies with mature institutions, no prior research has systematically applied this methodology to South Asian unemployment dynamics characterized by ongoing structural transformation, demographic dividend pressures, and dual labor market structures. The results elucidate a pronounced inverse correlation between economic growth (GDP) and Foreign Direct Investment (FDI) with unemployment, particularly in countries exhibiting elevated unemployment rates. Conversely, inflation (INF) is shown to exacerbate unemployment at lower quantiles, while interest rates (IR) contribute to higher unemployment at elevated quantiles. Population growth (POP) exerts differential effects on unemployment, with a more substantial impact in nations characterized by lower unemployment. Countries experiencing high unemployment (75th-90th percentiles) should prioritize aggressive GDP growth promotion and FDI attraction strategies with expected elasticities exceeding -0.10, while those at lower unemployment quantiles require careful monetary policy calibration to prevent labor market overheating. This research provides a systematic quantile regression analysis of South Asian unemployment determinants, revealing region-specific threshold effects that inform differentiated policy approaches rather than uniform regional prescriptions.</p>

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South Asian cross-country impact analysis of macro-economic factors on unemployment: a quantile regression approach

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月29日

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  • Li Qi,
  • Mousumi Akter,
  • Hero Rana Barua Mito,
  • Md Shahriar Kabir Sajib,
  • Ahnaf Aiman Abdi

摘要

This study examines the influence of pivotal macroeconomic determinants on unemployment across eight South Asian nations, utilizing a panel dataset spanning from 2001 to 2023 sourced from World Development Indicators. Through the application of Quantile Regression, this analysis unveils how the interplay between these economic variables varies across distinct unemployment quantiles. This methodological approach affords a comprehensive understanding of how macroeconomic factors exert divergent effects on both low and high unemployment rates in diverse national contexts. While global quantile regression studies examine post-industrial economies with mature institutions, no prior research has systematically applied this methodology to South Asian unemployment dynamics characterized by ongoing structural transformation, demographic dividend pressures, and dual labor market structures. The results elucidate a pronounced inverse correlation between economic growth (GDP) and Foreign Direct Investment (FDI) with unemployment, particularly in countries exhibiting elevated unemployment rates. Conversely, inflation (INF) is shown to exacerbate unemployment at lower quantiles, while interest rates (IR) contribute to higher unemployment at elevated quantiles. Population growth (POP) exerts differential effects on unemployment, with a more substantial impact in nations characterized by lower unemployment. Countries experiencing high unemployment (75th-90th percentiles) should prioritize aggressive GDP growth promotion and FDI attraction strategies with expected elasticities exceeding -0.10, while those at lower unemployment quantiles require careful monetary policy calibration to prevent labor market overheating. This research provides a systematic quantile regression analysis of South Asian unemployment determinants, revealing region-specific threshold effects that inform differentiated policy approaches rather than uniform regional prescriptions.