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<p>Despite population health efforts in Pakistan, socioeconomic and environmental factors that affect life expectancy are inadequately studied. This study examines the relationship between life expectancy at birth and key determinants from 1990 to 2024. The long-term cointegration is detected using the Autoregressive Distributed Lag (ARDL) bounds test. Results show that long-term life expectancy is positively affected by urban population and secondary school enrollment, while negatively affected by CO₂ emissions and unemployment. Government health expenditure also reduces life expectancy in the long run, indicating inadequate utilization of healthcare resources. The quantile regression approach is used as a robustness test and yields results similar to those of the ARDL estimates. Granger causality analysis reveals a feedback relationship between carbon emissions and life expectancy at birth. At the same time, there is a unidirectional causality running from urbanization to life expectancy and healthcare expenditures. Further, unemployment and carbon emissions Granger-cause healthcare expenditures and urbanization, respectively. The findings emphasize the necessity of SDG-aligned, cross-sectoral, and coordinated policy actions. This applies notably to Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-being), SDG 4 (Quality Education), SDG 8 (Decent Work and Economic Growth), and SDG 13 (Climate Action), which address health, education, economic development, and climate change.</p>

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Human development under environmental and socioeconomic pressures: an ARDL-based assessment of life expectancy in Pakistan

  • 期刊论文

  • 发表日期：

    2026年5月25日

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  • Muhammad Khalid Anser,
  • Muhammad Imran,
  • Helmi Ali Mkaouar,
  • Jameel Ahmad Khader,
  • Alaa Shoukry,
  • Wasfi Yengui,
  • Kamran Azam,
  • Khalid Zaman

摘要

Despite population health efforts in Pakistan, socioeconomic and environmental factors that affect life expectancy are inadequately studied. This study examines the relationship between life expectancy at birth and key determinants from 1990 to 2024. The long-term cointegration is detected using the Autoregressive Distributed Lag (ARDL) bounds test. Results show that long-term life expectancy is positively affected by urban population and secondary school enrollment, while negatively affected by CO₂ emissions and unemployment. Government health expenditure also reduces life expectancy in the long run, indicating inadequate utilization of healthcare resources. The quantile regression approach is used as a robustness test and yields results similar to those of the ARDL estimates. Granger causality analysis reveals a feedback relationship between carbon emissions and life expectancy at birth. At the same time, there is a unidirectional causality running from urbanization to life expectancy and healthcare expenditures. Further, unemployment and carbon emissions Granger-cause healthcare expenditures and urbanization, respectively. The findings emphasize the necessity of SDG-aligned, cross-sectoral, and coordinated policy actions. This applies notably to Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-being), SDG 4 (Quality Education), SDG 8 (Decent Work and Economic Growth), and SDG 13 (Climate Action), which address health, education, economic development, and climate change.