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Breaking the Perverse Health-debt Cycle in Sri Lanka: Policy Options

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  • Samaratunge, Ramanie
  • Kumara, Ajantha Sisira
  • Abeysekera, Lakmal

Abstract

This paper proposes a finite mixture model to examine how health adversities influence indebtedness of Sri Lankan households. After accounting for unobserved heterogeneity, our empirical analysis reveals that households headed by ill-health members and those with hospitalization are inevitably more vulnerable to indebtedness. The ill-health status of other working-age members also creates milder effects on household indebtedness. We confirm that the health-debt cycle is more severe for urban households, compared to their rural counterparts. The study is testimony to re-emphasizing the role of government in providing much-needed financial protection to vulnerable households and implementing differentiated-policy packages for urban and rural sectors in order to effectively break the health-debt cycle.

Suggested Citation

  • Samaratunge, Ramanie & Kumara, Ajantha Sisira & Abeysekera, Lakmal, 2020. "Breaking the Perverse Health-debt Cycle in Sri Lanka: Policy Options," Journal of Policy Modeling, Elsevier, vol. 42(3), pages 728-745.
  • Handle: RePEc:eee:jpolmo:v:42:y:2020:i:3:p:728-745
    DOI: 10.1016/j.jpolmod.2020.01.003
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    Cited by:

    1. Pengpeng Yue & Aslihan Gizem Korkmaz & Zhichao Yin & Haigang Zhou, 2022. "The rise of digital finance: Financial inclusion or debt trap," Papers 2201.09221, arXiv.org.
    2. Yue, Pengpeng & Korkmaz, Aslihan Gizem & Yin, Zhichao & Zhou, Haigang, 2022. "The rise of digital finance: Financial inclusion or debt trap?," Finance Research Letters, Elsevier, vol. 47(PA).

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    More about this item

    Keywords

    Ill-health; Household surveys; Indebtedness; Unobserved-heterogeneity; Living sector;
    All these keywords.

    JEL classification:

    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

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