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What Factors Matter for Choice of Livelihood among the Older Workers in Sri Lanka?

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  • Samanthi Bandara

Abstract

Having a stable livelihood not only gives a financial safeguard for ageing but also works as a policy solution for rapid ageing. Like many other countries, Sri Lanka is also confronting a rapid ‘population ageing’ phenomenon. Population ageing not only affects structural changes in the population but also impacts a country’s macroeconomic and social conditions. Enforcing human resource policy solutions to retain older workers in the labour force longer is one of the measures which can prevent the economy, as well as individual households, from the excess burden of old age dependents. This study aims to investigate the factors which explain the choice of livelihood of persons aged over 50 years. Two multinomial logit models were used to determine the factors affecting labour force participation and sector participation (public, private and self-employed). Varme’s occupation choice model (2000) was employed as the theoretical model. Entering to different job opportunities is mostly concentrated in the urbanized cities and job opportunities in less-developed districts are limited only to the public sector. In addition, lower educated people have less chance to engage in employment, and a majority of them are unemployed. Higher educated people mostly work in public sector, than in the private sector. Accordingly, effective policy decision needs to be taken to redistribute the benefits of economic development equitably.

Suggested Citation

  • Samanthi Bandara, 2017. "What Factors Matter for Choice of Livelihood among the Older Workers in Sri Lanka?," Indian Journal of Human Development, , vol. 11(2), pages 210-231, August.
    • Handle: RePEc:sae:inddev:v:11:y:2017:i:2:p:210-231
    DOI: 10.1177/0973703017737863
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    References listed on IDEAS

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    1. Meilian Zhang & Ting Yin & Emiko Usui & Takashi Oshio & Yi Zhang, 2024. "Unraveling the determinants of overemployment and underemployment among older workers in Japan: A machine learning approach," The Japanese Economic Review, Springer, vol. 75(4), pages 691-737, December.

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