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Does the old-age pension scheme improve household welfare? Evidence from India

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  • Unnikrishnan, Vidhya
  • Imai, Katsushi S.

Abstract

As India’s population has been ageing due to declines in fertility and mortality rates, more policy emphasis has been placed on reducing poverty among the elderly. The present study aims to examine the effect of Indira Gandhi National Old Age Pension Scheme (IGNOAPS) on household welfare indicators, such as consumption expenditure, income, assets, and poverty. Using the household longitudinal data based on the India Human Development Survey in 2004–5 and 2011–12, we have applied the Propensity Score Matching to build a counterfactual group and have used the propensity-score weighted fixed effects model to eliminate time-invariant unobservable household characteristics. The results show that the IGNOAPS participation increased consumption expenditure, food and non-food expenditure and assets, while reducing the household labour supply. The sub-sample estimations show that these effects are observed only when recipients are women. However, the results of Difference-in-Difference model imply that the poverty-reducing effect deteriorated in 2011–12 after the government made several changes to programme specifications in 2007. This was likely because some households which accessed IGNOAPS after 2007 reduced the labour supply significantly while keeping the level of consumption.

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  • Unnikrishnan, Vidhya & Imai, Katsushi S., 2020. "Does the old-age pension scheme improve household welfare? Evidence from India," World Development, Elsevier, vol. 134(C).
  • Handle: RePEc:eee:wdevel:v:134:y:2020:i:c:s0305750x20301431
    DOI: 10.1016/j.worlddev.2020.105017
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    2. Vidhya Unnikrishnan & Kunal Sen, 2020. "Old-age pensions and female labour supply in India," WIDER Working Paper Series wp-2020-90, World Institute for Development Economic Research (UNU-WIDER).
    3. Kang, Ji Young & Park, Sojung & Ahn, Seoyeon, 2022. "The effect of social pension on consumption among older adults in Korea," The Journal of the Economics of Ageing, Elsevier, vol. 22(C).
    4. Yannick Markhof & Isabela Franciscon & Nicolò Bird & Pedro Arruda, 2021. "Social assistance programmes in South Asia: an evaluation of socio-economic impacts," Research Report 62, International Policy Centre for Inclusive Growth.
    5. Yoko Niimi & Charles Yuji Horioka, 2023. "Elderly poverty and its measurement," Chapters, in: Jacques Silber (ed.), Research Handbook on Measuring Poverty and Deprivation, chapter 29, pages 307-315, Edward Elgar Publishing.
    6. Yang, Feng-An & Chang, Hung-Hao, 2023. "Impact of a pension program on healthcare utilization among older farmers: Empirical evidence from health claims data," World Development, Elsevier, vol. 169(C).
    7. Sridhar Kundu & Maynor Cabrera, 2022. "Fiscal Policies and their Impact on Income Distribution in India," Commitment to Equity (CEQ) Working Paper Series 120, Tulane University, Department of Economics.
    8. María Laura Alzua & Natalia Cantet & Ana C. Dammert & Damilola Olajide, 2023. "The Wellbeing Effects of an Old Age Pension: Experimental Evidence for Ekiti State in Nigeria," CEDLAS, Working Papers 0322, CEDLAS, Universidad Nacional de La Plata.
    9. Chatterjee, Sidharta, 2022. "Rationalizing Decision Choices: What Influences our Social Decision Making?," MPRA Paper 114985, University Library of Munich, Germany.
    10. Anqi Zhang & Katsushi S. Imai, 2022. "Does a Universal Pension Reduce Elderly Poverty in China?," Economics Discussion Paper Series 2203, Economics, The University of Manchester.
    11. Unnikrishnan, Vidhya & Pinet, Melanie & Marc, Lukasz & Boateng, Nathaniel Amoh & Boateng, Ethel Seiwaa & Pasanen, Tiina & Atta-Mensah, Maya & Bridonneau, Sophie, 2022. "Impact of an integrated youth skill training program on youth livelihoods: A case study of cocoa belt region in Ghana," World Development, Elsevier, vol. 151(C).
    12. Vidhya Unnikrishnan & Subhasish Dey, 2023. "Political meddling in social assistance programme: Panel data evidence from India," Journal of International Development, John Wiley & Sons, Ltd., vol. 35(6), pages 1346-1364, August.
    13. Nelson Kemboi Yego & Juma Kasozi & Joseph Nkurunziza, 2023. "Optimizing Pension Participation in Kenya through Predictive Modeling: A Comparative Analysis of Tree-Based Machine Learning Algorithms and Logistic Regression Classifier," Risks, MDPI, vol. 11(4), pages 1-21, April.
    14. Dong, Shizheng & Zhang, Zili & Han, Yiduo & Si, Yanwu, 2023. "Do pension subsidies reduce household education expenditure inequality? Evidence from China," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 532-540.
    15. Anqi Zhang & Katsushi S. Imai, 2022. "Does a Universal Pension Reduce Elderly Poverty in China?," Discussion Paper Series DP2022-30, Research Institute for Economics & Business Administration, Kobe University.
    16. Alzua, Maria Laura & Cantet, Maria Natalia & Dammert, Ana & Olajide, Daminola, 2020. "Mental Health Effects of an Old Age Pension: Experimental Evidence for Ekiti State in Nigeria," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304176, Agricultural and Applied Economics Association.
    17. Nawaz, Saima & Iqbal, Nasir, 2021. "How cash transfers program affects environmental poverty among ultra-poor? Insights from the BISP in Pakistan," Energy Policy, Elsevier, vol. 148(PB).

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    More about this item

    Keywords

    Pension; Ageing; IGNOAPS; Poverty; Household Welfare; India;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare

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