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Poverty Response to the Household Type of Elderly and Old-Age Pension

Author

Listed:
  • Andrews Doeh Agblobi
  • Anthony Kofi Osei-Fosu
  • Hadrat Yusif

Abstract

This paper investigates the effect of household type and old-age pension on poverty in Ghana. Primary data was collected from households with the elderly across six Districts in the country. A binary logistic regression estimation was used for the analyses. The result shows that whereas there was 14.4 times probability of being poor by living in an elderly only household, there is a 2.2 times probability of being poor in a household of the elderly and working-age person. The findings also show that the probability of a pension recipient being poor was 0.143 times less likely as compared to those that were not. Thus, there was a significant negative relationship between receipt of old-age pension and poverty. The study recommends that public policy on old age poverty alleviation must include pension provisions while those that use basic salary should consider using gross salary for pension calculation.

Suggested Citation

  • Andrews Doeh Agblobi & Anthony Kofi Osei-Fosu & Hadrat Yusif, 2020. "Poverty Response to the Household Type of Elderly and Old-Age Pension," Business and Management Research, Business and Management Research, Sciedu Press, vol. 9(4), pages 1-20, December.
    • Handle: RePEc:jfr:bmr111:v:9:y:2020:i:4:p:20
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    References listed on IDEAS

    as
    1. Bruce, Neil & Turnovsky, Stephen J., 2013. "Social security, growth, and welfare in overlapping generations economies with or without annuities," Journal of Public Economics, Elsevier, vol. 101(C), pages 12-24.
    2. Ousmane Faye, 2007. "Basic Pensions and Poverty Reduction in Sub-Saharan Africa," CREPP Working Papers 0707, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.
    3. Fiona Stewart & Juan Yermo, 2009. "Pensions in Africa," OECD Working Papers on Insurance and Private Pensions 30, OECD Publishing.
    4. Armando Barrientos, 2014. "Is There a Role for Social Pensions in Asia?," Asia and the Pacific Policy Studies 201502, Crawford School of Public Policy, The Australian National University.
    5. Olivia Anku-Tsede & Albert Amankwaa & Aaron Amertowo, 2015. "Managing Pension Funds in Ghana: An Overview," Business and Management Research, Business and Management Research, Sciedu Press, vol. 4(1), pages 25-33, March.
    6. Akanksha Negi & Jeffrey M. Wooldridge, 2021. "Revisiting regression adjustment in experiments with heterogeneous treatment effects," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 504-534, April.
    7. Daniele Franco & Maria Rosaria Marino & Pietro Tommasino, 2008. "Pension Policy and Poverty in Italy: Recent Developments and New Priorities," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 67(2), pages 119-160, July.
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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