The Effects of Mortality Shocks on Household Spending on Education, Health and Nutrition



Death in family is a tragic event with life-changing consequences for the surviving members. When the deceased person is a prime-aged adult, the economic shock created by the event can even be catastrophic. While death at older ages may be anticipated, death at prime age is often sudden and unanticipated. Such unanticipated death can often be a consequence of natural disasters. But death among adult household members can also be relatively quick as a consequence of HIV/AIDS and other life–threatening viral illnesses. In such situations, death may not be completely unanticipated, yet likely quick and disruptive enough so as to inhibit coping mechanisms from being put in place to negate the impacts of the death-event itself.


Household Size Adult Mortality Consumption Growth Education Expenditure Adult Death 
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  1. Aguero, J., Carter, M. R. et al. (2007). “Poverty and Inequality in the First Decade of South Africa’s Democracy: What Can Be Learnt from Panel Data from KwaZulu-Natal?” Journal of African Economies, vol. 16: 782–812.CrossRefGoogle Scholar
  2. Beegle, K., De Weerdt, J. and Dercon, S. (2008). “Adult Mortality and Consumption Growth in the Age of HIV/AIDS.” Economic Development and Cultural Change, vol. 56: 299–326.CrossRefGoogle Scholar
  3. Carter, M. R., May, J., Agüero, J., and Ravindranath, S. (2007). “The Economic Impacts of Premature Adult Mortality: Panel Data Evidence from KwaZulu-Natal, South Africa.” AIDS, vol. 21: S67–73.CrossRefGoogle Scholar
  4. Chapoto, A. and Jayne, T. S. (2008). “Impact of AIDS-Related Mortality on Farm Household Welfare in Zambia.” Economic Development and Cultural Change, vol. 56 (2): 327–74.CrossRefGoogle Scholar
  5. Dercon, S., Hoddinott, J., and Woldehanna, T. (2005). “Shocks and Consumption in 15 Ethiopian Villages, 1999–2004.” Journal of African Economies, vol. 14 (4): 559–85.CrossRefGoogle Scholar
  6. Dorrington, R. E., Johnson, L. F., Bradshaw, E. and Daniel, T. (2006). The Demographic Impact of HIV/AIDS in South Africa: National and Provincial Indicators for 2006. Cape Town: Centre for Actuarial Research, South African Medical Research Council and Actuarial Society of South Africa.Google Scholar
  7. Fallon, P. and Lucas, R. E. B. (2002). “The Impact of Financial Crises on Labor Markets, Household Incomes, and Poverty: A Review of Evidence.” World Bank Research Observer, vol. 17 (1): 21–45.CrossRefGoogle Scholar
  8. Fiske, E. B. and Ladd, H. F. (2004). Elusive Equity: Education Reform in Post-Apartheid South Africa. Washington, DC: Brookings Institution Press.Google Scholar
  9. Hosegood, V., Vanneste, A. M., and Timaeus, I. M. (2004). “Levels and Causes of Adult Mortality in Rural South Africa: The Impact of AIDS.” AIDS, vol. 18 (4): 663.CrossRefGoogle Scholar
  10. Kinsey, B., Burger, K., and Gunning, J. W. (1998). “Coping with Drought in Zimbabwe: Survey Evidence on Responses of Rural Households to Risk.” World Development, vol. 26 (1): 89–110.CrossRefGoogle Scholar
  11. Kochar, A. (1995). “Explaining Household Vulnerability to Idiosyncratic Income Shocks.” American Economic Review, vol. 85 (2): 159–64.Google Scholar
  12. Mather, D., Donovan, C, Jayne, T. S. et al. (2004). A Cross-Country Analysis of Household Responses to Adult Mortality in Rural Sub-Saharan Africa: Implications for HIV/AIDS Mitigation and Rural Development Policies. MSU International Development, Working Papers.Google Scholar
  13. May, J., Carter, M. R., Haddad, L., and Maluccio, J. (2000). “KwaZulu-Natal Income Dynamics Study (KIDS) 1993–98: A Longitudinal Household Database for South African Policy Analysis.” Development Southern Africa, vol. 17: 567–81.CrossRefGoogle Scholar
  14. May, J. D., Aguero, J., Carter, M. R., and Timaeus, I. M. (2007). “The KwaZulu-Natal Income Dynamics Study (KIDS) Third Wave: Methods, First Findings and an Agenda for Future Research.” Development Southern Africa, vol. 24: 629–48.CrossRefGoogle Scholar
  15. Paxson, C. (1992). “Using Weather Variability to Estimate the Response of Savings to Transitory Income in Thailand.” American Economic Review, vol. 82 (1): 15–33.Google Scholar
  16. Sarris, A., Hoffmann, V, and Christiaensen, L. (2007). Gauging the Welfare Effects of Shocks in Rural Tanzania. World Bank, Policy Research, Working Paper Series, No. 4406.Google Scholar

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