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Estimating Vulnerability to Poverty using Panel data: Evidence from Indonesia

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  • Adama BAH

    (Centre d'Etudes et de Recherches sur le Développement International(CERDI))

Abstract

Traditional poverty measures fail to indicate the degree of risk of becoming or remaining poor that households are confronted to. They can therefore be misleading in the context of implementing poverty reduction policies. In this paper I propose a method to estimate an index of ex ante vulnerability to poverty, defined as the probability of being poor in the (near) future given current observable characteristics, using panel data. This method relies on the estimation of the expected mean and variance of future consumption conditional on current consumption and observable characteristics. It generates a vulnerability index, or predicted probability of future poverty, which performs well in predicting future poverty, including out of sample. About 80% of households with a 2000 vulnerability index of 100% are actually poor in 2007. This approach provides information on the population groups that have a high probability of becoming or remaining poor in the future, whether currently poor or not. It is therefore useful to complement traditional poverty measures such as the poverty headcount, in particular for the design and planning of poverty reduction policies.

Suggested Citation

  • Adama BAH, 2013. "Estimating Vulnerability to Poverty using Panel data: Evidence from Indonesia," Working Papers 201325, CERDI.
    • Handle: RePEc:cdi:wpaper:1511
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    References listed on IDEAS

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    1. Martin Ravallion & Michael Lokshin, 2007. "Lasting Impacts of Indonesia’s Financial Crisis," Economic Development and Cultural Change, University of Chicago Press, vol. 56(1), pages 27-56, October.
    2. Duncan Thomas & Elizabeth Frankenberg & James P. Smith, 2001. "Lost but Not Forgotten: Attrition and Follow-up in the Indonesia Family Life Survey," Journal of Human Resources, University of Wisconsin Press, vol. 36(3), pages 556-592.
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    4. Thomas, Duncan & Witoelar, Firman & Frankenberg, Elizabeth & Sikoki, Bondan & Strauss, John & Sumantri, Cecep & Suriastini, Wayan, 2012. "Cutting the costs of attrition: Results from the Indonesia Family Life Survey," Journal of Development Economics, Elsevier, vol. 98(1), pages 108-123.
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    6. repec:bla:revinw:v:47:y:2001:i:4:p:473-87 is not listed on IDEAS
    7. Wenefrida Dwi Widyanti & Asep Suryahadi & Sudarno Sumarto & Athia Yumna, "undated". "The Relationship between Chronic Poverty and Household Dynamics: Evidence from Indonesia," Working Papers 339, Publications Department.
    8. Pritchett, Lant & Suryahadi, Asep & Sumarto, Sudarno, 2000. "Quantifying vulnerability to poverty - a proposed measure, applied to Indonesia," Policy Research Working Paper Series 2437, The World Bank.
    9. Stefan Dercon & Pramila Krishnan, 2000. "Vulnerability, seasonality and poverty in Ethiopia," Journal of Development Studies, Taylor & Francis Journals, vol. 36(6), pages 25-53.
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    Cited by:

    1. Higashikata, Takayuki & Hashiguchi, Yoshihiro, 2017. "The causal effect of urbanization on rural poverty reduction: quasi-experimental evidence using Indonesian urban area data," IDE Discussion Papers 673, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    2. Jehane Simona-Moussa, 2020. "The Subjective Well-Being of Those Vulnerable to Poverty in Switzerland," Journal of Happiness Studies, Springer, vol. 21(5), pages 1561-1580, June.
    3. Zhang Huafeng, 2016. "Household vulnerability and economic status during disaster recovery and its determinants: a case study after the Wenchuan earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(3), pages 1505-1526, September.

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    More about this item

    Keywords

    Poverty; Vulnerability; Household consumption;
    All these keywords.

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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