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An exercise to evaluate an anti-poverty program with multiple outcomes using program evaluation

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  • Tonmoy Islam, T.M.

Abstract

To measure the effectiveness of programs with multiple outcomes, I combine multidimensional poverty measures with difference-in-difference matching estimators. I apply this technique on an anti-poverty program and show it is a more comprehensive measure of poverty reduction than a unidimensional measure.

Suggested Citation

  • Tonmoy Islam, T.M., 2014. "An exercise to evaluate an anti-poverty program with multiple outcomes using program evaluation," Economics Letters, Elsevier, vol. 122(2), pages 365-369.
    • Handle: RePEc:eee:ecolet:v:122:y:2014:i:2:p:365-369
    DOI: 10.1016/j.econlet.2013.12.032
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    References listed on IDEAS

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    1. Sabina Alkire, Maria Emma Santos, 2010. "Acute Multidimensional Poverty: A New Index for Developing Countries," OPHI Working Papers 38, Queen Elizabeth House, University of Oxford.
    2. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
    3. Alkire, Sabina & Foster, James, 2011. "Counting and multidimensional poverty measurement," Journal of Public Economics, Elsevier, vol. 95(7), pages 476-487.
    4. Mª Casilda Lasso de la Vega & Ana Urrutia & Henar Diez, 2009. "The Bourguignon and Chakravarty multidimensional poverty family: A characterization," Working Papers 109, ECINEQ, Society for the Study of Economic Inequality.
    5. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    6. François Bourguignon & Satya R. Chakravarty, 2019. "The Measurement of Multidimensional Poverty," Themes in Economics, in: Satya R. Chakravarty (ed.), Poverty, Social Exclusion and Stochastic Dominance, pages 83-107, Springer.
    7. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    8. David Hulme & Karen Moore, 2007. "Assisting the poorest in Bangladesh: Learning from BRAC’s ‘Targeting the Ultra Poor’ Programme," Global Development Institute Working Paper Series 0107, GDI, The University of Manchester.
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    Cited by:

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    2. Lara de Melo Barbosa Andrade & Gilvan Ramalho Guedes & Kenya Valeria Micaela de Souza Noronha & Cláudio Moisés Santos e Silva & Jéferson Pereira Andrade & Albert Smith Feitosa Suassuna Martins, 2021. "Health-related vulnerability to climate extremes in homoclimatic zones of Amazonia and Northeast region of Brazil," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-24, November.
    3. Libang Ma & Xinglong Che & Junhui Zhang & Fang Fang & Meimei Chen, 2019. "Rural Poverty Identification and Comprehensive Poverty Assessment Based on Quality-of-Life: The Case of Gansu Province (China)," Sustainability, MDPI, vol. 11(17), pages 1-18, August.
    4. Zhineng Hu & Jing Ma & Qiong Feng & C. Patrick Scott & Hani I. Mesak, 2022. "The detection dilemma of marginally non‐poor households in poverty alleviation evaluation: Evidence from a linear quantile mixed model," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1491-1517, August.
    5. Sophie Song and Katsushi S. Imai, 2018. "Does the Hunger Safety Net Programme Reduce Multidimensional Poverty? Evidence from Kenya," OPHI Working Papers ophiwp124.pdf, Queen Elizabeth House, University of Oxford.

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    More about this item

    Keywords

    Program evaluation; Multidimensional poverty index;

    JEL classification:

    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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