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Micro Level Estimation of Income - Simulated welfare mapping (poverty maps) for Paraguay 1992 and 2002

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  • Thomas Otter

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    Abstract

    Recent theoretical and empirical advances have brought income and wealth distributions back into a prominent position in growth and development theories, and as determinants of specific socio-economic outcomes, such as health or levels of violence and related phenomenon of inequality. To improve empirical investigation, new techniques were required for the simulation of small scale welfare indicators, such as income and its related distribution. Elbers, Lanjouw and Lanjouw (2003) designed a statistical procedure to combine different types of data and take advantage of the detail in household sample surveys and the comprehensive coverage of a census. The method extends the literature on small area statistics (Ghosh and Rao (1994), Rao (1999)) by developing estimators of population parameters which are non-linear functions of the underlying variable of interest (for example per capita income) by deriving them from the full unit level distribution of that variable. The most famous output of these exercises is known as “poverty maps”. The use of these poverty maps is an important poverty reduction policy implementation tool used for selecting the poorest villages in the country (or villages where the greatest number of poor people are), such as the programs Bolsa Escuela in Brasil, Progreso in Mexico, Puente in Chile, Bolsa Familia in Argentina, Bono de Desarrollo Humano in Ecuador or Tekopora in Paraguay; all of these conditional cash transfer programs, directly to extremely poor households.

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    Bibliographic Info

    Paper provided by Ibero-America Institute for Economic Research in its series Ibero America Institute for Econ. Research (IAI) Discussion Papers with number 187.

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    Length: 34 pages
    Date of creation: 05 May 2009
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    Handle: RePEc:got:iaidps:187

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    1. Bigman, David & Fofack, Hippolyte, 2000. "Geographical Targeting for Poverty Alleviation: An Introduction to the Special Issue," World Bank Economic Review, World Bank Group, vol. 14(1), pages 129-45, January.
    2. 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.
    3. Stephan Klasen, 2004. "In Search of the Holy Grail: How to Achieve Pro-Poor Growth?," Macroeconomics 0401005, EconWPA.
    4. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-66, May.
    5. Demombynes, Gabriel & Elbers, Chris & Lanjouw, Jenny & Lanjouw, Peter & Mistiaen, Johan & Ozler, Berk, 2002. "Producing an Improved Geographic Profile of Poverty: Methodology and Evidence from Three Developing Countries," Working Paper Series UNU-WIDER Research Paper , World Institute for Development Economic Research (UNU-WIDER).
    6. Pradhan, Menno, et al, 2001. "Eating Like Which "Joneses?" An Iterative Solution to the Choice of a Poverty Line "Reference Group."," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 47(4), pages 473-87, December.
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