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|dc.description.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.||en_US|
|dc.publisher|||aIbero-Amerika-Inst. für Wirtschaftsforschung |cGöttingen||en_US|
|dc.relation.ispartofseries|||aDiscussion papers, Ibero America Institute for Economic Research |x187||en_US|
|dc.title||Micro level estimation of income: Simulated welfare mapping (poverty maps) for Paraguay 1992 and 2002||en_US|
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