COMPUTATIONAL TOOLS FOR POVERTY MEASUREMENT AND ANALYSIS

Gaurav Datt

177 citations0/0 files storedAgEcon Search (University of Minnesota, USA)

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Income, Poverty, and Inequality Poverty, Education, and Child Welfare demographic modeling and climate adaptation

Abstract

This paper introduces some relatively simple computational tools for estimating poverty measures from the sort of data that are typically available from published sources. All that is required for using these tools is an elementary regression package. The methodology also easily lends itself to a number of poverty simulations that are discussed. The paper addresses the central question: How do we construct poverty measures from grouped data? Two broad approaches are examined: simple interpolation methods and methods based on parameterized Lorenz curves. The second method is examined in detail.

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References

1991Growth and redistribution components of changes in poverty measures : a decomposition with applications to Brazil and India in the 1980s 1980On a Class of Poverty Measures 1997Repayment performance in group-based credit programs in Bangladesh: An empirical analysis 1995Gender differentials in farm productivity: implications for household efficiency and agricultural policy 2002Is There an Intrahousehold ‘Flypaper Effect’? Evidence from a School Feeding Programme 1994Determinants of credit rationing: A study of informal lenders and formal credit groups in Madagascar 1989Elliptical Lorenz curves 1996Women's Economic Advancement Through Agricultural Change: A Review of Donor Experience

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