Multidimensional Poverty Measurement and Analysis: Chapter 10 – Some Regression Models for Af Measures
Alkire, S., Foster, J. E., Seth, S., Santos, M. E., Roche, J. M., and Ballon, P. (2015). Multidimensional Poverty Measurement and Analysis, Oxford: Oxford University Press, ch. 10
23 Pages Posted: 12 Mar 2015
Date Written: January 31, 2015
This Chapter provides the reader with a general modelling framework for analysing the determinants of the Alkire and Foster (2011) poverty measures for both micro and macro levels of analyses. At the micro level, we present a model where the focal variable is a person’s poverty status. At the macro level we present a model where the focal variable is an overall poverty measure like the poverty headcount ratio or the adjusted headcount ratio. The chapter presents these regression models within the structure of Generalized Linear Models (GLM’s), which allow accounting for bounded and discrete variables. GLMs encompass linear regression models, logit and probit models, and models for fractional data. Thus, they offer a general framework for our analysis of functional relationships with Alkire and Foster poverty measures.
Keywords: micro regressions; macro regressions; generalised linear models; logit/probit models; models for fractional data; determinants of poverty
JEL Classification: C01, C10
Suggested Citation: Suggested Citation