Multidimensional Poverty Measurement and Analysis: Chapter 10 – Some Regression Models for AF Measures

OPHI Working Papers

Chapter 10 provides the reader with a general modelling framework for analysing the determinants of poverty measures presented in Chapter 5 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 the 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 AF measures presented in Chapter 5. 

Citation: Alkire, S., Foster, J. E., Seth, S., Santos, M. E., Roche, J. M., and Ballon, P. (2015). 'Multidimensional Poverty Measurement and Analysis', OPHI Working Papers 91, Oxford: Oxford University Press, ch. 10

Also published in Multidimensional Poverty Measurement and Analysis, Oxford University Press, 2015.

Micro regressions, macro regressions, generalised linear models, logit/probit models, models for fractional data, determinants of poverty

Sabina Alkire, James E. Foster, Suman Seth, Maria Emma Santos, Jose M. Roche and Paola Ballon
Series Name
OPHI Working Papers
Publication date
JEL Codes
C01, C10
Publication Number
WP 91