Evaluating poverty determinants in Zambia with principle component analysis and logistic regression
Lincoln Daka, Humphrey Fandamu
Poverty is multi-dimensional in nature and depends on interactions of various socio-economic factors. Several demographic and health factors can shape up the economic status of a household, and theory suggests that the ability of a household to earn a given level of income can depend on the characteristics internal to the household. While most of the studies done on poverty determinants rely on the income, expenditure and consumption data, the data used in this study comes from the Demographic and Health Surveys, (DHS). The principal component analysis is used to create an asset index which gives the social economic status (SES) of each household. A Logistic regression is estimated based on this data with the SES (that is poor and non-poor) as the dependent variable and a set of demographic variables as the explanatory variables. The results presented in this paper suggest that the DHS data can be used to determine the correlates of poverty.
Lincoln Daka, Humphrey Fandamu. Evaluating poverty determinants in Zambia with principle component analysis and logistic regression. International Journal of Multidisciplinary Research and Development, Volume 3, Issue 2, 2016, Pages 320-327