Investigating the Connections between Income Poverty and Multidimensional Poverty: An Evidence From Punjab-MICS Survey Data

Abstract

The key objectives of this study are to measure the multidimensional poverty index by applying the Alkire Foster method on MICS survey data, to explore the determinants of multidimensional poverty, and to investigate the connections between income poverty and multidimensional poverty in Punjab-Pakistan. The logistic regression model is used to investigate the determinants of multidimensional poverty. The results of this study show that about 33 percent of the Punjab’s population is multi-dimensionally poor and 14 percent income poor. Over the Province Punjab, there are some districts which experiencing highest multidimensional poverty; such as Rajanpur, Dera Ghazi Khan, Muzaffargarh, Rahimyar Khan, and Bahawalpur. The result of the model shows that income poverty has statistically significant and positive influence on multidimensional poverty. While the household size, land ownership, and household head’s education have statistically significant and negative effect on multidimensional poverty. The study suggests that policies should be adopted to increase the income level at the household, an education level (to raise literacy rate), social welfare programs, and employment opportunities, etc. Policies should be designed to increase the physical, social, and economic access of people toward all dimensions of education, health, and standard of living to decrease multidimensional poverty in the Province.