Spatial analysis of multidimensional poverty in Pakistan: Do income and poverty score of neighboring regions matter?

Eradication of multidimensional poverty remains a significant issue for a number of low-income countries. It has significantly influenced economic development worldwide, and its abolition would improve human well-being and prosperity. In this study, a multidimensional poverty (MDP) index has been constructed by adopting the Alkire-Foster methodology and Geographic Information System application to (i) measure the multidimensional poverty in all districts of Pakistan, (ii) recognize the spatial patterns concerning MDP in Pakistan, (iii) examine the impact of per-capita income on MDP in Pakistan and, (iv) assess the spatial impact of neighbors’ poverty scores on MDP. The findings of the study indicated that the magnitude of both headcount and MDP varies across provinces and was found to be higher and lower in Balochistan and Punjab, respectively. The spatial results revealed that in terms of both MDP and headcount poverty, the majority of Punjab districts were significantly clustered in low and very low quantiles (low-low quadrants) whereas districts from Balochistan were concentrated in high and very high quantiles (high-high quadrants). Furthermore, the spatial regression showed that per capita income had substantially reduced the incidence of poverty both directly and indirectly. Most importantly, the poverty score of neighboring districts has significantly influenced the incidence of district own MDP. Based on the instant spatial results, Balochistan is considered the highly poverty-stricken province of Pakistan that needs government intervention and policy makers’ prioritization towards the study indicators to eradicate the incidence of multidimensional poverty.