Multi-Dimensional Poverty in the Newly Merged Tribal Districts of Khyber Pakhtunkhwa: Identifying The Key Areas of Priority

Abstract

Poverty measurement is a complex global challenge and a key target within the Sustainable Development Goals. Poverty is not a unidimensional issue tied solely to income or consumption but is instead a multidimensional phenomenon. This study investigates multidimensional poverty in the economically disadvantaged province of Khyber Pakhtunkhwa, Pakistan, with a specific focus on the newly merged tribal districts. Utilizing a nationally representative dataset, PSLM/HIES 2018-19, from the Pakistan Bureau of Statistics, the analysis is based on a sample size of 4464 households from Khyber Pakhtunkhwa. The study employs the Alkire-Foster methodology to measure multidimensional poverty, using dual cutoff points and constructing an index that incorporates nine dimensions: economic activity, living standards, environment, assets, education, health, food security, ICT access and women empowerment. The findings reveal a severe imbalance in poverty distribution across the province, with the seven recently merged tribal districts emerging as the poorest. Rural areas exhibit significantly higher multidimensional poverty compared to urban regions. Key covariates of poverty include remittances, the number of working household members, urban or rural location, and access to government canals for irrigation, all of which play a significant role in shaping household poverty status.