Cogent Economics & Finance (Oct 2023)

Rural Poverty profile in Pakistan: Incidence, Severity, and Correlates through Consumption Based Approach

  • Muhammad Mehboob Alam,
  • Sayed Irshad Hussain,
  • Akhtar Hussain,
  • Izhar Ul Hassan

DOI
https://doi.org/10.1080/23322039.2023.2276794
Journal volume & issue
Vol. 11, no. 2

Abstract

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AbstractThis study is an attempt to estimate the incidence, severity, depth, and determinants of poverty in Jhang district, Punjab, Pakistan. For this purpose, the data were collected from 1,000 households through a specifically designed questionnaire using multistages sampling technique in all four subdistricts of Jhang district. The study used both income-regression model and logistic regression to assess the impact of demographic and socioeconomic factors on poverty incidence. The results show that 54.3% of households are below the poverty line, including 16% extremely poor. Poverty measures including headcount index, severity, and depth of poverty are worse among the households headed by farmers, daily-wagers, and illiterates. Moreover, the results confirm that the household’s livestock population, landholding, ownership of agricultural land, total assets, and earners per household considerably reduced the poverty incidence in Jhang district. While household size, age of household head, economic dependency ratio, and total dependency ratio significantly increased the level of poverty. The study concludes that demographic and socioeconomic characteristics of the households are of greater importance in alleviating poverty generally in Pakistan but particularly in rural areas. Hence, it is suggested that governments should increase public spending on socioeconomic programs and services with a particular focus on education, women’s empowerment, family planning, employment opportunity, pro-agriculture policies, and equitable distribution of land and wealth to alleviate poverty in rural areas of Pakistan. Further research can be conducted by selecting large sample size and analyzing the household characteristics at the disaggregated level incorporating time variations to develop a more impactful policy framework.

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