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DC Field | Value | Language |
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dc.contributor.author | Sania Rehmat | - |
dc.date.accessioned | 2024-12-13T04:54:40Z | - |
dc.date.available | 2024-12-13T04:54:40Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | http://hdl.handle.net/123456789/30201 | - |
dc.description.abstract | The concept of poverty has evolved into a complex interplay of socioeconomic factors rather than mere monetary deprivation. There is an urgent need for researchers to move away from basic, one-dimensional assessments. As a result, the use of multidimensional diagnostics becomes critical for generating realistic and relevant policy recommendations. The study focuses on mapping multidimensional poverty in Pakistan from 2004–2005 to 2019–20, employing Amartya Sen's capability approach and the Alkire Foster (2011) methodology. The present study has considered education, health and living standard as the dimensions of wellbeing. It is based on micro data sets of Pakistan Social Living Standard Measurement. It identifies improvements in education, with a decline in deprivation over the last fifteen years, particularly in rural areas. Health deprivation, especially in child vaccination, decreased overall, with notable improvements in women's health. House quality and access to basic facilities improved across provinces, though rural areas faced more challenges. Asset deprivation decreased nationwide. Despite overall improvement, regional disparities persist, notably in Baluchistan, experiencing the lowest living standards. The research employed the Alkire Foster (2011) approach to assess magnitude and intensity of poverty in Pakistan, along its provinces and all districts. Poverty is measured in two ways, first is assigning equal weights to all dimensions and second is assigning weights according to relative importance of each dimension The study found that assigning same weights suppresses poverty. The results in general revealed that poverty has declined over last fifteen years in all parts of the country. Further we also found that poverty in rural areas is relatively higher in country due to lack of infrastructure and other basic facilities including schools and health care centers. Provincial comparison revealed that Punjab is the most privileged and Baluchistan is most deprived province of the country. Deprivation in Baluchistan is mainly due to inefficient infrastructure. The study also found intensity of poverty has substantially reduced over time. The study also explored the role of regional, social and household characteristics in poverty. We found that the education is one of the fundamental determinants of poverty, it has negative effect on poverty and thus can be useful in reducing poverty. We also found that dependency ratio is one of the strongest factors causing poverty. The probability of a household to be poor increases with the increase in dependency ratio. It was also seen that the probability of urban residents to be poor is less than the households living in rural areas. In general, urban areas of Pakistan have better infrastructure, better school system and better health facilities. Therefore, access to school and health care centers is relatively easy in urban areas. Secondly the quality of education and health care facilities are also better in urban areas. We also found that the age of the household head has negative effect on poverty, indicating that in general, households with aged heads are less prone to poverty. Regarding regional factors, we observed that income inequality in a region has a negative effect on poverty, the role of population density, number of hospitals and number of higher secondary schools is negligible in defining poverty. The study recommends policy measures, including enhancing education infrastructure, health campaigns, rural facilities, and overall living conditions. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Quaid I Azam University Islamabad | en_US |
dc.subject | Economics | en_US |
dc.title | Multidimensional Poverty in Pakistan: Regional and Temporal Analysis | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Ph.D |
Files in This Item:
File | Description | Size | Format | |
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ECO 1188.pdf | ECO 1188 | 5.22 MB | Adobe PDF | View/Open |
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