Income inequalities and subjective well-being have been increasingly identified in the literature as important measures of socio-economic cohesion. This is particularly relevant for developing economies that are typically characterised by strong population growth and relatively low incomes per head. Although in those economies a considerable share of resources is derived from rural areas, data availability for these regions is often an issue which precludes important insights into the overall socio-economic tissue of the developing world. This dissertation seeks to advance our knowledge on various aspects of inequalities and well-being with particular emphasis on rural Pakistan. At the core of the present monograph lie three chapters that deal with income inequality, subjective well-being as well as physical well-being (i.e. health). The empirical analysis is based on a unique survey dataset that covers the four provinces of rural Pakistan. The dissertation seeks to contribute to the existing literature in several dimensions. We decompose overall income inequality by its different types to disentangle which sources of income are inequality-increasing and which ones reduce socio-economic divergence. The empirical measurement and assessment of both subjective and physical well-being in rural Pakistan is a rather novel aspect. We introduce and examine different well-being measures as indicators of (subjective) poverty and find that well-being in rural areas is largely driven by financial factors. When it comes to health, however, overall results are less clear-cut. The thesis is therefore able to offer several policy recommendations for important socio-economic factors in rural Pakistan. On a more general note, some of the results discussed might also illuminate the policy debate in other geographic areas with similar characteristics.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:548985 |
| Date | January 2012 |
| Creators | Shams, Khadija |
| Publisher | University of Glasgow |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://theses.gla.ac.uk/3261/ |
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