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Wageningen University (2015)

The livelihood and poverty mapping analysis at regional level in Pakistan

Begum, Shazia

Titre : The livelihood and poverty mapping analysis at regional level in Pakistan

Auteur : Begum, Shazia

Université de soutenance : Wageningen University

Grade : Master of Science (MS) 2015

Résumé
An attempt has been made to map the incidence of uni-dimensional and multi-dimensional poverty simultaneously arguably for the first time in Pakistan. While multi-dimensional poverty map is calculated using PSLM 2010-11 ; small area estimation technique is utilized to map uni-dimensional poverty using both nationally representative HIES (Household Integrated Economic Survey) and district-level representative PSLM (Pakistan Standard of Living Measurement) for the same year of 2010-11. The result indicates the existence of spatial distribution of poverty pockets in each of the four provinces of Pakistan. Furthermore, it is also observed that these pockets of poverty are more concentrated in the desert and mountains regions of the country. Along with this, the poverty mapping exercise has shed light on the fact that poverty has a negative feedback effect implying that underdevelopment breeds further underdevelopment. Moreover, one overwhelming pattern observed is that extent of poverty exuberates when attention is turned to multi-dimensional poverty from uni-dimensional poverty measure. This hints towards a largely underdevelopment social sector in the country. However, as mentioned above, the performance of the social sector also has a geographical character with Punjab having a relatively stronger social sector track-record. Resultantly, Sindh, KPK, and Balochistan are lagging behind drastically in terms of social sector performance. Subsequently, it is found that Balochistan and KPK are the poorest regions multidimensionally along with Southern Sindh. In light of this, it is suggested that nationally representative policies for poverty alleviation integrate need for geographical poverty targeting.

Mots Clés  : Poverty mapping, Small Area estimation technique, multi-dimensional poverty, spatial distribution of poverty , poverty alleviation

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