This section deals with the studies regarding spatial and geographical poverty in Pakistan. Some important studies [4, 14, 20, 25, 45] are reviewed, and these are gives as follows.
Khan et al. [34] have found district-level multiple deprivations in Pakistan. The data of PSLM for the period of (2005) have been taken, and deprivation index has been constructed on the basis of education (illiteracy rate for females, illiteracy rate for male, out of school children), housing quality and congestion (percentage of homeless, percentage of home owing, inadequate material used in wall and roof, room available per member, and households having no facility of wash rooms), residential housing services (un-electrified households, households not using cooking gas, households did not have proper water facility), and employment (unemployment, employed labor force in non-manufacturing sectors). They have used PCA to generate deprivation index. The results suggested that Baluchistan province faces higher deprivation and after that KPK, Sindh, and Punjab, respectively. Moreover, district-wise analysis for least deprived suggested that Questta was at the top of least deprived district, yielding score of 46, and Sukhar, Peshawar, Faisalabad, Gujarat, Rawalpindi, Sialkot, Gujranwala, Lahore, and Karachi were, respectively, deprived districts of Pakistan. The list of the highest deprived districts of Baluchistan Musakhel, Awaran, Kharan, Zob, Qillah Saifullah, Panjgur, Jhal Magsi, Qilla Abdullah, Khuzdar, and Kohistan were, respectively, highly deprived of the aforementioned indicators. These are indicative of the presence of the spatial and geographical poverty in Pakistan and are required to provide them government consideration.
Cheema et al. [14] have investigated spatial and geographical poverty in Punjab province, and data have been collected from Multiple Indicators Cluster Survey (MICS) for the period of 2003–2004, and it has datum which was representative at district level. The main concern was district level and sub-province-wise poverty; therefore, Punjab has been classified into four regions: Northern Punjab, South Punjab, West Punjab, and central Punjab. Central Punjab consisted of Faisalabad, Lahore, Gujranwala, Sheikhupura, Pakpatan, Sargodha, Hafizabad, Norowal, Gujrat, and Sialkot, Kasur, T.T. Singh, Jhang, Okara, and Sahiwal. North Punjab consisted of Attock, Chakwal, Rawalpindi, and Jahelum. South Punjab comprised Vehari, Lodhran, Multan, R.Y. Khan, Bahawalnagar, and Bahawal pur. Finally, West Punjab consisted of Bhakkar, Mianwali, Rajan Pur, Khushab, Layyah, Muzaffargarh, and D.G. Khan. To calculate poverty, they used deprivation indices, which were calculated by using multiple indicators education, housing quality, housing services, employment, social indicators, and poverty head counts as well. They calculated it with the help of PCA, and they also used simple poverty headcount. The results were suggestive that South and West part of the Punjab were found highly poor in terms of all poverty methods, i.e., headcount ratio and deprivation indices. The least poor part of the Punjab was central Punjab where people were enjoying much better standard of living as compared to all other provinces. There were found high poverty and deprivation differences within regions and across districts as well and poverty profile was also suggested that households which had more educated persons were less deprived. Further findings of the study suggested that poverty estimates differed regarding household characteristics as well.
Naveed and Ali [45] have found spatial distribution of poverty where district level or clustered poverty has been detected; actually, this study is conducted under SDPI. They calculated multidimensional poverty by using Alkir and foster approach with the help of data collected from HIES/PSLM (2007–2009). Four key dimensions were utilized to construct multidimensional poverty, i.e., education (household members attainment of primary education, child enrollment status), asset ownership (household assets, and landholding), health (access to health care facility, maternal health care), and living conditions of the households (facility of drinking water, sanitation, fuel used for cooking, quality of housing, and electrification). The main focus of the study was to disaggregate that constructed poverty index from national level to subnational level and further extended it to district level, and secondly the study identified the poorest and least poor district, and finally clustering of the geographical poverty was focused. The estimated results showed that overall one-third of the population were found below poverty line, and strong rural/urban poverty incidences could be observed within provinces. The highest poverty incidences about Baluchistan (52%) were come out and KPK (32%), Sindh (44%), and only 19% poverty were found in Punjab. It showed that Punjab province is least poor, whereas other provinces were having relatively higher poverty incidences. Moreover, the disaggregated analyses highlighted there were intra- and inter-provinces’ disparities regarding poverty estimates were persistently found. South Punjab was the poorest area of Punjab, southern districts of KPK, and Southwestern part of the Sindh have been emerged as highly poor areas of the respective provinces. Additionally, this study gave the estimates of vulnerability, and it was found rural areas were more vulnerable than that of urban, and overall vulnerability was 16 percent in Pakistan.
Arif [4] has seen through the poverty profile of Pakistan by using survey-census type data set conducted by Benazir Income Support program (BISP). The main concern of this study was to overcome the shortcoming of previous studies regarding poverty profile of Pakistan and that was small data size. BISP was helpful to calculate asset-based poverty, and the author constructed the poverty in different ways, i.e., multidimensional poverty, and proxy means test (PMT), etc., while using PMT, recommended threshold that was used by BISP to do smooth cash transfer to people who have PMT score less than or equal to 16.7. He found spatial poverty, and poverty regarding household characteristics such as age, dependency ratio, education, employment-wise, and regarding agro-climatic zones. The results were suggesting the poverty incidences that were found having high variation amongst districts, and agro-climatic zones of Pakistan. Baluchistan has appeared as highly poor provinces and even districts of this province were also found highly poor as compared to districts of other provinces. Arid and mixed zones were found highly poor areas, whereas rice–wheat and cotton-wheat areas were relatively facing lower poverty incidences. The results were indicating that there was poverty incidences varied through the household characteristics. Those households which have high or severe dependency ratio were facing high poverty incidences; moreover, high differences were found regarding sex, age, and education of the households.
Fatima [25] has analyzed the prevalence of poverty across agro-climatic regions of the Pakistan. The study has classified Pakistan into nine agro-climatic zones, which were arid zones of Punjab, mixed zones, rice–wheat zones and cotton-wheat zones of Punjab, low-intensity regions of Punjab, similarly cotton-wheat and rice–wheat Sindh, mixed zones of Sindh, and some zones with respect to KPK, and Baluchistan. The study has employed HIES/PSLM (2007–2008) data, and the study has used consumption as the indicator of welfare, and aggregate consumption was adjusted. Three poverty measures were employed, which were 1) head count ratio, average poverty gap, and squared poverty gap to estimate poverty zone wise. The findings were suggesting that Baluchistan was highly poor province because most of its regions were found extremely poor. Less poor regions were rice–wheat, cotton-wheat zones of the Punjab, whereas arid area of Punjab was also found less poor as compared to other provinces. After Baluchistan, major regions of KPK were also appeared as poor areas. Moreover, low-intensity zones of the Punjab were facing also poverty higher than that of other provinces.
Khan et al. [35] investigate the variation of the multidivisional rural poverty across the region in case of Pakistan. In order to find out the long-run social well-being, they employed the multidirectional socioeconomic measurement of poverty. They incorporate three important dimensions, i.e., health, education, and housing facilities, for accessing rural MDP. Their analysis showed signification variations in MDP rates across region over the time periods (1998–1999, 2001–2002, 2004–2005, 2005–2006, and 2007–2008). Poverty mapping helped in identifying the poor regions, e.g., Zhob, Kalat, and D I Khan were identified as the poorest region in map. However, by visualizing the rural MDP in all time periods implies that poverty alleviation strategies may also be reshaped. Dual approach may be opted to decrease the deprivations of socioeconomic facilities, i.e., direct and indirect strategies. Direct strategies encompass for improvement of health, education, and housing facilities in rural areas. Targeted policies may be evolved with respect to highest deprivation in terms of education, health, and housing in identified poor regions. Corresponding to the type of deprivation, education, health, and housing facilities provided to extremely poor to identify regions. Increased number of health units, free schooling and stipend for students, and free health facilities for deserving rural households may be helpful to eradicate the rural poverty. Regarding indirect steps, the government may take the necessary steps to increase the income level, improve the access to health, education, health facilities, provide subsidized agriculture inputs, and create non-farm employment opportunities, easy access to farm machinery, credit facilities and necessary extension services to the rural households. The outcome of indirect strategy is more sustainable and provides freedom to rural households to decide on the weakest dimension for their spending.
Finally, the aforementioned discussion indicates that poverty varies across provinces, agro-climatic zones, and districts as well. Spatial poverty exists in Pakistan, and there is a need to trace out the asset-based poverty at subnational level in case of Pakistan.