MULTIDIMENSIONAL POVERTY DISPARITY IN PAKISTAN

It is argued that poverty is more than lack of income and consumption. In other words, unidimensional approach is not able to present true picture of deprivation. As the poor person can be deprived from education, good health, nutritious food and clean drinking water. Therefore, this study aimed to determine multidimensional poverty in Pakistan at provincial, regional level for all available surveys of Pakistan Social and living standard (PSLM). This study covered three dimensions’ education, health and living standard along with nine sub-dimensions. The present study used Alkire foster methodology with different cutoff for rural and urban regions. The result revealed that Pakistan multidimensional poverty index (MPI) in 2004-05 is 0.16 which is slightly decreased to 0.12 in 2019-20. In the same way, head count index showed a little decline of 1 percent i.e. 49% in 2004-05 to 48% in 2019-20. Similarly, intensity of poverty declined from 33% in 2004-05 to 31% in 2019-20. The empirical analysis showed little improvement in health, education and living condition over the past sixteen years. Further, multidimensional poverty remains higher in rural areas than urban areas. This study identified that the most deprived province is Balochistan among all provinces. From policy perspective government officials can alleviate poverty by providing education and employment opportunities. As it is the basic condition of millennium and sustainable development goals (MDG’s) to give basic needs of life such as food, shelter and education.


INTRODUCTION
The Sustainable development goals (SDGs) are based on the condition to fulfill the requirements of current generation without harming the needs of future generation.The very first objective of SDGs is "to end poverty in all its forms everywhere".However poverty is still a wide spread across the globe, From the last two decades for the first time global extreme poverty1 is expected to rise in 2020 due to the dispersion of COVID-19 pandemic.According to (World Bank, 2020)1.4percent of the world's population may slip into extreme poverty as a result of the epidemic and global recession.Therefore, eliminating poverty in all its dimension is the biggest global issue and crucial for sustainable development.
Pakistan is fifth populous country with 63% live in rural areas and 37% in urban areas.From 2001 to 2015 the poverty head count has been declined from 31.0 to 4.0 percent "measured at the international poverty line of $1.90 PPP 2011 per day".The decrease in poverty was the result of expansion in economic activities, out migration and remittances.But COVID-19 outbreak cause macroeconomic crisis by which most of the labor force loss their job and income.Thus, poverty rate has raised to 5.3 percent in 2019-20 where more than 2 million people fall below poverty line (World Bank Group, 2020).The multidimensional poverty report published by United Nations Development Program (UNDP 2016) shows that 54.6% of rural population is multidimensional deprived i.e. 21.4% in rural Punjab, 41.5% in Sindh.29,5% in Khyber Pakhtunkhwa and 48.2% in rural Baluchistan (Padda & Hameed, 2018).
Poverty is the hurdle in achieving other sustainable development goals (Cheng et al., 2018).Poverty also effects education, health and living standards.As the vicious circle of poverty cause the poor to remain deprived in multiple aspects i.e. access to clean drinking water, sanitation, basic education and health facilities.Therefore, eliminating poverty in all these dimensions is the main challenge for present world and an essential requirement for sustainable development (Padda & Hameed, 2018).For elimination, first we need proper identification and measurements of poverty.Traditionally measuring poverty involves three steps2 .First determine the welfare indicators, which is based on both monetary and non-monetary approaches such as household income or consumption expenditure.Similarly, non-monetary measured of household's welfare consist of spending on food, education, living standard and health.Second step involves to define poverty line which separate poor from non-poor.Third step is based on aggregation of welfare indicator into an index of poverty.Generally, poverty is more than income, consumption and expenditure.For instance, poor person can be deprived from good health, nutritious food, clean drinking water and education.According to (Bourguignon, 2003) poverty arises because of deficiency in basic needs like health and education services, facility of public services etc.Therefore, to take income as one factor for poverty will not represent the true picture.According to United Nation Development Program 1.3 billion people are multidimensional deprived.Poor person cannot come out vicious of poverty.
In Pakistan poverty is of multidimensional in nature i.e. different aspects of poverty affect welfare of people.For instance, lack of access to attain basic education, inadequate health facilities, poor quality of housing and living standard.Unidimensional measured of poverty based on income/consumption is insufficient to represent the depth and true picture of deprivation.The wellknown Chronic Poverty Research Center (Hulme et al., 2005) see the sight that deprivation of people cannot be measured only through monetary term (income) rather it has various indicators such as scarce resources of health and education, malnutrition, unsafe drinking water, poor sanitation and house quality (Saleem & Bilal Khan, 2018).Pakistan is developing country where root cause of deprivation is necessary to tackle the poverty.Thus multidimensional poverty index (MPI) contributes to measurement of poverty through different dimensions such as education, health and living standard.The MPI make available evidence for policy makers to identify the nature and depth of deprivation.So policy makers reformed the anti-poverty policies and plans to lessen poverty ratio.
The present study is based on capability approach proposed by (Sen, 1999), according to which social and economic deprivation should be estimated in term of capabilities owned by those who live in them.In this way, Sen consider multiple dimensions of people other than monetary measures of poverty.As measurement of poverty only in monetary term is not useful because it ignore multiple aspects (Ravallion, 2011).From policy point of view, it highlights that measurement of poverty by multidimensional approach recommend the social and economic structural change to alleviate poverty in the long run.Whereas unidimensional approach promotes policies that lessen poverty in short run.The main contribution of this study are: first it is pioneer study to estimate multidimensional poverty index for latest survey of PSLM (2019-20) along all other available surveys i.e. of sixteen years' time period.Second most of the previous work consider same benchmark for rural and urban region of a country.This study will contribute in exiting literature by setting different benchmark for rural and urban areas.Because rural and urban areas dynamics are not same for instances, gain from education in urban area is higher than rural area thus same benchmark for education is not acceptable.Similarly, there is vast difference between rural and urban house quality and access to other basic facilities.For instance, health services availability in rural areas is far different from urban such as child birth assistance by midwife doesn't considered deprived in rural areas.

REVIEW OF LITERATURE
Poverty has been serious challenge in the history of developing world as 22% of 107 developing country are multidimensional poor.When the deprivation is decomposed age wise, then half of the multidimensional deprived people are children under age of 18.Similarly, regional analysis shows that multidimensional deprived people 84.3% live in South Asia (530 million) and Sub Saharan Africa (558 million) (UNDP & OPHI, 2020).
Over the globe in response to the drawbacks of traditional poverty measures, Multidimensional poverty empirically examined by Cerioli and Zani (1990) (Silber, 2005).They proposed the fuzzy approach for the first time.After that many empirical research has done on multidimensional poverty.
Similarly, in Pakistan many research has been done on multidimensional poverty after 2000s, however we have studied only those studies which empirically examine the MDPI regional wise.From the literature we found that Jamal et al (2003) present the overall deprivation picture for the four provinces of Pakistan based on the Population and Housing Census of 1998 to look at five main factors for analysis: education, residential housing services, congestion, employment, and housing quality.The UNDP's Human Development Index was utilized as the basis for the study's analysis.According to the findings, Punjab had 18 million people living in extreme poverty.They numbered 9 million in Sindh and 6 million in Baluchistan.In the NWFP, there were also 9 million individuals who were extremely poor.The Multidimensional poverty index was estimated first by Jamal (2009).They find that most vulnerable province is rural Baluchistan with small town cities and MDP is less in urban areas than rural.Naveed & Islam (2010) measure multi-dimensional poverty by applying Alkire and Foster methodology for two provinces Punjab and KPK.The result for both provinces poverty severity is higher in rural areas than urban.Similarly, MDP for districts of Punjab is examined (Awan et al., 2011).They take data from MICS for the year 2003.By using same methodology of Alkire and Foster by (Sarwar Awan et al., 2012).Further Jamal (2012) use seven more non-monetary factors and estimated by Categorical Principal Components Analysis (CATPCA).Their analyses reveal that MDP is less in urban areas than rural.Most deprived province in term of multidimensional is Baluchistan and least deprives is Punjab.During 2005 to 2011 poverty incidence first decline then rises.Similar trend is observed for rural region, whereas urban regions shows declining trend for overall period.The empirical result shows that highest multidimensional poverty is found in Baluchistan followed by Sindh, NWFP and Punjab.Moreover, Niazi & Khan, (2012) examine the education deprivation and multidimensional poverty for Punjab province of Pakistan.They conclude that education deprivation as well as multidimensional poverty both found lower in urban areas of Punjab.Overall, regional analyses of Pakistan show that MDP is less in urban areas than rural, whereas provincial analyses show that least multidimensional poverty found in Punjab, whereas highest in Balochistan for both rural and urban areas (Jamal 2011;Naveed and Ali, 2012;Saboor et al, 2015;Naveed, Wood and Ghaus, 2016;Saleem and Khan, 2017;Pedda and Hameed, 2018;Naveed and Ghaus, 2018;Mehmood and Hussain, 2020).This because of lack of basic health facilities, safe drinking water deficiency, poor infrastructure, lack of employment opportunities are the main drivers of poverty disparity across provinces (Khan 2011).
This can be concluded that deprivation is not the result of single factor like low income or consumption.To the best of our knowledge there is no study which examined the multidimensional poverty across regions (rural/urban) of four provinces of Pakistan for the last sixteen years.We cannot compare the result of previous studies as every study has different methodology and benchmark.There is need of study which represent the complete picture of multidimensional poor region and people.Second contribution of our study to existing literature is that we have set separate bench mark for rural and urban areas.Before this study it has not been calculated.
For Pakistan very few studies are conducted for rural urban regions of all four provinces, the summary is given in appendix Table A1.That shows the regions covered by previous Studies for multidimensional Poverty and Table A2 presented in appendix represent the summary of dimensions covered by previous Studies for multi-dimensional Poverty.From the Table A2 it can be seen that mostly studies analyzed deprivation in education, health, standard of living, land holdings and ownership of assets.This study will consider additional variables i.e. means of transportation and access to basic facilities where we have included access to market, schools, hospitals and safe drinking water.Moreover, we have used different cutoff for rural and urban region for each indicator.Whereas earlier studies use same benchmark for rural and urban regions.

DATA SOURCE
For measuring multidimensional poverty, the data is taken from Pakistan Social and Living Standard (PSLM) survey, as this survey cover all the social and economic indicators at provincial and district level.We are taking PSLM surveys for the year 2004-05, 2006-07, 2008-09, 2010-11, 2012-13, 2014-15, and 2019-20

METHODOLOGY
The methodology used in this study for Multidimensional poverty is adopted from Alkire & Santos, (2014, 2010) who proposed global MPI first in human development report in 2010 with collaboration of UNDP.Further Sabina Alkire and James Foster elaborate the multidimensional poverty index by taking head count index (percentage of deprived people) and intensity of deprivation from individual suffer.The present study estimates the multi-dimensional poverty by using Alkire & Foster, (2008) methodology in which the data will be expressed in term of deprivation rather than achievement.Following steps are involved in the measurement of multidimensional poverty.

Step 1. Define unit of analysis and dimension
The unit of analysis refers to the identification of poor and non-poor at individual and household level.In case of Pakistan's national MPI use household as unit of analysis.All member of household taken together and receive same deprivation score.However, unit of analysis for result is individual, for instance head count ratio is the percentage of people who are deprived rather than percentage of deprived household.Second is the selection dimension which depends on author's research priorities, country political and economic context and availability of PSLM data.In this study total nine indicators of three dimensions are used.

Step 2. Define deprivation cutoff for each dimension
In this study we have used three dimensions' education, health and living standard.The deprivation in these dimensions determines multidimensional poverty.The deprivation cutoff of each dimensions and its sub dimensions is given below in detail.
I. Education Education build social and economic wellbeing as it enhances the individual's knowledge, creativity and technological skills which increase the social welfare of society and improve standard of living.Further, education plays fundamental role in improving the income distribution and helps the poor to get rid of poverty.Education used as indicator of multidimensional poverty by all of the studies.Table 2 shows the previous studies use education benchmark.

II.
Health Good health is one of the main determinants of welfare.An individual's health is associated with income, education, access to healthcare services and living condition.In developing countries economic position is linked with health status of their inhabitants.Health is essential for reducing poverty and inequality.Moreover, poor health also affects the quality of labor supply.For the achievement of Millennium Development Goals health indicators are on priority.To measure deprivation in health many indicators are used such as access to health facility pre and post-natal, malnourished, child mortality and immunization.The present study shall consider all the variables which are available in PSLM data and these are child immunization and married women health that is based on pre-natal and post-natal care.

Child Health • Immunization
Any child is not immunized (household is deprived if even one child has not completed 80% vaccination) Any child is not immunized (household is deprived if even one child has not completed 80% vaccination)

III.
Living Standard Indicator of living standard determines the quality of life.Living condition includes all the indicators that are included in global MPI to detect house quality, access to basic life facilities like safe drinking water, access to school and health institution, proper sanitation, source of light and cooking.All these factors give the comprehensive information about the well-being of household.The improved living condition of inhabitant has positive impact on economic growth of a country.Previous studies mentioned in table A2 have used living standard like house quality, ownership of land and assets, access to safe drinking water, sanitation facility etc.This study shall consider household assets, house quality, access to basic facilities and means of transportation.Households don't have five or more than five household assets.
Households don't have five or more than five household assets.
Step 3 Assign weight to each Dimension After the identification of deprived and non-deprived indicators each sub-dimension is multiplied to its weight.Assigning weight to each dimension is an important step in measuring multidimensional poverty.Alkire and Foster methodology allows to assign different weight to different dimensions depends upon preferences and other socio-economic factors.As all the dimensions are not of equal importance.For example, health and means of transportation are not of the same importance.Therefore, in this study we have assigned unequal weights to each indicators following Government of Pakistan UNDP report (2015).Step 4 Deprivation score for each household considering all dimensions Weighted deprivation score can be obtained by taking the sum of all the weighted deprivation.
Mathematically it can be written as Step 5 Poverty Cutoff Poverty cutoff is the final deprivation cutoff on sum of weighted household deprivation for each dimension.Below this poverty cutoff household will be considered as multidimensional poor.There are n dimensions then poverty cutoff will be fixed as 0 < P < n.In this study we have followed government of Pakistan poverty cutoff value which is 3 1 i.e.33.3%.following National MPI same threshold is applied to determine the deprived household.All those who weighted deprivation score is greater or equal to 33.3% are considered as multidimensional poor.
Step 6. Calculate deprived household (head count index) Head count index shows the percentage of people who are identified as multidimensional poor.It is obtained by dividing the deprived number of household to the total number of household.
where H shows head count index, Q total number of deprived people, N is total number of individuals.
Step 7. Calculate intensity of poverty Average deprivation shows intensity of poverty.The average percentage of dimension in which poor people are deprived.It is obtained by dividing the deprived dimensions with total number of deprived population.

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Step 8. Calculate Multidimensional Poverty Head count ratio gives the proportion of the people who are living below poverty line.While intensity of poverty gives the depth of deprivation face by the individuals who are living below poverty line.
Multidimensional poverty index (MPI) or adjust head count index is the product of head count ratio and intensity of poverty.Thus it is a single measure which represent both the "breadth and depth of deprivation".
Mathematically the MPI can be written as  =  ×  (4) Where  shows incidence of poverty.The percentage of people who are multidimensional poor and  represent intensity of poverty.The average percentage of dimensions in which people are deprived.

RESULT AND DISCUSSION
In this section we will presents the complete estimates of multidimensional poverty in Pakistan based on seven PSLM surveys i.e. from 2004-05 to 2019-20.In this study we have used three dimensions of wellbeing to determine multidimensional deprivation in each province along rural urban regions.First we will present the head count index at national and provincial level then intensity of poverty at national and provincial level.Then we will go towards the trends in multidimensional poverty index over sixteen years.
a. Head Count Index at National and Provincial Level The Table 6 shows the proportion of deprived people at national and provincial level along absolute change for seven round surveys.The head count index shows the proportion of poor which almost remain constant i.e. 49% in 2004-05 to 48% in 2019-20.Over the sixteen years of time period the head count index at national level shows only1.5 percent decline in absolute term.The slightly reduction in proportion of poor people shows a little improvement in health, education and living condition over the past sixteen years.This is because of ineffective implementation of pro-poor policies as poverty alleviation programs only account for around 2% of GDP.Further, the global financial crisis of 2007-09 and a series of terrible natural disasters -most notably the earthquake of 2005 and the floods of 2010 -all had an impact on Pakistan's economy, with direct and indirect effects on poverty alleviation.6 that rural area has higher head count index than urban areas.This means rural population is more deprived than urban in term of access to education and health facilities and living condition.This is because households in rural locations may be unable to receive vital health and welfare services due to limited transportation alternatives.This makes access to healthcare providers and social services limited.Consequently, it does isolation on both a physical and social level.income and economic growth aren't equally shared among the regions.In rural areas land distribution is skewed which has major contribution in higher deprivation of region.Although agriculture is the most common activity in rural areas, a significant section of the rural work force, estimated to be more than 40%, is fully dependent on non-farm enterprises.Low economic growth and a reduction in public sector development spending appear to have had a significant impact on the growth of non-farm activities.Further, Head count ratio of rural areas in 2010-11 to 2019-20 is two times higher than urban head count index.The absolute decline in rural head count index is of 16 percent and 13 percent decline is observed in urban area.This finding of our study is consistent with the (Jamal, 2012,Sustainable Development Policy Institute (SDPI), 2016, UNDP and OPHI, 2016).
The proportion of poor shows wide variation at provincial level.In the table 6 it is shown that over sixteen years of time period Baluchistan has the highest head count ratio followed by KPK, Sindh and Punjab.Balochistan has some characteristics of being a backward province with a low standard of living, dismal growth rate, lowest infrastructure, worst water crisis, and weakest fiscal base.Bad economic performance translates into poor living conditions.The disparities at regional level is highest found in Sindh, where rural poverty is three times greater than urban poverty in 2019.20.while in other provinces rural poverty is two times higher than urban poverty.
The Table 6 shows ratio of poor people in Punjab is 38 percent in 2004-05 which decline to 25 percent in 2019-20 that displays reduction of 13 percent in absolute term.This is the highest decline in head count index followed by KPK where proportion of poor people declined by 10 percent.The proportion of poor in Punjab remain least among provinces.Because government of Punjab implement different programs such as Punjab Economic Opportunities Programme.Due to its fertile land and rivers most of the population is engaged to agriculture.While Sindh and Baluchistan has the least decline of 7 percent in head count.Higher reduction in proportion of poor (head count ratio) is seen only for rural areas of Baluchistan.While KPK and Punjab show more reduction of poverty in urban areas than rural.Sindh rural areas shows no change over time in head count ratio.
All the above estimates show different level of poverty for four provinces with rural, urban regions.Over time each region is able to reduce poverty differently.There are many factors which affect the incidence of poverty for instance size of family, density of population, quality of governance, access to public services, use of natural resources etc.
b. Intensity of Poverty at National and Provincial Level At national level average intensity of deprivation is 33 percent in 2004-05.The shows that each poor person on average is deprived in one third of weighted indicators.The above Table 7 illustrate that the average deprivation which shows the share of deprivation each poor person experience face on average is 33 percent in 2004-05 falls to 31.2 percent in 2019-20.That shows only two percent reduction in average deprivation.Similar to the head count ratio the intensity of poverty is higher in rural areas than urban.
There are considerable differences among provinces in intensity of poverty face by the poor given in graph.The average deprivation face by poor is highest in Baluchistan between all provinces.For instance, in 2019-20 Baluchistan's poor experience two times higher deprivation than Punjab's poor.The intensity of poverty highest reduction of 8 percent is occurred in Sindh and lowest in KPK i.e. of 5 percent.
The above Table 7 shows that Sindh has the highest disparity between rural and urban region i.e. people of rural areas face 23 percent more average deprivation than people of urban region.While Punjab has the least disparity between rural and urban region of 7 percent.Intensity of poverty highly declines in urban region of KPK followed by Punjab and Sindh.While reduction in average deprivation is greater in rural areas of Baluchistan.
c. Multidimensional Poverty Index at National and Provincial Level The Alkire and Foster approach proposed a measure which provide both aspects (incidence of poverty and intensity of poverty) into single measure known as adjusted head count index or multidimensional poverty index (MPI).The MPI is the product of head count index and average deprivation face by poor.At national level adjusted head count index shows a very small decline of 0.04 point from 2004-05 to 2019-20 as shown in Table 8.However, reduction in poverty is of 5% from 2004-05 to 2014-15.This reduction was due to increase in economic opportunities along out-migration which cause rise in remittances.Whereas, in 2018-19 Pakistan went through a macroeconomic crisis.Moreover, COVID-19 lockdown worsen the condition of poor households as half of the population loss their job and income.As a result, poverty has been increased from 11.7% to 12.2% in 2019-20.The above Table 8 shows that adjusted head count index for rural areas is more than three times higher than urban areas.The MPI value for overall Pakistan in 2019-20 is 0.12 which means deprived people in Pakistan face 12 percent of total deprivation i.e. if people are deprived in all indicators.Over the sixteen years in rural areas adjusted head count index drop in absolute term by 9 points and 6 points in urban areas.There is overall small decline of 0.04 points in multidimensional poverty index.
The above Table 8 shows that Baluchistan has two times higher MPI value than national and five times higher than Punjab.Many socioeconomic factors, as well as the province's weakest state institutions in several areas are responsible for higher MPI in Balochistan.Rather of being a focus of economic activity it is burdened by the toils of the field and rangeland, as well as tribal tensions.In many ways, Balochistan has Inherent geographical weaknesses led over the centuries to low population density.The modernization process, which transformed the country from a poor rural nation into a semiindustrialized economy, has not benefited all provinces equally.Combined with political neglect, this destined Balochistan to the periphery of economic and institutional development.Similarly, KPK has 1 point higher adjusted head count index value than national MPI value.While Sindh and Punjab has lower MPI value than national value.Sindh capital is Karachi which is one of the world's largest megacities.According to the Sindh Board of Investment, provincial economic activity accounts Sindh collects 70 percent of all income taxes and 62 percent of all sales taxes in the country.Pakistan's 54 percent of textile units and 45 percent of sugar mills are located in the Sindh province.As Pakistan's most important export is textiles.Sindh also produces half of Pakistan's total seafood exports, one-third of the country's rice, sugar cane, mango, and vegetable crop production, and one-third of the country's rice, sugar cane, mango, and vegetable crop output.Similarly, Punjab is the industrialized province of Pakistan.Further, it is most fertile and populated province, because of its rivers.
Over the time period from 2004-05 to 2019-20 Punjab has absolute decline of 5 percent and all other provinces show similar decline of 7 percent in MPI.For all the provinces MPI value is higher for rural areas than urban.The highest inequality among rural and urban region is observed in Sindh i.e. rural value is 4.2 times higher than urban in 2004-05 which increased to 8.1 in 2019-20 because of decrease in MPI value.While Baluchistan has least rural urban disparity that remain at 2 percent from 2004-05 to 2019-20.In case of Punjab rural urban gap ratio increase from 1.5 in 2004-05 to 3.1 in 2019-20.Further, the declination of MPI remain same for rural and urban areas of Punjab, Sindh and KPK.While rural areas of Baluchistan have highest absolute decline in MPI value.

CONCLUSION
From the last few years' multidimensional poverty is recognized as multi-face phenomena that contains multiple features of deprivation.As the consumption based poverty don't consider the deprivation in other factors like education, health, food and living condition.Further enhancement in income doesn't guarantee the provision of all other basic facilities.Thus poverty has multiple aspects of deprivation which poor people face.The objective of this study is to present comprehensive analysis of multidimensional poverty by using seven round of PSLM survey i.e. from 2004-05 to 2019-20.This study uses Alkire and Foster methodology by taking three dimensions of wellbeing that is education, health and living standard.The nine sub-dimensions are child, young's and adult education, child immunization and married women health along house quality, means of transportation, access to basic facilities and ownership of household goods.
The empirical result reveals that Pakistan's 12 percent of population is deprived in multi indicators for the year 2019-20.The incidence of poverty is about 46 percent in rural region and 21 percent in urban region.It shows that rural people are more deprived in term of education, health and living standard.Inter-provincial comparison reveals that Baluchistan has the highest incidence of poverty while Punjab has the least proportion of deprived people.Similarly, average deprivation face by poor is highest in both rural and urban regions of Baluchistan.In term of population the share of Baluchistan's population is lowest i.e. 10 percent in overall population.Among provinces multidimensional poverty index value is least in Punjab (5%) followed by Sindh (4%) and KPK (1%).To attain sustainable development by reducing poverty, the federal and provincial government should allocate funds to the most deprived regions as in our study rural areas of all provinces are more deprived, therefore government should provide rural industries, education opportunities and other basic health facilities.Moreover, government should give loan to poor individual so that that can start their own living such as shops other small business.Most of population live in rural areas so the government should introduce policies which promote agriculture growth by encouraging agro-based industries.The policy make should focus on deprived region such as Baluchistan province and rural areas of all provinces.
. The district wise PSLM survey is initiated in July 2004.This survey is useful to tackle Pakistan's performance in achieving the millennium development goals.As this survey has questions regarding education, health, income, employment, living condition and assets.The number of household has been increased with passage of time as latest edition of PSLM 2019-20 is seventh round of district level survey with sample of 160654 households.Out of which 110672 are rural households and 49982 are households from urban region.Table1.Distribution ofHouseholds from PSLM 2004-05 to PSLM 2019-20.

Table 2 .
Education Cutoff for Analyzing Multidimensional Poverty

Table 3 .
Health Cutoff for Analyzing Multidimensional Poverty Health

Table 4 .
Living Standard Cutoff for Analyzing Multidimensional Poverty

Table 5 .
Summary of Equal and Unequal Weights given to Each Dimension

Table 6 .
Head Count Index from 2004-05 to 2019-20 at National and Provincial level In Pakistan poverty has been analyzed as rural phenomena.It is shown in Table

Table 7 .
Average Deprivation from 2004-05 to 2019-20 at National and Provincial level