Poverty headcount ratio at national poverty lines (% of population) in Pakistan was reported at 21.9 % in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. Pakistan - Poverty headcount ratio at national poverty line (% of population) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Pakistan PK: Poverty Headcount Ratio at National Poverty Lines: % of Population data was reported at 24.300 % in 2015. This records a decrease from the previous number of 29.500 % for 2013. Pakistan PK: Poverty Headcount Ratio at National Poverty Lines: % of Population data is updated yearly, averaging 44.100 % from Dec 1998 (Median) to 2015, with 9 observations. The data reached an all-time high of 64.300 % in 2001 and a record low of 24.300 % in 2015. Pakistan PK: Poverty Headcount Ratio at National Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Poverty. National poverty headcount ratio is the percentage of the population living below the national poverty lines. National estimates are based on population-weighted subgroup estimates from household surveys.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

Pakistan PK: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data was reported at 75.400 % in 2015. This records a decrease from the previous number of 79.500 % for 2013. Pakistan PK: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data is updated yearly, averaging 87.600 % from Dec 1987 (Median) to 2015, with 12 observations. The data reached an all-time high of 96.900 % in 1990 and a record low of 75.400 % in 2015. Pakistan PK: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Poverty. Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Dataset

This dataset was created by Hammad Farooq

Released under MIT

Contents

Pakistan: Poverty ratio, percent living on less than 5.50 USD a day: The latest value from 2018 is 84.5 percent, an increase from 83.8 percent in 2015. In comparison, the world average is 26.46 percent, based on data from 91 countries. Historically, the average for Pakistan from 1987 to 2018 is 91.55 percent. The minimum value, 83.8 percent, was reached in 2015 while the maximum of 98 percent was recorded in 1990.

Pakistan PK: Poverty Gap at $1.90 a Day: 2011 PPP: % data was reported at 0.500 % in 2015. This records a decrease from the previous number of 0.900 % for 2013. Pakistan PK: Poverty Gap at $1.90 a Day: 2011 PPP: % data is updated yearly, averaging 2.650 % from Dec 1987 (Median) to 2015, with 12 observations. The data reached an all-time high of 20.600 % in 1987 and a record low of 0.500 % in 2015. Pakistan PK: Poverty Gap at $1.90 a Day: 2011 PPP: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank: Poverty. Poverty gap at $1.90 a day (2011 PPP) is the mean shortfall in income or consumption from the poverty line $1.90 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Pakistan PK: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data was reported at 39.700 % in 2013. This records a decrease from the previous number of 46.400 % for 2011. Pakistan PK: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data is updated yearly, averaging 60.400 % from Dec 1987 (Median) to 2013, with 11 observations. The data reached an all-time high of 87.900 % in 1987 and a record low of 39.700 % in 2013. Pakistan PK: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank: Poverty. Poverty headcount ratio at $3.20 a day is the percentage of the population living on less than $3.20 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Abstract

The Pakistan Social & Living Standards Measurement Survey 2018-2019 is the main mechanism to provide data for: - Monitoring development plans at district level. - Assessment of programs initiated under Poverty Reduction Strategy Paper (PRSP). - Planners / Policy Makers, Research workers, Statisticians and National / International Organizations use the data. - Estimation of Multidimensional Poverty Index (MPI) from PSLM district level survey. - Estimation of consumption based poverty (CBN from PSLM/ HIES Provincial level survey.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Universe

The universe for survey consists of all urban and rural areas of the four provinces of Pakistan, excluded military restricted areas. The areas of erstwhile FATA have now been covered in Khyber Pakhtunkhwa.

Kind of data

Sample survey data [ssd]

Sampling procedure

For the 2018-2019 Pakistan Social and Living Measurement Survey stratified two-stage sample design has been adopted for the survey.

Sampling Frame The Pakistan Bureau of Statistics (PBS) has developed its own urban area frame. Each city or town is divided into enumeration blocks. Each enumeration block is comprised to 200-250 houses on the average with well-defined boundaries and maps. In urban areas each enumeration block is treated as PSU while in rural areas villages are divided into blocks with well-defined boundaries and maps and each separate block within village is considered as PSU.

Stratification Plan - Urban Domain: For urban domain, each administrative division for all four provinces has been considered as an independent stratum. - Rural Domain: For rural domain, each administrative district in Punjab, Sindh and Khyber Pakhtunkhawa and each administrative division in Balochistan, has been considered as an independent stratum. - Selection of primary sampling units (PSUs): Enumeration blocks in both Urban and rural domains are taken as Primary Sampling Units (PSUs). Sample PSUs from each ultimate stratum/sub-stratum are selected with probability proportional to size (PPS) method of sampling scheme. In both Urban and Rural domains, the number of households in an enumeration block has been taken as measure of size. - Selection of secondary sampling units (SSUs): The households of sample PSUs have been taken as Secondary Sampling Units (SSUs). 12 and 16 households have been selected from urban and rural domains respectively by using systematic sampling technique.

Mode of data collection

Face-to-face [f2f]

Research instrument

There are two structured questionnaires (one for males and another one for females). The topics of the questionnaires include: - Demographic characteristics - Education - Health - Population welfare - Household characteristics - Water sanitation and hygiene - Household income, consumption and expenditure - Household assets, household amenities - Saving and liabilities

Incorporated Modules: - Food Insecurity Experience Scale (FIES) - Out of pocket health expenditure

Multi-Dimensional Poverty Index is a new measure to compute acute poverty. The MPI complements consumption-based poverty measures by reflecting deprivations that individuals face in other dimensions such as education, health and standard of living. The MPI captures the severe deprivations that each person experiences with respect to education, health and standard of living. MPI is the product of two components: 1) Incidence of poverty (H): the percentage of people who are identified as multidimensionally poor, or the poverty headcount. 2) Intensity of poverty (A): the average percentage of dimensions in which poor people are deprived. In simple terms it means how intense, how bad the multidimensional poverty is, on average, for those who are poor. Based on the index values for the latest year (2014/15), the five districts with the highest MPI are Killa Abdullah, Harnai, Barkhan, Kohistan and Ziarat. Most of these districts also have the highest levels of the incidence (headcount) and intensity of poverty in all of Pakistan. On the other hand, the six districts with the lowest index value are Islamabad, Lahore, Karachi, Rawalpindi, Jhelum and Attock. These districts also have the lowest poverty headcounts in the country. Data Sources: Data is taken from the report on Multidimensional Poverty which has been developed in collaboration with the Oxford Poverty and Human Development Initiative (OPHI) and the United Nations Development Programme (UNDP), Pakistan. Data Accusation Method: The methodology used to determine Pakistan's MPI is adopted from Alkire and Santos' (2010, 2014) work on the global MPI, undertaken in collaboration with UNDP. Time Period: 2014/15 Definition of variables Multi-Dimensional Poverty Index is represented by "MPI_incide" field. Introduction about Data: This map allows to explore Multi-Dimensional Poverty Index at district level of Pakistan.

Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 27.900 % in 2018. This records a decrease from the previous number of 28.600 % for 2015. Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 38.000 % from Dec 1987 (Median) to 2018, with 13 observations. The data reached an all-time high of 67.300 % in 1987 and a record low of 27.900 % in 2018. Poverty Headcount Ratio at Societal Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Social: Poverty and Inequality. The poverty headcount ratio at societal poverty line is the percentage of a population living in poverty according to the World Bank's Societal Poverty Line. The Societal Poverty Line is expressed in purchasing power adjusted 2017 U.S. dollars and defined as max($2.15, $1.15 + 0.5*Median). This means that when the national median is sufficiently low, the Societal Poverty line is equivalent to the extreme poverty line, $2.15. For countries with a sufficiently high national median, the Societal Poverty Line grows as countries’ median income grows.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Pakistan PK: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 33.500 % in 2015. This records an increase from the previous number of 30.700 % for 2013. Pakistan PK: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 32.050 % from Dec 1987 (Median) to 2015, with 12 observations. The data reached an all-time high of 33.500 % in 2015 and a record low of 28.700 % in 1996. Pakistan PK: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Poverty. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Abstract

The World Bank is interested in gauging the views of clients and partners who are either involved in development in Pakistan or who observe activities related to social and economic development. The World Bank Country Assessment Survey is meant to give the World Bank's team that works in Pakistan, greater insight into how the Bank's work is perceived. This is one tool the World Bank uses to assess the views of its critical stakeholders. With this understanding, the World Bank hopes to develop more effective strategies, outreach and programs that support development in Pakistan. The World Bank commissioned an independent firm to oversee the logistics of this effort in Pakistan.

The survey was designed to achieve the following objectives: - Assist the World Bank in gaining a better understanding of how stakeholders in Pakistan perceive the Bank; - Obtain systematic feedback from stakeholders in Pakistan regarding: · Their views regarding the general environment in Pakistan; · Their overall attitudes toward the World Bank in Pakistan; · Overall impressions of the World Bank's effectiveness and results, knowledge and research, and communication and information sharing in Pakistan; and · Perceptions of the World Bank's future role in Pakistan. - Use data to help inform the Pakistan country team's strategy.

Geographic coverage

National

Analysis unit

Stakeholder

Universe

Stakeholders of the World Bank in Pakistan

Kind of data

Sample survey data [ssd]

Sampling procedure

In May thru July 2012, 1,000 stakeholders of the World Bank in Pakistan were invited to provide their opinions on the Bank's assistance to the country by participating in a country survey. Participants in the survey were drawn from among the office of the President or Prime Minister; the office of a Minister; the office of a Parliamentarian; employees of a ministry, ministerial department, or implementation agency; consultants/contractors working on World Bank-supported projects/programs; project management units (PMUs) overseeing implementation of a project; local government officials or staff; bilateral agencies; multilateral agencies; private sector organizations; private foundations; the financial sector/private banks; NGOs; community-based organizations (CBOs); the media; independent government institutions; trade unions; faith-based groups; academia/research institutes/think tanks; and the judiciary branch.

Mode of data collection

Mail Questionnaire [mail]

Research instrument

The Questionnaire consists of 8 Sections:

A. General Issues facing Pakistan: Respondents were asked to indicate whether Pakistan is headed in the right direction, what they thought were the top three most important development priorities, and which areas would contribute most to reducing poverty and generating economic growth in Pakistan.

B. Overall Attitudes toward the World Bank: Respondents were asked to rate their familiarity with the World Bank, the Bank’s effectiveness in Pakistan, Bank staff preparedness, the extent to which the Bank should seek to influence the global development agenda, their agreement with various statements regarding the Bank’s work, and the extent to which the Bank is an effective development partner. Respondents were also asked to indicate the sectoral areas on which it would be most productive for the Bank to focus its resources, the Bank’s greatest values and greatest weaknesses in its work, the most and least effective instruments in helping to reduce poverty in Pakistan, with which groups the Bank should work more, and to what reasons respondents attributed failed or slow reform efforts.

C. World Bank Effectiveness and Results: Respondents were asked to rate the extent to which the Bank’s work helps achieve sustainable development results in Pakistan, the extent to which the Bank meets Pakistan’s need for knowledge services and financial instruments, and the Bank’s level of effectiveness across thirty-six development areas, such as anti-corruption and economic growth.

D. The World Bank’s Knowledge: Respondents were asked to indicate how frequently they consult Bank knowledge/research, the areas on which the Bank should focus its research efforts, and to rate the effectiveness and quality of the Bank’s knowledge/research, including how significant of a contribution it makes to development results, its technical quality, the Bank’s effectiveness at providing linkage to non-Bank expertise, and the extent to which Pakistan received value for money from fee-for-service products/services.

E. Working with the World Bank: Respondents were asked to rate their level of agreement with a series of statements regarding working with the Bank, such as the World Bank’s “Safeguard Policy” requirements being reasonable and the Bank disbursing funds promptly.

F. The Future Role of the World Bank in Pakistan: Respondents were asked to rate how significant a role the Bank should play in Pakistan’s development in the near future and to indicate what the Bank should do to make itself of greater value in Pakistan.

G. Communication and Information Sharing: Respondents were asked to indicate where they get information about economic and social development issues, how they prefer to receive information from the Bank, their access to the Internet, and their usage and evaluation of the Bank’s website. Respondents were asked about their awareness of the Bank’s Access to Information policy, past information requests from the Bank, and their level of agreement that they use more data from the World Bank as a result of the Bank’s Open Data policy. Respondents were also asked their level of agreement that they know how to find information from the Bank and that the Bank is responsive to information requests.

H. Background Information: Respondents were asked to indicate their current position, specialization, whether they professionally collaborate with the World Bank, their exposure to the Bank in Pakistan, and their geographic location.

Response rate

A total of 512 stakeholders participated in the country survey (51%).

In 2024, the unemployment rate in Pakistan was at approximately 5.47 percent, a slight increase from 5.41 percent the previous year. Unemployment as an economic key indicatorThe unemployment rate of a country represents the share of people without a job in the country’s labor force, i.e. unemployed persons among those who are able and/or willing to work. Among other factors, it takes population growth into account, and thus increases in the labor force, as well as the age of the population. A high unemployment rate usually indicates economic troubles, with a popular example being Greece, where the unemployment rate skyrocketed from 7.76 percent in 2008 to 27.5 percent as a result of the Great Recession. From plowshares to keyboardsWhile Pakistan’s unemployment slumped below the one percent mark in 2010, it is now on the rise again and currently standing at just over four percent. Traditionally, most Pakistanis work in agriculture however, the lion’s share of the country’s GDP is generated by services, like tourism, banking, and IT. While agriculture is still important for Pakistan’s economy, the services sector is gaining ground in the country, and more and more people are moving to urban areas from the countryside to find jobs in the cities.

Pakistan PK: Poverty Headcount Ratio at $2.15 a Day: 2017 PPP: % of Population data was reported at 4.900 % in 2018. This records a decrease from the previous number of 5.100 % for 2015. Pakistan PK: Poverty Headcount Ratio at $2.15 a Day: 2017 PPP: % of Population data is updated yearly, averaging 20.200 % from Dec 1987 (Median) to 2018, with 13 observations. The data reached an all-time high of 67.300 % in 1987 and a record low of 4.900 % in 2018. Pakistan PK: Poverty Headcount Ratio at $2.15 a Day: 2017 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Social: Poverty and Inequality. Poverty headcount ratio at $2.15 a day is the percentage of the population living on less than $2.15 a day at 2017 purchasing power adjusted prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Abstract

The PSLM Project is designed to provide Social & Economic indicators in the alternate years at provincial and district levels. The project was initiated in July 2004 and will continue up to June 2015. The data generated through surveys is used to assist the government In formulating the poverty reduction strategy as well as development plans at district level and for the rapid assessment of program in the overall context of MDGs. As such this survey is one of the main mechanisms for monitoring MDGs indicators. It provides a set of representative, population-based estimates of social indicators and their progress under the PRSP/MDGs. For Millennium Development Goals (MDGs), UN has set 18 targets for 48 indicators for its member countries to achieve by 2015. Pakistan has committed to implement 16 targets and 37 indicators out of which 6 targets and 13 indicators are monitored through PSLM Surveys. The PSLM surveys are conducted at district level and at Provincial level respectively at alternate years. PSLM District level survey collects information on key Social indicators whereas through provincial level surveys (Social & HIES) collects information on social indicators as well as on Income and Consumption while in specific sections also information is also collected about household size; the number of employed people and their employment status, main sources of income; consumption patterns; the level of savings; and the consumption of the major food items. However, Planning Commission also uses this data for Poverty analysis.

Another important objective of the PSLM Survey is to try to establish the distributional impact of development programs; whether the poor have benefited from the program or whether increased government expenditure on the social sectors has been captured by the better off. The sample size of PSLM surveys district level is approximately 80000 households and approximately 18000 at Provincial level.

Main Indicators: Indicators on Demographic characteristics, Education, Health, Employment, Household Assets, Household Amenities, Population Welfare and Water Supply & Sanitation are developed at National/Provincial /District levels.

Geographic coverage

National coverage

Analysis unit

Households and Individuals

Universe

The universe of this survey consists of all urban and rural areas of all four provinces, AJK and Gilgit Baltistan. FATA and Military restricted areas have been excluded from the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: Pakistan Bureau of statistics PBS has developed its own urban area frame. Each city/town is divided into enumeration blocks. Each enumeration block is comprised to 200-250 households on the average with well-defined boundaries and maps .The list of enumeration blocks as updated from field on the prescribed Performa by Quick Count Technique in 2013 for urban and the list of villages/mouzas/dehs or its part (block), updated during House listing in 2011 for conduct of Population Census, are taken as sampling frame. Enumeration blocks and villages are considered as Primary Sampling Units (PSUs) for urban and rural domains respectively. A project to update the rural blocks is currently in hand.

Stratification Plan

Urban Areas: Large sized cities having population five laces and above have been treated as independent stratum. Each of these cities has further been sub-stratified into low, middle and high income groups. The remaining cities/towns within each defunct administrative division have been grouped together to constitute an independent stratum.

Rural Areas: The entire rural domain of a district for Khyber Pakhtunkhwa, Punjab, and Sindh provinces has been considered as independent stratum, whereas in Balochistan province defunct administrative division has been treated as stratum.

Sample Size and its Allocation: To determine optimum sample size for this survey, 6 indicators namely Literacy rate, Net enrolment rate at primary level, Population 10+ that ever attended school, Contraceptive prevalence of women age 15-49 years, Children age 12-23 months who are fully immunized and post natal consultation for ever married women aged 15-49 years were taken into consideration. Keeping in view the prevalence of these indicators at different margin of errors, reliability of estimates and field resources available a sample of size 19620 households distributed over 1368 PSUs (567 urban and 801 rural) has been considered sufficient to produce reliable estimates in respect of all four provinces with urban rural breakdown, however data was collected from 1307 PSU’S by covering 17989 household.

Sample Design: A two-stage stratified sample design has been adopted for this survey.

Selection of primary sampling Units (PSUs): Enumeration blocks in urban and rural domains have been taken as PSUs. In urban and rural domains sample PSUs from each stratum have been selected by PPS method of sampling scheme; using households in each block as Measure of size (MOS).

Selection of Secondary Sampling Units (SSUs): Households within PSU have been considered as SSUs. 16 and 12 households have been selected from urban/rural domains respectively by systematic sampling scheme with a random start.

Sampling deviation

Out of 1368 PSUs, of all four provinces 61 PSUs (11 urban and 50 rural PSUs) of Balochistan were dropped due to bad law and order situation and the remaining 1307 PSUs (556 urban and 751 rural) comprising 17989 households were covered.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

At both individual and household level, the PSLM Survey collects information on a wide range of topics using an integrated questionnaire. The questionnaire comprises a number of different sections, each of which looks at a particular aspect of household behavior or welfare. Data collected under Round IX includes education, diarrhea, immunization, reproductive health, pregnancy history, maternity history, family planning, pre and post-natal care and access to basic services.

Cleaning operations

Data quality in PSLM Survey has been ensured through a built in system of checking of field work by the supervisors in the field and by the in charge of the concerned Regional/Field offices. Teams from the headquarters also pay surprise visits and randomly check the work done by the enumerators. Regional/ Field offices ensured the data quality through preliminary editing at their office level. The entire data entry was carried at the PBS headquarter Islamabad and specially designed data entry programme had a number of built in consistency checks.

Data appraisal

To determine the reliability of the estimates confidence interval and Standard error of important key indicators have been worked out and are attached at the end of each section of the survey report, provided under the 'Related Materials' tab

Poverty and Vulnerability Assessment (PVA) is a district level household survey to understand vulnerability of households to environmental and socioeconomic changes with focus on mountain specificity as well as their coping strategies and adaptive capacity. Under the Adaptation to Change program, the Himalaya Climate Change Adaptation Programme (HICAP) initiative have conducted the survey among 1139 households across 3 Union Councils in Khyber-Pakhtunkhwa and Gilgit-Baltistan provinces in the Upper Indus sub-basin in Pakistan. The households were selected following a probability based multi-stage cluster sampling approach.

In 1800, the population of the area of modern-day Pakistan was estimated to be just over 13 million. Population growth in the 19th century would be gradual in the region, rising to just 19 million at the turn of the century. In the early 1800s, the British Empire slowly consolidated power in the region, eventually controlling the region of Pakistan from the mid-19th century onwards, as part of the British Raj. From the 1930s on, the population's growth rate would increase as improvements in healthcare (particularly vaccination) and sanitation would lead to lower infant mortality rates and higher life expectancy. Independence In 1947, the Muslim-majority country of Pakistan gained independence from Britain, and split from the Hindu-majority country of India. In the next few years, upwards of ten million people migrated between the two nations, during a period that was blemished by widespread atrocities on both sides. Throughout this time, the region of Bangladesh was also a part Pakistan (as it also had a Muslim majority), known as East Pakistan; internal disputes between the two regions were persistent for over two decades, until 1971, when a short but bloody civil war resulted in Bangladesh's independence. Political disputes between Pakistan and India also created tension in the first few decades of independence, even boiling over into some relatively small-scale conflicts, although there was some economic progress and improvements in quality of life for Pakistan's citizens. The late 20th century was also characterized by several attempts to become democratic, but with intermittent periods of military rule. Between independence and the end of the century, Pakistan's population had grown more than four times in total. Pakistan today Since 2008, Pakistan has been a functioning democracy, with an emerging economy and increasing international prominence. Despite the emergence of a successful middle-class, this is prosperity is not reflected in all areas of the population as almost a quarter still live in poverty, and Pakistan ranks in the bottom 20% of countries according to the Human Development Index. In 2020, Pakistan is thought to have a total population of over 220 million people, making it the fifth-most populous country in the world.

This layer contains information about the risk of food insecurity according to the Integrated Context Analysis (ICA) performed in Pakistan in 2017. Given that no other food security outcome data was available at district level for the whole country, the analysis was carried out using poverty data as a proxy for vulnerability to food insecurity. Data source: UNDP, 2004/05 to 2005/06. The key indicator used for the analysis was the Multi-Dimensional Poverty Index (MPI), with the threshold set to 0.329 - average of all the district-level observations over 6 PSLM rounds. It should be noted that 33 districts in the country did not have MPI data available and are not covered by this specific analysis.

In 2024, India’s real gross domestic product (GDP) growth rate was around **** percent, the highest in South Asia. In contrast, Nepal reported the lowest real GDP growth rate in the region at approximately **** percent that year, but it was forecasted to increase to **** percent in 2026.Economy in South Asia In general, South Asia encompasses Sri Lanka, Pakistan, Afghanistan, Bangladesh, Nepal, India and Bhutan. In 2020, India had a GDP of over *** trillion U.S. dollars, while Bangladesh and Sri Lanka followed. The Maldives and Bhutan were among the countries with the lowest GDP in the Asia-Pacific region. In South Asia, the main economic activities include the services sector as well as the industrial and manufacturing sectors.Society in South AsiaFrom the South Asian countries, Bangladesh had the highest share of people living below the poverty line. The Maldives and Sri Lanka exhibited the highest and second-highest GDP per capita among the South Asian countries in 2021.

Pakistan PK: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at 2.820 % in 2013. Pakistan PK: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging 2.820 % from Dec 2013 (Median) to 2013, with 1 observations. Pakistan PK: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank: Poverty. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.