Actual value and historical data chart for Pakistan Poverty Headcount Ratio At National Poverty Line Percent Of Population

This dataset provides key indicators related to poverty and inequality in Pakistan (1987–2020). It includes yearly values of:

Income share distribution across different quintiles (2nd 20%, 3rd 20%, 4th 20%)

Population living in slums (% of urban population)

Country codes and metadata for integration with other datasets

📊 Dataset Columns

Country Name – Name of the country (Pakistan)

Country ISO3 – ISO3 country code (PAK)

Year – Year of observation

Indicator Name – Poverty/inequality indicator

Indicator Code – Corresponding World Bank / UN indicator code

Value – Numerical value of the indicator

🌍 Source

The dataset is based on World Bank development indicators related to poverty and inequality.

🔎 Possible Use Cases

Analyzing poverty and inequality trends in Pakistan

Studying income distribution across population groups

Socio-economic and policy research

Visualization projects

Training machine learning models for poverty prediction

📌 Note: This dataset has been cleaned and structured for easier analysis on Kaggle.

Yearly (annual) dataset of the Pakistan Poverty Rate, including historical data, latest releases, and long-term trends from 1987-12-31 to 2018-12-31. Available for free download in CSV format.

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.

Historical dataset showing Pakistan poverty rate by year from 1987 to 2018.

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. Pakistan 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. Pakistan 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).

This dataset provides annual data on key economic, social, and environmental indicators affecting poverty levels in Pakistan from the year 2000 to 2023. It includes crucial variables such as GDP growth rate, inflation, unemployment, poverty headcount ratio, agricultural growth, government social spending, external debt, and climate-related disasters. The dataset highlights significant trends, including the economic impact of the 2010 floods, COVID-19 pandemic (2020–2022), and the 2022 economic crisis. It serves as a valuable resource for researchers, policymakers, and analysts studying poverty dynamics and economic development in Pakistan.

Pakistan PK: Poverty Headcount Ratio at $1.90 a Day: 2011 PPP: % of Population data was reported at 4.000 % in 2015. This records a decrease from the previous number of 6.100 % for 2013. Pakistan PK: Poverty Headcount Ratio at $1.90 a Day: 2011 PPP: % of Population data is updated yearly, averaging 16.200 % from Dec 1987 (Median) to 2015, with 12 observations. The data reached an all-time high of 62.200 % in 1987 and a record low of 4.000 % in 2015. Pakistan PK: Poverty Headcount Ratio at $1.90 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 $1.90 a day is the percentage of the population living on less than $1.90 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.

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.

This paper summarizes the approach used to estimate monetary poverty for Pakistan in 2019–20 at the district level. The small area estimation method is used to impute welfare from the Household Income and Expenditure Survey 2018–19 into the Pakistan Social and Living Standard Measurement Survey 2019–20. This application differs from the standard small area estimation implementations that use a survey-to-census method because the two surveys are household surveys. Using surveys instead of a census as the target data offers additional information for modeling poverty, but it also comes at the expense of noise due to sampling. Monetary poverty rates are estimated for 126 districts in Punjab, Sindh, Khyber Pakhtunkhwa, and Balochistan, including, for the first time, the districts of the former Federal Administered Tribal Areas and the former Frontier Regions. Using the Census Empirical Best method, the analysis obtains poverty estimates with higher precision and accuracy than those of the methodology previously implemented in Pakistan.

16.50 (%) in 2018. Population below $1.9 a day is the percentage of the population living on less than $1.9 a day at 2005 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.

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.

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

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.

This dataset provides a comprehensive overview of various hunger-related metrics in Pakistan from 2020 to 2023. It includes critical indicators such as the percentage of the population living under poverty, malnutrition rates, food insecurity levels, access to clean water, food production index, and the rate of underweight children. These metrics are essential for understanding the current state of hunger and nutritional challenges faced by the population in Pakistan.

Key Features:

Year:The year of data collection (2020-2023).

Population_Under_Poverty: The percentage of the population living below the poverty line.

Malnutrition_Rate:The percentage of the population suffering from malnutrition.

Food_Insecurity: The percentage of the population experiencing food insecurity.

Access_to_Clean_Water: The percentage of the population with access to clean water.

Food_Production_Index: An index value representing the level of food production.

Children_Underweight:The percentage of children underweight for their age.

Use Cases: This dataset is useful for analyzing trends in hunger and nutrition over recent years in Pakistan. It can support research in areas such as public health, economic development, and food security. The data is valuable for policymakers, researchers, and organizations focused on addressing hunger and improving nutritional outcomes.

ObjectiveThe current study aimed to assess the relation between multi-dimension poverty, treatment-seeking behavior, and antibiotic misuse among urinary tract infection (UTI) patients.MethodA cross-sectional approach was utilized to recruit patients who had a history of UTI in the previous month from two provinces of Pakistan. The treatment-seeking behavior and antibiotic misuse data were collected on a self-developed questionnaire, whereas the poverty data were collected on a modified multi-dimension poverty index (MPI). Descriptive statistics were applied to summarize the data. The logistic regression analysis was carried out to assess the association of multi-dimension poverty with patient treatment-seeking behavior and antibiotic misuse.ResultsA total of 461 participants who had UTI symptoms in the previous month were recruited. Most of the participants in the severely deprived stage treated the UTI (p 

Pakistan PK: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data was reported at 18.200 % in 2013. Pakistan PK: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data is updated yearly, averaging 18.200 % from Dec 2013 (Median) to 2013, with 1 observations. Pakistan PK: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban 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. Urban poverty headcount ratio is the percentage of the urban population living below the national poverty lines.; ; 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.

This statistic shows the most important import partners for Pakistan in 2023. In 2023, the most important import partner for Pakistan was China with a share of 25 percent in all imports.

Profile of multidimensional health poverty in Pakistan: 2013–14 to 2018–19.

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%).