24 datasets found
  1. Largest cities in Pakistan 2023

    • statista.com
    Updated Apr 29, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Largest cities in Pakistan 2023 [Dataset]. https://www.statista.com/statistics/421370/largest-cities-in-pakistan/
    Explore at:
    Dataset updated
    Apr 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Pakistan
    Description

    This statistic shows the biggest cities in Pakistan as of 2023. In 2023, approximately 18.87 million people lived in Karāchi, making it the biggest city in Pakistan.

  2. T

    Pakistan - Population In Largest City

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 24, 2013
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS (2013). Pakistan - Population In Largest City [Dataset]. https://tradingeconomics.com/pakistan/population-in-largest-city-wb-data.html
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset updated
    Jul 24, 2013
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Pakistan
    Description

    Population in largest city in Pakistan was reported at 17648555 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Pakistan - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

  3. Pakistan PK: Population in Largest City

    • ceicdata.com
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com, Pakistan PK: Population in Largest City [Dataset]. https://www.ceicdata.com/en/pakistan/population-and-urbanization-statistics/pk-population-in-largest-city
    Explore at:
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    Pakistan
    Variables measured
    Population
    Description

    Pakistan PK: Population in Largest City data was reported at 15,020,931.000 Person in 2017. This records an increase from the previous number of 14,650,981.000 Person for 2016. Pakistan PK: Population in Largest City data is updated yearly, averaging 6,793,799.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 15,020,931.000 Person in 2017 and a record low of 1,853,325.000 Person in 1960. Pakistan PK: Population in Largest City 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: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

  4. T

    Pakistan - Population In The Largest City

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 20, 2013
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS (2013). Pakistan - Population In The Largest City [Dataset]. https://tradingeconomics.com/pakistan/population-in-the-largest-city-percent-of-urban-population-wb-data.html
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset updated
    Jul 20, 2013
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Pakistan
    Description

    Population in the largest city (% of urban population) in Pakistan was reported at 18.31 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Pakistan - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

  5. Pakistan PK: Population in Largest City: as % of Urban Population

    • ceicdata.com
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com, Pakistan PK: Population in Largest City: as % of Urban Population [Dataset]. https://www.ceicdata.com/en/pakistan/population-and-urbanization-statistics/pk-population-in-largest-city-as--of-urban-population
    Explore at:
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    Pakistan
    Variables measured
    Population
    Description

    Pakistan PK: Population in Largest City: as % of Urban Population data was reported at 20.922 % in 2017. This records a decrease from the previous number of 20.928 % for 2016. Pakistan PK: Population in Largest City: as % of Urban Population data is updated yearly, averaging 21.610 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 23.038 % in 1980 and a record low of 18.670 % in 1960. Pakistan PK: Population in Largest City: as % 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: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted average;

  6. F

    Geographical Outreach: Number of Branches in 3 Largest Cities, Excluding...

    • fred.stlouisfed.org
    json
    Updated Nov 10, 2016
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2016). Geographical Outreach: Number of Branches in 3 Largest Cities, Excluding Headquarters, for Commercial Banks for Pakistan [Dataset]. https://fred.stlouisfed.org/series/PAKFCBODCLNUM
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Nov 10, 2016
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    Pakistan
    Description

    Graph and download economic data for Geographical Outreach: Number of Branches in 3 Largest Cities, Excluding Headquarters, for Commercial Banks for Pakistan (PAKFCBODCLNUM) from 2004 to 2015 about branches, Pakistan, banks, and depository institutions.

  7. o

    Pakistan - Population of Major Cities - Datasets - Open Data Pakistan

    • opendata.com.pk
    Updated Jan 13, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2020). Pakistan - Population of Major Cities - Datasets - Open Data Pakistan [Dataset]. https://opendata.com.pk/dataset/pakistan-population-of-major-cities
    Explore at:
    Dataset updated
    Jan 13, 2020
    Area covered
    Pakistan
    Description

    This provincial level data provides population statistics for major cities of Pakistan.

  8. F

    Geographical Outreach: Number of Branches in 3 Largest Cities, Excluding...

    • fred.stlouisfed.org
    json
    Updated Nov 10, 2016
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2016). Geographical Outreach: Number of Branches in 3 Largest Cities, Excluding Headquarters, for Deposit Taking Microfinance Institutions (MFIs) for Pakistan [Dataset]. https://fred.stlouisfed.org/series/PAKFCBODMFLNUM
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Nov 10, 2016
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    Pakistan
    Description

    Graph and download economic data for Geographical Outreach: Number of Branches in 3 Largest Cities, Excluding Headquarters, for Deposit Taking Microfinance Institutions (MFIs) for Pakistan (PAKFCBODMFLNUM) from 2004 to 2015 about microfinance, branches, Pakistan, and deposits.

  9. Time Use Survey 2007 - Pakistan

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Mar 29, 2019
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Federal Bureau of Statistics (2019). Time Use Survey 2007 - Pakistan [Dataset]. https://catalog.ihsn.org/index.php/catalog/3537
    Explore at:
    Dataset updated
    Mar 29, 2019
    Dataset provided by
    Pakistan Bureau of Statisticshttp://pbs.gov.pk/
    Authors
    Federal Bureau of Statistics
    Time period covered
    2007
    Area covered
    Pakistan
    Description

    Abstract

    A primary objective of the national Time Use Survey in Pakistan is to account for the 24 hours time in term of the full spectrum of activities carried out during the duration. The objectives of the survey are specified as under:- - To profile the quantum and distribution of paid/unpaid work as a means to infer policy/programme implications from the perspective of gender equity. - To collect and analyze the time use pattern of the individuals in order to help draw inferences for employment and welfare programmes. - To collect and analyze the comprehensive information about the time spent by people on marketed and non-marketed economic activities covered under the 1993-SNA, non-marketed non-SNA activities within the General Production Boundary and personal care and related activities that cannot be delegated to others. - To use the data in generating more reliable estimates on work force.

    Geographic coverage

    The survey covers all urban and rural areas of the four provinces of Pakistan defined as such by 1998 Population Census excluding Federally Administered Tribal Areas (FATA) and certain administrative areas of NWFP. The population of geographic areas excluded from the survey constitutes about 2 percent of the total population as enumerated in 1998 Population Census. The population excluded is located in difficult terrain and its enumeration through personal interview is not possible within the given constraints of time, access and cost.

    Analysis unit

    Households Individuals

    Universe

    The universe consists of all urban and rural areas of the four provinces of Pakistan, defined as such by Population Census 1998, excluding FATA & Military Restricted Areas. The population of excluded area constitutes about 3% of the total population and is located in different terrain.

    Sampling procedure

    Sampling Frame Federal Bureau of Statistics has developed its own sampling frame for all urban areas of the country. Each city/town has been divided into a number of enumeration blocks. Each enumeration block consists of 200-250 households on the average with well-defined boundaries and maps. The sampling frame i.e. lists of enumeration blocks as up-dated through Economic Census 2003-04 and the lists of villages/mouzas/dehs published by Population Census Organization as a result of 1998 Population Census have been taken as sampling frame. Enumeration blocks and villages are considered as primary sampling unites (PSUs) for urban and rural domain respectively.

    Stratification a) Urban Domain i) Large Sized Cities Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawapur, Hyderabad, Sukkur, Peshawar, Quetta and Islamabad are considered as large sized cities. Each of these cities constitutes a separate stratum which is further sub-stratified according to low, middle, high income groups based on the information collected in respect of each enumeration block at the time of demarcation/up-dating of urban area sampling frame. ii) Remaining urban areas After excluding the population of large sized cities from the population of respective administrative division, the remaining urban population of administrative division of four provinces is grouped together to form a stratum called other urban. Thus ex-division in remaining urban areas in the four provinces constitutes a stratum. b) Rural Domain In rural domain, each administrative district in the Punjab, Sindh and NWF Provinces is considered as independent and explicit stratum whereas, in Balochistan, each administrative division constitutes a stratum.

    Sample size and its Allocation Keeping in view the resources available, a sample size of 19600 sample households has been considered appropriate to provide estimates of key characteristics at the desired level. The entire sample of households (SSUs) has been drawn from 1388 Primary Sampling Units (PSUs) out of which 652 are urban and 736 are rural. In order to control seasonal variation etc. sample has been distributed evenly over four quarters. This has facilitated to capture the variation due to any seasonal activity as urban population is more heterogeneous therefore, a higher proportion of sample size has been allocated to urban domain. Similarly NWFP and Balochistan being the smaller province, have been assigned higher proportion of sample in order to get reliable estimates. After fixing the sample size at provincial level, further distribution of sample PSUs to different strata in rural and urban domains in each province has been made proportionately.

    Sample Design A three-stage stratified sample design has been adopted for the survey. Sample Selection Procedure a) Selection of Primary Sampling Unites (PSUs) Enumeration blocks in urban domain and mouzas/dehs/villages in rural domain are taken as primary sampling unites (PSUs). In the urban domain, sample PSUs from each ultimate stratum/sub-stratum is selected with probability proportional to size (PPS) method of sampling scheme. In urban domain, the number of households in enumeration block as up-dated through Economic Census 2003-04 and population of 1998 Census for each village/mouza/deh are considered as measure of size. b) Section of Secondary Sampling Units (SSUs) Households within sample PSUs are taken as secondary sampling unites (SSUs). A specified number of households i.e. 12 from each urban sample PSU and 16 from each rural sample PSU are selected with equal probability using systematic sampling technique with a random start. Different households are selected in each quarter. c) Selection of Third Stage Sampling Units i.e. Individuals/Persons (TSUs) From the sample households, individuals/persons aged 10+ years within each sample households (SSUs) have been taken as third stage sampling units (TSUs). Two individuals aged 10 years and above among the eligible individuals/persons from each sample household have been interviewed using a selection grid.The grid and selection steps are detailed on p13 of the survey report available under external resources.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaire has been framed in the light of contemporary precedents and practices in vogue in the developing countries. The recommendations of Gender Responsive Budgeting Initiatives (GRBI) expert who visited Pakistan in June 2006 have been taken into account. Further, the advice of local experts hailing both from data producing and using agencies has also been considered. Survey Questionnaire and Manual of Instructions, for the Supervisors & Enumerators, was finalized jointly by Federal Bureau of Statistics and GRBI Project staff. The questionnaire was also pre-tested and reviewed accordingly. The questionnaire adopted for the survey is given at Annexure-A. All the households selected in the sample stand interviewed. Diary part of the questionnaire is filled-in from two respondents selected from each of the enumerated households. The questionnaire consists of the following six parts. Section-1: Identification of the area, respondents, detail of field visits and staff entrusted with supervision, editing and coding. Section-2: Detailed information about the socio-economic and demographic particulars of the selected households and individuals. Some of the important household characteristics i.e. ownership status and type of the household, earthquake damage, household items, sources of energy, drinking water, transport, health & education facilities, sources of income, monthly income, age and sex composition of the population. Section-3: Demographic detail such as age, sex, marital status, educational level, having children, employment status, source of income etc. of the selected respondent of that household Section-4: Comprised of diary to record the activities performed by the first selected respondent through the 24 hours period between 4.00 a.m. of the day preceding the day of interview and 3.00 a.m. on the day of the interview. Section-5 and 6 pertain to the second selected respondent of the selected household. The diary which is the core instrument of the time use study is divided into forty eight half-hour slots. An open ended question about the activities performed during the thirty minutes was asked from the respondent. Provision for minimum of recording three activities through half hour slot was made. In case of reporting more than one activity, the respondent was probed whether these activities were carried out simultaneously or one after the other. Similarly, the two locations of performing the activities were also investigated in the diary part of the questionnaire. The activities recorded in the diary are then coded by the field enumerator according to the activity classification given at Annex-B.

    Cleaning operations

    Soon after data collection, the field supervisors manually clean, edit and check the filled in questionnaire and refer back to field where necessary. This does not take much time since most of the manual editing is done in the field. Further editing is done by the subject matter section at the Headquarter. Also during data entry, further editing of error identified by applying computer edit checks is done. In edit checks, data ranges in numerical values are used to eliminate erroneous data as a result of mistakes made during coding. Thus, the survey records are edited and corrected through a series of computer processing stages.

  10. i

    Demographic and Health Survey 2006-2007 - Pakistan

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Jul 6, 2017
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    National Institute of Population Studies (2017). Demographic and Health Survey 2006-2007 - Pakistan [Dataset]. https://catalog.ihsn.org/catalog/2576
    Explore at:
    Dataset updated
    Jul 6, 2017
    Dataset authored and provided by
    National Institute of Population Studies
    Time period covered
    2006 - 2007
    Area covered
    Pakistan
    Description

    Abstract

    The 2006-07 Pakistan Demographic and Health Survey (PDHS) was undertaken to address the monitoring and evaluation needs of maternal and child health and family planning programmes. The survey was designed with the broad objective to provide policymakers, primarily in the Ministries of Population Welfare and Health, with information to improve programmatic interventions based on empirical evidence. The aim is to provide reliable estimates of the maternal mortality ratio (MMR) at the national level and a variety of other health and population indicators at national, urban-rural, and provincial levels.

    The 2006-07 Pakistan Demographic and Health Survey (PDHS) is the fifth in a series of demographic surveys conducted by the National Institute of Population Studies (NIPS) since 1990. However, the PDHS 2006-07 is the second survey conducted as part of the worldwide Demographic andHealth Surveys programme. The survey was conducted under the aegis of the Ministry of Population Welfare and implemented by the National Institute of Population Studies. Other collaborating institutions include the Federal Bureau of Statistics, the Aga Khan University, and the National Committee for Maternal and Neonatal Health. Technical support was provided by Macro International Inc. and financial support was provided by the United States Agency for International Development (USAID). The United Nations Population Fund (UNFPA) and United Nations Children's Fund (UNICEF) provided logistical support for monitoring the fieldwork for the PDHS.

    The 2006-07 PDHS supplements and complements the information collected through the censuses and demographic surveys conducted by the Federal Bureau of Statistics. It updates the available information on population and health issues, and provides guidance in planning, implementing, monitoring and evaluating health and population programmes in Pakistan. Some of the findings of the PDHS may seem at variance with data compiled by other sources. This may be due to differences in methodology, reference period, wording of questions and subsequent interpretation. This fact may be kept in mind while analyzing and comparing PDHS data with other sources. The results of the survey assist in the monitoring of the progress made towards meeting the Millennium Development Goals (MDGs).

    The 2006-07 PDHS includes topics related to fertility levels and determinants, family planning, fertility preferences, infant, child and maternal mortality and their causes, maternal and child health, immunization and nutritional status of mothers and children, knowledge of HIV/AIDS, and malaria. The 2006-07 PDHS also includes direct estimation of maternal mortality and its causes at the national level for the first time in Pakistan. The survey provides all other estimates for national, provincial and urban-rural domains. This being the fifth survey of its kind, there is considerable trend information on reproductive health, fertility and family planning over the past one and a half decades.

    More specifically, PDHS had the following objectives: - Collect quality data on fertility levels and preference, family planning knowledge and use, childhood—and especially neonatal—mortality levels and awareness regarding HIV/ AIDS and other indicators relevant to the Millennium Development Goals and the Poverty Reduction Strategy Paper; - Produce a reliable national estimate of the MMR for Pakistan, as well as information on the direct and indirect causes of maternal deaths using verbal autopsy instruments; - Investigate factors that impact on maternal and neonatal morbidity and mortality (i.e., antenatal and delivery care, treatment of pregnancy complications, and postnatal care); - Improve the capacity of relevant organizations to implement surveys and analyze and disseminate survey findings.

    Geographic coverage

    The survey provides estimates at national, urban and rural, and provincial levels (each as a separate domain).

    The sample for the 2006-07 PDHS represents the population of Pakistan excluding the Federally Administered Northern Areas (FANA) and restricted military and protected areas. Although the Federally Administered Tribal Areas (FATA) were initially included in the sample, due to security and political reasons, it was not possible to cover any of the sample points in the FATA.

    In urban areas, cities like Karachi, Lahore, Gujranwala, Faisalbad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta, and Islamabad were considered as large-sized cities.

    Analysis unit

    • Household
    • Children under five years
    • Women age 15-49
    • Men

    Kind of data

    Sample survey data

    Sampling procedure

    The 2006-07 PDHS is the largest-ever household based survey conducted in Pakistan. The sample is designed to provide reliable estimates for a variety of health and demographic variables for various domains of interest. The survey provides estimates at national, urban and rural, and provincial levels (each as a separate domain). One of the main objectives of the 2006-07 Pakistan Demographic and Health Survey (PDHS) is to provide a reliable estimate of the maternal mortality ratio (MMR) at the national level. In order to estimate MMR, a large sample size was required. Based on prior rough estimates of the level of maternal mortality in Pakistan, a sample of about 100,000 households was proposed to provide estimates of MMR for the whole country. For other indicators, the survey is designed to produce estimates at national, urban-rural, and provincial levels (each as a separate domain). The sample was not spread geographically in proportion to the population; rather, the smaller provinces (e.g., Balochistan and NWFP) as well as urban areas were over-sampled. As a result of these differing sample proportions, the PDHS sample is not self-weighting at the national level.

    The sample for the 2006-07 PDHS represents the population of Pakistan excluding the Federally Administered Northern Areas (FANA) and restricted military and protected areas. Although the Federally Administered Tribal Areas (FATA) were initially included in the sample, due to security and political reasons, it was not possible to cover any of the sample points in the FATA.

    In urban areas, cities like Karachi, Lahore, Gujranwala, Faisalbad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta, and Islamabad were considered as large-sized cities. Each of these cities constitutes a stratum, which has further been substratified into low, middle, and high-income groups based on the information collected during the updating of the urban sampling frame. After excluding the population of large-sized cities from the population of respective former administrative divisions, the remaining urban population within each of the former administrative divisions of the four provinces was grouped together to form a stratum.

    In rural areas, each district in Punjab, Sindh, and NWFP provinces is considered as an independent stratum. In Balochistan province, each former administrative division has been treated as a stratum. The survey adopted a two-stage, stratified, random sample design. The first stage involved selecting 1,000 sample points (clusters) with probability proportional to size-390 in urban areas and 610 in rural areas. A total of 440 sample points were selected in Punjab, 260 in Sindh, 180 in NWFP, 100 in Balochistan, and 20 in FATA. In urban areas, the sample points were selected from a frame maintained by the FBS, consisting of 26,800 enumeration blocks, each including about 200-250 households. The frame for rural areas consists of the list of 50,588 villages/mouzas/dehs enumerated in the 1998 population census.

    The FBS staff undertook the task of a fresh listing of the households in the selected sample points. Aside from 20 sample points in FATA, the job of listing of households could not be done in four areas of Balochistan due to inability of the FBS to provide household listings because of unrest in those areas. Another four clusters in NWFP could not be covered because of resistance and refusal of the community. In other words, the survey covered a total of 972 sample points.

    The second stage of sampling involved selecting households. In each sample point, 105 households were selected by applying a systematic random sampling technique. This way, a total of 102,060 households were selected. Out of 105 sampled households, ten households in each sample point were selected using a systematic random sampling procedure to conduct interviews for the Long Household and the Women's Questionnaires. Any ever-married woman aged 12-49 years who was a usual resident of the household or a visitor in the household who stayed there the night before the survey was eligible for interview.

    Mode of data collection

    Face-to-face

    Research instrument

    The following six types of questionnaires were used in the PDHS: - Community Questionnaire - Short Household Questionnaire - Long Household Questionnaire - Women’s Questionnaire - Maternal Verbal Autopsy Questionnaire - Child Verbal Autopsy Questionnaire

    The contents of the Household and Women’s Questionnaires were based on model questionnaires developed by the MEASURE DHS programme, while the Verbal Autopsy Questionnaires were developed by Pakistani experts and the Community Questionnaire was patterned on the basis of one used by NIPS in previous surveys.

    NIPS developed the draft questionnaires in consultation with a broad spectrum of technical experts, government agencies, and local and international organizations so as to reflect relevant issues of population, family planning, HIV/AIDS, and other health areas. A number of meetings were organized

  11. f

    Accessibility: Travel Time-Cost to Major Cities (Pakistan - ~ 500m)

    • data.apps.fao.org
    Updated Feb 19, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). Accessibility: Travel Time-Cost to Major Cities (Pakistan - ~ 500m) [Dataset]. https://data.apps.fao.org/map/catalog/srv/resources/datasets/0090dcf8-8300-4558-8288-d8e48720e773
    Explore at:
    Dataset updated
    Feb 19, 2025
    Area covered
    Pakistan
    Description

    Accessibility to major cities dataset is modelled as raster-based travel time/cost analysis, computed for the 26 largest cities (>250k habitants) in the country. The following cities are included: City - Population Chiniot 278,528 Nawabshah 279,338 Mingora 331,377 Okara 358,146 Kasur 358,296 Mardan 359,024 Wah Cantonment 379,534 Sahiwal 388,795 Gujrat 390,758 Dera Ghazi Khan 397,362 Rahimyar Khan 420,963 Sheikhūpura 473,269 Larkana 488,006 Sukkur 500,401 Sialkot 656,730 Sargodha 658,208 Bahawalpur 762,774 Quetta 999,385 Hyderabad 1,733,622 Multan 1,872,641 Peshawar 1,969,823 Gujranwala 2,028,421 Rawalpindi Islamabad 3,106,827 Faisalabad 3,210,158 Lahore 11,119,985 Karachi 14,884,402 This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (or optimal location).

  12. Social and Living Standards Measurement Survey 2014-2015, Round 10 -...

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    Updated Jan 16, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Pakistan Bureau of Statistics (2021). Social and Living Standards Measurement Survey 2014-2015, Round 10 - Pakistan [Dataset]. https://datacatalog.ihsn.org/catalog/8508
    Explore at:
    Dataset updated
    Jan 16, 2021
    Dataset authored and provided by
    Pakistan Bureau of Statisticshttp://pbs.gov.pk/
    Time period covered
    2014 - 2015
    Area covered
    Pakistan
    Description

    Abstract

    The Pakistan Social and Living Standards Measurement (PSLM) Survey is one of the main mechanisms for monitoring the implementation of the Poverty Reduction Strategy Paper (PRSP). It provides a set of representative, population-based estimates of social indicators and their progress under the PRSP. These include intermediate as well as 'output' measures, which assess what is being provided by the social sectors - enrolment rates in education, for example. They include a range of 'outcome' measures, which assess the welfare of the population - Immunisation Rate, for example.

    An important objective of the PSLM Survey is to try to establish what the distributional impact of PRSP has been. Policymakers need to know, for example, whether the poor have benefited from the programme or whether increased government expenditure on the social sectors has been captured by the better off.

    Geographic coverage

    National, excluding military restricted areas.

    Analysis unit

    • Individual
    • Household

    Universe

    The universe of this survey consists of all urban and rural areas of the four provinces and Islamabad excluding military restricted areas.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Sampling Frame: Pakistan Bureau of Statistics (PBS) has developed its own area sampling frame for both Urban and Rural domains. Each city/town is divided into enumeration blocks. Each enumeration block is comprised of 200 to 250 households on the average with well-defined boundaries and maps. The list of enumeration blocks are updated from field on the prescribed proforma by Quick Count technique for urban domain in 2013 and the updated list of villages/mouzas/dehs or its part (block), based on House Listing 2011 for conduct of Population Census are taken as sampling frames. Enumeration blocks are considered as Primary Sampling Units (PSUs) for urban and rural domains respectively.

    Stratification Plan Urban Domain: Large cities Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta and Islamabad are considered as large cities. Each of these cities constitutes a separate stratum, further substratified according to low, middle and high income groups based on the information collected in respect of each enumeration block at the time of demarcation/ updating of urban area sampling frame. Remaining Urban Areas: In all the four provinces after excluding the population of large cities from the population of an administrative division, the remaining urban population is grouped together to form a stratum. Rural Domain: Each administrative district for all four provinces namely Punjab, Sindh, Khyber Pakhtunkhwa (KP) and Balochistan is 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 is considered as measure of size.

    Selection of secondary sampling units (SSUs): The listed households of sample PSUs are taken as Secondary Sampling Units (SSUs). A specified number of households i.e. 12 from each urban sample PSU and 16 from rural sample PSU are selected with equal probability using systematic sampling technique with a random start.

    Sample Size and its Allocation: Keeping in view the objectives of the survey, the sample size for the four provinces has been fixed at 5428 sample blocks (PSU’s) comprising 81,992 households (SSU’s), which is expected to produce reliable results at the district level.

    Detailed sampling plan is attached as Appendix A of the survey report.

    Sampling deviation

    It is worth mentioning here that Panjgur district of Balochistan was dropped from the scope of the survey at the allocation stage due to prevailing situation in Panjgur district. While 7 PSUs from Sindh, 13 PSUs from KP and 82 PSUs from Balochistan province ( including Kech district) were dropped from the scope of the survey during execution of the survey due to law and order situation.

    Mode of data collection

    Face-to-face [f2f]

    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 X includes Education, Health, Water & Sanitation and Household Economic Situation & Satisfaction by facilities and services use.

    Cleaning operations

    Data quality in PSLM Survey has been ensured through built in system of checking of fieldwork by the supervisors in the field as well as teams from the headquarters. Regional/ Field offices ensured the data quality through preliminary editing at their office level. The entire data entry was carried out at the PBS headquarter Islamabad and the data entry programme used had a number of in built consistency checks.

  13. Social and Living Standards Measurement Survey 2006-2007, Public Use File -...

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    Updated Jan 16, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Federal Bureau of Statistics (2021). Social and Living Standards Measurement Survey 2006-2007, Public Use File - Pakistan [Dataset]. https://catalog.ihsn.org/catalog/8543
    Explore at:
    Dataset updated
    Jan 16, 2021
    Dataset provided by
    Pakistan Bureau of Statisticshttp://pbs.gov.pk/
    Authors
    Federal Bureau of Statistics
    Time period covered
    2006 - 2007
    Area covered
    Pakistan
    Description

    Abstract

    The Pakistan Social and Living Standards Measurement Survey is one of the main mechanisms for monitoring the implementation of the MDGs and PRSP. It provides a set of representative, population-based estimates of social indicators and their progress under MDGs and PRSP. These include intermediate as well as ‘output’ measures, which assess what is being provided by the social sectors – enrolment rates in education, for example. They include a range of ‘outcome’ measures, which assess the welfare of the population Immunisation Rate, for example.

    An important objective of the PSLM Survey is to try to establish what is the distributional impact of different government programs carried out in Social Sector. Policymakers need to know, for example, whether the poor have benefited from the programme or whether increased government expenditure on the social sectors has been captured by the better off.

    Geographic coverage

    National, excluding military restricted areas

    Analysis unit

    • Individual
    • Household

    Universe

    The universe of this survey consists of all urban and rural areas of the four provinces and Islamabad excluding military restricted areas.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Sampling Frame: Federal Bureau of Statistics has developed its own urban area frame, which was up-dated in 2003. Each city/town has been divided into enumeration blocks consisting of 200-250 households identifiable through sketch map. Each enumeration block has been classified into three categories of income groups i.e. low, middle and high keeping in view the living standard of the majority of the people. List of villages published by Population Census Organization obtained as a consequence of Population Census 1998 has been taken as rural frame.

    Stratification Plan: A. Urban Domain: Islamabad, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Bahawalpur, Sargodha, Sialkot, Karachi, Hyderabad, Sukkur Peshawar and Quetta, have been considered as large sized cities. Each of these cities constitutes a separate stratum and has further been sub-stratified according to low, middle and high-income groups. After excluding population of large sized city (s), the remaining urban population in each district in all the provinces has been grouped together to form a stratum. B. Rural Domain: Each district in the four provinces of Pakistan has been treated an independent stratum.

    Sample Size and Its Allocation: Keeping in view the objectives of the survey the sample size for the four provinces has been fixed at 73,953 households comprising 5,198 sample villages / enumeration blocks, which is expected to produce reliable results at each district.

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

    Selection of Primary Sampling Units (PSUs): Villages and enumeration blocks in urban and rural areas respectively have been taken as Primary Sampling Units (PSUs). Sample PSUs have been selected from strata/sub-strata with PPS method of sampling technique.

    Selection of Secondary Sampling Units (SSUs): Households within sample PSUs have been taken as Secondary Sampling Units (SSUs). A specified number of households i.e 16 and 12 from each sample PSU of rural & urban area have been selected respectively using systematic sampling technique with a random start.

    Mode of data collection

    Face-to-face [f2f]

    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 behaviour or welfare. Data collected under Round III include education, health, immunisation, diarrhoea, its treatment, and pre and post-natal care, housing conditions and access to basic services and amenities.

    Cleaning operations

    Data quality in PSLM Survey has been ensured through built in system of checking of field work by the supervisors in the field as well as teams from the headquarters. Regional/ Field offices ensured the data quality through preliminary editing at their office level. The entire data entry was carried at the FBS headquarter Islamabad and the data entry programme used had a number of in built consistency checks.

    Response rate

    Non-response in the entire survey is negligible

  14. f

    HIV screening and testing among those identified as presumptive for TB,...

    • plos.figshare.com
    xls
    Updated Jun 21, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Sharaf Ali Shah; Shahina Qayyum; Saifullah Baig; Nikhat Iftikhar; Rubab Lubna Bukhari; Wajid Ali; Marina Smelyanskaya; Jacob Creswell (2023). HIV screening and testing among those identified as presumptive for TB, Sindh Pakistan. [Dataset]. http://doi.org/10.1371/journal.pgph.0000913.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Sharaf Ali Shah; Shahina Qayyum; Saifullah Baig; Nikhat Iftikhar; Rubab Lubna Bukhari; Wajid Ali; Marina Smelyanskaya; Jacob Creswell
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Sindh, Pakistan
    Description

    HIV screening and testing among those identified as presumptive for TB, Sindh Pakistan.

  15. Social and Living Standards Measurement Survey 2005-2006 - Pakistan

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    Updated Mar 29, 2019
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Federal Bureau of Statistics (2019). Social and Living Standards Measurement Survey 2005-2006 - Pakistan [Dataset]. https://catalog.ihsn.org/catalog/6845
    Explore at:
    Dataset updated
    Mar 29, 2019
    Dataset provided by
    Pakistan Bureau of Statisticshttp://pbs.gov.pk/
    Authors
    Federal Bureau of Statistics
    Time period covered
    2005 - 2006
    Area covered
    Pakistan
    Description

    Abstract

    The Pakistan Social and Living Standards Measurement Survey (PSLM) 2005-06 is aimed to provide detailed outcome indicators on Education, Health, Population Welfare, Water & Sanitation and Income & Expenditure. The data provided by this survey is used by the government in formulating the policies in social sector initiated under Poverty Reduction Strategy Paper (PRSP) and Medium Term Development Framework (MTDF) in the overall context of MDGs.

    Geographic coverage

    National Coverage

    Analysis unit

    Households and Individuals.

    Universe

    The universe of this survey consists of all urban and rural areas of the four provinces and Islamabad excluding military restricted areas

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Sampling Frame:

    The Federal Bureau of Statistics (FBS) has developed its own urban area frame, which was up-dated in 2003. Each city/town has been divided into enumeration blocks consisting of 200- 250 households identifiable through sketch map. Each enumeration block has been classified into three categories of income groups i.e. low, middle and high keeping in view the living standard of the majority of the people. List of villages published by Population Census Organization obtained as a consequence of Population Census 1998 has been taken as rural frame.

    Stratification Plan:

    A. Urban Domain: Islamabad, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Bahawalpur, Sargodha, Sialkot, Karachi, Hyderabad, Sukkur, Peshawar and Quetta, have been considered as large sized cities. Each of these cities constitute a separate stratum and has further been sub-stratified according to low, middle and high-income groups. After excluding population of large sized city (s), the remaining urban population in each defunct Division in all the provinces has been grouped together to form a stratum.

    B. Rural Domain: Each district in the Punjab, Sindh and NWFP provinces has been grouped together to constitute a stratum. Whereas defunct administrative Division has been treated as stratum in Balochistan province.

    Sample Size and Its Allocation: Keeping in view the objectives of the survey the sample size for the four provinces has been fixed at 15453 households comprising 1109 sample village/ enumeration blocks, which is expected to produce reliable results.

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

    Selection of Primary Sampling Units (PSUs): Villages and enumeration blocks in urban and rural areas respectively have been taken as Primary Sampling Units (PSUs). Sample PSUs have been selected from strata/sub-strata with PPS method of sampling technique.

    Selection of Secondary Sampling Units (SSUs): Households within sample PSUs have been taken as Secondary Sampling Units (SSUs). A specified number of households i.e. 16 and 12 from each sample PSU of rural & urban area have been selected respectively using systematic sampling technique with a random start.

    Mode of data collection

    Face-to-face [f2f]

    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 II include 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 built in system of checking of field work by the supervisors in the field as well as teams from the headquarters. Regional/ Field offices ensured the data quality through preliminary editing at their office level. The entire data entry was carried at the FBS headquarter Islamabad and the data entry programme used had a number of in built consistency checks.

    Data appraisal

    To determine the reliability of the estimates, Coefficient of Variation (CV’s) and confidence Limit of important key indicators have been worked out and are attached as Appendix - C of the survey report (provided under Related Materials).

  16. M

    Lahore, Pakistan Metro Area Population 1950-2025

    • macrotrends.net
    csv
    Updated Apr 30, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    MACROTRENDS (2025). Lahore, Pakistan Metro Area Population 1950-2025 [Dataset]. https://www.macrotrends.net/global-metrics/cities/22046/lahore/population
    Explore at:
    csvAvailable download formats
    Dataset updated
    Apr 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1950 - May 28, 2025
    Area covered
    Pakistan
    Description

    Chart and table of population level and growth rate for the Lahore, Pakistan metro area from 1950 to 2025.

  17. M

    Karachi, Pakistan Metro Area Population 1950-2025

    • macrotrends.net
    csv
    Updated Apr 30, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    MACROTRENDS (2025). Karachi, Pakistan Metro Area Population 1950-2025 [Dataset]. https://www.macrotrends.net/global-metrics/cities/22044/karachi/population
    Explore at:
    csvAvailable download formats
    Dataset updated
    Apr 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1950 - May 29, 2025
    Area covered
    Pakistan
    Description

    Chart and table of population level and growth rate for the Karachi, Pakistan metro area from 1950 to 2025.

  18. Employment by economic sector in Pakistan 2022

    • statista.com
    Updated Jan 30, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Employment by economic sector in Pakistan 2022 [Dataset]. https://www.statista.com/statistics/383781/employment-by-economic-sector-in-pakistan/
    Explore at:
    Dataset updated
    Jan 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Pakistan
    Description

    In 2022, 36.43 percent of the workforce in Pakistan worked in the agricultural sector, about a quarter worked in industry, and 38.05 percent in the services sector. The primary sectorThe most common breakdown of a country’s economy is into three sectors; the primary sector, which includes agriculture, raw materials, fishing, and hunting, the secondary sector, which is also called the industrial sector and includes manufacturing, and the tertiary sector, which encompasses intangible goods and services, like financial services, tourism, or telecommunications. Usually, an advanced economy focuses on the services sector, while in a developing economy, the primary sector is still prevalent. In Pakistan, agriculture plays an important role in trade and production, and most Pakistanis are employed in the agricultural sector – however, the services sector generates the lion’s share of GDP Is Pakistan on the verge of being a developed country?Typically, a developed country shifts GDP generation and employment to intangible goods, which also often means that its citizens move to the city, away from rural areas. In Pakistan, urbanization progresses slowly, and most inhabitants live in rural areas. One reason for this is Pakistan’s vast arable land area, which allows for the production and export of raw materials. To be a developed country, Pakistan still needs to put in some work and improve the standard of living and infrastructure, among other factors.

  19. Pakistan Number of Registered Vehicles

    • ceicdata.com
    Updated Jul 15, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2018). Pakistan Number of Registered Vehicles [Dataset]. https://www.ceicdata.com/en/indicator/pakistan/number-of-registered-vehicles
    Explore at:
    Dataset updated
    Jul 15, 2018
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2011 - Dec 1, 2022
    Area covered
    Pakistan
    Description

    Key information about Pakistan Number of Registered Vehicles

    • Pakistan Number of Registered Vehicles was reported at 7,020,803 Unit in Dec 2022.
    • This records an increase from the previous number of 6,692,474 Unit for Dec 2021.
    • Pakistan Number of Registered Vehicles data is updated yearly, averaging 2,739,117 Unit from Dec 1990 to 2022, with 33 observations.
    • The data reached an all-time high of 7,020,803 Unit in 2022 and a record low of 1,411,226 Unit in 1990.
    • Pakistan Number of Registered Vehicles data remains active status in CEIC and is reported by CEIC Data.
    • The data is categorized under World Trend Plus’s Global Economic Monitor – Table: No of Registered Vehicles: Annual.

    CEIC shifts year-end for annual No of Registered Vehicles. No of Registered Vehicles is calculated by subtracting No of Registered Two Wheels Motorcycles and Three Wheels Motorcycles from Total No of Registered Vehicles. The Pakistan Bureau of Statistics provides Total No of Registered Vehicles, No of Registered Two Wheels Motorcycles and Three Wheels Motorcycles. Total No of Registered Vehicles, No of Registered Two Wheels Motorcycles and Three Wheels Motorcycles are reported in annual frequency, ending in June of each year.

  20. Unemployment rate in Pakistan 2023

    • statista.com
    Updated Jan 31, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Unemployment rate in Pakistan 2023 [Dataset]. https://www.statista.com/statistics/383735/unemployment-rate-in-pakistan/
    Explore at:
    Dataset updated
    Jan 31, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1999 - 2023
    Area covered
    Pakistan
    Description

    In 2023, the unemployment rate in Pakistan was at approximately 5.41 percent, a slight decrease from 5.49 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.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2025). Largest cities in Pakistan 2023 [Dataset]. https://www.statista.com/statistics/421370/largest-cities-in-pakistan/
Organization logo

Largest cities in Pakistan 2023

Explore at:
Dataset updated
Apr 29, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Pakistan
Description

This statistic shows the biggest cities in Pakistan as of 2023. In 2023, approximately 18.87 million people lived in Karāchi, making it the biggest city in Pakistan.

Search
Clear search
Close search
Google apps
Main menu