28 datasets found
  1. a

    Asian Population Change 2010-2020 Wichita / Sedgwick County

    • ict-opendata-cityofwichita.hub.arcgis.com
    • data-cityofwichita.hub.arcgis.com
    Updated Mar 17, 2022
    + more versions
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    City of Wichita GIS (2022). Asian Population Change 2010-2020 Wichita / Sedgwick County [Dataset]. https://ict-opendata-cityofwichita.hub.arcgis.com/maps/c247c80993c94eea8c46f1fcefd01b7d
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    Dataset updated
    Mar 17, 2022
    Dataset authored and provided by
    City of Wichita GIS
    Area covered
    Description

    The US Census Bureau defines Asian as "A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. This includes people who reported detailed Asian responses such as: Indian, Bangladeshi, Bhutanese, Burmese, Cambodian, Chinese, Filipino, Hmong, Indonesian, Japanese, Korean, Laotian, Malaysian, Nepalese, Pakistani, Sri Lankan, Taiwanese, Thai, Vietnamese, Other Asian specified, Other Asian not specified.". 2020 Census block groups for the Wichita / Sedgwick County area, clipped to the county line. Features were extracted from the 2020 State of Kansas Census Block Group shapefile provided by the State of Kansas GIS Data Access and Support Center (https://www.kansasgis.org/index.cfm).Change in Population and Housing for the Sedgwick County area from 2010 - 2020 based upon US Census. Census Blocks from 2010 were spatially joined to Census Block Groups from 2020 to compare the population and housing figures. This is not a product of the US Census Bureau and is only available through City of Wichita GIS. Please refer to Census Block Groups for 2010 and 2020 for verification of all data Standard block groups are clusters of blocks within the same census tract that have the same first digit of their 4-character census block number. For example, blocks 3001, 3002, 3003… 3999 in census tract 1210.02 belong to Block Group 3. Due to boundary and feature changes that occur throughout the decade, current block groups do not always maintain these same block number to block group relationships. For example, block 3001 might move due to a change in the census tract boundary. Even if the block is no longer in block group 3, the block number (3001) will not change. However, the identification string (GEOID20) for that block, identifying block group 3, would remain the same in the attribute information in the TIGER/Line Shapefiles because block identification strings are always built using the decennial geographic codes.Block groups delineated for the 2020 Census generally contain between 600 and 3,000 people. Local participants delineated most block groups as part of the Census Bureau's Participant Statistical Areas Program (PSAP). The Census Bureau delineated block groups only where a local or tribal government declined to participate or where the Census Bureau could not identify a potential local participant.A block group usually covers a contiguous area. Each census tract contains at least one block group and block groups are uniquely numbered within census tract. Within the standard census geographic hierarchy, block groups never cross county or census tract boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian, Alaska Native, and Native Hawaiian areas.Block groups have a valid range of 0 through 9. Block groups beginning with a zero generally are in coastal and Great Lakes water and territorial seas. Rather than extending a census tract boundary into the Great Lakes or out to the 3-mile territorial sea limit, the Census Bureau delineated some census tract boundaries along the shoreline or just offshore.

  2. T

    Pakistan Population

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +17more
    csv, excel, json, xml
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    TRADING ECONOMICS, Pakistan Population [Dataset]. https://tradingeconomics.com/pakistan/population
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    json, csv, xml, excelAvailable download formats
    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
    Dec 31, 1960 - Dec 31, 2023
    Area covered
    Pakistan
    Description

    The total population in Pakistan was estimated at 240.5 million people in 2023, according to the latest census figures and projections from Trading Economics. This dataset provides - Pakistan Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  3. P

    Pakistan Household Income per Capita

    • ceicdata.com
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    Pakistan Household Income per Capita [Dataset]. https://www.ceicdata.com/en/indicator/pakistan/annual-household-income-per-capita
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    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Jun 1, 2005 - Jun 1, 2019
    Area covered
    Pakistan
    Description

    Key information about Pakistan Household Income per Capita

    • Pakistan Annual Household Income per Capita reached 587.069 USD in Jun 2019, compared with the previous value of 650.644 USD in Jun 2016.
    • Pakistan Annual Household Income per Capita data is updated yearly, available from Jun 2005 to Jun 2019, with an averaged value of 508.977 USD.
    • The data reached an all-time high of 650.644 USD in Jun 2016 and a record low of 290.069 USD in Jun 2005.

    CEIC calculates Annual Household Income per Capita from annual Monthly Average Household Income multiplied by 12 and annual Average Household Size and converts it into USD. The Pakistan Bureau of Statistics provides Average Household Income in local currency and Average Household Size. The State Bank of Pakistan average market exchange rate is used for currency conversions. Household Income per Capita is in annual frequency, ending in June of each year.

  4. i

    Demographic and Health Survey 2006-2007 - Pakistan

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Jul 6, 2017
    + more versions
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    National Institute of Population Studies (2017). Demographic and Health Survey 2006-2007 - Pakistan [Dataset]. https://catalog.ihsn.org/catalog/2576
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    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

  5. M

    Pakistan Population Growth Rate 1950-2025

    • macrotrends.net
    csv
    Updated Feb 28, 2025
    + more versions
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    MACROTRENDS (2025). Pakistan Population Growth Rate 1950-2025 [Dataset]. https://www.macrotrends.net/global-metrics/countries/PAK/pakistan/population-growth-rate
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    csvAvailable download formats
    Dataset updated
    Feb 28, 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

    Area covered
    Pakistan
    Description

    Chart and table of Pakistan population from 1950 to 2025. United Nations projections are also included through the year 2100.

  6. Countries with the most Facebook users 2024

    • statista.com
    • wwwexpressvpn.online
    Updated May 22, 2024
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    Statista (2024). Countries with the most Facebook users 2024 [Dataset]. https://www.statista.com/statistics/268136/top-15-countries-based-on-number-of-facebook-users/
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    Dataset updated
    May 22, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2024
    Area covered
    Worldwide
    Description

    Which county has the most Facebook users? There are more than 378 million Facebook users in India alone, making it the leading country in terms of Facebook audience size. To put this into context, if India’s Facebook audience were a country then it would be ranked third in terms of largest population worldwide. Apart from India, there are several other markets with more than 100 million Facebook users each: The United States, Indonesia, and Brazil with 193.8 million, 119.05 million, and 112.55 million Facebook users respectively. Facebook – the most used social media Meta, the company that was previously called Facebook, owns four of the most popular social media platforms worldwide, WhatsApp, Facebook Messenger, Facebook, and Instagram. As of the third quarter of 2021, there were around 3,5 billion cumulative monthly users of the company’s products worldwide. With around 2.9 billion monthly active users, Facebook is the most popular social media worldwide. With an audience of this scale, it is no surprise that the vast majority of Facebook’s revenue is generated through advertising. Facebook usage by device As of July 2021, it was found that 98.5 percent of active users accessed their Facebook account from mobile devices. In fact, almost 81.8 percent of Facebook audiences worldwide access the platform only via mobile phone. Facebook is not only available through mobile browser as the company has published several mobile apps for users to access their products and services. As of the third quarter 2021, the four core Meta products were leading the ranking of most downloaded mobile apps worldwide, with WhatsApp amassing approximately six billion downloads.

  7. Number of millionaires Pakistan 2006-2026

    • statista.com
    Updated Feb 13, 2023
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    Statista (2023). Number of millionaires Pakistan 2006-2026 [Dataset]. https://www.statista.com/statistics/785036/pakistan-number-of-millionaires/
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    Dataset updated
    Feb 13, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Pakistan
    Description

    In 2016, there were approximately 19.2 thousand millionaires in Pakistan. The number of individuals owning one million U.S. dollars or more in Pakistan is expected to rise to 26.9 thousand by 2026.

    HNWI forecast in Pakistan

    Individuals with investible assets of at least one million U.S. dollars in current exchange rate terms are considered high net worth. The number of high-net-worth individuals in Pakistan is expected to rise overall between 2022 and 2028, settling at just under eight thousand individuals.

    Countries with the highest millionaire rate

    In 2021, Switzerland had the highest rate of millionaires in the world, with 16.4 percent of the adult population owning assets worth more than one million U.S. dollars. Luxembourg came in second, with 16.2 percent of the population being millionaires, and Iceland came in third. Furthermore, over 22 million people in the United States were among the world's top one percent of ultra-high net-worth individuals in 2021. China came second, with over five million top one percent wealth holders worldwide.

  8. Socio-Economic Assessment of Pakistani Refugees in Afghanistan's Khost and...

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated May 21, 2021
    + more versions
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    United Nations High Commissioner for Refugees (UNHCR) (2021). Socio-Economic Assessment of Pakistani Refugees in Afghanistan's Khost and Paktika Provinces 2017 - Afghanistan [Dataset]. https://microdata.worldbank.org/index.php/catalog/3997
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    Dataset updated
    May 21, 2021
    Dataset provided by
    United Nations High Commissioner for Refugeeshttp://www.unhcr.org/
    Authors
    United Nations High Commissioner for Refugees (UNHCR)
    Time period covered
    2017
    Area covered
    Afghanistan
    Description

    Abstract

    Afghanistan hosts a protracted population of Pakistani refugees, who fled North Waziristan Agency in 2014 as a result of a joint military offensive by Pakistani government forces against non-state armed groups. As of May 2017, UNHCR has biometrically registered over 50,000 refugees in Khost province and 36,000 refugees in Paktika province, where access remains a challenge. Over 16,000 of these refugees receive shelter and essential services in the Gulan camp in Khost province, while most of the others live among the host population in various urban and rural locations.

    To better understand the needs of the refugees and the host communities, UNHCR and WFP agreed to conduct a joint assessment of Pakistani refugees in Khost and Paktika. The data collection commenced in May 2017 and covered 2,638 refugee households (2,198 in Khost and 440 in Paktika).

    Geographic coverage

    Areas hosting Pakistani refugees in Afghanistan's Khost and Paktika provinces. This includes Gulan refugee camp as well as various non-camp sites, spread across 10 districts.

    Analysis unit

    Household and individual

    Universe

    All Pakistani refugees living in Afghanistan's Khost and Paktika provinces.

    UNHCR PPG: -

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The survey's objective was to deliver representative data of all Pakistani refugees living in Afghanistan's Khost and Paktika provinces. The total population of Pakistani refugees in these provinces at the time of the survey was estimated at around 18,000 households.

    For this survey a stratified, two-stage (i.e. clustered) sample design was applied. The 10 refugee-hosting districts of Khost and Paktika were considered sampling strata, but within these the refugee-dense locations of Gulan camp and Lakan (in Maton district) were considered separate strata, resulting in 12 sampling strata overall. Within each of these strata, first a selection of villages was drawn with probability-proportional-to-size, then second a selection of households was drawn from UNHCR's registration database.

    The total sample size was 2,638 refugee households.

    NB: The original data collection also included a small number of households from the neighboring host communities; however, these observations were dropped from the public-release version of the dataset.

    Sampling deviation

    None.

    Mode of data collection

    Face-to-face [f2f]

    Cleaning operations

    The dataset presented here has undergone light checking, cleaning, and restructuring (data may still contain errors) as well as anonymization (includes removal of direct identifiers and sensitive variables and grouping values of select variables). Moreover, households interviewed from host communities were removed.

    Response rate

    Information unavailable.

  9. Enterprise Survey 2007 - Pakistan

    • microdata.worldbank.org
    Updated Sep 26, 2013
    + more versions
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    Enterprise Survey 2007 - Pakistan [Dataset]. https://microdata.worldbank.org/index.php/catalog/659
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    Dataset updated
    Sep 26, 2013
    Dataset authored and provided by
    World Bankhttp://worldbank.org/
    Time period covered
    2006 - 2007
    Area covered
    Pakistan
    Description

    Abstract

    This research was conducted in Pakistan between January 2006 and December 2007. Data from 935 manufacturing and service sector registered establishments was analyzed.

    The objective of the survey is to obtain feedback from enterprises in client countries on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

    The survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. The questionnaire also assesses the survey respondents' opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.

    Geographic coverage

    National

    Analysis unit

    The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Establishments were selected using stratified random sampling design. The survey covered manufacturing and services sectors and generated a large enough sample size for selected industries to conduct statistically robust analyses. With level of precision at a minimum 7.5 percent for 90 percent confidence intervals about estimates of population proportions and mean of log sales at the national, provincial and industry level.

    The sampling frame was drawn from the 2005 Economic Census of Pakistan, conducted by Pakistan's Federal Bureau of Statistics (FBS). As the target population was formal, urban manufacturing and services establishments with more than 5 full-time employees, the census identified 583,329 manufacturing firms and 1,566,722 establishments in Wholesale/Retail trade & Restaurants.

    In accordance with the size and make up of the economy, the manufacturing sector was stratified into five 2-digit Pakistan Standard Industrial Classification (PSIC) sectors: (i) food processing, (ii) textiles, apparel & leather, (iii) chemicals and products, (iv) metal and electric machinery, and (v) sports goods and handicrafts with a residual stratum based on the 14 largest cities from the four provinces of the country. Services establishments engaged in wholesale & retail trade, hotels & restaurants were grouped to constitute an independent stratum for each provincial capital.

    Within each industry, the total sample size was distributed to the provincial/city sub-strata based on proportional allocation in order to be representative of the nation, the industry groups and the urban areas of each of the four provinces. Given the domination of smaller firms in sample frame, a sampling approach which oversampled larger firms was employed to ensure a sufficient number of large enterprise which otherwise might be underrepresented.

    The specific steps involved: (i) extracting from the frame and dividing into activity/industry groups with selection made in proportion to each group's contribution to total industrial employment, (ii) allocating the establishments selected in to each industry group across the provinces/cities selected using a proportional allocation, and (iii) selecting the establishments for each province/city sub-stratum with a probability of selection which is inversely proportional to size (i.e. larger firms will be selected with a higher probability). Due to the oversampling of larger firms, weights were computed so that inferences about the population could be extrapolated from the sample.

    The Pakistan Enterprise Survey 2007 sample was also designed to include up to 600 firms from the original sample of Pakistan ICS 2002. Out of a total of 846 establishments surveyed in 2002 (panel firms with location and other identifiers). The remaining firms were kept as potential replacements in case of non-response by an establishment of similar characteristics in the original panel sample. In the end, 402 firms were interviewed out of 795 firms contacted.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The current survey instruments are available: - Pakistan 2007 Manufacturing Sector Questionnaire; - Pakistan 2007 Services Sector Questionnaire.

    The survey is fielded via two instruments in order to not ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm.

    The survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

    Response rate

    The field work involved a sample of almost 2700 firms with more than 2300 firms contacted in order to complete the survey of 1337 firms - 57 percent success rate. Of the 1000 non-successful contacts, about 45 percent were not located due to poor contact information and 25 percent refused to participate. Of the rest, 20 percent were closed and 10 percent were either non-responsive or produced non-usable data. For the non-panel sample, the response rate was slightly higher at 60 percent, but of the 612 nonresponding firms, 55 percent were not found due to insufficient contact information, 21 percent refused participation, 11 percent were non-usable and 13 percent were confirmed as closed.

  10. Countries with the largest Muslim population in 2022

    • statista.com
    Updated Jan 23, 2025
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    Statista (2025). Countries with the largest Muslim population in 2022 [Dataset]. https://www.statista.com/statistics/374661/countries-with-the-largest-muslim-population/
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    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    World
    Description

    In 2022, Indonesia has the largest population of Muslims worldwide with around 241.5 million. This was followed with around 225.6 million Muslims in Pakistan and 211.16 million Muslims in India.

  11. Pakistan - Demographics, Health and Infant Mortality Rates

    • data.unicef.org
    Updated Sep 9, 2015
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    UNICEF (2015). Pakistan - Demographics, Health and Infant Mortality Rates [Dataset]. https://data.unicef.org/country/pak/
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    Dataset updated
    Sep 9, 2015
    Dataset authored and provided by
    UNICEFhttp://www.unicef.org/
    Description

    UNICEF's country profile for Pakistan, including under-five mortality rates, child health, education and sanitation data.

  12. Share of generation Z population age groups APAC 2023, by country and gender...

    • statista.com
    Updated Nov 15, 2024
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    Statista (2024). Share of generation Z population age groups APAC 2023, by country and gender [Dataset]. https://www.statista.com/statistics/1323656/apac-share-of-gen-z-population-age-groups-by-country-and-gender/
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    Dataset updated
    Nov 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Asia–Pacific
    Description

    In the Pakistan, the male population aged between 20 to 24 amounted to about 9.74 percent of the total male population in 2023. In contrast, the male population aged between 20 to 24 in Hong Kong amounted to about 4.5 percent of the total male population in 2021. The female Gen Z population in the Asia-Pacific region took up a smaller share among the female population overall compared to their male counterparts.

  13. Distribution of gross domestic product (GDP) across economic sectors...

    • statista.com
    Updated Oct 16, 2024
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    Statista (2024). Distribution of gross domestic product (GDP) across economic sectors Pakistan 2023 [Dataset]. https://www.statista.com/statistics/383256/pakistan-gdp-distribution-across-economic-sectors/
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    Dataset updated
    Oct 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Pakistan
    Description

    In 2023, agriculture contributed around 23.37 percent to the GDP of Pakistan, 20.76 percent came from the industry, and over half of the economy’s contribution to GDP came from the services sector. Divisions of the economy There are three main sectors of economy: The primary sector encompassed agriculture, fishing and mining. The secondary sector is the manufacturing sector, also known as the industry sector; and last but not least, the tertiary sector, alias the services sector, which includes services and intangible goods, like tourism, financial services, or telecommunications. Today, most developed countries have a well-established services sector that contributes the lion’s share to their GDP. On the other hand, economies that still need support and are still developing typically rely on agriculture to fuel their economy. If they transition to a developed nation, it is usually because their economy is now able to focus on services as an economic driver. Pakistan’s economic driver Although Pakistan is not considered a fully developed nation yet, over half of its annual GDP is now generated by the services sector. However, the primary sector plays an important role for the country: It is still responsible for almost a quarter of GDP contribution, and it employs almost half of Pakistan’s workforce. Pakistan is rich in arable land, which explains why the majority of the Pakistani population lives in rural areas, producing and selling sugarcane, wheat, cotton, and rice, which are also exported to other countries.

  14. n

    Facebook users in Pakistan

    • napoleoncat.com
    png
    Updated Jan 15, 2024
    + more versions
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    NapoleonCat (2024). Facebook users in Pakistan [Dataset]. https://napoleoncat.com/stats/facebook-users-in-pakistan/2024/01
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    pngAvailable download formats
    Dataset updated
    Jan 15, 2024
    Dataset authored and provided by
    NapoleonCat
    License

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

    Time period covered
    Jan 2024
    Area covered
    Pakistan
    Description

    There were 57 320 000 Facebook users in Pakistan in January 2024, which accounted for 24.7% of its entire population. The majority of them were men - 76%. People aged 18 to 24 were the largest user group (23 200 000). The highest difference between men and women occurs within people aged 25 to 34, where men lead by 15 800 000.

  15. s

    Economic inactivity

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Dec 11, 2023
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    Race Disparity Unit (2023). Economic inactivity [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/work-pay-and-benefits/unemployment-and-economic-inactivity/economic-inactivity/latest
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    csv(4 MB), csv(3 MB)Available download formats
    Dataset updated
    Dec 11, 2023
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England, Wales and Scotland
    Description

    In 2022, the highest and lowest rates of economic inactivity were in the combined Pakistani and Bangladeshi (33%) and white 'other’ (15%) ethnic groups.

  16. Pakistan Number of Registered Vehicles

    • ceicdata.com
    Updated Jul 15, 2018
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    CEICdata.com (2018). Pakistan Number of Registered Vehicles [Dataset]. https://www.ceicdata.com/en/indicator/pakistan/number-of-registered-vehicles
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    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.

  17. Pakistan Stores Distributed by Number of Employee

    • aftership.com
    Updated Jan 16, 2024
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    AfterShip (2024). Pakistan Stores Distributed by Number of Employee [Dataset]. https://www.aftership.com/ecommerce/statistics/regions/pk
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    Dataset updated
    Jan 16, 2024
    Dataset authored and provided by
    AfterShiphttps://www.aftership.com/
    License

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

    Area covered
    Pakistan
    Description

    This chart provides a detailed overview of the number of Pakistan online retailers by Number of Employee. Most Pakistan stores' Number of Employee are Less than 10, there are 20.48K stores, which is 94.79% of total. In second place, 271 stores' Number of Employee are 20 to 50, which is 1.25% of total. Meanwhile, 231 stores' Number of Employee are 10 to 20, which is 1.07% of total. This breakdown reveals insights into Pakistan stores distribution, providing a comprehensive picture of the performance and efficient of online retailer.

  18. Number of international students in the U.S. 2023/24, by country of origin

    • statista.com
    Updated Mar 3, 2025
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    Statista (2025). Number of international students in the U.S. 2023/24, by country of origin [Dataset]. https://www.statista.com/statistics/233880/international-students-in-the-us-by-country-of-origin/
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    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the academic year 2023/24, there were 331,602 international students from India studying in the United States. International students The majority of international students studying in the United States are originally from India and China, totaling 331,602 students and 277,398 students respectively in the 2023/24 school year. In 2022/23, there were 467,027 international graduate students , which accounted for over one third of the international students in the country. Typically, engineering and math & computer science programs were among the most common fields of study for these students. The United States is home to many world-renowned schools, most notably, the Ivy League Colleges which provide education that is sought after by both foreign and local students. International students and college Foreign students in the United States pay some of the highest fees in the United States, with an average of 24,914 U.S. dollars. American students attending a college in New England paid an average of 14,900 U.S. dollars for tuition alone and there were about 79,751 international students in Massachusetts . Among high-income families, U.S. students paid an average of 34,700 U.S. dollars for college, whereas the average for all U.S. families reached only 28,026 U.S. dollars. Typically, 40 percent of families paid for college tuition through parent income and savings, while 29 percent relied on grants and scholarships.

  19. Non-British population of the UK 2021, by nationality

    • statista.com
    Updated Dec 19, 2024
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    Statista (2024). Non-British population of the UK 2021, by nationality [Dataset]. https://www.statista.com/statistics/759859/non-british-population-in-united-kingdom-by-nationality/
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    Dataset updated
    Dec 19, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United Kingdom
    Description

    In 2020/21 there were approximately 696,000 Polish nationals living in the United Kingdom, the highest non-British population at this time. Indian and Irish were the joint second-largest nationalities at approximately 370,000 people.

  20. United Kingdom - ethnicity

    • statista.com
    Updated Sep 5, 2024
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    Statista (2024). United Kingdom - ethnicity [Dataset]. https://www.statista.com/statistics/270386/ethnicity-in-the-united-kingdom/
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    Dataset updated
    Sep 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2011
    Area covered
    United Kingdom
    Description

    In 2011, 87.2 percent of the total population of the United Kingdom were white British. A positive net migration in recent years combined with the resultant international relationships following the wide-reaching former British Empire has contributed to an increasingly diverse population.

    Varied ethnic backgrounds

    Black British citizens, with African and/or African-Caribbean ancestry, are the largest ethnic minority population, at three percent of the total population. Indian Britons are one of the largest overseas communities of the Indian diaspora and make up 2.3 percent of the total UK population. Pakistani British citizens, who make up almost two percent of the UK population, have one of the highest levels of home ownership in Britain.

    Racism in the United Kingdom

    Though it has decreased in comparison to the previous century, the UK has seen an increase in racial prejudice during the first decade and a half of this century. Racism and discrimination continues to be part of daily life for Britain’s ethnic minorities, especially in terms of work, housing, and health issues. Moreover, the number of hate crimes motivated by race reported since 2012 has increased, and in 2017/18, there were 3,368 recorded offenses of racially or religiously aggravated assault with injury, almost a thousand more than in 2013/14.

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City of Wichita GIS (2022). Asian Population Change 2010-2020 Wichita / Sedgwick County [Dataset]. https://ict-opendata-cityofwichita.hub.arcgis.com/maps/c247c80993c94eea8c46f1fcefd01b7d

Asian Population Change 2010-2020 Wichita / Sedgwick County

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Dataset updated
Mar 17, 2022
Dataset authored and provided by
City of Wichita GIS
Area covered
Description

The US Census Bureau defines Asian as "A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. This includes people who reported detailed Asian responses such as: Indian, Bangladeshi, Bhutanese, Burmese, Cambodian, Chinese, Filipino, Hmong, Indonesian, Japanese, Korean, Laotian, Malaysian, Nepalese, Pakistani, Sri Lankan, Taiwanese, Thai, Vietnamese, Other Asian specified, Other Asian not specified.". 2020 Census block groups for the Wichita / Sedgwick County area, clipped to the county line. Features were extracted from the 2020 State of Kansas Census Block Group shapefile provided by the State of Kansas GIS Data Access and Support Center (https://www.kansasgis.org/index.cfm).Change in Population and Housing for the Sedgwick County area from 2010 - 2020 based upon US Census. Census Blocks from 2010 were spatially joined to Census Block Groups from 2020 to compare the population and housing figures. This is not a product of the US Census Bureau and is only available through City of Wichita GIS. Please refer to Census Block Groups for 2010 and 2020 for verification of all data Standard block groups are clusters of blocks within the same census tract that have the same first digit of their 4-character census block number. For example, blocks 3001, 3002, 3003… 3999 in census tract 1210.02 belong to Block Group 3. Due to boundary and feature changes that occur throughout the decade, current block groups do not always maintain these same block number to block group relationships. For example, block 3001 might move due to a change in the census tract boundary. Even if the block is no longer in block group 3, the block number (3001) will not change. However, the identification string (GEOID20) for that block, identifying block group 3, would remain the same in the attribute information in the TIGER/Line Shapefiles because block identification strings are always built using the decennial geographic codes.Block groups delineated for the 2020 Census generally contain between 600 and 3,000 people. Local participants delineated most block groups as part of the Census Bureau's Participant Statistical Areas Program (PSAP). The Census Bureau delineated block groups only where a local or tribal government declined to participate or where the Census Bureau could not identify a potential local participant.A block group usually covers a contiguous area. Each census tract contains at least one block group and block groups are uniquely numbered within census tract. Within the standard census geographic hierarchy, block groups never cross county or census tract boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian, Alaska Native, and Native Hawaiian areas.Block groups have a valid range of 0 through 9. Block groups beginning with a zero generally are in coastal and Great Lakes water and territorial seas. Rather than extending a census tract boundary into the Great Lakes or out to the 3-mile territorial sea limit, the Census Bureau delineated some census tract boundaries along the shoreline or just offshore.

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