Actual value and historical data chart for Pakistan Rural Population Percent Of Total Population

The share of urban population in Pakistan stood at ***** percent in 2023. In a steady upward trend, the share rose by ***** percentage points from 1960.

Description This dataset contains demographic information from the Pakistan Population Census conducted in 2017. It provides detailed population data at various administrative levels within Pakistan, including provinces, divisions, districts, and sub-divisions. The dataset also includes information on urban and rural populations, gender distribution, transgender individuals, sex ratios, population figures from the 1998 census, and annual growth rates.

Features Province: The administrative provinces or regions of Pakistan where the census data was collected.

Division: The divisions within each province. Divisions are the second level of administrative divisions in Pakistan.

District: Districts within each division, representing larger administrative units.

Sub-Division: Sub-divisions or tehsils within each district, providing more localized data.

Area: The land area (in square kilometers) of each sub-division.

Urban Population 2017: The population of urban areas within each sub-division for the year 2017.

Rural Population 2017: The population of rural areas within each sub-division for the year 2017.

Male Population 2017: The male population within each sub-division for the year 2017.

Female Population 2017: The female population within each sub-division for the year 2017.

Transgender Population 2017: The population of transgender individuals within each sub-division for the year 2017.

Sex Ratio 2017: The sex ratio, calculated as the number of females per 1000 males, within each sub-division for the year 2017.

Population in 1998: The total population of each sub-division as recorded in the 1998 census.

Annual Growth Rate: The annual growth rate of the population in each sub-division, calculated as the percentage increase from 1998 to 2017.

Data Source The data in this dataset was collected from official Pakistan Population Census reports and may include data from various government sources. It is essential to provide proper attribution and reference the original sources when using this dataset for analysis or research.

Data Usage Researchers and analysts can use this dataset to explore demographic trends, population growth, urbanization rates, gender distribution, and more within Pakistan at different administrative levels. Ensure compliance with ethical and legal guidelines when using this data for research or public sharing.

Please note that this description is a template, and you should adapt it based on the actual data sources and specific details of your dataset when creating it for Kaggle or any other platform.

The share of urban population in Pakistan amounted to 38.04 percent in 2023. In a steady upward trend, the share rose by 15.94 percentage points from 1960.

Explore the nuanced evolution of Pakistan's population through this comprehensive dataset. Covering annual demographics from 1951 to 2021, it delineates the urban-rural divide and gender-specific population trends. While census data anchors the counts for pivotal years like 1951, 1961, 1972, 1981, and 1998, estimated figures bridge the gaps for 1991-1997 and 1999-2015. Unravel the societal fabric with insights into the distribution shifts and gender demographics, derived from Ministry of Planning, Development, and Special Initiatives records. Ideal for examining historical patterns and projecting future trends in Pakistan's populace.

Dataset Description This dataset consists of annual position of population of Pakistan. This data is bifurcated on the basis of urban/rural and male/female population. Data is on calendar year basis.

Note: 1. Data for 1951, 1961, 1972, 1981 and 1998 is based on Census. 2. Estimated figures for period 1991-1997 and 1999-2015. 3. Population distribution of urban and rural is not available for 1951,1961, 1991-1997 and 1999-2015. Data Source Ministry of Planning, Development and Special Initiatives Data Frequency Occasionally Annual Available Since 1951 Available Upto 2021

Pakistan PK: Rural Population data was reported at 125,219,401.000 Person in 2017. This records an increase from the previous number of 123,198,129.000 Person for 2016. Pakistan PK: Rural Population data is updated yearly, averaging 71,910,572.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 125,219,401.000 Person in 2017 and a record low of 34,981,764.000 Person in 1960. Pakistan PK: Rural 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. Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population. Aggregation of urban and rural population may not add up to total population because of different country coverages.; ; World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.; Sum;

Actual value and historical data chart for Pakistan Urban Population Percent Of Total

Pakistan PK: Rural Population Growth data was reported at 1.627 % in 2017. This records a decrease from the previous number of 1.673 % for 2016. Pakistan PK: Rural Population Growth data is updated yearly, averaging 2.224 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 3.024 % in 1983 and a record low of 1.627 % in 2017. Pakistan PK: Rural Population Growth 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. Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population.; ; World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.; Weighted average;

This scatter chart displays urban population (people) against rural population (people) in Pakistan. The data is filtered where the date is 2021. The data is about countries per year.

Abstract

The major aim of the survey is to collect a set of comprehensive statistics on the various dimensions of country’s civilian labour force as a means to pave the way for skill development, planning, employment generation, assessing the role and importance of the informal sector and, sizing up the volume, characteristics and contours of employment. The broad objectives of the survey are as follows: - To collect data on the socio-demographic characteristics of the total population i.e. age, sex, marital status, level of education, current enrolment and migration etc; - To acquire current information on the dimensions of national labour force; i.e. number of persons employed, unemployed, and underemployed or out of labour market; - To gather descriptive facts on the engagement in major occupational trades and the nature of work undertaken by the institutions/organizations; - To profile statistics on employment status of the individuals, i.e. whether they are employers, own account workers, contributing family workers or paid employees (regular/casual); - To classify non-agricultural enterprises employing household member(s) as formal and informal; - To quantify the hours worked at main/subsidiary occupations; - To provide data on wages and mode of payment for paid employees; - To make an assessment of occupational health and safety of employed persons by causes, type of treatment, conditions that caused the accident/injury and time of recovery; and - To collect data on the characteristics of unemployed persons i.e. age, sex, level of education, previous experience if any, occupation, industry, employment status related to previous job, waiting time invested in the quest for work, their availability for work and expectations for future employment.

Geographic coverage

National coverage.

The survey covers all urban and rural areas of the four provinces of Pakistan defined as such by1998 Population Census, excluding Federally Administered Tribal Areas (FATA) and military restricted areas. The population of excluded areas constitutes about 2% of the total population.

All sample enumeration blocks in urban areas and mouzas/dehs/villages in rural areas were enumerated except three sample areas (PSUs), due to law & order and recent flood. However, the number of sample households enumerated (36420) is high (equivalent) 99.9% of the total sample size) to the estimated sample size (36464).

Analysis unit

• Individual aged 10 years and above
• Household

Universe

The universe for Labour Force Survey consistsed of all urban and rural areas of the four provinces of Pakistan defined as such by 1998 Population Census excluding FATA and military restricted areas. The population of excluded areas constitutes about 2% of the total population. The following groups were also excluded non-settled population, persons living in institutions and foreigners.

Kind of data

Sample survey data [ssd]

Frequency of data collection

Quarterly.

Sampling procedure

Sample Design: A stratified two-stage sample design is adopted for the survey.

Sampling Frame: Federal Bureau of Statistics (FBS) has developed its own sampling frame for urban areas. 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 as updated through Economic Census 2003 and the list of villages/mouzas/dehs of 1998 Population Census are taken as sampling frames. Enumeration blocks & villages 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 sub-stratified 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 in the Punjab, Sindh and Khyber Pakhtunkhwa (KP) is considered an independent stratum whereas in Balochistan, each administrative division constitutes a stratum.

• Selection of primary sampling units (PSUs): Enumeration blocks in urban domain and mouzas/dehs/villages in rural are taken as Primary Sampling Units (PSUs). In the urban domain, sample PSUs from each ultimate stratum/sub-stratum are selected with probability proportional to size (PPS) method of sampling scheme. In urban domain, the number of households in an enumeration block as updated through Economic Census 2003 and village population of 1998 Census for rural domain 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, 16 from rural sample PSU are selected with equal probability using systematic sampling technique with a random start.

• Sample Size and Its Allocation: A sample of 36,464 households is considered appropriate to provide reliable estimates of key labour force characteristics at National/Provincial level. The entire sample of households (SSUs) is drawn from 2580 Primary Sampling Units (PSUs) out of which 1204 are urban and 1376 are rural. The overall sample has been distributed evenly over four quarters independently. As urban population is more heterogeneous therefore, a higher proportion of sample size is allocated to urban domain. To produce reliable estimates, a higher proportion of sample is assigned to Khyber Pk and Balochistan in consideration to their smallness. After fixing the sample size at provincial level, further distribution of sample PSUs to different strata in rural and urban domains in each province is made proportionately.

Mode of data collection

Face-to-face [f2f]

Research instrument

Structured questionnaire.

Cleaning operations

Editing and coding is done at headquarter by the subject matter section. Computer edit checks are applied to get even with errors identified at the stage of data entry. The relevant numerical techniques are used to eliminate erroneous data resulting from mistakes made during coding. The survey records are further edited and rectified through a series of computer processing stages.

Response rate

99.9%

Data appraisal

Notwithstanding complete observance of the requisite codes to ensure reliability of data, co-efficient of variations, computed in the backdrop of 5% margin of error exercised for determining sample size, are also given below to affirm the reliability of estimates.

Pakistan PK: Urban Population data was reported at 71,796,554.000 Person in 2017. This records an increase from the previous number of 70,005,347.000 Person for 2016. Pakistan PK: Urban Population data is updated yearly, averaging 31,121,090.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 71,796,554.000 Person in 2017 and a record low of 9,926,529.000 Person in 1960. Pakistan PK: 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. Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. Aggregation of urban and rural population may not add up to total population because of different country coverages.; ; World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.; Sum;

This scatter chart displays urban population (people) against rural land area (km²) in Pakistan. The data is about countries per year.

Pakistan's data extracted from the World Data Bank provides valuable insights into various factors that help deduce the country's Human Development Index (HDI) and economic situation. These indicators shed light on demographic trends, economic performance, and social development. Let's explore some key indicators and their implications for Pakistan's human development and economic status.

Urban population and Rural population: The distribution of the population between urban and rural areas indicates the level of urbanization and the development of infrastructure. A higher urban population might suggest better access to amenities and services in cities, while a larger rural population may indicate the importance of agriculture and the need for rural development.

Population and Population growth (annual %): The total population and its growth rate are crucial in assessing demographic trends and planning for the future. A high population growth rate can put strain on resources and social services, while a stable or declining growth rate allows for better management of development programs.

Gender-related indicators (Population, female, and Population, male (% of total population)): These indicators highlight gender imbalances in the population. A relatively equal distribution of male and female populations is crucial for gender equality and social development.

Birth rate, crude (per 1,000 people), and Mortality rate, infant (per 1,000 live births): Birth and infant mortality rates are essential indicators of healthcare and overall social development. Lower birth and infant mortality rates signify better healthcare facilities and improved living conditions.

GDP (current US$) and Inflation, GDP deflator (annual %): GDP represents the total economic output of a country and reflects its overall economic health. Inflation rates indicate the stability of prices and the impact on consumers' purchasing power.

GNI (current US$) and Gross national expenditure (current US$): GNI measures the total income earned by a country's residents, while gross national expenditure tracks the total spending on goods and services. These indicators help gauge the country's economic performance and fiscal health.

Total reserves (includes gold, current US$): Total reserves provide insight into a country's ability to meet its financial obligations and handle external economic shocks.

Services, value-added (current US$), Merchandise exports, and Merchandise imports (current US$): These indicators reflect the performance of the services and trade sectors, indicating the extent of economic diversification and international trade.

Military expenditure (current USD): Military expenditure is an essential factor in understanding a country's defense priorities and allocation of resources.

Adjusted savings: education expenditure (current US$) and Food production index (2014-2016 = 100): Investment in education is crucial for human development, while the food production index indicates a country's ability to meet its food needs and food security.

By analyzing these indicators collectively, policymakers, economists, and development experts can assess Pakistan's progress in human development and economic growth. Addressing challenges in healthcare, education, gender equality, and economic diversification can contribute to improving the Human Development Index and promoting sustainable economic development in Pakistan.

This dataset is about countries per year in Pakistan. It has 64 rows. It features 4 columns: country, urban land area, and rural population.

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.

This dataset captures urbanization trends across various provinces of Pakistan, derived from national population surveys. It includes yearly or decadal population statistics for each province, segmented to reflect rural-to-urban migration and demographic shifts. 📅 Time Span 1981 – 2025 (including historical and projected population figures)

Pakistan PK: Rural Land Area data was reported at 751,709.500 sq km in 2010. This stayed constant from the previous number of 751,709.500 sq km for 2000. Pakistan PK: Rural Land Area data is updated yearly, averaging 751,709.500 sq km from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 751,709.500 sq km in 2010 and a record low of 751,709.500 sq km in 2010. Pakistan PK: Rural Land Area 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: Land Use, Protected Areas and National Wealth. Rural land area in square kilometers, derived from urban extent grids which distinguish urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights. Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Sum;

Description: This dataset presents comprehensive employment and demographic statistics for various districts across Pakistan, with a focus on gender-specific and regional insights. The dataset covers a range of indicators related to the labor market, population, and literacy rates, offering valuable insights into the socio-economic landscape of the country.

Columns: - Province: The administrative division within Pakistan. - Division: Subdivisions within provinces. - District: The specific geographic districts within divisions. - Indicator: This column captures a diverse set of socio-economic indicators, including but not limited to: - Total Population: The total population of the district. - Employment Rate: The proportion of the working-age population currently employed. - Labor Force: The number of individuals actively participating in the labor force. - Working Age Population: The count of individuals within the working-age bracket. - Literacy Rate: The percentage of the population with basic literacy skills. - Gender-specific Employment Data: Employment data for both male and female populations, including employment rates, labor force participation, and more. - Area Type: Distinguishes between urban and rural areas within districts. - Total: Represents the total value of the corresponding indicator, typically combining both male and female data. - Male: Provides gender-specific data for male individuals. - Female: Provides gender-specific data for female individuals.

Significance of the "Indicator" Column: The "Indicator" column serves as the key to understanding various socio-economic aspects of each district in Pakistan. It offers a comprehensive view of the employment landscape, population dynamics, and literacy rates. By analyzing different indicators, researchers and data enthusiasts can gain insights into: - The distribution of employment opportunities across regions and gender. - The educational attainment of the population. - Labor force participation and unemployment trends. - Demographic variations within districts.

This dataset empowers analysts to explore the nuances of employment and demographic patterns, facilitating evidence-based research and informed policy decisions. Whether you're interested in gender-specific employment, literacy rates, or overall labor market dynamics, this dataset provides a valuable resource for in-depth investigations and data-driven insights into Pakistan's diverse socio-economic landscape.

Abstract

The Pakistan Integrated Household Survey (PIHS) was conducted jointly by the Federal Bureau of Statistics (FBS), Government of Pakistan, and the World Bank. The survey was part of the Living Standards Measurement Study (LSMS) household surveys that have been conducted in a number of developing countries with the assistance of the World Bank. The purpose of these surveys is to provide policy makers and researchers with individual, household, and community level data needed to analyze the impact of policy initiatives on living standards of households.

The Pakistan Integrated Household Survey was carried out in 1991. This nationwide survey gathered individual and household level data using a multi-purpose household questionnaire. Topics covered included housing conditions, education, health, employment characteristics, selfemployment activities, consumption, migration, fertility, credit and savings, and household energy consumption. Community level and price data were also collected during the course of the survey.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Communities

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the PIHS was drawn using a multi-stage stratified sampling procedure from the Master Sample Frame developed by FBS based on the 1981 Population Census.

SAMPLE FRAME:

This sample frame covers all four provinces (Punjab, Sindh, NWFP, and Balochistan) and both urban and rural areas. Excluded, however, are the Federally Administered Tribal Areas, military restricted areas, the districts of Kohistan, Chitral and Malakand and protected areas of NWFP. According to the FBS, the population of the excluded areas amounts to about 4 percent of the total population of Pakistan. Also excluded are households which depend entirely on charity for their living.

The sample frame consists of three main domains: (a) the self-representing cities; (b) other urban areas; and (c) rural areas. These domains are further split up into a number of smaller strata based on the system used by the Government to divide the country into administrative units. The four provinces of Pakistan mentioned above are divided into 20 divisions altogether; each of these divisions in turn is then further split into several districts. The system used to divide the sample frame into the three domains and the various strata is as follows: (a) Self-representing cities: All cities with a population of 500,000 or more are classified as self-representing cities. These include Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Hyderabad and Peshawar. In addition to these cities, Islamabad and Quetta are also included in this group as a result of being the national and provincial capitals respectively. Each self-representing city is considered as a separate stratum, and is further sub-stratified into low, medium, and high income groups on the basis of information collected at the time of demarcation or updating of the urban area sample frame. (b) Other urban areas: All settlements with a population of 5,000 or more at the time of the 1981 Population Census are included in this group (excluding the self-representing cities mentioned above). Urban areas in each division of the four provinces are considered to be separate strata. (c) Rural areas: Villages and communities with population less than 5,000 (at the time of the Census) are classified as rural areas. Settlements within each district of the country are considered to be separate strata with the exception of Balochistan province where, as a result of the relatively sparse population of the districts, each division instead is taken to be a stratum.

Main strata of the Master Sample frame

Domain / Punjab / Sindh / NWFP / Balochistan / PAKISTAN Self-representing cities / 6 / 2 / 1 / 1 / 10 Other urban areas / 8 / 3 / 5 / 4 / 20 Rural areas / 30 / 14 / 10 / 4 / 58 Total 44 / 19 / 16 / 9 / 88

As the above table shows, the sample frame consists of 88 strata altogether. Households in each stratum of the sample frame are exclusively and exhaustively divided into PSUs. In urban areas, each city or town is divided into a number of enumeration blocks with welldefined boundaries and maps. Each enumeration block consists of about 200-250 households, and is taken to be a separate PSU. The list of enumeration blocks is updated every five years or so, with the list used for the PIHS having been modified on the basis of the Census of Establishments conducted in 1988. In rural areas, demarcation of PSUs has been done on the basis of the list of villages/mouzas/dehs published by the Population Census Organization based on the 1981 Census. Each of these villages/mouzas/dehs is taken to be a separate PSU. Altogether, the sample frame consists of approximately 18,000 urban and 43,000 rural PSUs.

SAMPLE SELECTION:

The PIHS sample comprised 4,800 households drawn from 300 PSUs throughout the country. Sample PSUs were divided equally between urban and rural areas, with at least two PSUs selected from each of the strata. Selection of PSUs from within each stratum was carried out using the probability proportional to estimated size method. In urban areas, estimates of the size of PSUs were based on the household count as found during the 1988 Census of Establishments. In rural areas, these estimates were based on the population count during the 1981 Census.

Once sample PSUs had been identified, a listing of all households residing in the PSU was made in all those PSUs where such a listing exercise had not been undertaken recently. Using systematic sampling with a random start, a short-list of 24 households was prepared for each PSU. Sixteen households from this list were selected to be interviewed from the PSU; every third household on the list was designated as a replacement household to be interviewed only if it was not possible to interview either of the two households immediately preceding it on the list.

As a result of replacing households that could not be interviewed because of non-responses, temporary absence, and other such reasons, the actual number of households interviewed during the survey - 4,794 - was very close to the planned sample size of 4,800 households. Moreover, following a pre-determined procedure for replacing households had the added advantage of minimizing any biases that may otherwise have arisen had field teams been allowed more discretion in choosing substitute households.

SAMPLE DESIGN EFFECTS:

The three-stage stratified sampling procedure outlined above has several advantages from the point of view of survey organization and implementation. Using this procedure ensures that all regions or strata deemed important are represented in the sample drawn for the survey. Picking clusters of households or PSUs in the various strata rather than directly drawing households randomly from throughout the country greatly reduces travel time and cost. Finally, selecting a fixed number of households in each PSU makes it easier to distribute the workload evenly amongst field teams. However, in using this procedure to select the sample for the survey, two important matters need to be given consideration: (a) sampling weights or raising factors have to be first calculated to get national estimates from the survey data; and (b) the standard errors for estimates obtained from the data need to be adjusted to take account for the use of this procedure.

Mode of data collection

Face-to-face [f2f]

Research instrument

The PIHS used three questionnaires: a household questionnaire, a community questionnaire, and a price questionnaire.

HOUSEHOLD QUESTIONNAIRE:

The PIHS questionnaire comprised 17 sections, each of which covered a separate aspect of household activity. The various sections of the household questionnaire were as follows: 1. HOUSEHOLD INFORMATION 2. HOUSING 3. EDUCATION 4. HEALTH 5. WAGE EMPLOYMENT 6. FAMILY LABOR 7. ENERGY 8. MIGRATION 9. FARMING AND LIVESTOCK 10. NON-FARM ENTERPRISE ACTIVITIES 11. NON-FOOD EXPENDITURES AND INVENTORY OF DURABLE GOODS 12. FOOD EXPENSES AND HOME PRODUCTION 13. MARRIAGE AND MATERNITY HISTORY 14. ANTHROPOMETRICS 15. CREDIT AND SAVINGS 16. TRANSFERS AND REMITTANCES 17. OTHER INCOME

The household questionnaire was designed to be administered in two visits to each sample household. Apart from avoiding the problem of interviewing household members in one long stretch, scheduling two visits also allowed the teams to improve the quality of the data collected.

During the first visit to the household (Round 1), the enumerators covered sections 1 to 8, and fixed a date with the designated respondents of the household for the second visit. During the second visit (Round 2), which was normally held two weeks after the first visit, the enumerators covered the remaining portion of the questionnaire and resolved any omissions or inconsistencies that were detected during data entry of information from the first part of the survey.

Since many of the sections of the questionnaire pertained specifically to female members of the household, female interviewers were included in conducting the survey. The household questionnaire was split into two parts (Male and Female). Sections such as SECTION 3: EDUCATION, which solicited information on all individual members of the household (male as well as female) were included in both parts of the questionnaire. Other sections such as SECTION 2: HOUSING and SECTION 12: FOOD EXPENSES AND HOME PRODUCTION , which collected data at the aggregate household level, were included in either the male questionnaire or the female questionnaire, depending upon which member of the household was more likely

The dataset contains Decade and State wise Urban, Rural, Total Population and Decadal Growth Rate

Note: 1. The Population figures exclude population of areas under unlawful occupation of Pakistan and China, where Census could not be taken. 2. In Arunachal Pradesh, the census was conducted for the first time in 1961. 3. Population data of Assam include Union Territory of Mizoram, which was carved out of Assam after the 1971. 4. The 1981 Census could not be held in Assam. Total Population for 1981 has been worked out by Interpolation. 5. The 1991 Census could not be held in Jammu & Kashmir. Total Population for 1991 has been worked out by Interpolation. 6. India and Manipur figures include estimated Population for those of the three sub-divisions viz., Mao Maram,Paomata and Purul of Senapati district of Manipur as census result of 2001 in these three sub-divisions were cancelled due to technical and administrative reasons