In 2024, the median household income in the United States was 83,730 U.S. dollars. This reflected an increase from the previous year. Household income The median household income depicts the income of households, including the income of the householder and all other individuals aged 15 years or over living in the household. Income includes wages and salaries, unemployment insurance, disability payments, child support payments received, regular rental receipts, as well as any personal business, investment, or other kinds of income received routinely. The median household income in the United States varied from state to state. In 2024, Massachusetts recorded the highest median household income in the country, at 113,900 U.S. dollars. On the other hand, Mississippi, recorded the lowest, at 55,980 U.S. dollars.Household income is also used to determine the poverty rate in the United States. In 2024, 10.6 percent of the U.S. population was living below the national poverty line. This was the lowest level since 2019. Similarly, the child poverty rate, which represents people under the age of 18 living in poverty, reached a three-decade low of 14.3 percent of the children. The state with the widest gap between the rich and the poor was New York, with a Gini coefficient score of 0.52 in 2024. The Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality, while a score of one indicates complete inequality.

Key information about Russia Household Income per Capita

• Russia Annual Household Income per Capita reached 8,179.992 USD in Dec 2024, compared with the previous value of 7,549.747 USD in Dec 2023.
• Russia Annual Household Income per Capita data is updated yearly, available from Dec 1992 to Dec 2024, with an averaged value of 7,177.112 USD.
• The data reached an all-time high of 9,660.697 USD in Dec 2013 and a record low of 183.584 USD in Dec 1992.
• In the latest reports, Retail Sales of Russia grew 1.800 % YoY in Sep 2025.

CEIC calculates Annual Household Income per Capita from Monthly Average Household Income per Capita multiplied by 12 and converts it into USD. Federal State Statistics Service provides Average Household Income per Capita in local currency. The Bank of Russia average market exchange rate is used for currency conversions.

In 2024, about 44.7 percent of White households in the United States had an annual median income of over 100,000 U.S. dollars. By comparison, only 26.8 percent of Black households were in this income group. Asian Americans, on the other hand, had the highest median income per household that year.

Abstract

The Household Integrated Income and Consumption Survey (HIICS) 2015-16, is designed by merging Household Integrated Economic Survey (HIES) and Family Budget Survey (FBS). The HIES is a large, complex household survey that collects information on a number of different socio-economic dimensions, which has been conducted through PSLM/HIES surveys under PSLM project since 2005-2005. It provides information at national/provincial level with urban/rural breakdown. This survey contains data collected from 24,238 household based on 1605 urban and rural primary sampling units (PSUs). The period of field enumeration of HIES as part of HIICS 2015-2016 was from September 2015 to June 2016.

The Household Integrated Income and Consumption Survey presents household income and consumption expenditure data for the year 2015-2016. The format of the report is almost the same as of the earlier Household Integrated Economic Survey (HIES) conducted over the years 2004-2005, 2005-2006, 2007-2008, 2010-2011, 2011-2012 and 2013-2014.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Universe

The universe for Household Integrated Income and Consumption Survey (HIICS) 2015-16 consists of all urban and rural areas of the four provinces of Pakistan excluding Federally Administered Tribal Areas (FATA) and military restricted areas. The population of excluded areas constitutes about 2% of the total population.

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

B) Stratification Plan: The stratification plan for HIICS survey for urban and rural areas is as follows: - 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 for three provinces namely Khyber Pakhtunkhwa (KP) Punjab, Sindh, and each administrative division for Balochistan is considered as an independent stratum.

C) Selection of Primary Sampling Units (PSUs): Enumeration blocks in both urban and rural domains are taken as Primary Sampling Units (PSUs). Sample PSUs from each ultimate stratum/sub-stratum are selected with probability proportional to size (PPS) method of sampling scheme. In both Urban and Rural domains, the number of households in an enumeration block is considered as measure of size.

D) 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. 16 from both urban and rural sample PSU are selected with equal probability using systematic sampling technique with a random start.

E) Sample Size and its Allocation: Keeping in view the objectives of the survey, the sample size for the four provinces has been fixed at 1668 sample blocks (PSU's) comprising 26688 households (SSU's), which is expected to produce reliable results at provincial level with urban and rural break down.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaire for this survey was especially designed by merging Household Integrated Economic Survey (HIES) and Family Budget Survey (FBS). The structure of the questionnaire is as follows:

• Surevy information
• Household roster
• Employment and income (females and males)
• Education (females and males)
• Housing (females only)

Consumption module: - Household consumption expenditure (females and males) - Tranfers received and paid out (during last one year) (male only) - Buildings and land owned by members of this household (male only) - Financial assets and liabilities, loans and credit (male only) - Agricultural sheet (male only) - Livestock, poultry, fish, forestry, honey bee (male only) - Non-agricultural establishment (male only) - Balance sheet for income and expenditure (male only) - Information and communication technology (females and males)

The graph presents the median monthly salary in the United States from 2000 to 2025. The x-axis represents the years, labeled from '00 to '25*, while the y-axis shows the salary amounts in U.S. dollars per month. Throughout this twenty-five-year period, the median monthly salary consistently increased from $2491.67 in 2000 to $5195.67 in 2025. The data highlights a steady upward trend, with annual salaries rising each year without any declines. Notably, the salary grew by approximately $200 each year from 2000 to 2019, surged to $4265.08 in 2020, and continued to climb each subsequent year, reaching $5023.42 by 2024. This consistent growth reflects economic advancements and potential increases in workforce compensation over the decade. The information is depicted in a line graph format, effectively illustrating the continuous rise in median monthly salaries across the specified years.

Census Tracts:Census tracts are designed to be relatively homogeneous units with respect to population characteristics, economic status, and living conditions. They are used for the presentation of census data and comparison across different census years. The boundaries of census tracts generally follow visible and identifiable features, and they do not cross state or county lines.This feature class is essential for detailed demographic analysis, urban planning, and resource allocation. It is available for public use and can be accessed through platforms like ArcGIS.Population Range: Each census tract generally contains between 1,200 to 8,000 people, with an optimum size of 4,000 people.Data Fields:Tract Code (TRACTCE20): 6-digit code identifying the census tract.State Code (STATEFP20): 2-digit code identifying the state.County Code (COUNTYFP20): 3-digit code identifying the county.ACS Data:The 2022 American Community Survey (ACS) Tract Data provides detailed demographic, social, economic, and housing statistics for small geographic areas, such as census tracts.Detailed Tables: Provide the most granular estimates on all selected topics for City of Salinas.Data Types: The data includes estimates on various topics such as population demographics, economic status, housing characteristics, and social factors.Selected ACS Fields:Median Age (b01002e1)Population (b01003e1)Households (b11001e1)Housing Units (b25001e1)Average Household Size (b25010e1)Households at 200% Federal Poverty Level (c17002e8)Median Household Income (b19013e1)Per Capita Income (b19301e1)Bachelor's Degree or Higher (b99152e2)High School Degree or Higher (b15003e17)Limited English Households (c16002e1)Households (dp04_001e)Vacant Units (dp04_0003e)Renter-Occupied Units (dp04_0047e)

Costa Rica is the country with the highest minimum monthly wage in Latin America. According to the minimum salary established by law as of January 2025, workers in the Central American country enjoy a basic monthly wage of over 726 U.S. dollars, an increase of 2.37 percent compared to the previous year. They also earn over 200 U.S. dollars more than the second place, Uruguay. On the other side of the spectrum is Venezuela, where employees are only guaranteed by law a minimum salary of 130 bolívares or little more than 2.50 dollars per month. Can Latin Americans survive on a minimum wage? Even if most countries in Latin America have instated laws to guarantee citizens a basic income, these minimum standards are often not enough to meet household needs. For instance, it was estimated that almost 25 million people in Mexico lacked basic housing services. Salary levels also vary greatly among Latin American economies. In 2020, the average net monthly salary in Mexico was barely higher than Chile's minimum wage in 2021. What can a minimum wage afford in Latin America? Latin American real wages have generally risen in the past decade. However, consumers in this region still struggle to afford non-basic goods, such as tech products. Recent estimates reveal that, in order to buy an iPhone, Brazilian residents would have to work at least two months to be able to pay for it. A gaming console, on the other hand, could easily cost a Latin American worker several minimum wages.

Abstract

The Ghana Living Standards Survey (GLSS) is a nationwide survey carried out by the Government of Ghana (Ghana Statistical Service) with the support of the World Bank (Social Dimensions of Adjustment Project Unit). The objective of the survey is to provide data to the government for measuring the living standards of the population and the progress made in raising them. The survey data will permit a more effective formulation and implementation of policies designed to improve the welfare of the population.

The GLSS was launched in September 1987 and is currently planned to be undertaken over a five-year period. The five interval ensures that a steady stream of data becomes available to monitor the impact of the Government's Economic Recovery Program, including the Program of Actions to Mitigate the Social Costs of Adjustment (PAMSCAD). GLSS provides data on various aspects of the Ghanaian household economic and social activities and the interactions between these activities. Data are collected at three levels: the individual level, the household level and community level. The household questionnaire was administered to 1525 households over a six month period from september 1987 to march 1988.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Community
• Commodity

Kind of data

Sample survey data [ssd]

Sampling procedure

The methodology that was used reflects the purpose of the survey. To balance the desire for a large, representative sample with the expense of a long, detailed survey instrument, a sample size of 3,200 households was selected. The households were to be chosen in such a manner that each household had an equal probability of being selected. At the same time, the logistics of locating the households and conducting all interviews within a specific time frame required that the households be grouped into "workloads" of 16 households each. A final concern was that all three of the country's ecological zones (coastal, forest and savannah), and each of urban, semi-urban and rural areas (population greater than 5000, 1500 to 5000, and less than 1500, respectively) form the same proportion in the sample as they do in the national population.

To achieve the three objectives simultaneously, a stratified selection process was used. For the 1984 Census, all of Ghana was divided into approximately 13,000 enumeration areas (EAs). From this list it was determined what proportion of the 200 GLSS workloads should be selected from each of the nine zone/urban categories. Two hundred sampling areas were then selected from the enumeration areas in the sub-divided list. For each enumeration area, the probability of being selected was proportional to the number of households contained in that area.

After the 200 sampling areas were selected, households in those areas were enumerated in 1987. Therefore it was possible to take into account changes in the number of households and preserve the self-weighting nature of the sample. The 200 workloads were assigned among the 200 sampling areas with probability equal to the number of households in that area in 1987 divided by the number of households in that area in 1984 and multiplied by the total number of households in 1984 divided by the total number of households in 1987. That is, sampling areas that had greater than average increases in size had a greater than one chance of being selected. Thus, each sampling area was assigned zero, one, two, or even three workloads of sixteen households. The households (sixteen selected and four replacement for each workload) were then chosen randomly from the household list for each sampling area. The resulting list is 3200 households and 800 replacement households in something less than 200 sampling areas (specifically 178 in 1987-88 and 170 in 1988-89). Each group of 16, 32 or 48 households within a sampling area is referred to as a cluster in the GLSS data sets and in this document.

Mode of data collection

Face-to-face [f2f]

Research instrument

• The household survey contains modules (sections) to collect data on household demographic structure, housing conditions, schooling, health, employment, migration, expenditure and income, household non-agricultural businesses, agricultural activities, fertility and contraceptive use, savings and credit, and anthropometric (height and weight) measures.

• The community questionnaire collected data on the population of the community, a list of principal ethnic groups and religions, the length of time the community has existed and whether or not it has grown, principal economic activities, access to a motorable road, electricity, pipe-borne water, restaurant or food stall, post office, bank, daily market and public transport, employment, migration for jobs, existence of community development projects, schools and how far from the community, information is obtained on whether it is public or private, data on distance and travel time to the nearest of each of several types of health post, dispensary, pharmacy, maternity home, family planning clinic, type of crops grown in the community, how often and when they are planted and harvested, and how the harvest is generally sold.

• Price questionnaire collected information on prices from up to three vendors i.e. food, pharmaceutical and other non-food items.

Cleaning operations

The quality control of the data collection occured at three instances. First, on the field, the supervisor randormly visited 25% of the households already surveyed to verify the answers to some key questions. In addition the supervisor periodically attended interviews conducted by each interviewer. Second, in the regional office, the data entry computer package used performed consistency checks, so that inconsistencies and errors in data collected during the first round were immediately reported to the interviewers for verification during the second round. Finally, daily supervisory checks of the data entry process were performed.

Abstract

The 1993/94 Namibia Household Income and Expenditure Survey (HIES) is the first module of the National Household Survey Programme endorsed by the Government in 1993, a follow-up of the 1991 Population and Housing Census and represents one more step in providing useful statistics for charting and assessing the socio-economic development of the Namibian society. This programme is an integrated part of A Five-Year Development Plan of Statistics in Namibia. The purpose of the study is to highlight the living conditions of the Namibian people with the emphasis on the distribution of the economic resources among the Namibian households. The study provides a basic description of the living conditions in Namibia concerning economic activity, housing and infrastructure, possession of capital goods and property, economic standard as well as consumption and expenditure patterns.

Geographic coverage

National coverage

Analysis unit

• Individuals
• Households

Universe

The 1993/94 Namibia Household Income and Expenditure Survey covered all private households in Namibia. Institutional households (like hospitals, hostels, barracks and prisons) are not included in the HIES.

Kind of data

Sample survey data [ssd]

Sampling procedure

There are essentially two sampling procedures that were followed in the HIES 1993/94. One for Walvis Bay and one for the rest of Namibia. These will be addressed in turn. The HIES 1993/94 for most of Namibia follows a two stage sample design, taking random draws of geographical areas before randomly selecting households within that area. To do this, the Central Statistics Office (CSO), under the National Planning Commission (NPC), had to first develop a master sample frame. To develop this master sample frame, a set of geographical areas, Primary Sampling Units (PSUs), was created and contained, on average, between 80 and 200 households. These areas were built from the Enumeration Areas (EAs) prepared for the 1991 Population and Housing Census. Small EAs were combined with adjacent EAs to form PSUs of sufficient size. The rule applied was that the number of households in a PSU according to the 1991 Population and Housing Census should be at least 80 households. About 1300 of the 1695 PSUs are made up of single EAs from the 1991 Population and Housing Census while about 400 PSUs are formed by joining two or more EAs. The 1695 PSUs, covering the whole of Namibia (except the Walvis Bay area), were separated into strata of PSUs by region and by rural, small urban and urban areas. The stratification into rural, small urban and urban areas was based on a classification of enumeration areas conducted during the preparations of the 1991 Population and Housing Census. (Note: A different definition of rural and urban areas is used in the statistical reporting from the 1991 Population and Housing Census and the HIES.) The urban areas in the Khomas region and some urban areas in the Otjozondjupa region were further stratified into high income and middle/low income areas. In this way 32 strata were created for the sampling of PSUs As a result of the way the PSUs were created, the number of PSUs of the master sample frame in each region and in each stratum is roughly proportional to the number of households in the region and in the stratum respectively as estimated in the 1991 Population and Housing Census. Having developed the master sample frame, the HIES 1993/94 was sampled according to a Probability Proporitional to Size (PPS) of PSUs method in the first stage and a fixed size equal probability sample of households in each selected PSU in the seond. 192 PSUs were selected in the first stage as the master sample. Initially the master sample was proportionally allocated over the strata in the master sample frame according to the number of households in the 1991 Population and Housing Census. However, some modifications of the allocation were made based on the following: - The variation between households in income level seems to be generally larger in the urban areas than in the rural areas. - The survey costs are considerably lower in the urban areas. - There should be at least 10 PSUs sampled from each region to allow for reasonably good statistics from each region.

It was deemed necessary to have a slight oversampling in urban areas and in one region (Omaheke). A proportional allocation of the 192 PSUs over urban/rural areas gave 66 urban and 126 rural PSUs. But, given the above specifications, the selection of the master sample resulted into 81 urban and 111 rural PSUs. In the second stage, households were selected from the chosen PSUs. A list of households for each PSU was prepared during a separate listing exercise. The listing was carried out as closely as possible to the start of the data collection in a certain PSU i.e. the month before the HIES survey month of the PSU. The list of households in the PSU was used as the sampling frame for the selection of households and a systematic equal probability random sample of 24 households from each PSU was drawn. As initially mentioned, sampling was done slightly differently in Walvis Bay. This is because the region was not integrated in Namibia until 1 March 1994 and could therefore not be included in the HIES before that date. For planning and logistic reasons Walvis Bay was included in the survey somewhat later - from May 1994. This means that Walvis Bay was included in the HIES during the last six months of the survey year. The sampling procedure was different from the rest of Namibia. In Walvis Bay the municipality authorities have for administrative purposes created computerized registers of the households in all the three main town areas - Central Walvis Bay (incl. Langstrand), Kuisebmund and Narraville. Most of the households in Walvis Bay are covered by these registers. There are some areas, however, which are not covered by the administrative registers. These areas are the hostel areas of Walvis Bay and the area along the Kuiseb river where the Topnaar population lives. To cover also these population groups, CSO conducted listing of the households in these areas. For security reasons all the hostel areas could not be listed but some areas had to be excluded from the HIES. The number of listed households in the hostel areas was 99 and probably about the same number of households was not listed. The number of Topnaar households listed was 73.

Altogether 144 households from Walvis Bay were selected by mainly a stratified one-stage sample design to be included in the HIES sample. 24 households were sampled during each of the six months (6 * 24 = 144). Separate strata were defined for Central Walvis Bay (incl. Langstrand), Kuisebmund (excl. the hostel areas), Narraville, the hostel areas and the Topnaar population and altogether 36, 54, 36, 6 and 12 households respectively were sampled from each stratum. (During May-July 1994 10 households were selected each month in Kuisebmund excluding the hostel areas. During August-October 1994 only 8 households were selected in Kuisebmund excluding the hostel areas while 2 households were selected in the hostel areas.)

Sampling deviation

There were numerous issues related to coverage and data collection. These are extensively documented in Section 9 of the Technical and Administrative Report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The contents of the HIES set of questionnaires were mainly decided on by the statistical user community. The first user-producer meetings took place during March/April 1992 during the first short-term mission of two Swedish consultants. Users from the following institutions took part in these meetings: the National Planning Commission, the Ministry of Finance, the Ministry of Trade and Industry, the Ministry of Labour, the Ministry of Local Government and Housing, the Ministry of Lands, Resettlement and Rehabilitation , the Bank of Namibia, the Namibian Economic Policy Research Unit (NEPRU) and the Social Sciences Division of the University of Namibia. Based on the pilot survey experiences and other considerations, revisions of the HIES design took place during July - August 1993. Major changes were made in the questionnaires. All of the questionnaires were translated into the major languages of Namibia.

The main forms were: - FORM I: Particulars on Individuals and Households. Filled in at the first interview visit which normally took place the week before the survey month. - FORM II: Daily Record Book. Given to the household at the first visit. The Daily Record Book. The household was urged to record all their transactions on a daily basis in the book. If no literate person was available in the household or its proximity, frequent visits had to be paid by the interviewer. The first interview visit was followed by weekly visits to the household for collecting data on transactions. - FORM III: Cash disbursement and Receipts. Transactions in cash recorded by the household were transferred by the interviewers on a weekly basis. The interviewer also regularly probed the households for cash transactions which they might have forgotten to record in the Daily Record Book. - FORM IV: Transactions in Kind. The interviewer also probed the households for in kind transactions which they might have forgotten to record in the Daily Record Book. - FORM V: Household Opinions. Consists of a module about household opinions concerning how to improve the economic well-being of the households. The Form V interview took place at the last interview visit after the survey month when the data collection concerning all other forms was ready.

Cleaning

A dataset listing the richest zip codes in New York per the most current US Census data, including information on rank and average income.

The median annual earnings for full-time employees in the United Kingdom was just over 39,000 British pounds in 2025, compared with 37,400 pounds in the previous year. At the start of the provided time period, in 1999, the average full-time salary in the UK was 17,800 pounds per year, with median earnings exceeding 20,000 pounds per year in 2002, and 30,000 by 2019. Wages continue to grow faster than inflation in 2025 Between November 2021 and July 2023 inflation was higher than wage growth in the UK, with wages still outpacing inflation as of March 2025. At the peak of the recent wave of high inflation in October 2022, the CPI inflation rate reached a 41-year-high of 11.1 percent, wages were growing much slower at 6.1 percent. Since that peak, inflation remained persistently high for several months, only dropping below double figures in April 2023, when inflation was 8.7 percent, down from 10.1 percent in the previous month. For 2023 as a whole, the average annual rate of inflation was 7.3 percent but fell to 2.5 percent in 2024, but is forecast to increase to 3.2 percent in 2025. Highest and lowest-paid occupations As of 2023, the highest-paid occupation in the UK was that of Chief Executives and Senior Officials, who had an average weekly pay of approximately, 1,576 pounds. By contrast, the lowest-paid occupation that year was that of retail cashiers, and check-out operators, who earned approximately 383 pounds a week. For industry sectors as a whole, people who worked full-time in the electricity, gas, steam and air conditioning supply sector had the highest average earnings, at 955 pounds a week, compared with 505 pounds a week in the accommodation and food services sector, the lowest average earnings in 2023.

Abstract

The Ghana Living Standards Survey (GLSS), with its focus on the household as a key social and economic unit, provides valuable insights into living conditions in Ghana. The survey was carried out by the Ghana Statistical Service (GSS) over a 12-month period (April 1998 to March 1999). A representative nationwide sample of more than 5,998 households, containing over 25,000 persons, was covered in GLSS IV.

The fourth round of the GLSS has the following objectives: · To provide information on patterns of household consumption and expenditure disaggregated at greater levels. · In combination with the data from the earlier rounds to serve as a database for national and regional planning. · To provide in-depth information on the structure and composition of the wages and conditions of work of the labor force in the country. · To provide benchmark data for compilation of current statistics on average earnings, hours of work and time rates of wages and salaries that will indicate wage/salary differentials between industries, occupations, geographic locations and gender.

Additionally, the survey will enable policy-makers to · Identify vulnerable groups for government assistance; · Analyze the impact of decisions that have already been implemented and of the economic situation on living conditions of households; · Monitor and evaluate the employment policies and programs, income generating and maintenance schemes, vocational training and similar programs. The joint measure of employment, income and expenditure provides the basis for analyzing the adequacy of employment of different categories of workers and income-generating capacity of employment-related economic development.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Community
• Commodity

Kind of data

Sample survey data [ssd]

Sampling procedure

A nationally representative sample of households was selected in order to achieve the survey objectives. For the purposes of this survey the list of the 1984 population census Enumeration Areas (EAs) with population and household information was used as the sampling frame. The primary sampling units were the 1984 EAs with the secondary units being the households in the EAs. This frame, though quite old, was considered the best available at the time. Indeed, this frame was used for the earlier rounds of the GLSS.

In order to increase precision and reliability of the estimates, the technique of stratification was employed in the sample design, using geographical factors, ecological zones and location of residence as the main controls. Specifically, the EAs were first stratified according to the three ecological zones namely; Coastal, Forest and Savannah, and then within each zone further stratification was done based on the size of the locality into rural or urban.

A two-stage sample was selected for the survey. At the first stage, 300 EAs were selected using systematic sampling with probability proportional to size method (PPS) where the size measure is the 1984 number of households in the EA. This was achieved by ordering the list of EAs with their sizes according to the strata. The size column was then cumulated, and with a random start and a fixed interval the sample EAs were selected. It was observed that some of the selected EAs had grown in size over time and therefore needed segmentation. In this connection, such EAs were divided into approximately equal parts, each segment constituting about 200 households. Only one segment was then randomly selected for listing of the households. At the second stage, a fixed number of 20 households was systematically selected from each selected EA to give a total of 6,000 households. Additional 5 households were selected as reserve to replace missing households. Equal number of households was selected from each EA in order to reflect the labor force focus of the survey.

NOTE: The above sample selection procedure deviated slightly from that used for the earlier rounds of the GLSS, as such the sample is not self-weighting. This is because: - given the long period between 1984 and the GLSS 4 fieldwork the number of households in the various EAs are likely to have grown at different rates. - The listing exercise was not properly done as some of the selected EAs were not listed completely. Moreover, it was noted that the segmentation done for larger EAs during the listing was a bit arbitrary.

Mode of data collection

Face-to-face [f2f]

Research instrument

The main questionnaire used in the survey was the household questionnaire. In addition to this, there were community and Price questionnaires.

• Household Questionnaire: The household questionnaire was used to collect information on various topics some of which pertain to eligible individual household members. The questionnaire is in two parts, A and B.
• Community Questionnaire: The main aim of the community questionnaire was is to identify the economic infrastructure, education and health facilities existing in the villages, as well as any related problems that affects their welfare. The questionnaire was administered in the rural EAs only.
• Price Questionnaire: As part of the survey a price questionnaire was designed to collect prices of most essential commodities in the local markets.

Cleaning operations

Training: The project had 3 experienced computer programmers responsible for the data processing. Data processing started with a 2-weeks training of 15 data entry operators out of which the best 10 were chosen and 2 identified as standby. The training took place one week after the commencement of the fieldwork.

Data entry: Each data entry operator was assigned to one field team and stationed in the regional office of the GSS. The main data entry software used to capture the data was IMPS (Integrated Microcomputer Processing System). The data capture run concurrently as the data collection and lasted for 12 months.

Tabulation/Analysis: The IMPS data was read into SAS (Statistical Analysis System), after which the analysis and generation of the statistical tables were done using SAS.

Response rate

Out of the selected 6000 households 5999 were successfully interviewed. One household was further dropped during the data cleaning exercise because it had very few records for many of the sections in the questionnaire. This gave 5998 household representing 99.7% coverage. Overall, 25,694 eligible household members (unweighted) were covered in the survey.

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.

Abstract

The Household Integrated Economic Survey (HIES) has been conducted covering 16341 households by taking subsample of the 79000 households of District level survey. HIES provides important information on household income, savings, liabilities, consumption expenditure and consumption patterns at national and Provincial level with urban/rural breakdown. The survey also provides the requisite data on consumption to Planning & Development Division for estimation of poverty. The Income and consumption module is exactly the same which has been used previously for the HIES 2001-02, HIES 2005-06 and HIES 2007-08.

Geographic coverage

National

Analysis unit

• Household
• Individual

Universe

The universe of this Survey consists of all households in urban and rural areas of four provinces of Pakistan. However, Military restricted areas have been excluded from the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

A) Sampling Frame Separate sampling frames have been used in the survey for urban areas and rural areas as under.

Urban area: FBS has developed its own urban area frame. All urban areas comprising of cities/towns have been divided into mutually exclusive small compact areas known as enumeration blocks (E.Bs) identifiable through maps. Each enumeration block consists of about 200-250 households on the average. Each Enumeration block has been divided into low, middle and high income groups. Urban areas sampling frame consists of 26,698 enumeration blocks which had been updated through Economic Census conducted in the year 2003.

Rural areas: With regard to the rural areas, the lists of villages/mouzas/dehs according to population Census, 1998 have been used as sampling frame. In this frame, each village/mouza/deh is identifiable by its name, Had Bast number and Cadastral map etc. There are 50,588 mouzas/villages/dehs in the rural sub-universe of the survey.

Sample size and its Allocation: In view of the variability for the characteristics for which estimates are prepared, population distribution, available field resources and reliability constraints, a sample size of 16,341 households from 1180 sampled areas(enumeration blocks and villages) has been considered appropriate to provide reliable estimates of key characteristics at the National/Provincial level.

B) Stratification Plan Urban Area: In urban areas each of the large sized cities having population of 5 lac and above has been treated as an independent stratum. Each of these cities has further been substratified into low, middle and high-income groups. The remaining cities/towns within each administrative division of the respective province have been grouped together to constitute an independent stratum.

Rural Area: In the rural areas, the population of each district in Punjab, Sindh and Khyber Pakhtunkhwa Provinces has been grouped together to constitute a stratum. For Balochistan province each of administrative Division has been taken as a stratum.

C) Sample Design A two-stage stratified random sampling scheme was adopted for this survey. Enumeration blocks in urban areas and villages in rural areas were selected at first stage while households within the sample enumeration blocks/villages were selected at second stage.

Selection of Primary Sampling Units (PSUs). Enumeration blocks in the urban areas and mouzas/dehs/villages in rural areas have been taken as Primary Sampling Units (PSUs). In urban areas, sample PSUs from each stratum have been selected by probability proportional to size (PPS) method using households in each enumeration block as measure of size (MOS). Similarly in rural areas, population of each village has been taken as measure of size (MOS) for selection of sample villages using probability proportional to size (PPS) method.

Selection of Secondary Sampling Units (SSUs): Households within each sample Primary Sampling Units (PSU) have been considered as Secondary Sampling Units (SSU). A sample of 16 and 12 households from each sampled village of rural domain and enumeration block from urban domain respectively have been selected for this survey through systematic sampling scheme.

Mode of data collection

Face-to-face [f2f]

Research instrument

The household income and consumption part of PSLM questionnaire with some improvements has been used during the reference year. Both male and female enumerators worked together to collect information regarding Income and consumption of the household.

Structure of HIES Questionnaires for 2010-11: Section A: Survey Information Section B: Household Information Section C: Education Section D: Health Section E: Employment and Income Section F: Ownership of Assets Section G: Household Details Section H: Immunization and Diarrhea for Children Under 5 Years Section I: ever Married Women (Aged 15 to 49) Section J: Use and Satisfaction with Facilities and Services

Consumption Module Section L: Household Consumption Expenditure Section M: Selected Durable Consumption Items Owned/ Sold by The Household (During last one year) Section N: Transfers Received and paid Out (During last one year) Section P: Part A: Buildings and Land Owned by Members of this Household Part B: Financial Assets and Liabilities, Loan and Credit

Agricultural Sheet Non-agricultural Establishment Balance Sheet for Income and Expenditure

Abstract

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

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

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

Geographic coverage

National coverage

Analysis unit

Households and Individuals

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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

Stratification Plan

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

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

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

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

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

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

Sampling deviation

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

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

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

Cleaning operations

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

Data appraisal

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

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