Integrated Household Survey 1991
Pakistan, 1991
Federal Bureau of Statistics (FBS)
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Identification
Survey ID Number
PAK_1991_IHS_v01_EN_M_v01_A_OCS
Title
Integrated Household Survey 1991
Country
| Name | Country code |
|---|---|
| Pakistan | PAK |
Study type
Living Standards Measurement Study [hh/lsms]
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 analyse 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, self-employment 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.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households
Scope
Notes
The scope of the Pakistan IHS is:
· Household information
· Housing
· Education
· Health
· Wage employment
· Family labor
· Energy (male questionnaire)
· Energy (female questionnaire)
· Migration
· Farming and livestock
· Non-farm enterprise activities
· Non-food expenditures and inventory of durable goods
· Food expenses and home production
· Marriage and maternity history
· Anthropometrics
· Credit and savings
· Transfers and remittances
· Other income
· Household information
· Housing
· Education
· Health
· Wage employment
· Family labor
· Energy (male questionnaire)
· Energy (female questionnaire)
· Migration
· Farming and livestock
· Non-farm enterprise activities
· Non-food expenditures and inventory of durable goods
· Food expenses and home production
· Marriage and maternity history
· Anthropometrics
· Credit and savings
· Transfers and remittances
· Other income
Topics
| Topic | Vocabulary |
|---|---|
| Agriculture & Rural Development | FAO |
| Food (production, crisis) | FAO |
| Livestock | FAO |
| Labor | FAO |
| Access to Finance | FAO |
| Payment Systems | FAO |
| Migration & Remittances | FAO |
| Population & Reproductive Health | FAO |
Coverage
Geographic Coverage
National
Producers and sponsors
Primary investigators
| Name |
|---|
| Federal Bureau of Statistics (FBS) |
Producers
| Name | Role |
|---|---|
| The World Bank | Technical assistance |
Sampling
Sampling Procedure
(a) SAMPLE FRAME:
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. 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
(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. 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 well-defined 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.
(b) 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.
(c) 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.
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. 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
(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. 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 well-defined 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.
(b) 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.
(c) 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.
Weighting
To allow adjustment to be made for over-sampling of certain strata in the PIHS sample, sampling weights have been calculated, and have been incorporated into the PIHS data sets that are distributed. These raising factors should be used to weight data in order to obtain nationally representative statistics. The formula used to calculate the weight assigned to the various PSUs is as follows:
Wij = k x (1/Pij) x (Nj/Sj)
where Wij is the weight assigned to households in PSU j of stratum i, k is some constant, Pij is the assigned probability of selection of PSU j of stratum i, (i.e. the higher the given probability of selection, the lower the weight given to the PSU), Nj is the number of households in the PSU j as found during the listing exercise, and Sj is the number of households in the PSU j on which the PPS was based.
Wij = k x (1/Pij) x (Nj/Sj)
where Wij is the weight assigned to households in PSU j of stratum i, k is some constant, Pij is the assigned probability of selection of PSU j of stratum i, (i.e. the higher the given probability of selection, the lower the weight given to the PSU), Nj is the number of households in the PSU j as found during the listing exercise, and Sj is the number of households in the PSU j on which the PPS was based.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 1991-01 | 1991-12 |
Data Collection Mode
Face-to-face [f2f]
Data Appraisal
Estimates of Sampling Error
The PIHS sample was designed to yield representative statistics at the national and urban/rural) levels. Care however should be taken when interpreting results for smaller analytic domains as the sample was not designed to be representative at a more disaggregated level. Thus, even with the use of the sampling weights, statistics for the smaller provinces such as Balochistan are likely to have high standard errors given the relatively small sample size in these domains. In this regard, it is important to note that when calculating standard errors for estimates derived from the PIHS data, allowance must be made for the fact that the survey used a multi-staged sampling procedure. Calculating standard errors using methods outlined in elementary statistical textbooks is likely to underestimate the true magnitude of errors as the techniques presented in these books often assume that simple random selection was used when drawing the sample.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| LSMS Data Manager | The World Bank | [email protected] | http://go.worldbank.org/QJVDZDKJ60 |
Confidentiality
The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO
Access conditions
Micro datasets disseminated by FAO shall only be allowed for research and statistical purposes. Any user which requests access working for a commercial company will not be granted access to any micro dataset regardless of their specified purpose. Users requesting access to any datasets must agree to the following minimal conditions:
- The micro dataset will only be used for statistical and/or research purposes;
- Any results derived from the micro dataset will be used solely for reporting aggregated information, and not for any specific individual entities or data subjects;
- The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO;
- The micro dataset cannot be re-disseminated by users or shared with anyone other than the individuals that are granted access to the micro dataset by FAO.
- The micro dataset will only be used for statistical and/or research purposes;
- Any results derived from the micro dataset will be used solely for reporting aggregated information, and not for any specific individual entities or data subjects;
- The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO;
- The micro dataset cannot be re-disseminated by users or shared with anyone other than the individuals that are granted access to the micro dataset by FAO.
Citation requirements
Use of the dataset must be acknowledged by including a citation which would include:
- Identification of the Primary Investigator(s) and of the country
- Title of the survey (including the year of implementation)
- Survey reference number
- Source and date of download
Example:
Pakistan. Federal Bureau of Statistics and the World Bank. Pakistan Integrated Household Survey (PIHS) 1991. Ref. PAK_1991_PIHS_v01_M. Dataset downloaded from www.microdata.worldbank.org on [date]
- Identification of the Primary Investigator(s) and of the country
- Title of the survey (including the year of implementation)
- Survey reference number
- Source and date of download
Example:
Pakistan. Federal Bureau of Statistics and the World Bank. Pakistan Integrated Household Survey (PIHS) 1991. Ref. PAK_1991_PIHS_v01_M. Dataset downloaded from www.microdata.worldbank.org on [date]
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses
Metadata production
DDI Document ID
DDI_PAK_1991_IHS_v01_EN_M_v01_A_OCS_FAO
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Office of Chief Statistician | OCS | Food and Agriculture Organization | Adoption of metadata for FAM |
| Development Economics Data Group | DECDG | The World Bank | Documentation of the DDI |
DDI Document version
PAK_1991_IHS_v01_EN_M_v01_A_OCS_v01