Living Standards Survey 1985-1986, Wave 1 Panel
Côte d'Ivoire, 1985 - 1986
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Reference ID
CIV_1985-1986_LSS-W1_v01_EN_M_v01_A_OCS
Producer(s)
Direction de la Statistique
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Identification
Survey ID Number
CIV_1985-1986_LSS-W1_v01_EN_M_v01_A_OCS
Title
Living Standards Survey 1985-1986, Wave 1 Panel
Country
| Name | Country code |
|---|---|
| Côte d'Ivoire | CIV |
Study type
Living Standards Measurement Study [hh/lsms]
Series Information
This is the first "Enquête Permanente Auprès des Ménages" (EPAM) i.e. Living Standards Survey (LSS) conducted in Cote d'Ivoire and it is panel with the second, third and fourth LSS which were conducted in 1986, 1987 and 1888 respectively.
Abstract
The Côte d'Ivoire Living Standards Survey (LSS) was the first LSMS Survey to have field tested the methodology and questionnaire developed by LSMS. It consists of three complementary surveys: the household survey, the community survey and the price survey. The household survey collected detailed information on expenditures, income, employment, assets, basic needs and other socio-economic characteristics of the households. The Community Survey collected information on economic and demographic characteristics of the rural communities to which each cluster of households belonged. This was designed to enable the linkage of community level with household level data. The price survey component of the CILSS collected data on prices at the nearest market to each cluster of households, so that regional price indices could be constructed for the household survey. The Côte d'Ivoire Living Standards Survey (LSS) was undertaken over a period of four years, 1985-88, by the Direction de la Statistique in Côte d'Ivoire, with financial and technical support from the World Bank during the first two years of the survey. It was the first year-round household survey to have been undertaken by the Ivorian Direction de la Statistique. The sample size each year was 1600 households and the sample design was a rotating panel. That is, half of the households were revisited the following year, while the other half were replaced with new households. The survey thus produced four cross-sectional data sets as well as three overlapping panels of 800 households each (1985-86, 1986-87, 1987-88).
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households
Scope
Notes
The scope of the study includes:
(a) HOUSEHOLD QUESTIONNAIRE
- Household composition
- Housing
- Education
- Health
- Migration
- Characteristics of housing
- Agro-pastoral activities
- Non-farm self-employment
- Expenditures and inventory of durable goods
- Food expenditures
- Fertility
- Other income
- Savings and credit
- Anthropometrics
- Household composition last year
(b) COMMUNITY QUESTIONNAIRE
- Demographic Information
- Economy and Infrastructure
- Education
- Health
- Agriculture
(a) HOUSEHOLD QUESTIONNAIRE
- Household composition
- Housing
- Education
- Health
- Migration
- Characteristics of housing
- Agro-pastoral activities
- Non-farm self-employment
- Expenditures and inventory of durable goods
- Food expenditures
- Fertility
- Other income
- Savings and credit
- Anthropometrics
- Household composition last year
(b) COMMUNITY QUESTIONNAIRE
- Demographic Information
- Economy and Infrastructure
- Education
- Health
- Agriculture
Topics
| Topic | Vocabulary |
|---|---|
| Agriculture & Rural Development | FAO |
| Food (production, crisis) | FAO |
| Financial Sector | FAO |
| Access to Finance | FAO |
| Health | FAO |
| Infrastructure | FAO |
| Nutrition | FAO |
| Migration & Remittances | FAO |
Coverage
Geographic Coverage
National
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Direction de la Statistique | Ministère de l'Economie et des Finances |
Producers
| Name | Role |
|---|---|
| The World Bank | Technical assistance |
Sampling
Sampling Procedure
(a) SAMPLE DESIGN
The principal objective of the sample selection process for the LSS Household Survey was to obtain a nationally representative cross-section of African households, some of which could be interviewed in successive years as panel households. A two-stage sampling procedure was used. In the first stage, 100 Primary Sampling Units (PSUs) were selected across the country from a list of all PSUs available in the sampling frame. At the second stage, a cluster of 16 households was selected within each PSU. This led to a sample size of 1600 households a year, in 100 cluster s of 16 households each. Half of the households were replaced each year while the other half (the panel households in 1986, 1987 and 1988) were interviewed a second time. It is important to note that there was a change in the sampling procedures (the sampling frame, PSU selection process and listing procedures), used to select half of the clusters/households interviewed in 1987 (the other half were panel households retained from 1986), and all of the clusters/households interviewed in 1988. Households selected on the basis of the first set of sampling procedures will henceforth be referred to as Block 1 data while households based on the second set of sampling procedures will be referred to as Block 2 data.
(b) SAMPLE FRAME
1. Sampling Procedures for Block 1 Data
The Sampling Frame. The sampling frame for the 1985, 1986, and half of the 1987 samples (except for Abidjan and Bouaké) was a list of localities constructed on the basis of the 1975 Census, updated to 1983 by the demographers of the Direction de la Statistique and based on a total population estimated at 9.4 million in 1983.The Block 1 frame for Abidjan and Bouaké was based on data from a 1979-80 electoral census of these two cities. The electoral census had produced detailed maps of the two cities that divided each sector of the city into smaller sub-sectors (îlots). Sub-sectors with similar types of housing were grouped together by statisticians in the Direction de la Statistique to form PSUs. From a list of all PSUs in each city, along with each PSU's population size, the required number of PSUs were selected using a systematic sampling procedure. The step size was equal to the city's population divided by the number of PSUs required in each city. One problem identified in the selection process for Abidjan arose from the fact that one sector of the city (Yopougon) which had been relatively small in 1980 at the time of the electoral census, had since become the largest agglomeration in Côte d'Ivoire. This problem was presumably unavoidable since accurate population data for Yopougon was not available at the time of the PSU selection process.
Selection of PSUs. Geographic stratification was not explicitly needed because the systematic sampling procedure that was used to select the PSUs ensured that the sample was balanced with respect to region and by site type, within each region. The main geographical regions defined were: East Forest, West Forest, and Savannah. Site types varied as follows: large cities, towns, large and small villages, surrounding towns, village centers, and villages attached to them. The 100 PSUs were selected, with probabilities proportional to the size of their population, from a list of PSUs sorted by region and within each region, by site type. Selection of households within each PSU. A pre-survey was conducted in June-July of 1984, to establish the second-stage sampling frame, i.e. a list of households for each PSU from which 16 households could be selected. The same listing exercise was to be used for both the 1985 and 1986 surveys, in order to avoid having to conduct another costly pre-survey in the second year. Thus, the 1984 pre-survey had to provide enough households so as to be able to select two clusters of households in each PSU and to allow for replacement households in the event that some in the sample could not be contacted or refused to participate. A listing of 64 households in each PSU met this requirement. In PSUs with 64 households or fewer, every household was listed. In selecting the households, the "step" used was equal to the estimated number of households in the PSU divided by 64. For example, if the PSU had an estimated 640 households, then every tenth household was included in the listing, counted from a random starting point in the PSU. For operational reasons, the maximum step allowable was a step of 30. In practice, it appears that enumerators used doors, instead of housing structures, in counting the step. Al though enumerators were supposed to start the listing process from a random point in the PSU, in rural areas and small towns, reportedly, the lister started from the center of the PSU.
2. Sampling Procedures for Block 2 Data
The Sampling Frame. The sampling frame for Block 2 data was established from a list of places from the results of the Census of inhabited sites (RSH) performed in preparation for the 1988 Population Census. Selection of PSUs. The PSUs were selected with probability proportional to size. However, in order to save what might have been exorbitant costs of listing every household in each selected PSU in a pre-survey, the Direction de la Statistique made a decision to enumerate a smaller unit within each PSU. The area within each PSU was divided into smaller blocks called `îlots'. Households were then selected from a randomly chosen îlot within each PSU. The sample îlot was selected with equal probability within each PSU, not on the basis of probability proportional to size. (These îlots are reportedly relatively small compared with the size of PSUs selected for the Block 1 frame, but no further information is available about their geographical position within the PSUs.) Selection of households within each PSU. All households in each îlot selected for the Block 2 sample were listed. Sixteen households were then randomly chosen from the list of households for each îlot.
The principal objective of the sample selection process for the LSS Household Survey was to obtain a nationally representative cross-section of African households, some of which could be interviewed in successive years as panel households. A two-stage sampling procedure was used. In the first stage, 100 Primary Sampling Units (PSUs) were selected across the country from a list of all PSUs available in the sampling frame. At the second stage, a cluster of 16 households was selected within each PSU. This led to a sample size of 1600 households a year, in 100 cluster s of 16 households each. Half of the households were replaced each year while the other half (the panel households in 1986, 1987 and 1988) were interviewed a second time. It is important to note that there was a change in the sampling procedures (the sampling frame, PSU selection process and listing procedures), used to select half of the clusters/households interviewed in 1987 (the other half were panel households retained from 1986), and all of the clusters/households interviewed in 1988. Households selected on the basis of the first set of sampling procedures will henceforth be referred to as Block 1 data while households based on the second set of sampling procedures will be referred to as Block 2 data.
(b) SAMPLE FRAME
1. Sampling Procedures for Block 1 Data
The Sampling Frame. The sampling frame for the 1985, 1986, and half of the 1987 samples (except for Abidjan and Bouaké) was a list of localities constructed on the basis of the 1975 Census, updated to 1983 by the demographers of the Direction de la Statistique and based on a total population estimated at 9.4 million in 1983.The Block 1 frame for Abidjan and Bouaké was based on data from a 1979-80 electoral census of these two cities. The electoral census had produced detailed maps of the two cities that divided each sector of the city into smaller sub-sectors (îlots). Sub-sectors with similar types of housing were grouped together by statisticians in the Direction de la Statistique to form PSUs. From a list of all PSUs in each city, along with each PSU's population size, the required number of PSUs were selected using a systematic sampling procedure. The step size was equal to the city's population divided by the number of PSUs required in each city. One problem identified in the selection process for Abidjan arose from the fact that one sector of the city (Yopougon) which had been relatively small in 1980 at the time of the electoral census, had since become the largest agglomeration in Côte d'Ivoire. This problem was presumably unavoidable since accurate population data for Yopougon was not available at the time of the PSU selection process.
Selection of PSUs. Geographic stratification was not explicitly needed because the systematic sampling procedure that was used to select the PSUs ensured that the sample was balanced with respect to region and by site type, within each region. The main geographical regions defined were: East Forest, West Forest, and Savannah. Site types varied as follows: large cities, towns, large and small villages, surrounding towns, village centers, and villages attached to them. The 100 PSUs were selected, with probabilities proportional to the size of their population, from a list of PSUs sorted by region and within each region, by site type. Selection of households within each PSU. A pre-survey was conducted in June-July of 1984, to establish the second-stage sampling frame, i.e. a list of households for each PSU from which 16 households could be selected. The same listing exercise was to be used for both the 1985 and 1986 surveys, in order to avoid having to conduct another costly pre-survey in the second year. Thus, the 1984 pre-survey had to provide enough households so as to be able to select two clusters of households in each PSU and to allow for replacement households in the event that some in the sample could not be contacted or refused to participate. A listing of 64 households in each PSU met this requirement. In PSUs with 64 households or fewer, every household was listed. In selecting the households, the "step" used was equal to the estimated number of households in the PSU divided by 64. For example, if the PSU had an estimated 640 households, then every tenth household was included in the listing, counted from a random starting point in the PSU. For operational reasons, the maximum step allowable was a step of 30. In practice, it appears that enumerators used doors, instead of housing structures, in counting the step. Al though enumerators were supposed to start the listing process from a random point in the PSU, in rural areas and small towns, reportedly, the lister started from the center of the PSU.
2. Sampling Procedures for Block 2 Data
The Sampling Frame. The sampling frame for Block 2 data was established from a list of places from the results of the Census of inhabited sites (RSH) performed in preparation for the 1988 Population Census. Selection of PSUs. The PSUs were selected with probability proportional to size. However, in order to save what might have been exorbitant costs of listing every household in each selected PSU in a pre-survey, the Direction de la Statistique made a decision to enumerate a smaller unit within each PSU. The area within each PSU was divided into smaller blocks called `îlots'. Households were then selected from a randomly chosen îlot within each PSU. The sample îlot was selected with equal probability within each PSU, not on the basis of probability proportional to size. (These îlots are reportedly relatively small compared with the size of PSUs selected for the Block 1 frame, but no further information is available about their geographical position within the PSUs.) Selection of households within each PSU. All households in each îlot selected for the Block 2 sample were listed. Sixteen households were then randomly chosen from the list of households for each îlot.
Response Rate
During the first year of the survey, a total of 124 of the 1600 original sample households (7.8 percent) were not interviewed and were thus replaced by other households. The most common reason for non-response in the first year was the inability to locate the address or housing unit. Only 14 households (0.9 percent of the sample) were found but refused to participate, and these were all in Abidjan.
Weighting
Scott and Amenuvegbe address the problem arising from the fact that the estimates of population used to select PSUs with probability proportional to size, are often outdated and inaccurate. The degree of inaccuracy increases with the number of years that have elapsed since the previous census. The extent of inaccuracy becomes clear when the listing process is completed for the PSU and the 'correct' population size becomes available. This deviation between the PSU's estimated population size and the 'correct' size needs to be addressed either by varying the sample 'take' in each PSU or by assigning corrective weights for each PSU, m' i/ni or m'i/mi, where m'i is the number of households found in the ith PSU at the listing stage and ni or mi is the measure of size (n=population, m=households) used in the first stage PSU selection. [Note: Omission of this weight has two effects:
(1) a bias in favor of PSUs whose population has grown relatively slowly (or diminished) since the census, and against those that have grown exceptionally fast
(2) a bias in favor of PSUs whose current mean household size is relatively large (Chris Scott, personal communication).]
As has been mentioned earlier, the LSS implemented a fixed 'take' of 16 households per cluster, and one cluster per PSU. Given these rules, any attempt to address this issue would have to rely on corrective m'i/ni weights. However, it is not possible to calculate these weights either for Block 1 data (m' I is not available since only 64 households per cluster were listed); or for Block 2 data (m' i is not available since the enumeration area was the îlot and not the PSU).
(1) a bias in favor of PSUs whose population has grown relatively slowly (or diminished) since the census, and against those that have grown exceptionally fast
(2) a bias in favor of PSUs whose current mean household size is relatively large (Chris Scott, personal communication).]
As has been mentioned earlier, the LSS implemented a fixed 'take' of 16 households per cluster, and one cluster per PSU. Given these rules, any attempt to address this issue would have to rely on corrective m'i/ni weights. However, it is not possible to calculate these weights either for Block 1 data (m' I is not available since only 64 households per cluster were listed); or for Block 2 data (m' i is not available since the enumeration area was the îlot and not the PSU).
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 1985-02-22 | 1986-01-24 | Round 1 |
Data Collection Mode
Face-to-face [f2f]
Data Processing
Data Editing
The Household Questionnaire was almost entirely pre-coded, thus reducing errors involved in the coding process. Also, the decentralized data entry system allowed for immediate follow-up on inconsistencies that were detected by the data entry program. Household and personal identification codes were recorded in each section, facilitating merging data across sections
Data Appraisal
Estimates of Sampling Error
(a) ACCURACY
The general consensus is that the quality of the LSS household data is very good. An informal review of data quality conducted by Ainsworth and Mehra (1988) assessed the 1985 and 1986 LSS data in terms of their accuracy, completeness, and internal consistency. The LSS household data were found to score high marks on each of these three counts. One measure of data quality is the extent to which individuals in question respond for themselves during the interview, rather than having proxy responses provided for them by other household members. The investigation of CILSS household survey data for 1985 and 1986 showed that 93 percent of women responded for themselves to the fertility section and that 79 to 80 percent of all adult household members responded for themselves to the employment module. The percent of children responding for themselves to the employment module was far less, 43 to 45 percent. Nevertheless, these rates were found to be higher than for the Peru Living Standards Survey (29 percent).
(b) COMPLETENESS
Investigation of several variables and modules in the LSS (sex, age, parental characteristics, schooling, health, employment, migration, fertility, farming and family business), found that missing data in the household survey are rare. Rates for missing data were found to be close to 0 (0.01 to 0.05 percent) in many cases, but in any case, no higher than 0.76 percent.
The general consensus is that the quality of the LSS household data is very good. An informal review of data quality conducted by Ainsworth and Mehra (1988) assessed the 1985 and 1986 LSS data in terms of their accuracy, completeness, and internal consistency. The LSS household data were found to score high marks on each of these three counts. One measure of data quality is the extent to which individuals in question respond for themselves during the interview, rather than having proxy responses provided for them by other household members. The investigation of CILSS household survey data for 1985 and 1986 showed that 93 percent of women responded for themselves to the fertility section and that 79 to 80 percent of all adult household members responded for themselves to the employment module. The percent of children responding for themselves to the employment module was far less, 43 to 45 percent. Nevertheless, these rates were found to be higher than for the Peru Living Standards Survey (29 percent).
(b) COMPLETENESS
Investigation of several variables and modules in the LSS (sex, age, parental characteristics, schooling, health, employment, migration, fertility, farming and family business), found that missing data in the household survey are rare. Rates for missing data were found to be close to 0 (0.01 to 0.05 percent) in many cases, but in any case, no higher than 0.76 percent.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| LSMS Data Manager | The World Bank | [email protected] | surveys.worldbank.org/lsms |
Confidentiality
See https://microdata.worldbank.org/index.php/terms-of-use
Access conditions
In receiving these data it is recognized that the data are supplied for use within your organization, and you agree to the following stipulations as conditions for the use of the data:
1. The data are supplied solely for the use described in this form and will not be made available to other organizations or individuals. Other organizations or individuals may request the data directly.
2. Three copies of all publications, conference papers, or other research reports based entirely or in part upon the requested data will be supplied to:
Institut National de la Statistique
B.P. V55
Abidjan
Cote d'Ivoire
fax: (225)-21-44-01
e-mail: [email protected]
AND
The World Bank
Development Economics Research Group
LSMS Database Administrator
MSN MC3-306
1818 H Street, NW
Washington, DC 20433, USA
tel: (202) 473-9041
fax: (202) 522-1153
e-mail: [email protected]
3. The researcher will refer to the 1988 Côte d'Ivoire Living Standards Survey as the source of the information in all publications, conference papers, and manuscripts. At the same time, the Institut National de la Statistique is not responsable for the estimations reported by the analyst(s).
4. Users who download the data may not pass the data to third parties.
5. The database cannot be used for commercial ends, nor can it be sold.
1. The data are supplied solely for the use described in this form and will not be made available to other organizations or individuals. Other organizations or individuals may request the data directly.
2. Three copies of all publications, conference papers, or other research reports based entirely or in part upon the requested data will be supplied to:
Institut National de la Statistique
B.P. V55
Abidjan
Cote d'Ivoire
fax: (225)-21-44-01
e-mail: [email protected]
AND
The World Bank
Development Economics Research Group
LSMS Database Administrator
MSN MC3-306
1818 H Street, NW
Washington, DC 20433, USA
tel: (202) 473-9041
fax: (202) 522-1153
e-mail: [email protected]
3. The researcher will refer to the 1988 Côte d'Ivoire Living Standards Survey as the source of the information in all publications, conference papers, and manuscripts. At the same time, the Institut National de la Statistique is not responsable for the estimations reported by the analyst(s).
4. Users who download the data may not pass the data to third parties.
5. The database cannot be used for commercial ends, nor can it be sold.
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_CIV_1985-1986_LSS-W1_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 Research Group | DECDG | The World Bank | Generation of the DDI |
DDI Document version
CIV_1985-1986_LSS-W1_v01_EN_M_v01_A_OCS_v01