2006 LIVING CONDITIONS AND MONITORING SURVEY
5TH EDITION
Zambia, 2006 - 2007
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Reference ID
ZMB-ZSA-LCMS-2006-V1.0
Producer(s)
CENTRAL STATISTICAL OFFICE
Metadata
Created on
Jan 17, 2026
Last modified
Jan 29, 2026
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Identification
Survey ID Number
ZMB-ZSA-LCMS-2006-V1.0
Title
2006 LIVING CONDITIONS AND MONITORING SURVEY
Subtitle
5TH EDITION
Country
| Name | Country code |
|---|---|
| ZAMBIA | ZM |
Study type
Living Standards Measurement Study [hh/lsms]
Series Information
THE 2006 LCMS IS THE 4TH EDITION OF THE SERIES OF LIVING STANDARDS MEASUREMENT STUDIES.
The 2006 Living Conditions Monitoring Surveys were mainly designed to help monitor and evaluate the Fifth National Development Plan (FNDP), which spelt out Zambia’s main economic developmental programme for the period 2006-2010. The FNDP was part of the longer term programme of the Vision 2030, whose theme is to transform Zambia into “A prosperous middle-income nation by 2030”. The theme of the FNDP was“Broad based wealth and job creation through citizenry participation and technological advancement”. In December 2006 , CSO conducted the LCMS.
The 2006 Living Conditions Monitoring Surveys were mainly designed to help monitor and evaluate the Fifth National Development Plan (FNDP), which spelt out Zambia’s main economic developmental programme for the period 2006-2010. The FNDP was part of the longer term programme of the Vision 2030, whose theme is to transform Zambia into “A prosperous middle-income nation by 2030”. The theme of the FNDP was“Broad based wealth and job creation through citizenry participation and technological advancement”. In December 2006 , CSO conducted the LCMS.
Abstract
The main objective of the 2006 LCMS is to measure the wellbeing of the population in Zambia, and to provide trends in the different measures of societal wellbeing over time.
The following were the key objectives of the 2006 LCMS:
1. Monitor the level of poverty and its distribution in Zambia;
2. Monitor the impact of government policies and programmes on the well-being of the population
in Zambia;
3. Provide various users with a set of reliable indicators to monitor progress and development and
4. Identify vulnerable groups in society and enhance targeting of pro-poor policies and programmes.
The 2006 surveys were designed to produce reliable estimates at district, rural/urban, province and national levels
The following were the key objectives of the 2006 LCMS:
1. Monitor the level of poverty and its distribution in Zambia;
2. Monitor the impact of government policies and programmes on the well-being of the population
in Zambia;
3. Provide various users with a set of reliable indicators to monitor progress and development and
4. Identify vulnerable groups in society and enhance targeting of pro-poor policies and programmes.
The 2006 surveys were designed to produce reliable estimates at district, rural/urban, province and national levels
Kind of Data
Sample survey data [ssd]
Unit of Analysis
HOUSEHOLD
INDIVIDUALS
INDIVIDUALS
Version
Version Description
V1.0 EDITED ANONYMIZED DATASET FOR PUBLIC DISTRIBUTION
Version Date
2012-03-26
Scope
Notes
The scope of the 2006 LCMS included the following;
Household :Education, Household Welfare, Economic Activities, Agricultural production, Household Assets, Access to facilities, Mortality
Price Questioonaire: This contained questions on essential food and non food items that were sold in the community business entities
Household :Education, Household Welfare, Economic Activities, Agricultural production, Household Assets, Access to facilities, Mortality
Price Questioonaire: This contained questions on essential food and non food items that were sold in the community business entities
Topics
| Topic |
|---|
| DEMOGRAPHY AND MIGRATION |
| EDUCATION |
| HEALTH |
| INCOME |
| EXPENDITURE |
| ORPHANHOOD |
| ECONOMIC ACTIVITY |
| AGRICULTURE |
| ANTHROPOLOGY |
| ASSETS |
| HOUSEHOLD AMENITIES |
| ACCESS TO FACILITIES |
| MORTALITY |
Keywords
| Keyword |
|---|
| POVERTY |
| HOUSEHOLD INCOME |
| HOUSEHOLD CONSUMPTION |
| CHILD HEALTH AND NUTRITION |
| EXPENDITURE |
| MIGRATION |
| ORPHANHOOD |
| AGRICULTURAL PRODUCTION |
| DEVELOPMENTAL ISSUES |
| EDUCATION |
| HEALTH |
| DEMOGRAPHIC CHARECTERISTICS |
Coverage
Geographic Coverage
NATIONAL,
PROVINCE
RURAL/ URBAN
PROVINCE
RURAL/ URBAN
Universe
The survey covered all dejure household members (usual) while data on education and income was collected from all household members above the age of five.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| CENTRAL STATISTICAL OFFICE | MINISTRY OF FINANCE AND NATIONAL PLANNING |
Producers
| Name | Affiliation | Role |
|---|---|---|
| UNITED KINGDOM AID | UNITED KINGDOM | TECHNICAL SUPPORT |
| BRITISH DEPARTMENT OF INTERNATIONAL DEVELOPMENT | BRITAIN | TECHNICAL SUPPORT |
| GERMANY GOVERNMENT | GERMANY | TECHNICAL SUPPORT |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| GOVERNMENT OF THE REPUBLIC OF ZAMBIA | GRZ | FUNDING |
| BRITISH DEPARTMENT OF INTERNATIONAL DEVELOPMENT | DFID | FUNDING |
| GERMANY TECHNICAL CORPERATION | GIZ | FUNDING |
Other Identifications/Acknowledgments
Sampling
Sampling Procedure
The 2006 surveys was designed to cover a representative sample of about 20,000 non-institutionalised private households residing in both rural and urban parts of the country. A total of 1,000 Standard Enumeration Areas (SEAs) were drawn from a total of 16,717 SEAs nationwide in both surveys. It is important to note that the CSO had employed different sample survey methodologies at different times when conducting the surveys. With the exception of the 2002/2003 survey which used a longitudinal sample, all the remaining surveys have used a cross-sectional sample of household
The sampling frame used for the 2006 LCMSs was developed from the 2000 Census of Population and Housing. The country is administratively demarcated into nine provinces, which are further divided into 72 districts. The districts are further subdivided into 150 constituencies, which are in turn divided into wards. For the purposes of conducting household based surveys, wards are further divided into Census Supervisory Areas (CSAs), which are further subdivided into Standard Enumeration Areas (SEAs). The SEAs constituted the Primary Sampling Units (PSUs).
In order to have reasonable estimates at district level and at the same time take into account variation in the sizes of the districts, the survey adopted the Optimal Square Root sample allocation method (Leslie Kish, 1987). This approach offers a better compromise between equal and proportional allocation, i.e. small sized strata (districts) are allocated larger samples compared to proportional allocation. However, it should be pointed out that the sample size for the smallest districts was still fairly small; hence the need to examine the confidence intervals for the district-level estimates in order to determine whether the level of precision is adequate. The allocation of the sample points to rural and urban strata was approximately proportional. The distribution of the sample for the LCMS 2006 were initially the same but changed after the latter was adjusted to take into account the precision parameter.
During the 2006 survey, listing of all the households in the selected SEAs was done before a sample of households to be interviewed was drawn. In the case of rural SEAs, households were listed and stratified according to the scale of their agricultural activity. Therefore, there were four explicit strata created at the second sampling stage in each rural SEA: the Small Scale Agricultural Stratum (SSS), the Medium Scale Agricultural Stratum (MSS), the Large Scale Agricultural Stratum (LSS) and the Non-Agricultural Stratum (NAS). For the purposes of the surveys, seven, five and three households were selected from the SSS, MSS and NAS respectively. The large scale households were selected on a 100 per cent basis. The urban SEAs were explicitly stratified into low cost, medium cost and high cost areas based on CSO's and local authorities' classification of residential areas. From each rural and urban SEA, 15 and 25 households were selected respectively. However, the number of rural households selected in some cases exceeded the prescribed sample size of 15 households depending on the availability of large scale farming households. The selection of households from various strata was preceded by assigning each listed household with sampling serial numbers. The circular systematic sampling method was used to select households. The method assumes that households are arranged in a circle (G. Kalton, 1983) and the following relationship applies:
Let N = nk
Where:
N = total number of households assigned sampling serial numbers in a stratum
n = total desired sample size to be drawn from a stratum in an SEA
k = the sampling interval in a given SEA calculated as k=N/n.
The sampling frame used for the 2006 LCMSs was developed from the 2000 Census of Population and Housing. The country is administratively demarcated into nine provinces, which are further divided into 72 districts. The districts are further subdivided into 150 constituencies, which are in turn divided into wards. For the purposes of conducting household based surveys, wards are further divided into Census Supervisory Areas (CSAs), which are further subdivided into Standard Enumeration Areas (SEAs). The SEAs constituted the Primary Sampling Units (PSUs).
In order to have reasonable estimates at district level and at the same time take into account variation in the sizes of the districts, the survey adopted the Optimal Square Root sample allocation method (Leslie Kish, 1987). This approach offers a better compromise between equal and proportional allocation, i.e. small sized strata (districts) are allocated larger samples compared to proportional allocation. However, it should be pointed out that the sample size for the smallest districts was still fairly small; hence the need to examine the confidence intervals for the district-level estimates in order to determine whether the level of precision is adequate. The allocation of the sample points to rural and urban strata was approximately proportional. The distribution of the sample for the LCMS 2006 were initially the same but changed after the latter was adjusted to take into account the precision parameter.
During the 2006 survey, listing of all the households in the selected SEAs was done before a sample of households to be interviewed was drawn. In the case of rural SEAs, households were listed and stratified according to the scale of their agricultural activity. Therefore, there were four explicit strata created at the second sampling stage in each rural SEA: the Small Scale Agricultural Stratum (SSS), the Medium Scale Agricultural Stratum (MSS), the Large Scale Agricultural Stratum (LSS) and the Non-Agricultural Stratum (NAS). For the purposes of the surveys, seven, five and three households were selected from the SSS, MSS and NAS respectively. The large scale households were selected on a 100 per cent basis. The urban SEAs were explicitly stratified into low cost, medium cost and high cost areas based on CSO's and local authorities' classification of residential areas. From each rural and urban SEA, 15 and 25 households were selected respectively. However, the number of rural households selected in some cases exceeded the prescribed sample size of 15 households depending on the availability of large scale farming households. The selection of households from various strata was preceded by assigning each listed household with sampling serial numbers. The circular systematic sampling method was used to select households. The method assumes that households are arranged in a circle (G. Kalton, 1983) and the following relationship applies:
Let N = nk
Where:
N = total number of households assigned sampling serial numbers in a stratum
n = total desired sample size to be drawn from a stratum in an SEA
k = the sampling interval in a given SEA calculated as k=N/n.
Response Rate
The household response rate was calculated as the ratio of originally selected households with completed interviews over the total number of households selected. The household response rate was also generally very high with a national average of 98 per cent of the originally selected households for both survey periods. The household selection technique allows for a systematic method of replacing non-responding households.
Weighting
Due to the disproportionate allocation of the sample points to various strata, sampling weights are required to correct for differential representation of the sample at the national and sub-national levels. The weights of the sample are in this case equal to the inverse of the product of the two selection probabilities employed at each stage of selection.
The LCMS 2010 collected data on all usual household members in section 1 of the questionnaire. The weighted sum of the total number of household members (household size) is supposed to give a fairly good and accurate estimate of the current population in a particular domain such as district, province, rural/urban and national level for which this survey was designed.
The LCMS 2010 collected data on all usual household members in section 1 of the questionnaire. The weighted sum of the total number of household members (household size) is supposed to give a fairly good and accurate estimate of the current population in a particular domain such as district, province, rural/urban and national level for which this survey was designed.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2006-12 | 2007-01 | 1 |
Data Collection Mode
Face-to-face [f2f]
Supervision
DATA COLLECTION WAS DONE IN TEAMS OF 7 WITH ONE DRIVER, ONE SUPERVISOR AND FIVE ENUMERATORS. THE ROLE OF THE SUPERVISOR WAS TO;
PAY COURTESY CALL TO LOCAL AUTHORITY,
CORDINATE FIELD WORK BY IDENTIFYING THE WORK AREAS,
SUPERVISING LISTING OF HOUSEHOLDS BY ENUMERATORS
SAMPLING OF THE SELECTED HOUSEHOLDS.
FURTHER THE SUPERVISER WAS REPONSIBLE FOR EDITING AND CHECKING QUESTIONNAIRES FOR;
COMPLETENESS, CONSISTENCE AND LOGIC.
SURVEY CORDINATORS FROM THE PROVINCIAL CENTRES AND HEADQUARTERS VISITED THE TEAMS TO MONITOR DATA COLLECTION AND TO OFFERED LOGISTICAL SUPPORT.
PAY COURTESY CALL TO LOCAL AUTHORITY,
CORDINATE FIELD WORK BY IDENTIFYING THE WORK AREAS,
SUPERVISING LISTING OF HOUSEHOLDS BY ENUMERATORS
SAMPLING OF THE SELECTED HOUSEHOLDS.
FURTHER THE SUPERVISER WAS REPONSIBLE FOR EDITING AND CHECKING QUESTIONNAIRES FOR;
COMPLETENESS, CONSISTENCE AND LOGIC.
SURVEY CORDINATORS FROM THE PROVINCIAL CENTRES AND HEADQUARTERS VISITED THE TEAMS TO MONITOR DATA COLLECTION AND TO OFFERED LOGISTICAL SUPPORT.
Data Collection Notes
The 2006 field work involved 15 master trainers, 125 supervisors and 500 enumerators.
Data collection was conducted through face-to-face interviews with the main respondent. Data collection was done in teams of 7 with one driver, one supervisor and five enumerators. The enumerators were responsible for listing of households in the selected work area. After the listing process, the supervisors sample the required number of households according to region and stratum and allocates the households to the enumerators.
Data collection was conducted through face-to-face interviews with the main respondent. Data collection was done in teams of 7 with one driver, one supervisor and five enumerators. The enumerators were responsible for listing of households in the selected work area. After the listing process, the supervisors sample the required number of households according to region and stratum and allocates the households to the enumerators.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| CENTRAL STATISTICAL OFFICE | CSO | MINISTRY OF FINANCE AND NATIONAL PLANNING |
Questionnaires
Questionnaires
Data was collected using a structured household questionnaire. The questionnaire was in English and translations were only done during the actual interviews. In addition, the questionnaire contained sections that were administered to certain household members above the age of five. These included economic activity, income and education.
Data Processing
Data Editing
DATA WAS MANUALLY EDITED BY THE SUPERVISOR AND HIS /HER TEAM BEFORE THE TEAM MOVED TO THE NEXT WORK AREA TO CHECK FOR LOGIC, CONSISTENCE AND COMPLETENESS. WHERE INCONSISTENCIES WERE FOUND, THE ENUMERATOR WAS REQUIRED TO EITHER CALL THE REPSONDED FOR CLARIFICATION IF THE CONTACT NUMBER WAS AVAILABLE OR RE-VISIIT THE HOUSEHOLD. ONCE THE DATA WAS SUBMITTED AT THE PROVINCIAL OFFICE. BEFORE DATA ENTRY, QUESTIONNAIRES WERE SUBJECTED TO VIGOROUS LOGIC CHECKS FOR SKIP INSTRUCTIONS .THE DATA WAS FURTHER EDITED DURING DATA CLEANING
Other Processing
A DATA ENTRY SCREEN WAS CREATED USING CSPro. THIS SCREEN WAS USED TO ENTER THE DATA USING DESKTOP COMPUTERS. AN AVERAGE OF THREE DATA ENTRY OPERATORS WERE ALLOCATED TO EACH PROVINCE.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Head of Dissemination | Zambia Statistics Agency | info@zamstats.gov.zm | Link |
Confidentiality
The Agency shall,where statistics are designated as official statistics, protect the confidentiality and identity of the source of data.
Under the provision of the Statistics ACT no.13 of 2018, ZamStats is obliged to preserve the confidentiality of respondent information in all its census and survey data
Before being granted access to the dataset, all users have to formally agree:
1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by the Agency.
2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files.
3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the Agency
Access conditions
Micro data records are anonymised as per procedures before these are made available to users.
Micro data files are all free but under access policy Conditions:
Each dataset has an access policy :Public use file- Accessible to all and - Licensed datasets, accessible under conditions. The dataset has been anonymized and is available as a Public Use Dataset. It is accessible to all for statistical and research purposes only, under the following terms and conditions:
1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the Zambia Statistics Agency
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently.
Micro data files are all free but under access policy Conditions:
Each dataset has an access policy :Public use file- Accessible to all and - Licensed datasets, accessible under conditions. The dataset has been anonymized and is available as a Public Use Dataset. It is accessible to all for statistical and research purposes only, under the following terms and conditions:
1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the Zambia Statistics Agency
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently.
Citation requirements
Central Statistical Office (2012). Living Conditions Monitoring Survey report 2006 and 2010
Access authority
| Name | Affiliation | |
|---|---|---|
| Zambia Statistics Agency | MINISTRY OF FINANCE AND NATIONAL PLANNING | info@zamstats.gov.zm |
Disclaimer and copyrights
Disclaimer
Disclaimer : ZamStats will not bear any responsibility for the erroneous use of its data by researchers. Users should report inconsistencies in the data (both micro and aggregated) to ZamStats as soon as possible.
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 use
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 use
Copyright
(c) 2006, Central Statistical Office, Zambia
Metadata production
DDI Document ID
DDI-ZMB-ZSA-LCMS-2006-V1.0
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| ZAMBIA STATISTICS AGENCY | ZAMSTATS | MINISTRY OF FINANCE AND NATIONAL PLANNING | DOCUMENTING THE STUDY |
Date of Metadata Production
2026-01-13
DDI Document version
ZMB-ZSA-LCMS-2006-V1.0(JANUARY 2026)