Household Income and Expenditure Survey 2016-2017
Liberia, 2016 - 2017
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Reference ID
LBR_2016-2017_HIES-W3_v01_EN_M_v01_A_OCS
Producer(s)
Liberia Institute for Statistics and Geo-Information Services
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Metadata
Created on
Oct 14, 2020
Last modified
Nov 08, 2022
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Identification
Survey ID Number
LBR_2016-2017_HIES-W3_v01_EN_M_v01_A_OCS
Title
Household Income and Expenditure Survey 2016-2017
Country
| Name | Country code |
|---|---|
| Liberia | LBR |
Study type
Income/Expenditure/Household Survey [hh/ies]
Series Information
The Household Income and Expenditure Survey (HIES) 2016 is the third after the HIES of 1964 and the partially completed HIES of 2014 (interrupted due to the Ebola Virus Disease). With an improved design, the survey fieldwork was concluded on January 19, 2017.
Abstract
The main purpose of the Household Income Expenditure Survey (HIES) 2016 was to offer high quality and nationwide representative household data that provided information on incomes and expenditure in order to update the Consumer Price Index (CPI), improve National Accounts statistics, provide agricultural data and measure poverty as well as other socio-economic indicators. These statistics were urgently required for evidence-based policy making and monitoring of implementation results supported by the Poverty Reduction Strategy (I & II), the AfT and the Liberia National Vision 2030. The survey was implemented by the Liberia Institute of Statistics and Geo-Information Services (LISGIS) over a 12-month period, starting from January 2016 and was completed in January 2017. LISGIS completed a total of 8,350 interviews, thus providing sufficient observations to make the data statistically significant at the county level. The data captured the effects of seasonality, making it the first of its kind in Liberia.
Support for the survey was offered by the Government of Liberia, the World Bank, the European Union, the Swedish International Development Corporation Agency, the United States Agency for International Development and the African Development Bank. The objectives of the 2016 HIES were:
1) Update the Consumer Price Index (CPI): To obtain a new set of weights for the basket of goods and services that upgrade the Monrovia Consumer Price Index (MCPI) and the National Consumer Price Index (NCPI) and to revise the CPI basket of goods and services in Liberia to reflect the current consumption pattern of residence.
2) Improve National Accounts Statistics: To get information on annual household expenditure patterns in order to update the household component of the National Accounts.
3) Measure Poverty: To prepare robust poverty indices that enable the understanding of poverty dynamics across the country and of the factors influencing them.
4) Improve Agricultural Statistics: To obtain nationally representative and policy relevant agricultural statistics in order to undertake in-depth analysis of agricultural households.
5) Capture Socio-economic Impact of Ebola Virus Disease (EVD): To obtain a post-EVD dataset which allows for an in-depth analysis of the socioeconomic impact of EVD on households.
6) Benchmark Agenda for Transformation Indicators: To provide an update on selected socioeconomic indicators used to benchmark the government's policies embedded within the Agenda for Transformation.
7) Develop Statistical Capacity: Emphasize capacity building and development of sustainable statistical systems through every stage of the project to produce accurate and timely information about Liberia.
Support for the survey was offered by the Government of Liberia, the World Bank, the European Union, the Swedish International Development Corporation Agency, the United States Agency for International Development and the African Development Bank. The objectives of the 2016 HIES were:
1) Update the Consumer Price Index (CPI): To obtain a new set of weights for the basket of goods and services that upgrade the Monrovia Consumer Price Index (MCPI) and the National Consumer Price Index (NCPI) and to revise the CPI basket of goods and services in Liberia to reflect the current consumption pattern of residence.
2) Improve National Accounts Statistics: To get information on annual household expenditure patterns in order to update the household component of the National Accounts.
3) Measure Poverty: To prepare robust poverty indices that enable the understanding of poverty dynamics across the country and of the factors influencing them.
4) Improve Agricultural Statistics: To obtain nationally representative and policy relevant agricultural statistics in order to undertake in-depth analysis of agricultural households.
5) Capture Socio-economic Impact of Ebola Virus Disease (EVD): To obtain a post-EVD dataset which allows for an in-depth analysis of the socioeconomic impact of EVD on households.
6) Benchmark Agenda for Transformation Indicators: To provide an update on selected socioeconomic indicators used to benchmark the government's policies embedded within the Agenda for Transformation.
7) Develop Statistical Capacity: Emphasize capacity building and development of sustainable statistical systems through every stage of the project to produce accurate and timely information about Liberia.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households
Scope
Notes
The HIES 2016 survey covered the following topics:
- Household demographic characteristics
- Poverty
- Inequality
- Food security
- Household characteristics
- Education
- Health
- Employment
- Household non-farm enterprises
- Agriculture
- Transfers
- Shocks
- Subjective welfare
- Household demographic characteristics
- Poverty
- Inequality
- Food security
- Household characteristics
- Education
- Health
- Employment
- Household non-farm enterprises
- Agriculture
- Transfers
- Shocks
- Subjective welfare
Topics
| Topic | Vocabulary |
|---|---|
| Poverty | FAO |
| Food (production, crisis) | FAO |
| Agriculture & Rural Development | FAO |
| Gender | FAO |
| Health | FAO |
| Access to Finance | FAO |
| Fragile & Conflict-affected States | FAO |
Coverage
Geographic Coverage
National
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Liberia Institute for Statistics and Geo-Information Services | Government of Liberia |
Producers
| Name | Role |
|---|---|
| The World Bank | Technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| The World Bank | WB | Financial assistance |
| Government of Liberia | GovLBR | Financial assistance |
| Swedish International Development Cooperation Agency | SIDA | Financial assistance |
| United States Agency for International Development | USAID | Financial assistance |
| African Development Fund | AfDB | Financial assistance |
Sampling
Sampling Procedure
The original sample design for the HIES exploited two-phased clustered sampling methods, encompassing a nationally representative sample of households in every quarter and was obtained using the 2008 National Housing and Population Census sampling frame. The procedures used for each sampling stage are as follows:
i. First stage
Selection of sample EAs. The sample EAs for the 2016 HIES were selected within each stratum systematically with Probability Proportional to Size from the ordered list of EAs in the sampling frame. They are selected separately for each county by urban/rural stratum. The measure of size for each EA was based on the number of households from the sampling frame of EAs based on the 2008 Liberia Census. Within each stratum the EAs were ordered geographically by district, clan and EA codes. This provided implicit geographic stratification of the sampling frame.
ii. Second stage
Selection of sample households within a sample EA. A random systematic sample of 10 households were selected from the listing for each sample EA. Using this type of table, the supervisor only has to look up the total number of households listed, and a specific systematic sample of households is identified in the corresponding row of the table.
i. First stage
Selection of sample EAs. The sample EAs for the 2016 HIES were selected within each stratum systematically with Probability Proportional to Size from the ordered list of EAs in the sampling frame. They are selected separately for each county by urban/rural stratum. The measure of size for each EA was based on the number of households from the sampling frame of EAs based on the 2008 Liberia Census. Within each stratum the EAs were ordered geographically by district, clan and EA codes. This provided implicit geographic stratification of the sampling frame.
ii. Second stage
Selection of sample households within a sample EA. A random systematic sample of 10 households were selected from the listing for each sample EA. Using this type of table, the supervisor only has to look up the total number of households listed, and a specific systematic sample of households is identified in the corresponding row of the table.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2016-01 | 2017-01 |
Data Collection Mode
Face-to-face [f2f]
Data Processing
Data Editing
The data entry clerk for each team, using data entry software called CSPro, entered data for each household in the field. For each household, an error report was generated on-site, which identified key problems with the data collected (outliers, incorrect entries, inconsistencies with skip patterns, basic filters for age and gender specific questions etc.). The Supervisor along with the Data Entry Clerk and the Enumerator that collected the data reviewed these errors. Call-backs were made to households if necessary, to verify information and rectify the errors while in that EA. Once the data were collected in each EA, they were sent to LISGIS headquarters for further processing along with EA reports for each area visited. The HIES Technical committee converted the data into STATA and ran several consistency checks to manage overall data quality and prepared reports to identify key problems with the data set and called the field teams to update them about the same. Monthly reports were prepared by summarizing observations from data received from the field alongside statistics on data collection status to share with the field teams and LISGIS Management.
Access policy
Contacts
| Name | URL |
|---|---|
| Liberia Institute of Statistics and Geo-Information Services | Link |
Confidentiality
https://microdata.worldbank.org/index.php/terms-of-use
Access conditions
https://microdata.worldbank.org/index.php/terms-of-use
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example:
Liberia Institute for Statistics and Geo-Information Services. Household Income and Expenditure Survey (HIES) 2016, Ref. LBR_2016_HIES_v01_M. Dataset downloaded from [URL] on [date].
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example:
Liberia Institute for Statistics and Geo-Information Services. Household Income and Expenditure Survey (HIES) 2016, Ref. LBR_2016_HIES_v01_M. Dataset downloaded from [URL] 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_LBR_2016-2017_HIES-W3_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 Data Group | DECDG | The World Bank | Documentation of the DDI |
DDI Document version
LBR_2016-2017_HIES-W3_v01_EN_M_v01_A_OCS_v01