National Survey on Household Living Conditions and Agriculture - Wave 2, 2014 - 2015
Niger, 2014 - 2015
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Reference ID
NER_2014-2015_ECVMA-W2_v01_EN_M_v01_A_OCS
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Aug 25, 2020
Last modified
Nov 08, 2022
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Identification
Survey ID Number
NER_2014-2015_ECVMA-W2_v01_EN_M_v01_A_OCS
Title
National Survey on Household Living Conditions and Agriculture - Wave 2, 2014 - 2015
Country
| Name | Country code |
|---|---|
| Niger | NER |
Study type
Living Standards Measurement Study [hh/lsms]
Series Information
The ECVMA is the second integrated multi-topic household survey done for the purpose of evaluating poverty and living conditions in Niger under the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) program. It is a panel survey with the first survey done in 2011.
Abstract
Niger is part of the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) program. This program has developed a household level survey with a view to enhancing our knowledge of agriculture in Sub-Saharan Africa, in particular, its role in poverty reduction and the techniques for promoting efficiency and innovation in this sector. To achieve this objective, an innovative model for agricultural data collection in this region will need to be developed and implemented. To this end, activities conducted in the future will be supported by four main pillars: a multisectoral framework, institutional integration, analytical capacity building, and active dissemination.
First, agricultural statistical data collection must be part of an expanded and multisectoral framework that goes beyond the rural area. This will facilitate generation of the data needed to formulate effective agricultural policies throughout Niger and in the broader framework of the rural economy.
Second, agricultural statistical data collection must be supported by a well-adapted institutional framework suited to fostering collaboration and the integration of data sources. By supporting a multi-pronged approach to data collection, this project seeks to foster intersectoral collaboration and overcome a number of the current institutional constraints.
Third, national capacity building needs to be strengthened in order to enhance the reliability of the data produced and strengthen the link between the producers and users of data. This entails having the capacity to analyze data and to produce appropriate public data sets in a timely manner. The lack of analytical expertise in developing countries perpetuates weak demand for statistical data.
Consequently, the foregoing has a negative impact on the quality and availability of policy-related analyses. Scant dissemination of statistics and available results has compounded this problem.
In all countries where the LSMS-ISA project will be executed, the process envisioned for data collection will be a national household survey, based on models of LSMS surveys to be conducted every three years for a panel of households. The sampling method to be adopted should ensure the quality of the data, taking into account the depth/complexity of the questionnaire and panel size, while ensuring that samples are representative.
The main objectives of the ECVMA are to:
- Gauge the progress made with achievement of the Millennium Development Goals (MDGs);
- Facilitate the updating of the social indicators used in formulating the policies aimed at improving the living conditions of the population;
- Provide data related to several areas that are important to Niger without conducting specific surveys on individual topics ;
- Provide data on several important areas for Niger that are not necessarily collected in other more specific surveys.
First, agricultural statistical data collection must be part of an expanded and multisectoral framework that goes beyond the rural area. This will facilitate generation of the data needed to formulate effective agricultural policies throughout Niger and in the broader framework of the rural economy.
Second, agricultural statistical data collection must be supported by a well-adapted institutional framework suited to fostering collaboration and the integration of data sources. By supporting a multi-pronged approach to data collection, this project seeks to foster intersectoral collaboration and overcome a number of the current institutional constraints.
Third, national capacity building needs to be strengthened in order to enhance the reliability of the data produced and strengthen the link between the producers and users of data. This entails having the capacity to analyze data and to produce appropriate public data sets in a timely manner. The lack of analytical expertise in developing countries perpetuates weak demand for statistical data.
Consequently, the foregoing has a negative impact on the quality and availability of policy-related analyses. Scant dissemination of statistics and available results has compounded this problem.
In all countries where the LSMS-ISA project will be executed, the process envisioned for data collection will be a national household survey, based on models of LSMS surveys to be conducted every three years for a panel of households. The sampling method to be adopted should ensure the quality of the data, taking into account the depth/complexity of the questionnaire and panel size, while ensuring that samples are representative.
The main objectives of the ECVMA are to:
- Gauge the progress made with achievement of the Millennium Development Goals (MDGs);
- Facilitate the updating of the social indicators used in formulating the policies aimed at improving the living conditions of the population;
- Provide data related to several areas that are important to Niger without conducting specific surveys on individual topics ;
- Provide data on several important areas for Niger that are not necessarily collected in other more specific surveys.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households
Scope
Notes
The scope of the ECVMA includes:
Household questionnaire
- Socio-demographic characteristics of household members
- Education
- Health
- Characteristics of the labor market
- Non-agricultural enterprises
- Characteristics of the household dwelling
- Income of houshold members not derived from employment
- Fund transfers
- Negative shocks
- Non food household expenditure
- Food consumption
- Food security
- Aspirations of individuals from 15-25
- Psychology and attitudes of individuals 15-25
- Consumption of livestock owned by the household
- Children between ages 5-15 living outside the household
Agriculture and livestock questionnaire:
- Household's access to land
- Inputs, labor, types of crops and amount of harvest for rainy season agriculture
- Livestock
- Tree culture, perennials,
- Agricultural extension
- Climate change
Community Questionnaire:
- Relative existence and accessibility of social services
- Economy and infrastructure in the village/neighborhood
- Health
- Characteristics of agriculture in the village/neighborhood
- Livestock and negative shocks which the community has been victim during the last 5 years
- Community needs for infrastructure
- Local prices
Household questionnaire
- Socio-demographic characteristics of household members
- Education
- Health
- Characteristics of the labor market
- Non-agricultural enterprises
- Characteristics of the household dwelling
- Income of houshold members not derived from employment
- Fund transfers
- Negative shocks
- Non food household expenditure
- Food consumption
- Food security
- Aspirations of individuals from 15-25
- Psychology and attitudes of individuals 15-25
- Consumption of livestock owned by the household
- Children between ages 5-15 living outside the household
Agriculture and livestock questionnaire:
- Household's access to land
- Inputs, labor, types of crops and amount of harvest for rainy season agriculture
- Livestock
- Tree culture, perennials,
- Agricultural extension
- Climate change
Community Questionnaire:
- Relative existence and accessibility of social services
- Economy and infrastructure in the village/neighborhood
- Health
- Characteristics of agriculture in the village/neighborhood
- Livestock and negative shocks which the community has been victim during the last 5 years
- Community needs for infrastructure
- Local prices
Coverage
Geographic Coverage
National Coverage
Producers and sponsors
Funding Agency/Sponsor
| Name | Role |
|---|---|
| The World Bank | Financial and Technical Assistance |
Other Identifications/Acknowledgments
| Name |
|---|
| ECVMA Technical Committee |
Sampling
Weighting
In order to produce nationally representative statistics with the data, weights or expansion factors need to be applied. The sample weight (hhweight) is found in the constructed data sets (see Annex 2 of the Basic Information Document available under the related materials/documentation tab).
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2014-09 | 2014-11 | First Visit |
| 2015-01-27 | 2015-03-28 | Second Visit |
Data Collection Mode
Face-to-face paper [f2f]
Data Processing
Data Editing
The data entry was done in the field simultaneously with the data collection. Each data collection team included a data entry operator who key entered the data soon after it was collected. The data entry program was designed in CSPro, a data entry package developed by the US Census Bureau. This program allows three types of data checks: (1) range checks; (2) intra-record checks to verify inconsistencies pertinent to the particular module of the questionnaire; and (3) inter-record checks to determine inconsistencies between the different modules of the questionnaire.
The data as distributed represent the best effort to provide complete information. The data were collected and cleaned prior to the construction of the consumption aggregate. Using the same guidelines as were used in 2011, the households that are provided in the data set should have consumption data for both visits. This may not be the case. During the cleaning process, it was found that households had been misidentified which allowed more households to be included in the final consumption aggregate file (see below). The raw data that contains household/item level data that was used to calculate the consumption aggregate has been included in the distribution file.There are 3,614 households and 26,579 individuals in the data.
The data as distributed represent the best effort to provide complete information. The data were collected and cleaned prior to the construction of the consumption aggregate. Using the same guidelines as were used in 2011, the households that are provided in the data set should have consumption data for both visits. This may not be the case. During the cleaning process, it was found that households had been misidentified which allowed more households to be included in the final consumption aggregate file (see below). The raw data that contains household/item level data that was used to calculate the consumption aggregate has been included in the distribution file.There are 3,614 households and 26,579 individuals in the data.
Access policy
Contacts
| Name | URL |
|---|---|
| The World Bank Microdata Library | microdata.worldbank.org |
Confidentiality
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 data depositor.
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 data depositor.
Access conditions
Public use files, accessible to all
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:
Niger National Institute of Statistics. National Survey on Household Living Conditions and Agriculture (ECVMA) 2014. Ref. NER_2014_ECVMA_v02_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:
Niger National Institute of Statistics. National Survey on Household Living Conditions and Agriculture (ECVMA) 2014. Ref. NER_2014_ECVMA_v02_M. Dataset downloaded from [url] on [date].
Access authority
| Name |
|---|
| National Institute of Statistics |
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_NER_2014-2015_ECVMA-W2_v01_EN_M_v01_A_OCS_FAO
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Office of Chief Statistician | OCS | Food and Agriculture Organization | Metadata adapted for FAM |
| Development Economics Data Group | DECDG | The World Bank | Documentation of the DDI |
DDI Document version
NER_2014-2015_ECVMA-W2_v01_EN_M_v01_A_OCS_v01