Agricultural Productivity Module Survey 2017:SUF
Zimbabwe
Identification
idno
ZWE_2017_APM_v01_M
Title
Agricultural Productivity Module Survey 2017:SUF
Country
| Name | Country code |
|---|---|
| Zimbabwe | ZWE |
Abstract
The Zimbabwe National Statistics Agency (ZIMSTAT) together with the Ministry of Lands, Agriculture, Water, Climate and Rural Resettlement (MLAWCRR) conducted the Agricultural Productivity Module (APM) as part of the Poverty, Income, Consumption and Expenditure Survey (PICES) 2017. The APM survey was carried out with financial and technical assistance from the World Bank. The APM provides representative estimates at the national level. The APM survey collected detailed information on agricultural production of different types of smallholder farmers in Zimbabwe. These smallholders formed a subsample of households that were part of the PICES 2017 survey.
The objective of the APM Survey was twofold: (1) to collect, analyse and disseminate high-quality household level data on agriculture and welfare by introducing an additional innovative module to a subsample of the PICES 2017 survey; and (2) to strengthen national capacity for the collection and analysis of policy relevant data. This was done through promoting institutional interaction between ZIMSTAT and MLAWCRR, with technical and financial support from the World Bank.
The PICES-APM is intended to complement the Agricultural and Livestock Survey (ALS) as well as other agricultural data collected by ZIMSTAT. Data from the APM also supplements data collected by the MLAWCRR through its surveillance activities. The APM survey collected data on multiple topics of relevance to smallholder farming including on food and nutrition security. The data can be used to assess constraints for raising smallholder productivity as well as for reducing vulnerability, complementing the annual survey of the Zimbabwe Vulnerability Assessment Committee (ZIMVAC). Since the APM module was part of PICES 2017, information on welfare indicators such as household poverty status, education, health, housing as well as other income sources will also be available for these households. This will make it possible to assess the linkage between smallholder agricultural productivity and poverty and also to assess the impact of policy measures (e.g. a change in agricultural subsidies) on household welfare, and inform the design of better policies and programmes aimed at improving the lives of rural smallholder households in Zimbabwe.
The survey was conducted in Communal Lands, A1 Farms, Old Resettlement Farms and Small Scale Commercial Farms. The survey is representative for each of these four farm types and at national level. The topics covered in the survey include:
· Introduction and Sample Design
· Household Characteristics and Plot Details
· Input Use
· Field Crop Harvest and Field Crop Disposition
· Livestock Production, Livestock Holdings and Animal Costs
· Agricultural Capital
· Command Agriculture
· Agricultural Credit and Extension Services
· Food and Nutrition Security
The objective of the APM Survey was twofold: (1) to collect, analyse and disseminate high-quality household level data on agriculture and welfare by introducing an additional innovative module to a subsample of the PICES 2017 survey; and (2) to strengthen national capacity for the collection and analysis of policy relevant data. This was done through promoting institutional interaction between ZIMSTAT and MLAWCRR, with technical and financial support from the World Bank.
The PICES-APM is intended to complement the Agricultural and Livestock Survey (ALS) as well as other agricultural data collected by ZIMSTAT. Data from the APM also supplements data collected by the MLAWCRR through its surveillance activities. The APM survey collected data on multiple topics of relevance to smallholder farming including on food and nutrition security. The data can be used to assess constraints for raising smallholder productivity as well as for reducing vulnerability, complementing the annual survey of the Zimbabwe Vulnerability Assessment Committee (ZIMVAC). Since the APM module was part of PICES 2017, information on welfare indicators such as household poverty status, education, health, housing as well as other income sources will also be available for these households. This will make it possible to assess the linkage between smallholder agricultural productivity and poverty and also to assess the impact of policy measures (e.g. a change in agricultural subsidies) on household welfare, and inform the design of better policies and programmes aimed at improving the lives of rural smallholder households in Zimbabwe.
The survey was conducted in Communal Lands, A1 Farms, Old Resettlement Farms and Small Scale Commercial Farms. The survey is representative for each of these four farm types and at national level. The topics covered in the survey include:
· Introduction and Sample Design
· Household Characteristics and Plot Details
· Input Use
· Field Crop Harvest and Field Crop Disposition
· Livestock Production, Livestock Holdings and Animal Costs
· Agricultural Capital
· Command Agriculture
· Agricultural Credit and Extension Services
· Food and Nutrition Security
Unit of Analysis
Farming Households in the smallholder agricultural sector.
Version
Version number
v01 Edited, anonymous dataset for Scientific Use file distribution.
Coverage
Geographic Coverage
National Coverage of the 8 provinces of Zimbabwe which have rural areas. The survey excluded urban provinces such as Harare and Bulawayo. The survey covered the small holder agriculture consisting of Communal Lands, A1 Farms, Small Scale Commercial Farms and Old REsettlement Areas. Large Scale commecial farms were not covered.
Unit of Analysis
Farming Households in the smallholder agricultural sector.
Universe
Population can be enumerated using two methods: a "de jure" and a "de facto" population count. A " de jure" count is the enumeration of persons, who usually reside in a given place, whereas a "de facto" count is the enumeration of persons physically present at a specified place. For this survey we adopt the "de jure" concept. The usual members may be present or temporarily absent. We are thus concerned about the de jure household. A household is a single person or a group of people who usually live, cook and eat together, they may be related or not. The target population were thefarming households in the smallholder agricultural sector of rural Zimbabwe.
Producers and sponsors
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| World Bank | WB | Financial Support |
| Government of Zimbabwe | GOZ | Financial Support |
Sampling
Sampling Procedure
The Agricultural Productivity Module (APM), is a nationally representative survey on agricultural productivity in Zimbabwe. The survey covers four smallholder farming sectors namely Communal Lands (CL), Small Scale Commercial Farms (SSCF), Old Resettlement Areas (ORA) and A1 Farms. The PICES 2017 was based on a sample of 32,256 households which provides representative estimates at province and district levels. A total of 2 552 households were sampled for the APM survey.
The APM is a survey of smallholder households. The data was collected from a subsample of the households that were interviewed in 2017 Poverty, Income, Consumption and Expenditure Survey (PICES). Information on household characteristics, education, housing, etc. for these households was collected in the main PICES data collection. The sample excluded the A2 farmers and other large-scale commercial farmers as (i) their managers and cultivators did not always live in the local area; and (ii) the large farm sizes of large scale commercial farms made them less suitable for plot size measurement.
To select the APM subsample a two-stage sample design was used. The first stage involved the selection of enumeration areas from the PICES EAs that were in the March, April, and May 2017 sample. The EAs were selected using the Probability Proportional to Size (PPS) sampling method. The measure of size was the number of households enumerated during the 2012 population census. The PPS procedure assigns each sampling unit a specific chance to be selected in the sample before the sampling begins, and the chance is proportional to its measure of size.
The second stage involved the selection of households from a sample of PICES households using random systematic sampling method. Systematic sampling (SYS) is the selection of sampling units at a fixed interval from a list, starting from a randomly determined point. Selection is systematic because selection of the first sampling unit determines the selection of the remaining sampling units. The sample design strategy allowed for representativeness at national level as well as for Communal Lands, Small Scale Commercial Farms, A1 Farms, and Old Resettlement Areas.
The households were selected using Random Systematic Sampling (RSYS) method for EAs in APM Survey. A sample of 8 households per EA was selected from Communal Lands and Resettlement Areas and a census of all PICES households (i.e. 14 households) was taken for EAs in the A1 Farms and the Small Scale Commercial Farms (SSCF). A reserve of four extra households was selected per EA for replacement purposes, in case a selected household in the Communal Lands and Old Resettlement Areas was not an agricultural household.
The APM is a survey of smallholder households. The data was collected from a subsample of the households that were interviewed in 2017 Poverty, Income, Consumption and Expenditure Survey (PICES). Information on household characteristics, education, housing, etc. for these households was collected in the main PICES data collection. The sample excluded the A2 farmers and other large-scale commercial farmers as (i) their managers and cultivators did not always live in the local area; and (ii) the large farm sizes of large scale commercial farms made them less suitable for plot size measurement.
To select the APM subsample a two-stage sample design was used. The first stage involved the selection of enumeration areas from the PICES EAs that were in the March, April, and May 2017 sample. The EAs were selected using the Probability Proportional to Size (PPS) sampling method. The measure of size was the number of households enumerated during the 2012 population census. The PPS procedure assigns each sampling unit a specific chance to be selected in the sample before the sampling begins, and the chance is proportional to its measure of size.
The second stage involved the selection of households from a sample of PICES households using random systematic sampling method. Systematic sampling (SYS) is the selection of sampling units at a fixed interval from a list, starting from a randomly determined point. Selection is systematic because selection of the first sampling unit determines the selection of the remaining sampling units. The sample design strategy allowed for representativeness at national level as well as for Communal Lands, Small Scale Commercial Farms, A1 Farms, and Old Resettlement Areas.
The households were selected using Random Systematic Sampling (RSYS) method for EAs in APM Survey. A sample of 8 households per EA was selected from Communal Lands and Resettlement Areas and a census of all PICES households (i.e. 14 households) was taken for EAs in the A1 Farms and the Small Scale Commercial Farms (SSCF). A reserve of four extra households was selected per EA for replacement purposes, in case a selected household in the Communal Lands and Old Resettlement Areas was not an agricultural household.
Weighting
The preliminary APM anonymized data set is being released without weights. APM weights are being compiled and will be released togerher with the final APM anonymized data set. Researchers are strongly advised not to compile their own APM weights as the findings by different authors will be different. ZIMSTAT will therefore provide the final APM weights.
Data Collection
Mode of data collection
Face-to-face interviews with farming households.
Metadata production
Document ID
ZWE_2017_APM_v01_M
Producers
| Name | Abbreviation | Role |
|---|---|---|
| World Bank | WB | Financial & Technical Support |
| United Nations Children’s Fund | UNICEF | Technical Support |
| Ministry of Lands Agriculture, Water, Climate and Rural Resettlement | MLAWCRR | Technical Support |
| African Development Bank | AfDB | Technical Support |
| Department for International Development | DFID | Technical Support |
| Ministry of Finance and Economic Development | MOFED | Technical Support |
| United Nations Development Programme | UNDP | Technical Support |
| Ministry of Public Service Labour and Social Welfare | MPSLSW | Technical Support |
| Zimbabwe National Statistics Agency | ZIMSTAT | Technical Support |
| United Nations Population Fund | UNFPA | Technical Support |