Afrint Household Level Data 2002 and 2008
Round I & II
Ghana, 2001 - 2008
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Reference ID
GHA-C-DAMAA-AFRINT-2014-v1.0
Producer(s)
Lund University
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Metadata
Created on
Sep 12, 2014
Last modified
Sep 12, 2014
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1057999
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Identification
Survey ID Number
GHA-C-DAMAA-AFRINT-2014-v1.0
Title
Afrint Household Level Data 2002 and 2008
Subtitle
Round I & II
Translated Title
No translation
Country
| Name | Country code |
|---|---|
| Ghana | GHA |
Study type
Other Household Survey [hh/oth]
Series Information
Afrint stands for intensification of food crops agriculture in sub-Saharan Africa and has so far, consisted of two phases, Afrint I, which lasted from 2001 to 2004, and Afrint II between 2007 and 2010
Abstract
Afrint intensification of food crops agriculture in sub-Saharan Africa Swedish-African Research Network Agricultural development and its relation to food security and poverty alleviation Primary research in nine sub-Saharan African countries. Afrint - three phases 200I-2016.
Afrint I - 2001-2005: The African Food Crisis - the Relevance of Asian Experiences
Afrint II - 2007-2010:The Millennium Development Goals and the African Food Crisis
Afrint I - 2001-2005: The African Food Crisis - the Relevance of Asian Experiences
Afrint II - 2007-2010:The Millennium Development Goals and the African Food Crisis
Kind of Data
Aggregate data [agg]
Unit of Analysis
Household
Version
Version Description
Version1.0 (September, 2014)
Version Date
2010-09-30
Version Notes
The official starting date for the African sub-profjects was June 1st 2002.The collaboratin researchers worked for 60 days, and undertook to finalise their respective work packes according to the time plan.
The file contains the aggregated data of round I (2001-2005) and round II (2007-2010).
The file contains the aggregated data of round I (2001-2005) and round II (2007-2010).
Scope
Notes
Scope of Surey Round I (2001-2005)
Household demographic and socio-economic characteristics
Farm and crop management
Maize
Cassava
Cassava, marketing conditions
Sorghum
Rice
Other food crops and vegetables
Non-food cash crops
Land resources
Livestock
Labour resources
Institutional conditions
Incomes and expenditures
Scope of Survey Round II (2007-2010).
Household Demographic and Socio-Economic Characteristics
Farm and Crop Management
Crops
Maize
Cassava
Sorghum
Rice
Rural - Urban and Rural - Rural Linkages (staple crops)
Other food crops and vegetables (for local markets)
Non-food cash crops (wholly or partly for export)
Agricultural Techniques
Land resources
Livestock & Fish
Livestock
Household demographic and socio-economic characteristics
Farm and crop management
Maize
Cassava
Cassava, marketing conditions
Sorghum
Rice
Other food crops and vegetables
Non-food cash crops
Land resources
Livestock
Labour resources
Institutional conditions
Incomes and expenditures
Scope of Survey Round II (2007-2010).
Household Demographic and Socio-Economic Characteristics
Farm and Crop Management
Crops
Maize
Cassava
Sorghum
Rice
Rural - Urban and Rural - Rural Linkages (staple crops)
Other food crops and vegetables (for local markets)
Non-food cash crops (wholly or partly for export)
Agricultural Techniques
Land resources
Livestock & Fish
Livestock
Topics
| Topic | Vocabulary |
|---|---|
| Food (production, crisis) | World Bank |
Coverage
Geographic Coverage
Sub-Saharan Africa, (Ethiopia, Ghana, Keny, Malawi, Nigeria, Tanzania, Uganda, Zambia) Regions within selected countries
Geographic Unit
Regions within selected countries
Universe
Farming Household
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Lund University | Swedish Government |
Producers
| Name | Affiliation | Role |
|---|---|---|
| Goran Djurefeldt | Lund University | Project leader |
| Mikael Hammarkjold | Lund University | Team member |
| Hans Holmen | Lund University | Team member |
| Magnus Jirstrom | Lund University | Team member |
| Rolf Larsson | Lund Uniersty | Team member |
| Agnes Anderson Djurefeldt | Lund University | Team Leader |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Swedish International Development Authority | Sida | Funder |
| Bank of Sweden Tercentenary Foundation | BoSTF | Funder |
Sampling
Sampling Procedure
Data collection for the first round of the Afrint project was made in 2002. The data collected as part of the second round are referred to as 2008 data, although in some cases collected in late 2007. From the outset the research team selected five case study countries: Ghana, Kenya, Malawi, Nigeria and Tanzania. Outside francophone Africa, these five countries were ideally suited, in the researchers' view, to charting progress in intensification, induced from below by farmers themselves, or state induced, as in the Asian Green Revolution. At the insistence of Sida, to the original five countries, four more were added: Ethiopia, Mozambique, Uganda and Zambia. Unlike the original five, the three last mentioned countries were deemed less constrained with respect to productive resources in agriculture. Ethiopia on the other hand is peculiar in an African context, with its long history of plough agriculture, and feudal-like social formation. In this project, the heterogeneous sample of countries has proved less cumbersome to work with than one might have expected.
Formally, the Afrint sample was drawn in four stages, of which the country selection described above was the first one. The next stage was regions within countries, followed by selection of villages within regions, and with selection of farm households as the last stage. All stages except the final one have been based on purposive sampling. Data collection was sought to be made at all four levels.The households sampled within these countries were selected with respect to the agricultural potential of the areas in which they reside.The intention was to capture the dynamism in the areas that are 'above average' in terms of ecological and market (infrastructure) endowments but excluding the most extreme cases in this regard.For logistical reasons we could not aim for a sample which is representative in a statistical sense. Instead we aimed at a sample which is illustrative of conditions in the maize-cassava belt, excluding both lowpotential dry and remote areas and extreme outliers at the other end of the scale.
Thus we used a four-stage sample design, with purposive sampling at all stages, except the last one, where households were sampled after having made up household lists. When we compare point estimates from the sample with those from other sources, for examples yields for the various crops with FAO statistics, no apparent sample bias has been detected.
In addition to household questionnaires we also used village questionnaires. Respondents to village interviews were key persons, like villageleaders and extension agents. Investigators were also instructed to conduct focus group interviews with representatives for various segments of the village population, including women farmers. When going for a second round and a panel in 2008, we went for a balanced panel design, i.e. constructing the 2008 sample so that in itself it would be representative of village populations in 2008. This also involved sampling descendants when a household had been partitioned since 2002. In case of sizeable in-migration to a village, we also provided for sampling from the newly arrived households. The 2002-2008 panel thus is a subset of the two cross sectional samples. In itself this subset is not statistically representative of the village population in any of the two years
Formally, the Afrint sample was drawn in four stages, of which the country selection described above was the first one. The next stage was regions within countries, followed by selection of villages within regions, and with selection of farm households as the last stage. All stages except the final one have been based on purposive sampling. Data collection was sought to be made at all four levels.The households sampled within these countries were selected with respect to the agricultural potential of the areas in which they reside.The intention was to capture the dynamism in the areas that are 'above average' in terms of ecological and market (infrastructure) endowments but excluding the most extreme cases in this regard.For logistical reasons we could not aim for a sample which is representative in a statistical sense. Instead we aimed at a sample which is illustrative of conditions in the maize-cassava belt, excluding both lowpotential dry and remote areas and extreme outliers at the other end of the scale.
Thus we used a four-stage sample design, with purposive sampling at all stages, except the last one, where households were sampled after having made up household lists. When we compare point estimates from the sample with those from other sources, for examples yields for the various crops with FAO statistics, no apparent sample bias has been detected.
In addition to household questionnaires we also used village questionnaires. Respondents to village interviews were key persons, like villageleaders and extension agents. Investigators were also instructed to conduct focus group interviews with representatives for various segments of the village population, including women farmers. When going for a second round and a panel in 2008, we went for a balanced panel design, i.e. constructing the 2008 sample so that in itself it would be representative of village populations in 2008. This also involved sampling descendants when a household had been partitioned since 2002. In case of sizeable in-migration to a village, we also provided for sampling from the newly arrived households. The 2002-2008 panel thus is a subset of the two cross sectional samples. In itself this subset is not statistically representative of the village population in any of the two years
Deviations from the Sample Design
20.6 Percent
Response Rate
79.4 Percent
Weighting
The weight for the data was not provided
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2001 | 2002 | 1 yrs |
| 2007 | 2008 | 1 yrs |
Time periods
| Start date | End date | Cycle |
|---|---|---|
| 2001 | 2005 | 5 years |
| 2007 | 2010 | 5 years |
Data Collection Mode
Face-to-face [f2f]
Supervision
The enumerators and supervisors were trained at the same time, though supervisors received extra couching on supervision. Enumerators stayed in the villages during the survey period. Two enumerators were involved in administering the household questionnaires at a time. While one was probing, the other was writing down the answer.
Through this, errors in both probing and recording were minimized. Participatory Rural Appraisal techniques were used to administer the village level questionnaire in the selected villages.
Through this, errors in both probing and recording were minimized. Participatory Rural Appraisal techniques were used to administer the village level questionnaire in the selected villages.
Data Collection Notes
The research team worked with a two-pronged strategy for collecting data, building simultaneously on qualitative and quantitative methods. The core of the latter is a survey, which gives the quantitative backbone of the study. The study relied on two strategies: First by drawing as much as possible diachronic and historic data in the collection of qualitative material and other secondary data.
This was done in the macro studies, conducted by the partners in each country and subjected to comparative analysis by the Swedish team. Second, The research built a temporal dimension into the survey by asking the recall method, asking farmers to compare the present situation to earlier times.
This was done in the macro studies, conducted by the partners in each country and subjected to comparative analysis by the Swedish team. Second, The research built a temporal dimension into the survey by asking the recall method, asking farmers to compare the present situation to earlier times.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Göran Djurfeldt | G.D. | Dept of Sociology, Lund University |
| Hans Holmén, | H.H. | Institution for Thematic research, Linköping University |
| Magnus Jirström | M.J. | Dept of Social and Economic Geography, Lund University |
| Agnes Andersson | A.A | Dept of Social and Economic Geography, Lund University |
| Johanna Bergman-Lodin | J.B | Dept of Social and Economic Geography, Lund University |
| Cheryl Sjöström, | C.S. | Dept of Social and Economic Geography, Lund University |
| Dr. Wolday Amha | W.A | Ethiopian Economic Association |
| Dr. Teketel Abebe | T.A | Addis Ababa University |
| Dr. Mulat Demeke | M.D | Addis Ababa University |
| Professor Willis Oluoch-Kosura | W.O | African Economic Research Consortium (AERC) |
| Dr. Stephen K. Wambugu | S.K.W | Department of Geography, Kenyatta University |
Questionnaires
Questionnaires
Scope of Surey Round I (2001-2005)
Household demographic and socio-economic characteristics
Farm and crop management
Maize
Cassava
Cassava, marketing conditions
Sorghum
Rice
Other food crops and vegetables
Non-food cash crops
Land resources
Livestock
Labour resources
Institutional conditions
Incomes and expenditures
Scope of survey II
Household Demographic and Socio-Economic Characteristics
Farm and Crop Management
Crops
Maize
Cassava
Sorghum
Rice
Rural - Urban and Rural - Rural Linkages (staple crops)
Other food crops and vegetables (for local markets)
Non-food cash crops (wholly or partly for export)
Agricultural Techniques
Land resources
Livestock & Fish
Livestock
Household demographic and socio-economic characteristics
Farm and crop management
Maize
Cassava
Cassava, marketing conditions
Sorghum
Rice
Other food crops and vegetables
Non-food cash crops
Land resources
Livestock
Labour resources
Institutional conditions
Incomes and expenditures
Scope of survey II
Household Demographic and Socio-Economic Characteristics
Farm and Crop Management
Crops
Maize
Cassava
Sorghum
Rice
Rural - Urban and Rural - Rural Linkages (staple crops)
Other food crops and vegetables (for local markets)
Non-food cash crops (wholly or partly for export)
Agricultural Techniques
Land resources
Livestock & Fish
Livestock
Data Processing
Data Editing
No edting specification given
Other Processing
Not reported
Data Appraisal
Estimates of Sampling Error
No sampling error estimates given
Data Appraisal
No other froms of appraisal given.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Samuel Kobina Annim | C-DAMAA, University of Cape Coast | sannim@ucc.edu.gh | Link |
| Emmanuel Orkoh | C-DAMAA, University of Cape Coast | aorkoh@gmail.com | Link |
| Zelda Arku | C-DAMAA, University of Cape Coast | zeldaarku1@gmail.com | Link |
| Issac Koomson | C-DAMAA, University of Cape Coast | koomsonisaac@gmail.com | Link |
Confidentiality
Ghana Statistical Service (GSS) requires all users to keep information and microdata strictly confidential. In this regard, before being granted access to microdatasets, all users have to formally agree to observe the following:
1. Not to make copies of any files or portions of files to which access has been granted except with the authorization by GSS
2. Not to willfully identify any individual or household or establishment in the microdataset
3. To hold in strictest confidence, the identity of any individual or household or establishment that may be inadvertently revealed in any documents or discussion, or analysis. Such unintended identification revealed should be immediately brought to the attention of GSS.
4. Microdata obtained from GSS are protected by copyright law and therefore not for re-distribution or sale
5. Prospective clients or data users may be required to submit and sign an affidavit of confidentiality of microdata they access
Access conditions
The Ghana Statistical Service as a public institution has the obligation to promote data dissemination to facilitate national development. Making mcrodata available will enable students and the academia to conduct research works, assist investors to take business decision, help the individual to evaluate and take appropriate decisions. It will also assist the government to formulate appropriate policies and programmes to facilitate national development. GSS' policy framework provides access to data through:
1. Public use files. These categories of data sets are accessible by all without any payment. They are available on-line to all interested users, for research and statistical purposes only.
2. Licensed datasets. These categories of data sets are accessible under certain conditions. Thus, prospective clients/data users may access any data based on certain conditions set by the GSS
3. Datasets only accessible on location. We consider this category as a data enclave where some data sets are only accessible at GSS offices and prospective data users and researches have to physically be available at GSS offices for further discussions before data are released. Thus, data enclave would not be linked to the outside world through our web site or other medium.
The following terms and conditions apply:
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 for which access has been granted, except those authorized by GSS.
2. Not to use any technique in an attempt to identify any person, establishment, or sampling unit.
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 GSS.
4. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of GSS.
5. The data will be used for statistical and scientific research purposes only.
6. The data will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
7. No attempt will be made to identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the GSS.
8. No attempt will be made to produce links among datasets provided by the GSS with other datasets that could identify individuals or organizations.
9. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the GSS would cite the source of data in accordance with the citation statement provided with the dataset
10. An electronic copy of all reports and publications based on the requested data will be sent to the GSS.
1. Public use files. These categories of data sets are accessible by all without any payment. They are available on-line to all interested users, for research and statistical purposes only.
2. Licensed datasets. These categories of data sets are accessible under certain conditions. Thus, prospective clients/data users may access any data based on certain conditions set by the GSS
3. Datasets only accessible on location. We consider this category as a data enclave where some data sets are only accessible at GSS offices and prospective data users and researches have to physically be available at GSS offices for further discussions before data are released. Thus, data enclave would not be linked to the outside world through our web site or other medium.
The following terms and conditions apply:
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 for which access has been granted, except those authorized by GSS.
2. Not to use any technique in an attempt to identify any person, establishment, or sampling unit.
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 GSS.
4. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of GSS.
5. The data will be used for statistical and scientific research purposes only.
6. The data will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
7. No attempt will be made to identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the GSS.
8. No attempt will be made to produce links among datasets provided by the GSS with other datasets that could identify individuals or organizations.
9. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the GSS would cite the source of data in accordance with the citation statement provided with the dataset
10. An electronic copy of all reports and publications based on the requested data will be sent to the GSS.
Citation requirements
Centre for Data Archiving, Management, Analysis and Advocacy (C-DAMAA), Afrint Project, 2011 version 1.0
Disclaimer and copyrights
Disclaimer
The original collector of the data, GSS and any producers or sponsors cited in this document bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Copyright
(C) 2014, GHA
Metadata production
DDI Document ID
DDI-GHA-C-DAMAA-AFRINT-2002-2008-v1.0
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Centre for Data Archiving, Management, Analysis and Advocacy | C-DAMAA | University of Cape Coast | Documentation of the Study |
Date of Metadata Production
2014-09-12
DDI Document version
Version 1.0 (September, 2014)