Impact Evaluation of the Integrated Agricultural Productivity Project 2014
Bangladesh, 2014
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Reference ID
BGD_2014_IAPPIE-W2_v01_EN_M_v01_A_OCS
Producer(s)
Florence Kondylis, Maria Jones, Daniel Stein
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Metadata
Created on
Sep 09, 2020
Last modified
Nov 08, 2022
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Identification
Survey ID Number
BGD_2014_IAPPIE-W2_v01_EN_M_v01_A_OCS
Title
Impact Evaluation of the Integrated Agricultural Productivity Project 2014
Country
| Name | Country code |
|---|---|
| Bangladesh | BGD |
Study type
Other Household Survey [hh/oth]
Series Information
This is the midline round 2 survey of IAPP project conducted in Bangladesh.The baseline survey was conducted in 2012, round 1 of the midline survey was conducted in 2013 and the endline in 2015.
Abstract
The IAPP project is designed to improve the income and livelihoods of crop, fish, and livestock farmers in Bangladesh. It consists of four separate components:
Component 1: Technology Generation and Adaptation;
Component 2: Technology Adoption;
Component 3: Water Management;
Component 4: Project Management.
The Impact Evaluation (IE) of the IAPP project will contribute to understanding the drivers of technology adoption through two lenses. First, the overall project approach will be evaluated using a randomized phase-in of project villages (referred to as the "Overall Project Evaluation"). The Overall Project Evaluation will measure the effects of Components 2 and 3 of IAPP. All sub-components will be measured, with special focus on the crops and fisheries sub-components. Second, innovations will be tested through a randomized control trial to understand what approach to demonstration plots can deliver higher results (referred to as the "Demonstration Plot Evaluation"). The Demonstration Plot Evaluation is designed to test a fundamental question about technology adoption: to what extent can "learning by doing" increase technology adoption over "learning by observing"? It will compare the relative effectiveness of single demonstration plots (the standard approach) to more distributed demonstration strategies which allow more people to experiment with new technology. The Demonstration Plot Evaluation will focus on the crops sub-component.
Component 1: Technology Generation and Adaptation;
Component 2: Technology Adoption;
Component 3: Water Management;
Component 4: Project Management.
The Impact Evaluation (IE) of the IAPP project will contribute to understanding the drivers of technology adoption through two lenses. First, the overall project approach will be evaluated using a randomized phase-in of project villages (referred to as the "Overall Project Evaluation"). The Overall Project Evaluation will measure the effects of Components 2 and 3 of IAPP. All sub-components will be measured, with special focus on the crops and fisheries sub-components. Second, innovations will be tested through a randomized control trial to understand what approach to demonstration plots can deliver higher results (referred to as the "Demonstration Plot Evaluation"). The Demonstration Plot Evaluation is designed to test a fundamental question about technology adoption: to what extent can "learning by doing" increase technology adoption over "learning by observing"? It will compare the relative effectiveness of single demonstration plots (the standard approach) to more distributed demonstration strategies which allow more people to experiment with new technology. The Demonstration Plot Evaluation will focus on the crops sub-component.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households, Individuals
Scope
Notes
The scope of the Impact Evaluation of the Integrated Agricultural Productivity Project includes:
HOUSEHOLD
-Household Roster
-Education
-Labor
-Housing
-Social Networks
-Assets, Income and Expenditures
-Savings and Access to Finance
-Household Gardens
-Food Security
-Risk and Ambiguity Aversion
-Formal Insurance and Negative Shocks
AGRICULTURE
-Access to Extension and Other Trainings
-Farmer Groups
-Production
-Labor for Basic Agricultural Activities
-Irrigation
-Inputs
-Technologies
LIVESTOCK, POULTRY AND FISHERY
HOUSEHOLD
-Household Roster
-Education
-Labor
-Housing
-Social Networks
-Assets, Income and Expenditures
-Savings and Access to Finance
-Household Gardens
-Food Security
-Risk and Ambiguity Aversion
-Formal Insurance and Negative Shocks
AGRICULTURE
-Access to Extension and Other Trainings
-Farmer Groups
-Production
-Labor for Basic Agricultural Activities
-Irrigation
-Inputs
-Technologies
LIVESTOCK, POULTRY AND FISHERY
Topics
| Topic | Vocabulary |
|---|---|
| Agriculture & Rural Development | FAO |
| Food (production, crisis) | FAO |
Coverage
Geographic Coverage
North: Rangpur, Kurigram, Nilfamari and Lalmonirhat districts.
South: Barisal, Patuakhali, Barguna and Jhalokathi districts
South: Barisal, Patuakhali, Barguna and Jhalokathi districts
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Florence Kondylis | DIME, Development Research Group, World Bank |
| Maria Jones | DIME, Development Research Group, World Bank |
| Daniel Stein | DIME, Development Research Group, World Bank |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| The Global Agriculture and Food Security Program | GAFSP | Funding |
Sampling
Sampling Procedure
IAPP is comprised of two evaluation designs (i) technology adoption evaluation, and (ii) demonstration plot evaluation. Six districts (Kurigram, Nilfamari, Lalmonirhat, Patuakhali, Barguna, and Jhalokati) are only part of the technology adoption evaluation. In these six districts, eight unions were selected for the impact evaluation surveys. Within each union, two villages were surveyed. Each of these villages is eligible for all four components of the IAPP (crops, fisheries, livestock, and water management interventions). In each union, one of the sampled villages received IAPP interventions in 2012 and the other did not receive interventions until 2014.
Prior to the baseline survey, a full census of the sampled villages in these six districts was conducted to identify households eligible for and likely to participate in IAPP. IAPP interventions are based at the level of the farmer group, but at the time of the baseline survey, farmer groups were not yet formed. For that reason, census data was used to construct a sampling frame of likely participants in IAPP crop and fisheries groups. In each village, 16 households were sampled, half of which were selected as eligible for the crops groups and half for the fisheries groups. Eligibility was determined by IAPP targeting criteria, prioritizing crop farmers with marginal or small landholdings, and fishermen with access to ponds between 15-50 decimals. After sampling, the IAPP teams reached out to sampled farmers and attempted to involve them in IAPP groups. However, very few sampled farmers ended up joining livestock groups.
Two districts (Rangpur and Barisal) are included in both the technology adoption evaluation and the demonstration plots evaluation, and as such the sampling strategy in these districts was slightly different. Significantly more villages had to be sampled in these districts because of the DPE tests variations in project implementation. In all, 110 villages were sampled in each district.
The sample in the six districts in the technology adoption evaluation, the sample is representative of farmers who were eligible for participation in IAPP and were invited to join. The sample in the two additional technology adoption districts is representative of farmers who were eligible for participation in IAPP and were part of the initial IAPP group formation.
To read about sampling strategy in baseline survey, please refer to the document: iapp_baseline_report_final_with_appendices.pdf provided under the Related Materials tab.
Prior to the baseline survey, a full census of the sampled villages in these six districts was conducted to identify households eligible for and likely to participate in IAPP. IAPP interventions are based at the level of the farmer group, but at the time of the baseline survey, farmer groups were not yet formed. For that reason, census data was used to construct a sampling frame of likely participants in IAPP crop and fisheries groups. In each village, 16 households were sampled, half of which were selected as eligible for the crops groups and half for the fisheries groups. Eligibility was determined by IAPP targeting criteria, prioritizing crop farmers with marginal or small landholdings, and fishermen with access to ponds between 15-50 decimals. After sampling, the IAPP teams reached out to sampled farmers and attempted to involve them in IAPP groups. However, very few sampled farmers ended up joining livestock groups.
Two districts (Rangpur and Barisal) are included in both the technology adoption evaluation and the demonstration plots evaluation, and as such the sampling strategy in these districts was slightly different. Significantly more villages had to be sampled in these districts because of the DPE tests variations in project implementation. In all, 110 villages were sampled in each district.
The sample in the six districts in the technology adoption evaluation, the sample is representative of farmers who were eligible for participation in IAPP and were invited to join. The sample in the two additional technology adoption districts is representative of farmers who were eligible for participation in IAPP and were part of the initial IAPP group formation.
To read about sampling strategy in baseline survey, please refer to the document: iapp_baseline_report_final_with_appendices.pdf provided under the Related Materials tab.
Weighting
Considering the different sampling strategies explained above, we constructed probability weights to account for the consequent overrepresentation of Barisal and Rangpur districts. Table 1 in the study report shows the distribution of the sample across districts, separated into treatment and control, weighted and unweighted.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2014-06-01 | 2014-08-30 |
Data Collection Mode
Face-to-face [f2f]
Access policy
Contacts
| Name | Affiliation | URL |
|---|---|---|
| Microdata Library | The World Bank | microdata.worldbank.org |
Confidentiality
The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO
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- The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO;
- The micro dataset cannot be re-disseminated by users or shared with anyone other than the individuals that are granted access to the micro dataset by FAO.
- The micro dataset will only be used for statistical and/or research purposes;
- Any results derived from the micro dataset will be used solely for reporting aggregated information, and not for any specific individual entities or data subjects;
- The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO;
- The micro dataset cannot be re-disseminated by users or shared with anyone other than the individuals that are granted access to the micro dataset by FAO.
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:
Kondylis, Florence., Maria Jones., Daniel Stein. DIME, Development Research Group, World Bank. Impact Evaluation of the Integrated Agricultural Productivity Project 2014, Midline Household Survey - Round 2 (IAPPIE-ML2 2014). Ref: BGD_2014_IAPPIE-ML2_v01_M. 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:
Kondylis, Florence., Maria Jones., Daniel Stein. DIME, Development Research Group, World Bank. Impact Evaluation of the Integrated Agricultural Productivity Project 2014, Midline Household Survey - Round 2 (IAPPIE-ML2 2014). Ref: BGD_2014_IAPPIE-ML2_v01_M. 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_BGD_2014_IAPPIE-W2_v01_EN_M_v01_A_OCS_FAO
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank | Documentation of the DDI |
| Office of Chief Statistician | OCS | Food and Agriculture Organization | Metadata adoption for FAM |
DDI Document version
BGD_2014_IAPPIE-W2_v01_EN_M_v01_A_OCS_v01