RWA_2015-2018_LWHIE_v01_M
Impact, Maintenance, and Sustainability of Irrigation Impact Evaluation Survey 2015-2018
Baseline, First, Second, Third Follow-up
Name | Country code |
---|---|
Rwanda | RWA |
Agricultural Survey [ag/oth]
The Baseline and follow ups surveys are part of an impact evaluation of the Land Husbandry, Water Harvesting and Hillside Irrigation (LWH) Project in Rwanda. The Ministry of Agriculture in Rwanda (MinAgri) is implementing the LWH project with technical assistance from the World Bank. The LWH project ran from 2010 to 2018.
Sample survey data [ssd]
Household, Plot
Version 01. The datasets include the baselines and 3 follow up surveys for the first 3 schemes (in Karongi and Nyanza) and the baseline and 1 follow up survey for the 4th site (Rwamagana).
2019-09-30
The surveys covered the following topics:
The study covers 5 districts in Rwanda.
Name | Affiliation |
---|---|
Florence Kondylis | The World Bank |
Maria Jones | The World Bank |
John Loeser | The World Bank |
Jeremy Magruder | University of Berkeley |
Name |
---|
Global Agriculture Food Security Program |
International Initiative for Impact Evaluation |
International Growth Center |
For three of the sites that are being used for the spatial regression discontinuity analysis (K12, N23, and R34), we divided the site into 3 areas - CA buffer (BCA), CA Catchment buffer (BCAC), and CA terraces (TCA). BCA is the area inside of the CA (CA, below main canal) within 50m of the boundary of the CA. BCAC is the area in the CA Catchment (CAC, above main canal) within 50m of the boundary of the CA. TCA is the terraced farmland that is in the CA, but more than 50m from the boundary of the CA. The third site will be used for the within-CA experimental designs only, and as a result we focused our sampling in one area - the CA terraces (TCA).
We constructed our household sampling by dropping a uniform grid of points across the full site at 2-meter resolution, and then sampling points within the grid. After each point was sampled, we excluded any points within 10m of that point (to keep from selecting multiple points too close together).
Enumerators were then given GPS devices with the locations of the points, and sent to each point, with a key informant (often the village leader). For each point, they were asked to identify if the point was on cultivable land (this was to discard forest, swamps, thick bushes, bodies of water, or other terrain which would make cultivation impossible). They were asked to record, for points in cultivable land, in SurveyCTO, the following:
Additionally, they were asked to save their GPS track at the end of the day, as a way of tracking the number of hours they spent checking points and to verify that they visited each point. We used the data from this listing to construct a roster of all the unique names of cultivators, clustering points together when the names seemed identical. This roster (which contained the name of the individual, their village and phone number, the descriptions of the plots, and the villages in which the plots were located (identified using village shapefiles) and were organized by village) were then used to contact village leaders and verify that the listed individuals in fact existed. Multiple follow-ups were sometimes needed when village leaders suggested that one individual lived in a different village, or multiple village leaders said an individual lived in their village.
Finally, a sample plot was selected for each verified 2689 households. To select this sample plot, one point was randomly selected for each household. The probability of selecting a particular point was weighted - a weight of 1 was assigned to points in the BCA and BCAC, and a different weight was assigned for points in the TCA, to balance the number of sample plots in these areas.
The questionnaires being used to collect the datasets are divided into different modules. As the main objective of the LWH project is to increase the productivity and commercialization of hillside agriculture through irrigation and other land husbandry interventions, the agricultural modules are the most detailed. The modules contain several sections related to irrigation, since the objective of the studies are to better understand the impacts of irrigation on plot and household-level outcomes. In addition, the questionnaires contain modules on housing, labor, income/expenditures, shocks, agricultural extension, social networks and cooperation, financial access, and household assets. There is also a section dedicated to plot mapping.
Start | End | Cycle |
---|---|---|
2015-08-24 | 2015-10-27 | Baseline (Karongi and Nyanza) |
2017-05-15 | 2017-06-27 | Follow up 1 (Karongi and Nyanza) |
2017-11-13 | 2017-12-12 | Follow up 2 (Karongi and Nyanza) |
2018-10-31 | 2018-12-04 | Follow up 3 (Karongi and Nyanza) |
2018-01-23 | 2018-02-23 | Baseline (Rwamangana) |
2018-12-05 | 2018-12-19 | Follow up 1 (Rwamangana) |
In Karongi and Nyanza districts, the baseline and first to third follow ups surveys were conducted from August to October 2015, May to June 2017, November to December 2017 and October to December 2018 respectively.
In Rwamagana district, the baseline and first follow up survey were conducted from January to February 2018 and December 2018 respectively.
Name |
---|
Roshni Khincha |
The use of the datasets must be acknowledged using a citation which would include:
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.
Name | Affiliation | |
---|---|---|
Florence Kondylis | World Bank | fkondylis@worldbank.org |
Maria Jones | World Bank | mjones5@worldbank.org |
John Loeser | World Bank | jloeser@worldbank.org |
Jeremy Magruder | University of Berkeley | jmagruder@berkeley.edu |
DDI_RWA_2015-2018_LWHIE_v01_M
Name | Affiliation | Role |
---|---|---|
Development Economics Data Group | The World Bank | Documentation of the DDI |
2019-12-18
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