DDI_CPV_2006_MCC-WMS_v01_M Millennium Challenge Corporation 2015-01-15 NADA Version 1.0 (January 2015) Version 2.0 (June 2015). Edited version based on Version 01 (DDI-MCC-CPV-WMAS-IND-2012-v1) that was done by Millennium Challenge Corporation. Water Management and Services 2006-2013 MCC-WMS 2006-13 CPV_2006_MCC-WMS_v01_M Clifford Zinnes Christopher Nicoletti NADA Millennium Challenge Corporation Monitoring & Evaluation Division Independent Performance Evaluation Raw data for internal use only Irrigation Agriculture Farmers Water supply investment Agriculture and Irrigation This evaluation will investigate how adoption of drip irrigation technology, access to credit and conversion from traditional crop subsistence level farming to high value horticultural and fruit crops will impact household incomes of participating farmers distinct from non-participating farmer households. In order to fully measure the impact of these activities on farmer household income, MCC intends to conduct a post-compact evaluation which will compare the change in average household income prior to and following participation in the program. The fundamental research question to be answered is “Do the increased costs of investment in drip irrigation technology, access to credit and conversion from traditional crop subsistence level farming to high value horticultural and fruit crops increase annual agricultural production sufficient to raise participating farmer households out of rural poverty? Republic of Cabo Verde The islands of Fogo, Santo Antão, and Saint Nicholas in Cabo Verde Individuals Farmers in treatment and control areas Sample survey data [ssd] Instituto Nacional de Estatística de Cabo Verde The sampling frame comprises several districts from one watershed on each island. Approximately 21 farmer groups (the primary statistical unit or PSU) received access to irrigation, each with 5 to 10 farmers (the secondary sampling unit or SSU) per PSU. Neither the locations for the intervention nor assignment of locations to treatment and comparison were selected randomly by project designers. Treatment zones were chosen based on their suitability for new infrastructure; comparison zones were chosen based on expert opinion on what constituted comparable counterfactuals along relevant dimensions (see below). Hence, in addition to the need to correct for potential selection bias, the external validity of the evaluation will be limited to other similar locations. On the other hand, since censuses were administered, there would be no sampling error. The intended stratification was by island (watershed) and head-of-household gender. The agency contracted to carry out the surveys consistently failed to collect key data properly and the consultant hired to assess data quality did not detect this failure, leading to a re-worked evaluation design and sampling plan. This was developed using a multi-site hierarchical design to meet generally accepted levels of rigor: a statistical power of 80 percent at a level of significance of 5 percent, assuming that site and farmergroup effects together capture 70 percent of impact variance. Under a fixed-effects design, a minimum detectable effect size (MDES) of 20 percent would be achievable (US$1,000 spread over a 5-year period, or about $200 per year). Here, just 5 treated and 5 (synthesized) comparison farmers (SSUs) per PSU would be needed for a total sample size of 210. Under a randomeffects design (with a treatment effect variance of 5 percent), a MDES of 22-25 percent should be achievable. Here, an equal number of 8-10 treated and (synthesized) comparison farmers would be required for a total sample size of 336 to 420. These power calculations indicate that while overall impacts could be inferred for a sample pooled across the three watersheds, the only detectable disaggregated impact for this MDES range would be the overall impact on Santo Antão. Analogous power calculations find that gender-specific impacts could only be detected in a fixed-effects specification at an MDES of 24 percent and if the sample were pooled across the three watersheds. These results are due to the limited size of the comparison group and relatively lower number of female heads of household in the sample. The original design of the cyclical surveys did not permit some of the key priorities of the MCC (such as gender impact) to be addressed and was sub-optimal with regard to the size and extent of the comparison group. Therefore, the cyclical surveys were dropped completely as a source of evaluation baseline data and instead the evaluation used the relevant data from the Baseline Agricultural Census and Socioeconomic Census of 2006. In 2013 a single survey instrument that combined the relevant questions from these two baseline censuses was administered for the evaluation endline. Millennium Challenge Corporation Millennium Challenge Corporation http://data.mcc.gov/evaluations/index.php/catalog/154 Cost: None Nicoletti, Christopher and Clifford Zinnes. Impact Evaluation of the MCC WMAS Project in Cape Verde Compact. Jaunary 2012.