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<codeBook version="1.2.2" ID="SEN_2011_MCC-IWRM_v01_M" xml-lang="en" xmlns="http://www.icpsr.umich.edu/DDI" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.icpsr.umich.edu/DDI http://www.icpsr.umich.edu/DDI/Version1-2-2.xsd">
<docDscr>
  <citation>
    <titlStmt>
      <IDNo>DDI_SEN_2011_MCC-IWRM_v01_M</IDNo>
    </titlStmt>
    <prodStmt>
      <producer abbr="MCC" affiliation="" role="Review of Metadata">Millennium Challenge Corporation</producer>
      <prodDate date="2014-11-05">2014-11-05</prodDate>
      <software version="v5">NADA</software>
    </prodStmt>
    <verStmt>
      <version>Version 1.1 (December 2014)
Version 2.0 (June 2015). Edited version based on Version 01 (DDI-MCC-SEN-IMPAQ-IWRM-2014-v01) that was done by Millennium Challenge Corporation.</version>
    </verStmt>
  </citation>
</docDscr>
<stdyDscr>
  <citation>
    <titlStmt>
      <titl>Irrigation and Water Resource Management 2011-2012</titl>
      <subTitl/>
      <altTitl>MCC-IWRM 2011-12</altTitl>
      <parTitl/>
      <IDNo>SEN_2011_MCC-IWRM_v01_M</IDNo>
    </titlStmt>
    <rspStmt>
      <AuthEnty affiliation="">Impaq International</AuthEnty>
    </rspStmt>
    <prodStmt>
      <copyright/>
      <software version="5.0" date="2021-04-14">NADA</software>
      <fundAg abbr="MCC" role="">Millennium Challenge Corporation</fundAg>
      <grantNo/>
    </prodStmt>
    <distStmt>
      <contact affiliation="Millennium Challenge Corporation" URI="" email="impact-eval@mcc.gov">Monitoring &amp; Evaluation Division</contact>
      <depDate date=""/>
      <distDate date=""/>
    </distStmt>
    <serStmt>
      <serName>Independent Performance Evaluation</serName>
      <serInfo/>
    </serStmt>
    <verStmt>
      <version date="">Anonymized dataset for public distribution</version>
      <verResp/>
      <notes/>
    </verStmt>
    <biblCit format=""/>
    <notes/>
  </citation>
  <stdyInfo>
    <studyBudget/>
    <subject>
                  
                  
    </subject>
    <abstract>This evaluation report presents findings from the baseline data collected for the Irrigation and Water Resources Management (IWRM) project, which serves as the primary data source for evaluating the activities of the IWRM project.  This report provides an overview of the current irrigation and agricultural situation in the Senegal River Valley. Additionally, the report provides a comparison of treatment and comparison households to check for systematic differences between groups at the time of the baseline survey. 

In the IWRM, the selection of areas to receive the project interventions was not random. Rather, it was based on a variety of factors, including political, social and environmental. In the absence of random assignment, we will use a Difference-in-Differences (DID) methodology combined with propensity score matching (DID-PSM) to estimate the impact of the IWRM activities. The baseline data includes community level and household level data. Community level data includes information about regional and socioeconomic characteristics of the village. Household level data sets were collected in 3 waves, one for each agricultural season.</abstract>
    <sumDscr>
      <collDate date="2011-12-01" event="start" cycle="Passage 1"/>
      <collDate date="2012-03-30" event="end" cycle="Passage 1"/>
      <collDate date="2012-04-01" event="start" cycle="Passage 2"/>
      <collDate date="2012-07-31" event="end" cycle="Passage 2"/>
      <collDate date="2012-08-01" event="start" cycle="Passage 3"/>
      <collDate date="2012-11-30" event="end" cycle="Passage 3"/>
      <nation abbr="SEN">Senegal</nation>
      <geogCover>The Senegal River Valley (SRV). The SRV is located in the northern part of Senegal, in the delta of the Senegal River and in Podor District.</geogCover>
      <geogUnit/>
      <anlyUnit/>
      <universe>Habitants in the Senegal River Valley (SRV) in the northern part of Senegal

Three waves of data have been planned for the baseline and follow-up surveys in the Delta and Podor areas to cover the different agricultural seasons.</universe>
      <dataKind>Observation data/ratings [obs]</dataKind>
    </sumDscr>
    <!-- qualityStatement - ddi2.5 - complex type
     
     This structure consists of two parts, standardsCompliance and otherQualityStatements. 
     In standardsCompliance list all specific standards complied with during the execution of this 
     study. Note the standard name and producer and how the study complied with the standard. 
     Enter any additional quality statements in otherQualityStatements.
     
     -->
    <qualityStatement>
      <standardsCompliance>
        <standard>
          <standardName/>
          <producer/>
        </standard>
        <complianceDescription/>
      </standardsCompliance>
      <otherQualityStatement/>
    </qualityStatement>
    <notes/>
    <!-- exPostEvaluation ddi2.5
      Use this section to describe evaluation procedures not address in data evaluation processes. 
      These may include issues such as timing of the study, sequencing issues, cost/budget issues, 
      relevance, instituional or legal arrangments etc. of the study. 
      
      The completionDate attribute holds the date the evaluation was completed. 
      The type attribute is an optional type to identify the type of evaluation with or without 
      the use of a controlled vocabulary.
    -->
    <exPostEvaluation completionDate="" type="">
      <evaluationProcess/>
      <outcomes/>
    </exPostEvaluation>
  </stdyInfo>
  <method>
    <dataColl>
      <timeMeth/>
      <dataCollector abbr="ANSD" affiliation="">Agence Nationale de Statistique et de la Démographie</dataCollector>
      <!-- collectorTraining - DDI2.5
        
        Collector Training

        Describes the training provided to data collectors including internviewer training, process testing, 
        compliance with standards etc. This is repeatable for language and to capture different aspects of the 
        training process. The type attribute allows specification of the type of training being described.
        
        -->
      <collectorTraining type=""/>
      <frequenc/>
      <sampProc>To implement the DID analysis, we needed to draw the sample of households for the study from both the treatment and comparison areas. The previous evaluation contractor determined that the sample size needed to estimate the combined impact of the irrigation and land intervention in the Delta was 2,612 households: 1,306 from the treatment area and 1,306 from the comparison area.

For Podor, the sample size was initially constrained by the amount of land available for distribution, i.e. approximately 400 ha. MCA-S expected to distribute approximately 1 ha per household, meaning that the household sample size is approximately equivalent to the number of hectares available for distribution. The final sample size for Podor is 440 households in the treatment area and 440 households in the comparison area.</sampProc>
      <sampleFrame>
        <sampleFrameName/>
        <custodian/>
        <universe/>
        <frameUnit isPrimary="">
          <unitType numberOfUnits=""/>
        </frameUnit>
        <updateProcedure/>
      </sampleFrame>
      <deviat>To implement DID with ex-ante matching, households should be matched before the survey.  This requires a detailed enumeration in the treatment and comparison areas to collect a set of variables that can match treatment and comparison households. In the spring of 2012, the Agence Nationale de la Statistique et de la Démographie (ANSD) conducted extensive enumeration in the Delta area, including the Saint Louis and Dagana departments, for a total of about 11,600 households. IMPAQ used the enumeration files to sample and match households. The target sample sizes for the Delta were 1,306 treatment households and 1,306 matched comparison households. To achieve this sample size, IMPAQ provided slightly larger samples to ANSD to allow for some non-response because the survey effort may not have reached 100 percent of the sample. Specifically, we selected 1,637 treatment and 1,637 comparison households (about 25 percent more than the proposed sample sizes).  

From the enumeration file, we randomly sampled 1,637 treatment households. We then matched each treatment household with a comparison household identified as the most similar in relevant pre-treatment characteristics. 

In the spring of 2012, ANSD completed an extensive enumeration in the Podor area.  Specifically, 1,617 households were enumerated in the treatment area and 585 were enumerated in the comparison area. For the impact evaluation, it is important that the treatment group include households that will actually get the treatment (irrigation and land). However, at the time of sampling, we could not find a clear way to identify which households would receive irrigated land in Podor. Because the enumeration data includes 1,617 households in the treatment area and we needed to identify the 440 households that would receive land, a random sample would not ensure that we select enough households that actually receive land. 
 
Given the urgency of selecting the samples and proceeding with the survey, MCA-S and IMPAQ agreed to survey all households (1,617) in the enumerated treatment area. This approach ensured that our survey sample would capture the households that would receive land (treatment group). In addition, we agreed to survey a random sample of 440 households in the Podor comparison area (out of a total of 585 households in the enumeration). Moving forward quickly was very important to avoid wasting time and resources. Furthermore, waiting until spring 2014 (when land decisions are expected to be finalized) could have jeopardized our ability to have useful baseline data because the intervention may take place before the baseline data collection.</deviat>
      <collMode/>
      <resInstru/>
      <!-- instrumentDevelopment - DDI2.5             
        Describe any development work on the data collection instrument. Type attribute allows for the optional use of a defined development type with or without use of a controlled vocabulary.
        -->
      <instrumentDevelopment type=""/>
      <collSitu>Because most of the key outcome variables relate to agricultural production, they are season-dependent. Senegal has three cropping cycles. To obtain reliable farm production/yields estimates, MCA-S decided to interview producers shortly after each harvest. As a result, three waves of data have been planned for the baseline and follow-up surveys in the Delta and Podor areas to cover the different agricultural seasons. The three seasons are:
- Passage 1 - December 1, 2011 - March 31, 2012 [Contre Saison Froide ]  
- Passage 2 - April 1, 2012 - July 31, 2012                 [Contre Saison Chaude] 
- Passage 3 - August 1, 2012 - November 31, 2012                 [Rainy season].</collSitu>
      <actMin/>
      <ConOps/>
      <weight/>
      <cleanOps/>
    </dataColl>
    <notes/>
    <anlyInfo>
      <respRate/>
      <EstSmpErr/>
      <dataAppr/>
    </anlyInfo>
    <stdyClas/>
    <dataProcessing type=""/>
    <codingInstructions relatedProcesses="" type="">
      <txt/>
      <command formalLanguage=""/>
    </codingInstructions>
  </method>
  <dataAccs>
    <setAvail>
      <accsPlac URI="http://data.mcc.gov/evaluations/index.php/catalog/123">Millennium Challenge Corporation</accsPlac>
      <origArch>Millennium Challenge Corporation
http://data.mcc.gov/evaluations/index.php/catalog/123
Cost: None</origArch>
      <avlStatus/>
      <collSize/>
      <complete/>
      <fileQnty/>
      <notes/>
    </setAvail>
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      <restrctn/>
      <citReq/>
      <deposReq/>
      <conditions/>
      <disclaimer/>
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    <notes/>
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  <notes/>
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