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  <docDscr>
    <citation>
      <titlStmt>
        <titl>
          DDI-NER-IE-EDU-2011-v4
        </titl>
        <IDNo>
          DDI-MCC-NER-IE-EDU-2011-v01
        </IDNo>
      </titlStmt>
      <prodStmt>
        <producer abbr="Mathematica" role="Independent Evaluator">
          Mathematica Policy Research
        </producer>
        <prodDate date="2017-06-01">
          2017-06-01
        </prodDate>
        <software version="4.0.9" date="2013-04-23">
          Nesstar Publisher
        </software>
      </prodStmt>
      <verStmt>
        <version>
          Version 1
        </version>
        <notes>
          Primary school age children in rural Niger
        </notes>
      </verStmt>
    </citation>
    <docSrc>
      <titlStmt>
        <titl>
          Niger Threshold I
        </titl>
      </titlStmt>
      <prodStmt>
        <prodPlac>
          Education (Edu)
        </prodPlac>
      </prodStmt>
      <notes>
        Mathematica Policy Research conducted a rigorous evaluation of the component to increase girls’ education, IMAGINE (IMprove the educAtion of Girls In NigEr), under the first phase of the Niger Threshold Program, which included the construction of girl friendly schools. The evaluation assessed whether, and the extent to which, the program affected the school enrollment, attendance and performance of children in the 68 villages where IMAGINE was implemented.
      </notes>
    </docSrc>
    <notes>
      The objective of IMAGINE was to increase girls' school enrollment, attendance and completion rates through the construction of new girl-friendly schools and a set of complementary activities.
    </notes>
  </docDscr>
  <stdyDscr>
    <citation>
      <titlStmt>
        <titl>
          IMAGINE
        </titl>
        <IDNo>
          DDI-MCC-NER-IE-EDU-2011-v01
        </IDNo>
      </titlStmt>
      <rspStmt>
        <AuthEnty>
          Mathematica Policy Research
        </AuthEnty>
      </rspStmt>
      <prodStmt>
        <software version="4.0.9" date="2013-04-23">
          Nesstar Publisher
        </software>
        <fundAg abbr="MCC">
          Millennium Challenge Corporation
        </fundAg>
      </prodStmt>
      <distStmt>
        <contact/>
      </distStmt>
      <serStmt>
        <serName>
          Independent Impact Evaluation
        </serName>
      </serStmt>
      <verStmt>
        <version>
          Anonymized dataset for public distribution
        </version>
        <verResp affiliation="Randomization"/>
      </verStmt>
    </citation>
    <stdyInfo>
      <subject>
        <keyword>
          IMAGINE
        </keyword>
        <keyword>
          Niger
        </keyword>
        <keyword>
          Niger Threshold Program
        </keyword>
        <keyword>
          Girls' education
        </keyword>
        <keyword>
          School construction
        </keyword>
        <keyword>
          Early education assessments
        </keyword>
        <topcClas>
          Basic skills education
        </topcClas>
        <topcClas>
          Compulsory and preschool education
        </topcClas>
        <topcClas>
          Educational policy
        </topcClas>
        <topcClas>
          Children
        </topcClas>
        <topcClas>
          Youth
        </topcClas>
        <topcClas vocab="MCC Sector">
          Education
        </topcClas>
      </subject>
      <abstract>
        <![CDATA[This impact evaluation uses random assignment at the village level to estimate impacts of the IMAGINE program on enrollment, attendance, learning and other education outcomes for primary school-age children in Niger.  IMAGINE follow-up data were collected in 2011. NECS Wave 1 data (which were also used to estimate longer term impacts of IMAGINE) were collected in 2013. 

After one year (using the data collected in 2011) the Impact Evaluation of Niger's IMAGINE program found that IMAGINE had a 4.3 percentage point positive impact on primary school enrollment, no impact on attendance, and no impact on math and French test scores. The program impacts were generally larger for girls than for boys. For girls, the program had an 8 percentage point positive impact on enrollment and a 5.4 percentage point impact on attendance. The program had no impact on girls’ math scores, though there is suggestive evidence it may have had a positive impact of 0.09 standard deviations on girls’ French test scores. No significant impacts were detected for boys’ enrollment, attendance, or test scores. Finally, impacts were larger for younger children (ages 7-10), than for those between the ages of 10 and 12.

After four years (using data collected in 2013 during the NECS Wave 1 data collection), the Niger IMAGINE Long-Term Evaluation found that IMAGINE had a 8.3 percentage point positive impact on enrollment and a  7.9 percentage point negative impact on absenteeism.  On average, children in treatment villages scored 0.13 standard deviations higher on the math assessment than children in control villages (significant at the 5 percent level). Test scores in French for children in treatment villages were higher than in control villages, but were not statistically significant. The evaluation found  large and significant impacts of the program on enrollment, attendance, and math scores for females,
compared to more modest and less significant impacts for males.]]>
      </abstract>
      <sumDscr>
        <collDate date="2011-01" event="start" cycle="First follow-up"/>
        <collDate date="2011-02" event="end" cycle="First follow-up"/>
        <collDate date="2013-10" event="start" cycle="Second follow-up"/>
        <collDate date="2013-11" event="end" cycle="Second follow-up"/>
        <nation abbr="NER">
          Niger
        </nation>
        <geogCover>
          The program was implemented in rural villages throughout Niger.
        </geogCover>
        <anlyUnit>
          Individuals, households, schools, and community
        </anlyUnit>
        <universe>
          <![CDATA[IMAGINE: Households and children ages 5-12 living in rural Niger.

NECS Wave 1: Households and children ages 5-14 living in rural Niger.]]>
        </universe>
        <dataKind>
          Sample survey data [ssd]
        </dataKind>
      </sumDscr>
    </stdyInfo>
    <method>
      <dataColl>
        <dataCollector affiliation="IMAGINE data collection">
          University of Ougadougou
        </dataCollector>
        <dataCollector affiliation="IMAGINE data collection ">
          University of Niamey
        </dataCollector>
        <dataCollector abbr="CIERPA" affiliation="NECS Wave 1 data collection">
          Centre International d’Etudes et de Recherches Sur Les Populations Africaines
        </dataCollector>
        <sampProc>
          <![CDATA[The IMAGINE sample contains 178 villages, from which 40 households with school age children were to be selected per village. We encountered 11 villages that had fewer than 40 eligible households, leading to 149 fewer households in the sample than initially anticipated.  As a result, our sample contains information from 6,791 households, 16,351 children between the ages of 5-12.  Village census data was collected as well as information on the school(s) in the village. Information for 198 schools is in the sample. The response rate is 99.9% for households, and 100% for the school questionnaire. These response rates exclude the 3 villages that were not surveyed because of security issues. 

The NECS Wave 1 sample contains 204 villages, from which 40 households with school age children were to be selected per village.  We encountered 22 villages that had fewer than 40 eligible households, leading to 267 fewer households in the sample than initially anticipated.  As a result, our wave 1 sample contains information from 7,893 households, 17,266 children between the ages of 5-14.  Village level information was also gathered, as was information that was directly observable for the main school in each village. Information for 202 schools is in the sample. The response rate is 99.9% for households, 94.6% for individual children, and 99.0% for school infrastructure.]]>
        </sampProc>
        <deviat>
          For the IMAGINE data collection, we were unable to visit 3 villages due to insecurity in the region.
        </deviat>
        <resInstru>
          Individuals, households, schools, and community
        </resInstru>
        <sources/>
        <collSitu>
          Please refer to the Impact Evaluation of Niger's IMAGINE Program Final Report for more information on the IMAGINE data collection and the Niger NECS Impact Evaluation Baseline Report for more information on the NECS Wave 1 data collection.
        </collSitu>
        <actMin>
          <![CDATA[For IMAGINE, the data collection team hired and trained 54 interviewers to collect village, household, invidual and school data. They were organized by linguistic groups into 9 teams, with each team comprised of 5 interviewers led by an experienced field supervisor. The teams were then assigned a region and surveys were conducted simultaneously throughout the country. 

For NECS Wave 1, the data collection team hired and trained 56 interviewers to collect household and school data. They were organized by linguistic groups into 14 teams, with each team comprised of 3 interviewers led by an experienced field supervisor. The teams were then assigned a region and surveys were conducted simultaneously throughout the country.]]>
        </actMin>
        <weight>
          There are no weights included in the public use data.
        </weight>
        <cleanOps>
          <![CDATA[Following completion of the IMAGINE data collection activities, the local data collection firm entered and cleaned the data using SPSS statistical analysis software. A team from Mathematica worked with the data collectors and oversaw the data entry and cleaning process. To verify that the data were entered correctly, we first spot-checked original questionnaires to ensure that the data collection was conducted according to protocol. Then, we randomly chose hard copy surveys from entire villages from different regions to check for quality and completeness. Finally, we compared data entered on the hard copies against data entered into the database. During this time, we also conducted preliminary checks on the data set for out-of-scope responses, item non-response, and inconsistent patterns. In addition, we tested and confirmed the ability to merge the household and school data.
 
For the NECS Wave 1 data collection, the local data collection firm entered and cleaned the data using The Census and Survey Processing System (CSPro).  Double data entry of 10% of the sample was implemented, and the accuracy of the double-entered data with the data that was originally received was checked. During this time, we also conducted preliminary checks on the data set for out-of-scope responses, item nonresponse, and inconsistent patterns, working with CIERPA to make the appropriate adjustments. In addition, we tested and confirmed the ability to merge the household and school data.

Upon receipt of the complete datasets, Mathematica conducted additional cleaning to correct out of range responses, address item nonresponse and inconsistent patterns, and improve the merge rate between the household and the school data.]]>
        </cleanOps>
      </dataColl>
      <notes>
        <![CDATA[IMAGINE: The local data collection firm manually entered  the data using SPSS statistical analysis software.

NECS Wave 1: The local data collection firm manually entered  the data using The Census and Survey Processing System (CSPro). 10% of the data were double entered for verification purposes.]]>
      </notes>
      <anlyInfo>
        <respRate>
          <![CDATA[The IMAGINE response rate is 99.9% for households, and 100% for the school questionnaire. These response rates exclude the 3 villages that were not surveyed because of security issues.  

The NECS Wave 1 response rate is 99.9% for households, 94.6% for individual children, and 99.0% for school infrastructure.]]>
        </respRate>
        <EstSmpErr>
          There are no estimates of sampling error included in the public use data.
        </EstSmpErr>
      </anlyInfo>
    </method>
    <dataAccs>
      <useStmt>
        <citReq>
          <![CDATA[Dumitrescu, A., D. Levy, C. Orfield, and M. Sloan. Niger IMAGINE Data 2011. V02. Washington, DC., Mathematica Policy Research. 

Bagby, E., A. Dumitrescu, C. Orfield, and M. Sloan. Niger2 Wave 1 Data 2014. V01. Washington, DC., Mathematica Policy Research.]]>
        </citReq>
        <conditions>
          Public use files, accessible to all
        </conditions>
      </useStmt>
    </dataAccs>
  </stdyDscr>
  <dataDscr/>
</codeBook>
