cag-case

hks-epod · Apr 3, 2017 · 7f790c8 · 7f790c8
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diff --git a/img/HKSlogo_EPoD_digitalLR.png b/img/HKSlogo_EPoD_digitalLR.png
diff --git a/www/index.html b/www/index.html
@@ -22,7 +22,7 @@
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-            <a href="http://epod.cid.harvard.edu/" target="_blank"><img alt="EPoD logo" src="img/logo.png" class="img-sidebar"></a>
+            <a href="http://epod.cid.harvard.edu/" target="_blank"><img alt="EPoD logo" src="img/HKSlogo_EPoD_digitalLR.png" class="img-sidebar"></a>
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@@ -119,7 +119,7 @@ <h2 id="challenge">A challenge</h2>
    Now add this: if you have a quick look at data routinely collected in the programme’s database, you see certain red flags. Beneficiaries of a workfare programme must log in “person days” of work to receive payment, and in a few districts, programme expenditures far exceed the number of recorded person days. It looks like fraud, but it escaped your analysis since it only happened in a few districts, and they stayed in the hat when you made your random draw.
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-   This question – how best to approach an audit of MGNREGA – was exactly the one that senior officials at the CAG posed to researchers at <a href="http://epod.cid.harvard.edu/" target="_blank">Evidence for Policy Design (EPoD) in 2014</a>. The two organizations were attempting to find common areas of focus for a possible multi-year engagement, so the CAG gave the Harvard-based group an audit they had already conducted and asked how they would have done it differently. EPoD produced an Evidence Brief detailing how, if the auditors had used an alternative sampling method, they would have been able to pay special attention to both the districts with a large eligible population and the “red flag” districts, and still preserve the random nature and geographical breadth of the sample. We describe the method below.
+   This question – how best to approach an audit of MGNREGA – was exactly the one that senior officials at the CAG posed to researchers at <a href="http://epod.cid.harvard.edu/" target="_blank">Evidence for Policy Design (EPoD)</a>  in 2014. The two organizations were attempting to find common areas of focus for a possible multi-year engagement, so the CAG gave the Harvard-based group an audit they had already conducted and asked how they would have done it differently. EPoD produced an Evidence Brief detailing how, if the auditors had used an alternative sampling method, they would have been able to pay special attention to both the districts with a large eligible population and the “red flag” districts, and still preserve the random nature and geographical breadth of the sample. We describe the method below.
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    EPoD continued its collaboration with auditors from the CAG over the following two years. As part of the <a href="http://epod.cid.harvard.edu/bcure" target="_blank">Building Capacity to Use Research Evidence (BCURE)</a> programme, funded by UK Aid, the researchers provided technical assistance on two live audits in 2015. They also conducted trainings of the CAG’s Indian Audits and Accounts Service officers, assisted in writing survey questionnaires, and trained field surveyors in new, tablet-based methods.