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Fields Changed

Registration

Field Before After
Study Withdrawn No
Intervention Completion Date November 30, 2017
Data Collection Complete Yes
Final Sample Size: Number of Clusters (Unit of Randomization) 132 blocks; 87 treatment, 45 control
Was attrition correlated with treatment status? No
Final Sample Size: Total Number of Observations 132 blocks; 3960 households
Final Sample Size (or Number of Clusters) by Treatment Arms 87 treatment blocks, 45 control blocks
Public Data URL https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/YEKB95
Is there a restricted access data set available on request? No
Program Files Yes
Program Files URL https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/YEKB95
Data Collection Completion Date November 30, 2018
Is data available for public use? Yes
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Papers

Field Before After
Paper Abstract We study the impact of reforms that introduced more stringent, biometric ID requirements into India's largest social protection program, using large-scale randomized and natural experiments. Corruption fell but with substantial costs to legitimate beneficiaries, 1.5-2 million of whom lost access to benefits at some point during the reforms. At the same time, adverse effects appear to have been driven primarily by decisions about the way the transition was managed, illustrating both the risks of rapid reforms, and how the impacts of promising new technologies can be highly sensitive to the protocols governing their use.
Paper Citation Muralidharan, Karthik, Paul Niehaus, and Sandip Sukhtankar. "Identity verification standards in welfare programs: Experimental evidence from India." Review of Economics and Statistics (2023): 1-46.
Paper URL https://direct.mit.edu/rest/article/doi/10.1162/rest_a_01296/114767/Identity-Verification-Standards-in-Welfare
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