{"doc_desc":{"idno":"DDI_IND_2018_ILMSDPBM-IE_v01_M_WB","producers":[{"name":"Development Economics Data Group","abbr":"DECDG","affiliation":"The World Bank","role":"Documentation of the study"}],"prod_date":"2025-06-24T04:00:00.000Z","version_statement":{"version":"Version 01 (June 2025)","version_date":"2025-06-24T04:00:00.000Z"}},"study_desc":{"title_statement":{"idno":"IND_2018_ILMSDPBM-IE_v01_M","title":"Improving Last-Mile Service Delivery using Phone-Based Monitoring Impact Evaluation 2018"},"authoring_entity":[{"name":"Jeffrey Weaver","affiliation":"University of Southern California"},{"name":"Karthik Muralidharan","affiliation":"UC San Diego, J-PAL, NBER, and BREAD"},{"name":"Paul Niehaus","affiliation":"UC San Diego, J-PAL, NBER, and BREAD"},{"name":"Sandip Sukhtankar","affiliation":"University of Virginia, J-PAL, and BREAD"}],"production_statement":{"funding_agencies":[{"name":"Strategic Impact Evaluation Fund","abbr":"SIEF","role":""}]},"distribution_statement":{"contact":[{"name":"Karthik Muralidharan","affiliation":" UC San Diego, J-PAL, NBER, and BREAD","email":"","uri":""},{"name":"Paul Niehaus","affiliation":" UC San Diego, J-PAL, NBER, and BREAD ","email":"","uri":""},{"name":"Sandip Sukhtankar","affiliation":" University of Virginia, J-PAL, and BREAD","email":"","uri":""},{"name":"Jeffrey Weaver","affiliation":"University of Southern California","email":"","uri":""},{"name":"Strategic Impact Evaluation Fund","affiliation":"The World Bank","email":"siefimpact@worldbank.org","uri":"https:\/\/www.worldbank.org\/en\/programs\/sief-trust-fund"}],"depositor":[{"name":"Meyhar Mohammed LNU","abbr":"","affiliation":"The World Bank","uri":""}],"deposit_date":"2024-01-25T05:00:00.000Z"},"series_statement":{"series_name":"Administrative Records, Other (ad\/oth]"},"version_statement":{"version":"v01: Edited, anonymized datasets for public distribution","version_date":"2025-06-24T04:00:00.000Z"},"study_info":{"keywords":[{"keyword":"State Capacity","vocab":"","uri":""},{"keyword":"Service Delivery","vocab":"","uri":""},{"keyword":"Mobile Phones","vocab":"","uri":""},{"keyword":"India","vocab":"","uri":""}],"abstract":"Improving \"last-mile\" public-service delivery is a recurring challenge in developing countries. Could the widespread adoption of mobile phones provide a scalable, cost-effective means for improvement? We use a large-scale experiment to evaluate the impact of phone-based monitoring on a program that transferred nearly a billion dollars to 5.7 million Indian farmers. In randomly-selected jurisdictions, officials were informed that program implementation would be measured via calls with beneficiaries. This led to a 7.8% reduction in the number of farmers who did not receive their transfers. The program was highly cost-effective, costing 3.6 cents for each additional dollar delivered.","coll_dates":[{"start":"2018-05-08","end":"2018-09-26","cycle":"All"}],"nation":[{"name":"India","abbreviation":"IND"}],"geog_coverage":"Telangana, India","analysis_unit":"District, mandal, MAO, plot","data_kind":"Administrative records data [adm]","notes":"This study covers topics related to state capacity, service delivery, and mobile phones."},"method":{"data_collection":{"sampling_procedure":"Details on sampling and experimental design can be found on the AEA RCT Registry located here: https:\/\/www.socialscienceregistry.org\/trials\/2942","research_instrument":"All variable names and descriptions are included in the \"readme.pdf\" file, which is available to download. \n\nNotes on the readme file: \n1) For labels and descriptions of the variables in the BalanceTests4.dta dataset, refer to BalanceTests3.dta in the readme file. The variables appear there. \n2) The rand and mandal_id variables in the miscdata.dta dataset and the dist_id, dist_mandal_uid_MC, and village_uid_MC variables in the mcdata.dta dataset are generated ID variables.","coll_situation":"Details on data collection can be found on the AEA RCT Registry located here: https:\/\/www.socialscienceregistry.org\/trials\/2942\n\nThe following publication, available to download, is supplemented by the data in this project:\nMuralidharan, Karthik, Paul Niehaus, Sandip Sukhtankar, and Jeffrey Weaver. \u201cImproving Last-Mile Service Delivery Using Phone-Based Monitoring.\u201d American Economic Journal: Applied Economics 13, no. 2 (April 2021): 52\u201382. https:\/\/doi.org\/10.1257\/app.20190783."},"method_notes":"Replication files are available to download."},"data_access":{"dataset_availability":{"access_place":"World Bank Microdata Library","access_place_url":""},"dataset_use":{"conf_dec":[{"txt":"","required":"true","form_no":"","form_uri":""}],"contact":[{"name":"Strategic Impact Evaluation Fund","affiliation":"The World Bank","email":"siefimpact@worldbank.org","uri":"https:\/\/www.worldbank.org\/en\/programs\/sief-trust-fund"}],"cit_req":"Use of the dataset must be acknowledged using a citation which would include:\n\u2022the identification of the Primary Investigator\n\u2022the title of the survey (including country, acronym and year of implementation)\n\u2022the survey reference number\n\u2022the source and date of download\n\nExample:\nJeffrey Weaver (University of Southern California), Karthik Muralidharan (UC San Diego, J-PAL, NBER, and BREAD), Paul Niehaus (UC San Diego, J-PAL, NBER, and BREAD) and Sandip Sukhtankar (University of Virginia, J-PAL, and BREAD). India - Improving Last-Mile Service Delivery using Phone-Based Monitoring Impact Evaluation 2018. Ref: IND_2018_ILMSDPBM-IE_v01_M. Dataset downloaded from [URL] on [date].","conditions":"Public Access","disclaimer":"The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses."}}},"schematype":"survey","tags":[{"tag":"DOI"}]}