Randomization Inference for Difference-in-Differences with Few Treated Clusters
Download full text from publisher
Other versions of this item:
- James G. MacKinnon & Matthew D. Webb, 2016. "Randomization Inference for Difference-in-Differences with Few Treated Clusters," Carleton Economic Papers 16-11, Carleton University, Department of Economics.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Ferman, Bruno & Pinto, Cristine, 2015.
"Inference in Differences-in-Differences with Few Treated Groups and Heteroskedasticity,"
67665, University Library of Munich, Germany.
- Ferman, Bruno & Pinto, Cristine Campos de Xavier, 2015. "Inference in differences-in-differences with few treated groups and heteroskedasticity," Textos para discussão 406, FGV/EESP - Escola de Economia de São Paulo, Getulio Vargas Foundation (Brazil).
- James G. MacKinnon & Matthew D. Webb, 2017. "Pitfalls when Estimating Treatment Effects Using Clustered Data," Working Papers 1387, Queen's University, Department of Economics.
- repec:tsj:stataj:y:17:y:2017:i:3:p:630-651 is not listed on IDEAS
- Timothy J. Bartik & Nathan Sotherland, 2015. "Migration and Housing Price Effects of Place-Based College Scholarships," Upjohn Working Papers and Journal Articles 15-245, W.E. Upjohn Institute for Employment Research.
- Christopher S. Carpenter & Emily C. Lawler, 2017. "Direct and Spillover Effects of Middle School Vaccination Requirements," NBER Working Papers 23107, National Bureau of Economic Research, Inc.
- Masayoshi Hayashi, 2017. "Do Central Grants Affect Welfare Caseloads? Evidence from Public Assistance in Japan," CIRJE F-Series CIRJE-F-1064, CIRJE, Faculty of Economics, University of Tokyo.
More about this item
KeywordsCRVE; grouped data; clustered data; panel data; randomization inference; difference-in-differences; wild cluster bootstrap;
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
NEP fieldsThis paper has been announced in the following NEP Reports:
StatisticsAccess and download statistics
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:qed:wpaper:1355. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mark Babcock). General contact details of provider: http://edirc.repec.org/data/qedquca.html .
We have no references for this item. You can help adding them by using this form .