• Media type: E-Book
  • Title: Regression Discontinuity Designs with a Continuous Treatment
  • Contributor: Dong, Yingying [Author]; Lee, Ying-Ying [Other]; Gou, Michael [Other]
  • Published: [S.l.]: SSRN, [2020]
  • Extent: 1 Online-Ressource (65 p)
  • Language: English
  • DOI: 10.2139/ssrn.3167541
  • Identifier:
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments April 1, 2019 erstellt
  • Description: The standard regression discontinuity (RD) design deals with a binary treatment. Manyempirical applications of RD designs involve continuous treatments. This paper establishesidentification and robust bias-corrected inference for such RD design. Causal identificationis achieved by utilizing any changes in the distribution of the continuous treatment at the RDthreshold (including the usual mean change as a special case). Our robust estimand incorporatesthe standard RD estimand as a special case. Applying the proposed approach, we estimatethe impacts of capital holdings on bank failure in the pre-Great Depression era in the UnitedStates. Our RD design takes advantage of the minimum capital requirements, which changediscontinuously with town size
  • Access State: Open Access