Randomized experiments from non-random selection in U.S. House elections.
This paper establishes the relatively weak conditions under which causal inferences from a regression-discontinuity (RD) analysis can be as credible as those from a randomized experiment, and hence under which the validity of the RD design can be tested by examining whether or not there is a discont...
| Publicado en: | Journal of Econometrics Vol. 142; no. 2; pp. 675 - 698 |
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| Formato: | Artículo |
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Elsevier Science
February 2008
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=511390447&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 511390447 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03044076 ECM jtl: Journal of Econometrics issn: 03044076 maglogo: N pubinfo: dt: February 2008 vid: 142 iid: 2 pid: 1004 pub: Elsevier Science artinfo: ui: 511390447 10.1016/j.jeconom.2007.05.004 ppf: 675 ppct: 23 formats: tig: atl: Randomized experiments from non-random selection in U.S. House elections. aug: au: Lee, David S. su: Experimental design United States legislators United States Congressional elections Regression analysis sug: subj: Experimental design United States legislators United States Congressional elections Regression analysis keyword: Congressmen -- Election ab: This paper establishes the relatively weak conditions under which causal inferences from a regression-discontinuity (RD) analysis can be as credible as those from a randomized experiment, and hence under which the validity of the RD design can be tested by examining whether or not there is a discontinuity in any pre-determined (or “baseline”) variables at the RD threshold. Specifically, consider a standard treatment evaluation problem in which treatment is assigned to an individual if and only if V>v0, but where v0 is a known threshold, and V is observable. V can depend on the individual's characteristics and choices, but there is also a random chance element: for each individual, there exists a well-defined probability distribution for V. The density function–allowed to differ arbitrarily across the population–is assumed to be continuous. It is formally established that treatment status here is as good as randomized in a local neighborhood of V=v0. These ideas are illustrated in an analysis of U.S. House elections, where the inherent uncertainty in the final vote count is plausible, which would imply that the party that wins is essentially randomized among elections decided by a narrow margin. The evidence is consistent with this prediction, which is then used to generate“near-experimental” causal estimates of the electoral advantage to incumbency. Copyright (c) 2007 Elsevier B.V. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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