 Jumpy or Kinky? Regression Discontinuity without the DiscontinuityNo 111207, Working Papers from University of California-Irvine, Department of Economics Abstract: Regression Discontinuity (RD) models identify local treatment effects by associating a discrete change in the mean outcome with a corresponding discrete change in the probability of treatment at a known threshold of a running variable. This paper shows that it is possible to identify the RD model treatment effect without a discontinuity. In particular, identification can come from a slope change (a kink) instead of a discrete level change (a jump) in the treatment probability. The intuition is based on L'hopital's rule. The identification results can also be interpreted using instrumental variables models. Estimators are proposed that can be applied in the presence or absence of a discontinuity, by exploiting either a jump, or a kink, or both. The proposed estimators are applied to investigate the "retirement-consumption puzzle." In particular, I estimate the impact of retirement on household food consumption by exploiting changes in the retirement probability at 62, the early retirement age in the US. Keywords: Regression discontinuity; Fuzzy design; Local average treatment effect; Identification; Jump; Kink; Threshold; Retirement; Consumption (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:irv:wpaper:111207 Access Statistics for this paper More papers in Working Papers from University of California-Irvine, Department of Economics Contact information at EDIRC. |
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