Regression Discontinuity Inference with Specification Error
David S. Lee and
David Card
No 322, NBER Technical Working Papers from National Bureau of Economic Research, Inc
Abstract:
A regression discontinuity (RD) research design is appropriate for program evaluation problems in which treatment status (or the probability of treatment) depends on whether an observed covariate exceeds a fixed threshold. In many applications the treatment-determining covariate is discrete. This makes it impossible to compare outcomes for observations "just above" and "just below" the treatment threshold, and requires the researcher to choose a functional form for the relationship between the treatment variable and the outcomes of interest. We propose a simple econometric procedure to account for uncertainty in the choice of functional form for RD designs with discrete support. In particular, we model deviations of the true regression function from a given approximating function -- the specification errors -- as random. Conventional standard errors ignore the group structure induced by specification errors and tend to overstate the precision of the estimated program impacts. The proposed inference procedure that allows for specification error also has a natural interpretation within a Bayesian framework.
JEL-codes: C1 C5 J0 (search for similar items in EconPapers)
Date: 2006-03
New Economics Papers: this item is included in nep-ecm
Note: TWP
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)
Downloads: (external link)
http://www.nber.org/papers/t0322.pdf (application/pdf)
Related works:
Journal Article: Regression discontinuity inference with specification error (2008) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberte:0322
Ordering information: This working paper can be ordered from
http://www.nber.org/papers/t0322
Access Statistics for this paper
More papers in NBER Technical Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().