Threshold Regression with Endogeneity
Ping Yu and
Peter Phillips
Additional contact information
Ping Yu: University of Hong Kong
No 1966, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University
Abstract:
This paper studies estimation and specification testing in threshold regression with endogeneity. Three key results differ from those in regular models. First, both the threshold point and the threshold effect parameters are shown to be identified without the need for instrumentation. Second, in partially linear threshold models, both parametric and nonparametric components rely on the same data, which prima facie suggests identification failure. But, as shown here, the discontinuity structure of the threshold itself supplies identifying information for the parametric coefficients without the need for extra randomness in the regressors. Third, instrumentation plays different roles in the estimation of the system parameters, delivering identification for the structural coefficients in the usual way, but raising convergence rates for the threshold effect parameters and improving efficiency for the threshold point. Specification tests are developed to test for the presence of endogeneity and threshold effects without relying on instrumentation of the covariates. The threshold effect test extends conventional parametric structural change tests to the nonparametric case. A wild bootstrap procedure is suggested to deliver finite sample critical values for both tests. Simulation studies corroborate the theory and the asymptotics. An empirical application is conducted to explore the effects of 401(k) retirement programs on savings, illustrating the relevance of threshold models in treatment effects evaluation in the presence of endogeneity.
Keywords: Threshold regression; Endogeneity; Local shifter; Identification; Efficiency; Integrated difference kernel estimator; Regression discontinuity design; Optimal rate of convergence; Partial linear model; Specification test; U-statistic; Wild bootstrap; Threshold treatment model; 401(k) plan (search for similar items in EconPapers)
JEL-codes: C12 C13 C14 C21 C26 (search for similar items in EconPapers)
Pages: 84 pages
Date: 2014-12
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)
Published in Journal of Econometrics (March 2018), 203(1): 50-68
Downloads: (external link)
https://cowles.yale.edu/sites/default/files/files/pub/d19/d1966.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 404 Not Found
Related works:
Journal Article: Threshold regression with endogeneity (2018) 
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:cwl:cwldpp:1966
Ordering information: This working paper can be ordered from
Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA
The price is None.
Access Statistics for this paper
More papers in Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University Yale University, Box 208281, New Haven, CT 06520-8281 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Brittany Ladd ().