Instrumental Variables Estimation and Weak-Identification-Robust Inference Based on a Conditional Quantile Restriction
Vadim Marmer () and
Shinichi Sakata
Microeconomics.ca working papers from Vancouver School of Economics
Abstract:
Extending the L1-IV approach proposed by Sakata (1997, 2007), we develop a new method, named the $rho_{tau}$-IV estimation, to estimate structural equations based on the conditional quantile restriction imposed on the error terms. We study the asymptotic behavior of the proposed estimator and show how to make statistical inferences on the regression parameters. Given practical importance of weak identification, a highlight of the paper is a proposal of a test robust to the weak identification. The statistics used in our method can be viewed as a natural counterpart of the Anderson and Rubin's (1949) statistic in the $rho_{tau}$-IV estimation.
Keywords: quantile regression; instrumental variables; weak identification (search for similar items in EconPapers)
JEL-codes: C21 C26 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2011-09-28, Revised 2011-09-28
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 (2)
Downloads: (external link)
http://microeconomics.ca/vadim_marmer/cqriv-20110817-2-ss.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 503 Service Unavailable (http://microeconomics.ca/vadim_marmer/cqriv-20110817-2-ss.pdf [302 Found]--> https://match.microeconomics.ca/vadim_marmer/cqriv-20110817-2-ss.pdf)
Related works:
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:ubc:pmicro:vadim_marmer-2011-26
Access Statistics for this paper
More papers in Microeconomics.ca working papers from Vancouver School of Economics
Bibliographic data for series maintained by Maureen Chin ().