sivqr: Smoothed IV quantile regression

David Kaplan

No 2009, Working Papers from Department of Economics, University of Missouri

Abstract: In this article, I introduce the sivqr command, which estimates the coefficients of the instrumental variables (IV) quantile regression model introduced by Chernozhukov and Hansen (2005). This model complements the alternative models underlying the commands cqiv, ivqreg2, and ivqte, and the sivqr command offers advantages over the apocryphal ivqreg command. Computationally, sivqr implements the smoothed estimator of Kaplan and Sun (2017), who show the smoothing improves both computation time and statistical accuracy. Standard errors are computed by Bayesian bootstrap; for non-i.i.d. sampling, sivqr is compatible with the bootstrap and svy bootstrap prefixes. I discuss syntax and the underlying methodology. Simulation and empirical examples illustrate the new sivqr command

Keywords: endogeneity; instrumental variables; structural (search for similar items in EconPapers)
JEL-codes: C87 (search for similar items in EconPapers)
Pages: 29 pages
Date: 2020
New Economics Papers: this item is included in nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://drive.google.com/file/d/1X7LbAIY_HGDexzhr5 ... 3Cu/view?usp=sharing (application/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:umc:wpaper:2009

Access Statistics for this paper

More papers in Working Papers from Department of Economics, University of Missouri Contact information at EDIRC.
Bibliographic data for series maintained by Chao Gu ().