Dealing with Endogeneity in Regression Models with Dynamic Coefficients

Chang-Jin Kim ()

Foundations and Trends(R) in Econometrics, 2010, vol. 3, issue 3, 165-266

Abstract: The purpose of this monograph is to present a unified econometric framework for dealing with the issues of endogeneity in Markovswitching models and time-varying parameter models, as developed by Kim (2004, 2006, 2009), Kim and Nelson (2006), Kim et al. (2008), and Kim and Kim (2009). While Cogley and Sargent (2002), Primiceri (2005), Sims and Zha (2006), and Sims et al. (2008) consider estimation of simultaneous equations models with stochastic coefficients as a system, we deal with the LIML (limited information maximum likelihood) estimation of a single equation of interest out of a simultaneous equations model. Our main focus is on the two-step estimation procedures based on the control function approach, and we show how the problem of generated regressors can be addressed in second-step regressions.

Keywords: Endogeneity; Markov-switching models; Time-series econometrics; Regression; Econometrics; Macroeconomics; Finance (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://dx.doi.org/10.1561/0800000010 (application/xml)

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:now:fnteco:0800000010

Access Statistics for this article

More articles in Foundations and Trends(R) in Econometrics from now publishers
Bibliographic data for series maintained by Lucy Wiseman ().