Dealing with endogeneity in regression models with dynamic coefficients

Research output: Contribution to journalArticle

6 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)165-266
Number of pages102
JournalFoundations and Trends in Econometrics
Volume3
Issue number3
DOIs
Publication statusPublished - 2009 Dec 1

Fingerprint

Regression model
Simultaneous equations model
Coefficients
Endogeneity
Control function
Econometrics
Maximum likelihood estimation
Two-step estimation
Generated regressors
Limited information
Time-varying parameter model

ASJC Scopus subject areas

  • Economics and Econometrics

Cite this

Dealing with endogeneity in regression models with dynamic coefficients. / Kim, Chang-Jin.

In: Foundations and Trends in Econometrics, Vol. 3, No. 3, 01.12.2009, p. 165-266.

Research output: Contribution to journalArticle

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