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 language | English |
|---|---|
| Pages (from-to) | 165-266 |
| Number of pages | 102 |
| Journal | Foundations and Trends in Econometrics |
| Volume | 3 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2009 Dec 1 |
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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 journal › Article
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TY - JOUR
T1 - Dealing with endogeneity in regression models with dynamic coefficients
AU - Kim, Chang-Jin
PY - 2009/12/1
Y1 - 2009/12/1
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=84868609171&partnerID=8YFLogxK
U2 - 10.1561/0800000010
DO - 10.1561/0800000010
M3 - Article
AN - SCOPUS:84868609171
VL - 3
SP - 165
EP - 266
JO - Foundations and Trends in Econometrics
JF - Foundations and Trends in Econometrics
SN - 1551-3076
IS - 3
ER -