Dealing with endogeneity in a time-varying parameter model: Joint estimation and two-step estimation procedures

Yunmi Kim, Chang-Jin Kim

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Summary In dealing with the problem of endogeneity in a time-varying parameter model, we develop the joint and two-step estimation procedures based on the control function approach. We show that a key to the success of the joint estimation procedure is in an appropriate state-space representation of the model. On the other hand, a correct treatment of the problem of generated regressors plays an important role in our two-step estimation procedure. Monte Carlo experiments confirm that the estimation procedures proposed in this paper work well in finite samples. Concerning our proposed endogeneity tests, the asymptotic distribution of both the likelihood ratio and Wald tests based on the second-step regression are reasonably well approximated by a χ2 distribution even in finite samples.

Original languageEnglish
Pages (from-to)487-497
Number of pages11
JournalEconometrics Journal
Volume14
Issue number3
DOIs
Publication statusPublished - 2011 Oct 1

Fingerprint

Two-step estimation
Time-varying parameter model
Endogeneity
Joint estimation
Finite sample
Control function
Generated regressors
State space
Monte Carlo experiment
Asymptotic distribution
Likelihood ratio test
Wald test

Keywords

  • Control function approach
  • Endogeneity
  • Generated regressors
  • Joint estimation procedure
  • Time-varying parameter model
  • Two-step estimation procedure

ASJC Scopus subject areas

  • Economics and Econometrics

Cite this

Dealing with endogeneity in a time-varying parameter model : Joint estimation and two-step estimation procedures. / Kim, Yunmi; Kim, Chang-Jin.

In: Econometrics Journal, Vol. 14, No. 3, 01.10.2011, p. 487-497.

Research output: Contribution to journalArticle

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