Semiparametric Bayesian inference in multiple equation models

Gary Koop, Dale J. Poirier, Justin Tobias

Research output: Contribution to journalArticle

21 Citations (Scopus)
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Abstract

This paper outlines an approach to Bayesian semiparametric regression in multiple equation models which can be used to carry out inference in seemingly unrelated regressions or simultaneous equations models with nonparametric components. The approach treats the points on each nonparametric regression line as unknown parameters and uses a prior on the degree of smoothness of each line to ensure valid posterior inference despite the fact that the number of parameters is greater than the number of observations. We develop an empirical Bayesian approach that allows us to estimate the prior smoothing hyperparameters from the data. An advantage of our semiparametric model is that it is written as a seemingly unrelated regressions model with independent normal-Wishart prior. Since this model is a common one, textbook results for posterior inference, model comparison, prediction and posterior computation are immediately available. We use this model in an application involving a two-equation structural model drawn from the labour and returns to schooling literatures.
Original languageEnglish
Pages (from-to)723-748
Number of pages25
JournalJournal of Applied Econometrics
Volume20
Issue number6
DOIs
Publication statusPublished - 9 Jun 2005

Fingerprint

regression
model comparison
structural model
textbook
Inference
Bayesian inference
labor
Seemingly unrelated regression
Structural equation model
Labor
Semiparametric model
Regression model
Bayesian approach
Nonparametric regression
Prediction
Model comparison
Semiparametric regression
Textbooks
Returns to schooling
Simultaneous equations model

Keywords

  • econometrics
  • finance
  • statistics
  • bayesian analysis
  • semiparametric regression

Cite this

Koop, Gary ; Poirier, Dale J. ; Tobias, Justin. / Semiparametric Bayesian inference in multiple equation models. In: Journal of Applied Econometrics. 2005 ; Vol. 20, No. 6. pp. 723-748.
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Semiparametric Bayesian inference in multiple equation models. / Koop, Gary; Poirier, Dale J.; Tobias, Justin.

In: Journal of Applied Econometrics, Vol. 20, No. 6, 09.06.2005, p. 723-748.

Research output: Contribution to journalArticle

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