A reformulation of the Hausman test for regression models with pooled cross-section-time-series data

Seung Ahn, Stuart Low

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

A Hausman test has been typically used to determine the consistency of the GLS estimator in static models with pooled cross-section-time-series data. Based on a GMM approach, we reformulate the Hausman test and find that it incorporates and tests only a limited set of moment restrictions. We also consider an alternative GMM statistic incorporating additional restrictions, which has power toward additional sources of model misspecification. Our Monte Carlo experiments demonstrate that while both the Hausman test and the alternative have good power detecting endogenous regressors, the alternative dominates if coefficients of regressors are nonstationary.

Original languageEnglish (US)
Pages (from-to)309-319
Number of pages11
JournalJournal of Econometrics
Volume71
Issue number1-2
StatePublished - Mar 1996

Fingerprint

Time Series Data
Reformulation
Regression Model
Cross section
Alternatives
Restriction
Model Misspecification
Monte Carlo Experiment
Statistic
Moment
Estimator
Time series data
Regression model
Hausman test
Coefficient
Demonstrate
Model

Keywords

  • GMM test
  • Hausman test
  • Non-stationary coefficients
  • Pooled cross-section-time-series data

ASJC Scopus subject areas

  • Economics and Econometrics
  • Finance
  • Statistics and Probability

Cite this

A reformulation of the Hausman test for regression models with pooled cross-section-time-series data. / Ahn, Seung; Low, Stuart.

In: Journal of Econometrics, Vol. 71, No. 1-2, 03.1996, p. 309-319.

Research output: Contribution to journalArticle

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