2015
DOI: 10.1016/j.jeconom.2014.09.002
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Testing for time-invariant unobserved heterogeneity in generalized linear models for panel data

Abstract: Recent literature on panel data has emphasized the importance of accounting for time-varying unobserved heterogeneity, which may stem either from time-varying omitted variables or macro-level shocks that affect each individual unit differently. In this paper, we propose a computationally convenient test for the null hypothesis of time-invariant individual effects. The proposed test is an application of Hausman (1978) specification test procedure and can be applied to generalized linear models for panel data, a… Show more

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Cited by 25 publications
(8 citation statements)
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“…We adjusted the panel-data regression for time to account for underlying trends and the total TCS score of each EU MS. GDP per capita was not included in the model as it did not improve the fit of the model. The fixed-effects specification accounts for time-invariant unobserved factors within each country [32].…”
Section: Discussionmentioning
confidence: 99%
“…We adjusted the panel-data regression for time to account for underlying trends and the total TCS score of each EU MS. GDP per capita was not included in the model as it did not improve the fit of the model. The fixed-effects specification accounts for time-invariant unobserved factors within each country [32].…”
Section: Discussionmentioning
confidence: 99%
“…Next, we estimate the FE and RE model on our panel data samples, and Hausman-test was used to test the orthogonality between regressors and unobserved time-invariant effects 15…”
Section: Discussionmentioning
confidence: 99%
“…However, this may be unrealistic where time varying unobserved heterogeneity could arise as a result of unobserved time varying omitted variables or macro level shocks which influence each observational unit (N) in a different way. As a consequence, parameter estimates may be biased when the individual effects are assumed to be time invariant when in fact they are really time varying, see Bartolucci et al (2013). This is also likely to be more problematic in long panels.…”
Section: Random Time Invariant Unobserved Heterogeneitymentioning
confidence: 99%