Arbeitspapier

A robust approach to heteroskedasticity, error serial correlation and slope heterogeneity for large linear panel data models with interactive effects

In this paper, we propose a robust approach against heteroskedasticity, error serial correlation and slope heterogeneity for large linear panel data models. First, we establish the asymptotic validity of the Wald test based on the widely used panel heteroskedasticity and autocorrelation consistent (HAC) variance estimator of the pooled estimator under random coefficient models. Then, we show that a similar result holds with the proposed bias-corrected principal component-based estimators for models with unobserved interactive effects. Our new theoretical result justifies the use of the same slope estimator and the variance estimator, both for slope homogeneous and heterogeneous models. This robust approach can significantly reduce the model selection uncertainty for applied researchers. In addition, we propose a novel test for the correlation and dependence of the random coefficient with covariates. The test is of great importance, since the widely used estimators and/or its variance estimators can become inconsistent when the variation of coefficients depends on covariates, in general. The finite sample evidence supports the usefulness and reliability of our approach.

Sprache
Englisch

Erschienen in
Series: ISER Discussion Paper ; No. 1037

Klassifikation
Wirtschaft
Hypothesis Testing: General
Estimation: General
Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
Thema
panel data
slope heterogeneity
interactive effects
test for correlated random coefficients

Ereignis
Geistige Schöpfung
(wer)
Hayakawa, Kazuhiko
Nagata, Shuichi
Yamagata, Takashi
Ereignis
Veröffentlichung
(wer)
Osaka University, Institute of Social and Economic Research (ISER)
(wo)
Osaka
(wann)
2018

Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Hayakawa, Kazuhiko
  • Nagata, Shuichi
  • Yamagata, Takashi
  • Osaka University, Institute of Social and Economic Research (ISER)

Entstanden

  • 2018

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