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First difference transformation in panel VAR models: Robustness, estimation, and inference

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  • Artūras Juodis

Abstract

This article considers estimation of Panel Vector Autoregressive Models of order 1 (PVAR(1)) with focus on fixed T consistent estimation methods in First Differences (FD) with additional strictly exogenous regressors. Additional results for the Panel FD ordinary least squares (OLS) estimator and the FDLS type estimator of Han and Phillips (2010) are provided. Furthermore, we simplify the analysis of Binder et al. (2005) by providing additional analytical results and extend the original model by taking into account possible cross-sectional heteroscedasticity and presence of strictly exogenous regressors. We show that in the three wave panel the log-likelihood function of the unrestricted Transformed Maximum Likelihood (TML) estimator might violate the global identification assumption. The finite-sample performance of the analyzed methods is investigated in a Monte Carlo study.

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  • Artūras Juodis, 2018. "First difference transformation in panel VAR models: Robustness, estimation, and inference," Econometric Reviews, Taylor & Francis Journals, vol. 37(6), pages 650-693, July.
    • Handle: RePEc:taf:emetrv:v:37:y:2018:i:6:p:650-693
    DOI: 10.1080/07474938.2016.1139559
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    Cited by:

    1. Artūras Juodis & Yiannis Karavias & Vasilis Sarafidis, 2021. "A homogeneous approach to testing for Granger non-causality in heterogeneous panels," Empirical Economics, Springer, vol. 60(1), pages 93-112, January.
    2. Saban Nazlioglu & Cagin Karul, 2024. "Testing for Granger causality in heterogeneous panels with cross-sectional dependence," Empirical Economics, Springer, vol. 67(4), pages 1541-1579, October.
    3. Elvis Dze Achuo, 2020. "How Efficient are Government Stringency Responses in Curbing the Spread of the COVID-19 Pandemic?," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 4(8), pages 629-635, August.
    4. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    5. Breitung, Jörg & Kripfganz, Sebastian & Hayakawa, Kazuhiko, 2022. "Bias-corrected method of moments estimators for dynamic panel data models," Econometrics and Statistics, Elsevier, vol. 24(C), pages 116-132.
    6. Juodis, Artūras & Poldermans, Rutger W., 2021. "Backward mean transformation in unit root panel data models," Economics Letters, Elsevier, vol. 201(C).

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