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

Arturas Juodis*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

11 Citations (Scopus)
551 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)650-693
Number of pages44
JournalEconometric Reviews
Volume37
Issue number6
DOIs
Publication statusPublished - 2018

Keywords

  • Bias correction
  • dynamic panel data
  • fixed T consistency
  • maximum likelihood
  • Monte Carlo simulation
  • INSTRUMENTAL-VARIABLE ESTIMATION
  • MAXIMUM-LIKELIHOOD-ESTIMATION
  • BIAS-CORRECTED ESTIMATION
  • AR(1)/UNIT ROOT MODEL
  • VECTOR AUTOREGRESSIONS
  • TIME-SERIES
  • EFFICIENT ESTIMATION
  • INITIAL CONDITIONS
  • COMPONENTS MODELS
  • GMM ESTIMATOR

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