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Econometrics, Volume 10, Issue 3

September 2022 - 4 articles

Cover Story: CCE is one of the most common methods with which to estimate panels with multifactor error structures. In this paper, we extend the CCE estimation to a dynamic panel data model with nonstationary multifactor error structures and establish the associated asymptotics. Monte Carlo simulations and empirical examples are also conducted to consider the finite sample performances of CCE estimations. View this paper
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Articles (4)

  • Article
  • Open Access
3,648 Views
17 Pages

This paper proposes a new spatial lag regression model which addresses global spatial autocorrelation arising from cross-sectional dependence between counts. Our approach offers an intuitive interpretation of the spatial correlation parameter as a me...

  • Article
  • Open Access
1 Citations
3,315 Views
41 Pages

A Parsimonious Test of Constancy of a Positive Definite Correlation Matrix in a Multivariate Time-Varying GARCH Model

  • Jian Kang,
  • Johan Stax Jakobsen,
  • Annastiina Silvennoinen,
  • Timo Teräsvirta and
  • Glen Wade

We construct a parsimonious test of constancy of the correlation matrix in the multivariate conditional correlation GARCH model, where the GARCH equations are time-varying. The alternative to constancy is that the correlations change deterministicall...

  • Article
  • Open Access
7 Citations
8,692 Views
27 Pages

In this paper, we consider the estimation of a dynamic panel data model with non-stationary multi-factor error structures. We adopted the common correlated effect (CCE) estimation and established the asymptotic properties of the CCE and common correl...

  • Article
  • Open Access
1 Citations
3,888 Views
24 Pages

This paper improves the existing literature on the shrinkage of high dimensional model and parameter spaces through Bayesian priors and Markov Chains algorithms. A hierarchical semiparametric Bayes approach is developed to overtake limits and misspec...

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Econometrics - ISSN 2225-1146