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Panel Vector Autoregressive Models: A Survey☆The views expressed in this article are those of the authors and do not necessarily reflect those of the ECB or the Eurosystem

In: VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims

Author

Listed:
  • Fabio Canova
  • Matteo Ciccarelli

Abstract

This article provides an overview of the panel vector autoregressive models (VAR) used in macroeconomics and finance to study the dynamic relationships between heterogeneous assets, households, firms, sectors, and countries. We discuss what their distinctive features are, what they are used for, and how they can be derived from economic theory. We also describe how they are estimated and how shock identification is performed. We compare panel VAR models to other approaches used in the literature to estimate dynamic models involving heterogeneous units. Finally, we show how structural time variation can be dealt with.

Suggested Citation

  • Fabio Canova & Matteo Ciccarelli, 2013. "Panel Vector Autoregressive Models: A Survey☆The views expressed in this article are those of the authors and do not necessarily reflect those of the ECB or the Eurosystem," Advances in Econometrics, in: VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims, volume 32, pages 205-246, Emerald Group Publishing Limited.
  • Handle: RePEc:eme:aecozz:s0731-9053(2013)0000031006
    DOI: 10.1108/S0731-9053(2013)0000031006
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    More about this item

    Keywords

    Panel VAR; estimation; identification; inference; C11; C30; C53;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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