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Modelling Time-Varying Parameters in Panel Data State-Space Frameworks: An Application to the Feldstein–Horioka Puzzle

  • Mariam Camarero
  • Juan SapenaEmail author
  • Cecilio Tamarit
Article
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Abstract

In this paper, we develop a very flexible and comprehensive state-space framework for modeling time series data. Our research extends the simple canonical model usually employed in the literature, into a panel-data time-varying parameters framework, combining fixed (both common and country-specific) and varying components. Under some specific circumstances, this setting can be understood as a mean-reverting panel time-series model, where the mean fixed parameter can, at the same time, include a deterministic trend. Regarding the transition equation, our structure allows for the estimation of different autoregressive alternatives, and include control instruments, whose coefficients can be set-up either common or idiosyncratic. This is particularly useful to detect asymmetries among individuals (countries) to common shocks. We develop a GAUSS code that allows for the introduction of restrictions regarding the variances of both the transition and measurement equations. Finally, we use this empirical framework to test for the Feldstein–Horioka puzzle in a 17-country panel. The results show its usefulness for solving complexities in macroeconomic empirical research.

Keywords

Feldstein–Horioka puzzle Panel unit root tests Multiple structural breaks Common factors Kalman Filter Time varying parameters 

JEL Classification

C23 F32 F36 

Notes

Acknowledgements

The authors are indebted to James D. Hamilton and J. LL. Carrion-i-Silvestre for providing them with the Gauss codes to implement some of the tests used in the paper. They also thank comments and suggestions from participants in the 5th ISCEF Symposium 2018 (Paris).

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.INTECO Joint Research Unit, Department of EconomicsUniversitat Jaume ICastellon de la PlanaSpain
  2. 2.Faculty of Economics and ManagementCatholic University of ValenciaValenciaSpain
  3. 3.INTECO Joint Research Unit, Department of Applied Economics IIUniversity of ValenciaValenciaSpain

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