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Economic Policy Uncertainty and Stock Market Returns in Pacific-Rim Countries: Evidence based on a Bayesian Panel VAR Model

Author

Listed:
  • Christina Christou

    (School of Economics and Management, Open University of Cyprus)

  • Juncal Cunado

    (University of Navarra, School of Economics, Spain)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria)

  • Christis Hassapis

    (Department of Economics, University of Cyprus)

Abstract

This paper examines the role of Economic Policy Uncertainty (EPU) on the stock market returns in a sample of 6 countries which includes Australia, Canada, China, Japan, Korea and the US using monthly data from January 1998 to December 2014. For our purpose, we use a restricted Panel Vector Autoregressive (PVAR) model estimated using the Stochastic Search Specification Selection (SSSS) prior (PVAR-SSSS). In order to account for international uncertainty spillovers, the impact of the own country’s EPU shocks and the US EPU shocks are considered. The main results suggest that stock market returns have not been significantly affected by the increased policy uncertainty levels observed during the last decade, except in the cases of Canada and the US. When uncertainty spillovers are considered, only Japanese and Korean stock market returns are influenced by US EPU shocks.

Suggested Citation

  • Christina Christou & Juncal Cunado & Rangan Gupta & Christis Hassapis, 2016. "Economic Policy Uncertainty and Stock Market Returns in Pacific-Rim Countries: Evidence based on a Bayesian Panel VAR Model," Working Papers 201661, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201661
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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