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Identifying high-frequency shocks with Bayesian mixed-frequency VARs

Author

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  • Alessia Paccagnini
  • Fabio Parla

Abstract

We contribute to research on mixed-frequency regressions by introducing an innovative Bayesian approach. Based on a new “high-frequency” identification scheme, we provide novel empirical evidence of identifying uncertainty shock for the US economy. As main findings, we document a “temporal aggregation bias” when we adopt a common low frequency model instead of estimating a mixed-frequency framework. The bias is amplified when we identify a higher frequency shock.

Suggested Citation

  • Alessia Paccagnini & Fabio Parla, 2021. "Identifying high-frequency shocks with Bayesian mixed-frequency VARs," CAMA Working Papers 2021-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Handle: RePEc:een:camaaa:2021-26
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    File URL: https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2021-02/26_2021_paccagnini_parla.pdf
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    Keywords

    Bayesian mixed-frequency VAR; MIDAS; uncertainty shocks; macro-financial linkages;
    All these keywords.

    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
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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