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Identifying high-frequency shocks with Bayesian mixed-frequency VARs


  • Alessia Paccagnini
  • Fabio Parla


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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    Cited by:

    1. Alain Hecq & Marie Ternes & Ines Wilms, 2023. "Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions," Papers 2301.10592,
    2. Alessandri, Piergiorgio & Gazzani, Andrea & Vicondoa, Alejandro, 2023. "Are the effects of uncertainty shocks big or small?," European Economic Review, Elsevier, vol. 158(C).

    More about this item


    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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