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Bayesian vector autoregressions

Author

Listed:
  • Silvia Miranda Agrippino

    (Bank of England and Centre for Economic Performance)

  • Giovanni Ricco

    (OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po)

Abstract

This article reviews Bayesian inference methods for Vector Autoregression models, commonly used priors for economic and financial variables, and applications to structural analysis and forecasting.

Suggested Citation

  • Silvia Miranda Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," SciencePo Working papers Main hal-03458277, HAL.
    • Handle: RePEc:hal:spmain:hal-03458277
    DOI: 10.1093/acrefore/9780190625979.013.478
    Note: View the original document on HAL open archive server: https://hal-sciencespo.archives-ouvertes.fr/hal-03458277
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    8. Kunovac, Davor & Palenzuela, Diego Rodriguez & Sun, Yiqiao, 2022. "A new optimum currency area index for the euro area," Working Paper Series 2730, European Central Bank.
    9. Demiessie, Habtamu, 2020. "COVID-19 Pandemic Uncertainty Shock Impact on Macroeconomic Stability in Ethiopia," MPRA Paper 102625, University Library of Munich, Germany, revised 31 Aug 2020.
    10. Karau, Sören, 2023. "Monetary policy and Bitcoin," Journal of International Money and Finance, Elsevier, vol. 137(C).
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    More about this item

    Keywords

    Bayesian inference; Vector Autoregression Models; BVAR; SVAR; forecasting;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • 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

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