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Bayesian Vector Autoregressions

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  • Tomasz Woźniak

Abstract

type="main" xml:lang="en"> This article provides an introduction to the burgeoning academic literature on Bayesian vector autoregressions, benchmark models for applied macroeconomic research. I first explain Bayes’ theorem and the derivation of the closed-form solution for the posterior distribution of the parameters of the model's given data. I further consider parameter shrinkage, a distinguishing feature of the prior distributions commonly employed in the analysis of large data. Finally, I describe the mechanisms that enable feasible computations for these linear models that efficiently extract the information content of many variables for economic forecasting and other applications.

Suggested Citation

  • Tomasz Woźniak, 2016. "Bayesian Vector Autoregressions," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 49(3), pages 365-380, September.
    • Handle: RePEc:bla:ausecr:v:49:y:2016:i:3:p:365-380
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    Cited by:

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    2. James Morley & Benjamin Wong, 2020. "Estimating and accounting for the output gap with large Bayesian vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 1-18, January.
    3. Berger, Tino & Richter, Julia & Wong, Benjamin, 2022. "A unified approach for jointly estimating the business and financial cycle, and the role of financial factors," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    4. Berger, Tino & Morley, James & Wong, Benjamin, 2023. "Nowcasting the output gap," Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
      • Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the output gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Morris, Stephen D., 2017. "DSGE pileups," Journal of Economic Dynamics and Control, Elsevier, vol. 74(C), pages 56-86.
    6. Sean Langcake & Tim Robinson, 2018. "Forecasting the Australian economy with DSGE and BVAR models," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 251-267, January.

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