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Large Bayesian VARs for Binary and Censored Variables

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  • Joshua C. C. Chan
  • Michael Pfarrhofer

Abstract

We extend the standard VAR to jointly model the dynamics of binary, censored and continuous variables, and develop an efficient estimation approach that scales well to high-dimensional settings. In an out-of-sample forecasting exercise, we show that the proposed VARs forecast recessions and short-term interest rates well. We demonstrate the utility of the proposed framework using a wide rage of empirical applications, including conditional forecasting and a structural analysis that examines the dynamic effects of a financial shock on recession probabilities.

Suggested Citation

  • Joshua C. C. Chan & Michael Pfarrhofer, 2025. "Large Bayesian VARs for Binary and Censored Variables," Papers 2506.01422, arXiv.org.
    • Handle: RePEc:arx:papers:2506.01422
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    References listed on IDEAS

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