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Bayesian local projections

Author

Listed:
  • Silvia Miranda-Agrippino
  • Giovanni Ricco

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

Abstract

We propose a Bayesian approach to Local Projections that optimally addresses the empirical bias-variance tradeoff inherent in the choice between VARs and LPs. Bayesian Local Projections (BLP) regularise the LP regression models by using informative priors, thus estimating impulse response functions potentially better able to capture the properties of the data as compared to iterative VARs. In doing so, BLP preserve the flexibility of LPs to empirical model misspecification while retaining a degree of estimation uncertainty comparable to a Bayesian VAR with standard macroeconomic priors. As a regularised direct forecast, this framework is also a valuable alternative to BVARs for multivariate out-of-sample projections.

Suggested Citation

  • Silvia Miranda-Agrippino & Giovanni Ricco, 2021. "Bayesian local projections," Working Papers hal-03373574, HAL.
  • Handle: RePEc:hal:wpaper:hal-03373574
    Note: View the original document on HAL open archive server: https://sciencespo.hal.science/hal-03373574
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    References listed on IDEAS

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    Cited by:

    1. Atsushi Inoue & `Oscar Jord`a & Guido M. Kuersteiner, 2023. "Inference for Local Projections," Papers 2306.03073, arXiv.org, revised Aug 2024.
    2. Tomás Opazo, 2023. "The Heterogeneous Effect of Monetary Policy Shocks: Evidence for US Households," Working Papers Central Bank of Chile 992, Central Bank of Chile.

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    More about this item

    Keywords

    local projections; VARs; bayesian techniques; impulse response functions; direct forecasting;
    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
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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