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Conditional forecasts and uncertainty about forecast revisions in vector autoregressions

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  • Jarocinski, Marek

Abstract

This note simplifies the Waggoner and Zha (1999) formula for the conditional distribution of shocks, discusses its linear algebraic intuition, and shows how to account for the dependence between the conditional and unconditional predictive densities when comparing them.

Suggested Citation

  • Jarocinski, Marek, 2010. "Conditional forecasts and uncertainty about forecast revisions in vector autoregressions," Economics Letters, Elsevier, vol. 108(3), pages 257-259, September.
    • Handle: RePEc:eee:ecolet:v:108:y:2010:i:3:p:257-259
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    References listed on IDEAS

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    1. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148, Elsevier.
    2. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
    3. Marek Jarocinski & Frank Smets, 2008. "House prices and the stance of monetary policy," Review, Federal Reserve Bank of St. Louis, vol. 90(Jul), pages 339-366.
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    Cited by:

    1. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 791-897, Elsevier.
    2. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    3. Michael W. McCracken & Joseph T. McGillicuddy, 2019. "An empirical investigation of direct and iterated multistep conditional forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 181-204, March.
    4. De Backer, Bruno & Dewachter, Hans & Iania, Leonardo, 2021. "Macrofinancial information on the post-COVID-19 economic recovery: Will it be V, U or L-shaped?," Finance Research Letters, Elsevier, vol. 43(C).
    5. Antolín-Díaz, Juan & Petrella, Ivan & Rubio-Ramírez, Juan F., 2021. "Structural scenario analysis with SVARs," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 798-815.
    6. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
    7. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers (Old Series) 1413, Federal Reserve Bank of Cleveland.
    8. Camba-Mendez, Gonzalo, 2012. "Conditional forecasts on SVAR models using the Kalman filter," Economics Letters, Elsevier, vol. 115(3), pages 376-378.
    9. Chan, Joshua C.C. & Pettenuzzo, Davide & Poon, Aubrey & Zhu, Dan, 2025. "Conditional forecasts in large Bayesian VARs with multiple equality and inequality constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 173(C).
    10. De Santis, Roberto A., 2015. "A measure of redenomination risk," Working Paper Series 1785, European Central Bank.
    11. Cafiso, Gianluca & Missale, Alessandro & Rivolta, Giulia, 2025. "The credit channel of the sovereign spread: A Bayesian SVAR analysis," Economic Modelling, Elsevier, vol. 144(C).
    12. Dieppe, Alistair & van Roye, Björn & Legrand, Romain, 2016. "The BEAR toolbox," Working Paper Series 1934, European Central Bank.

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