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Specifying vector autoregressions for macroeconomic forecasting

Author

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  • Robert B. Litterman
Abstract
This paper describes a Bayesian specification procedure used to generate a vector autoregressive model for forecasting macroeconomic variables. The specification search is over parameters of a prior. This quasi-Bayesian approach is viewed as a flexible tool for constructing a filter which optimally extracts information about the future from a set of macroeconomic data. The procedure is applied to a set of data and a consistent improvement in forecasting performance is documented.

Suggested Citation

  • Robert B. Litterman, 1984. "Specifying vector autoregressions for macroeconomic forecasting," Staff Report 92, Federal Reserve Bank of Minneapolis.
    • Handle: RePEc:fip:fedmsr:92
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    References listed on IDEAS

    as
    1. Chow, Gregory C & Lin, An-loh, 1971. "Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series," The Review of Economics and Statistics, MIT Press, vol. 53(4), pages 372-375, November.
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    Cited by:

    1. Pillai N., Vijayamohanan, 2008. "In Quest of Truth: The War of Methods in Economics," MPRA Paper 8866, University Library of Munich, Germany.
    2. Ford, Stephen A., 1986. "A Beginner'S Guide To Vector Autoregression," Staff Papers 13527, University of Minnesota, Department of Applied Economics.
    3. Aleksandra Nocoń, 2020. "Sustainable Approach to the Normalization Process of the UK’s Monetary Policy," Sustainability, MDPI, vol. 12(21), pages 1-14, November.
    4. Pentti Pikkarainen & Matti Virén, 1989. "Granger causality between money, output, prices and interest rates: Some cross-country evidence from the period 1875–1984," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 125(1), pages 74-82, March.
    5. Eduardo Loría Díaz & Emmanuel Gerardo Salas, 2019. "La relación entre robo y desempleo de varones jóvenes en México, 2005-2017," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 14(3), pages 433-446, Julio - S.
    6. Patricio Jaramillo, 2009. "Estimación de VAR Bayesianos para la Economía Chilena," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 24(1), pages 101-126, Junio.
    7. David Mortimer Krainz, 2011. "An Evaluation of the Forecasting Performance of Three Econometric Models for the Eurozone and the USA," WIFO Working Papers 399, WIFO.
    8. Francisco F. R. Ramos, 1996. "VAR Priors: Success or lack of a decent macroeconomic theory?," Econometrics 9601002, University Library of Munich, Germany.
    9. William M. Lupoletti & Roy H. Webb, 1984. "Defining and improving the accuracy of macroeconomic forecasts : contributions from a VAR model," Working Paper 84-06, Federal Reserve Bank of Richmond.
    10. Edward Offenbacher & Richard D. Porter & Georg Rich, 1983. "Empirical comparisons of credit and monetary aggregates using vector autoregressive methods," Economic Review, Federal Reserve Bank of Richmond, vol. 69(Nov), pages 16-29.
    11. Bennett T. McCallum, 1985. "Monetary vs. Fiscal Policy Effects: A Review of the Debate," NBER Working Papers 1556, National Bureau of Economic Research, Inc.
    12. Ford, Stephen A., 1986. "An Application Of Bayesian Vector Autoregression To The U.S. Turkey Market," Staff Papers 13982, University of Minnesota, Department of Applied Economics.
    13. Enrique M. Quilis(1), "undated". "Modelos Bvar: Especificación, Estimación E Inferencia," Working Papers 8-02 Classification-JEL :, Instituto de Estudios Fiscales.
    14. Karine Bouthevillain, 1993. "La prévision macro-économique : précision relative et consensus," Économie et Prévision, Programme National Persée, vol. 108(2), pages 97-126.

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