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Short-Term Forecasting

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  • Matteo Iacoviello

Abstract

This paper presents a "bridge model" for short-run (one or two quarters ahead) forecasting of Italian GDP, relying on industrial production and survey indicators as key variables that can help in providing a real-time first GDP estimate. For a one- to two-year horizon, it formulates and estimates a Bayesian VAR (BVAR) model of the Italian economy. Both the "bridge" and the BVAR model can be of great help in supplementing traditional judgmental or structural econometric forecasts. Given their simplicity and their good forecasting power, the framework may be usefully extended to other variables as well as to other countries

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Bibliographic Info

Paper provided by International Monetary Fund in its series IMF Working Papers with number 01/109.

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Length: 23
Date of creation: 01 Aug 2001
Date of revision:
Handle: RePEc:imf:imfwpa:01/109

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  1. Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers, Federal Reserve Bank of Minneapolis 274, Federal Reserve Bank of Minneapolis.
  2. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, Econometric Society, vol. 48(1), pages 1-48, January.
  3. Cogley, Timothy & Nason, James M, 1995. "Output Dynamics in Real-Business-Cycle Models," American Economic Review, American Economic Association, American Economic Association, vol. 85(3), pages 492-511, June.
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