Short-Term Forecasting; Projecting Italian GDPone Quarter to Two Years Ahead
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
|Date of creation:||01 Aug 2001|
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References listed on IDEAS
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- Litterman, Robert B, 1986.
"Forecasting with Bayesian Vector Autoregressions-Five Years of Experience,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 4(1), pages 25-38, January.
- Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers 274, Federal Reserve Bank of Minneapolis.
- Cogley, Timothy & Nason, James M, 1995. "Output Dynamics in Real-Business-Cycle Models," American Economic Review, American Economic Association, vol. 85(3), pages 492-511, June.
- Timothy Cogley & James M. Nason, 1993. "Output dynamics in real business cycle models," Working Papers in Applied Economic Theory 93-10, Federal Reserve Bank of San Francisco.
- Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January. Full references (including those not matched with items on IDEAS)
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