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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.

Econometrics --- Macroeconomics --- Industries: General --- Bayesian Analysis: General --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- State Space Models --- Business Fluctuations --- Cycles --- Prices, Business Fluctuations, and Cycles: Forecasting and Simulation --- Macroeconomics: Production --- Prices, Business Fluctuations, and Cycles: General (includes Measurement and Data) --- Forecasting and Simulation: Models and Applications --- Economic growth --- Econometrics & economic statistics --- Economic Forecasting --- Cyclical indicators --- Industrial production --- Vector autoregression --- GDP forecasting --- Production index --- Production --- Econometric analysis --- National accounts --- Business cycles --- Industries --- National income --- Economic theory --- United States --- Gdp forecasting