The Resolution of Macroeconomic Uncertainty: Evidence from Survey Forecast
AbstractWe develop an unobserved components approach to study surveys of forecasts containing multiple forecast horizons. Under the assumption that forecasters optimally update their beliefs about past, current and future state variables as new information arrives, we use our model to extract information on the degree of predictability of the state variable and the importance of measurement errors on that variable. Empirical estimates of the model are obtained using survey forecasts of annual GDP growth and inflation in the US with forecast horizons ranging from 1 to 24 months. The model is found to closely match the joint realization of forecast errors at different horizons and is used to demonstrate how uncertainty about macroeconomic variables is resolved.
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Bibliographic InfoPaper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2008-54.
Date of creation: 19 Sep 2008
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Fixed-event forecasts; multiple forecast horizons; Kalman filtering; survey data;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-09-29 (All new papers)
- NEP-CBA-2008-09-29 (Central Banking)
- NEP-ECM-2008-09-29 (Econometrics)
- NEP-FOR-2008-09-29 (Forecasting)
- NEP-MAC-2008-09-29 (Macroeconomics)
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