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The Resolution of Macroeconomic Uncertainty: Evidence from Survey Forecast

Andrew Patton () and Allan Timmermann ()

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: We 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.

Keywords: Fixed-event forecasts; multiple forecast horizons; Kalman filtering; survey data (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-for and nep-mac
Date: 2008-09-19
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