Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/31392 
Year of Publication: 
2008
Series/Report no.: 
Working Paper No. 08-5
Publisher: 
University of California, Department of Economics, Davis, CA
Abstract: 
A path forecast refers to the sequence of forecasts 1 to H periods into the future. A summary of the range of possible paths the predicted variable may follow for a given confidence level requires construction of simultaneous confidence regions that adjust for any covariance between the elements of the path forecast. This paper shows how to construct such regions with the joint predictive density and Scheffe's (1953) S-method. In addition, the joint predictive density can be used to construct simple statistics to evaluate the local internal consistency of a forecasting exercise of a system of variables. Monte Carlo simulations demonstrate that these simultaneous confidence regions provide approximately correct coverage in situations where traditional error bands, based on the collection of marginal predictive densities for each horizon, are vastly off mark. The paper showcases these methods with an application to the most recent monetary episode of interest rate hikes in the U.S. macroeconomy.
JEL: 
C32
C52
C53
Document Type: 
Working Paper

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