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Evaluating a Structural Model Forecast: Decomposition Approach

František Brázdik, Zuzana Humplova and Frantisek Kopriva

Working Papers from Czech National Bank

Abstract: When presenting the results of macroeconomic forecasting, forecasters often have to explain the contribution of data revisions, conditioning information, and expert judgment updates to the forecast update. We present a framework for decomposing the differences between two forecasts generated by a linear structural model into the contributions of the elements of the information set when anticipated and unanticipated conditioning is applied. The presented framework is based on a set of supporting forecasts that simplify the decomposition of the forecast update. The features of the framework are demonstrated by examining two forecast scenarios with the same initial prediction period but different forecast assumptions. The full capabilities of the decomposition framework are documented by an example forecast evaluation where the forecast from the Czech National Bank's Inflation Report III/2012 is assessed with respect to the updated forecast from Inflation Report III/2013.

Keywords: Data revisions; DSGE models; forecasting; forecast revisions (search for similar items in EconPapers)
JEL-codes: C53 E01 E47 (search for similar items in EconPapers)
Date: 2015-12
New Economics Papers: this item is included in nep-dge, nep-for and nep-mac
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Working Paper: Evaluating a Structural Model Forecast: Decomposition Approach (2014) Downloads
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