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Evaluating a Structural Model Forecast: Decomposition Approach

František Brázdik, Zuzana Humplova and Frantisek Kopriva

Research and Policy Notes from Czech National Bank

Abstract: Macroeconomic forecasters are often criticized for a lack of transparency when presenting their forecasts. To deter such criticism, the transparency of the forecasting process should be enhanced by tracing and explaining the effects of data revisions and expert judgment updates on variations in the forecasts. This paper presents a forecast decomposition analysis framework designed to examine the differences between two forecasts generated by a linear structural model. The differences between the forecasts considered can be decomposed into the contributions of various forecast elements, such as the effect of new data or expert judgment. The framework allows us to evaluate the contributions of forecast assumptions in the presence of expert judgment applied in the expected way. The simplest application of this framework examines alternative forecast scenarios with different forecast assumptions. Next, a one-period difference between the forecasts’ initial periods is added to the examination. Finally, a replication of the Inflation Forecast Evaluation presented in Inflation Report III/2013 is created to illustrate the full capabilities of the decomposition framework.

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: 2014-08
New Economics Papers: this item is included in nep-dge, nep-ecm, nep-for and nep-mac
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Working Paper: Evaluating a Structural Model Forecast: Decomposition Approach (2015) Downloads
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