Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity
Kajal Lahiri (),
Huaming Peng () and
Xuguang Simon Sheng ()
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Huaming Peng: Rensselaer Polytechnic Institute
No 2021-005, Working Papers from The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting
From the standpoint of a policy maker who has access to a number of expert forecasts, the uncertainty of a combined or ensemble forecast should be interpreted as that of a typical forecaster randomly drawn from the pool. This uncertainty formula should incorporate forecaster discord, as justified by (i) disagreement as a component of combined forecast uncertainty, (ii) the model averaging literature and (iii) central banksâ€™ communication of uncertainty via fan charts. Using new statistics to test for the homogeneity of idiosyncratic errors under the joint limits with both T and n approaching infinity simultaneously, we find that some previously used measures can significantly underestimate the conceptually correct benchmark forecast uncertainty.
Keywords: Central Bank Communication; Disagreement; Ensemble; Forecast Combination; Panel Data; Uncertainty (search for similar items in EconPapers)
JEL-codes: C12 C33 E37 (search for similar items in EconPapers)
Pages: 35 pages
New Economics Papers: this item is included in nep-for, nep-isf and nep-mac
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https://www2.gwu.edu/~forcpgm/2021-005.pdf First version, 2021 (application/pdf)
Working Paper: Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity (2020)
Working Paper: Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:gwc:wpaper:2021-005
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