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Testing for unreliable estimators and insignificant forecasts in combined forecasts
Author(s) -
Chandrasekharan Radha,
Moriarty Mark M.,
Wright Gordon P.
Publication year - 1994
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980130705
Subject(s) - estimator , forecast verification , consensus forecast , econometrics , forecast error , reliability (semiconductor) , computer science , covariance matrix , covariance , forecast skill , statistics , mathematics , power (physics) , physics , quantum mechanics
The reliability and precision of the weights used in combining individual forecasts, irrespective of the method of combination, is important in evaluating a combined forecast. The objective of this study is not to suggest the ‘best’ method of combining individual forecasts, but rather to propose exploratory procedures, that make use of all available sample information contained in the covariance matrix of individual forecast errors, to (1) detect if the weights used in combining forecasts are ‘reliable’ (and ‘stable’ if it is known that the covariance matrix of forecast errors is stationary over time) and (2) test for ‘insignificant’ individual forecasts used in forming a combined forecast. We present empirical applications using two‐year sales and individual forecast data provided by a major consumer durables manufacturer to illustrate the feasibility of our proposed procedures.