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Evaluating Forecasts of a Vector of Variables: A German Forecasting Competition
Author(s) -
Sinclair Tara,
Stekler Herman O.,
MullerDroge Hans Christian
Publication year - 2016
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.2390
Subject(s) - competition (biology) , multivariate statistics , variable (mathematics) , econometrics , german , multivariate analysis , economics , probabilistic forecasting , outcome (game theory) , computer science , mathematics , artificial intelligence , microeconomics , machine learning , geography , ecology , biology , probabilistic logic , mathematical analysis , archaeology
Abstract In this paper we explore methodologies appropriate for evaluating a forecasting competition when the participants predict a number of variables that may be related to each other and are judged for a single period. Typically, forecasting competitions are judged on a variable‐by‐variable basis, but a multivariate analysis is required to determine how each competitor performed overall. We use three different multivariate tests to determine an overall winner for a forecasting competition for the German economy across 25 different institutions for a single time period using a vector of eight key economic variables. We find that neglecting the cross‐variable relationships greatly alters the outcome of the forecasting competition. Copyright © 2016 John Wiley & Sons, Ltd.