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A novel ranking procedure for forecasting approaches using data envelopment analysis

Emrouznejad, Ali, Rostami-Tabar, Bahman and Petridis, Konstantinos 2016. A novel ranking procedure for forecasting approaches using data envelopment analysis. Technological Forecasting and Social Change 111 , pp. 235-243. 10.1016/j.techfore.2016.07.004

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Abstract

To compare the accuracy of different forecasting approaches an error measure is required. Many error measures have been proposed in the literature, however in practice there are some situations where different measures yield different decisions on forecasting approach selection and there is no agreement on which approach should be used. Generally forecasting measures represent ratios or percentages providing an overall image of how well fitted the forecasting technique is to the observations. This paper proposes a multiplicative Data Envelopment Analysis (DEA) model in order to rank several forecasting techniques. We demonstrate the proposed model by applying it to the set of yearly time series of the M3 competition. The usefulness of the proposed approach has been tested using the M3-competition where five error measures have been applied in and aggregated to a single DEA score.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Uncontrolled Keywords: Forecasting; Accuracy measure; Data Envelopment Analysis
Publisher: Elsevier
ISSN: 0040-1625
Date of First Compliant Deposit: 9 February 2017
Date of Acceptance: 4 July 2016
Last Modified: 18 Sep 2018 10:58
URI: http://orca.cf.ac.uk/id/eprint/98093

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