Testing the accuracy of event economic impact forecasts

RAMCHANDANI, Girish and COLEMAN, Richard (2012). Testing the accuracy of event economic impact forecasts. International Journal of Event and Festival Management, 3 (2), 188-200.

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Link to published version:: https://doi.org/10.1108/17582951211229726
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    Abstract

    Purpose - This paper examines the findings from ex ante and ex post economic impact appraisals of six major sports events. The ultimate aim of the paper is to identify the factors that cause differences between forecasts of direct expenditure and figures based on primary research.

    Design/methodology/approach - A direct expenditure forecast for each event was derived based on analysis of event documentation and informed assumptions applied from previous studies. Subsequently, a comprehensive study was undertaken involving primary data collection and associated desk research.

    Findings - Of the forecasts, three were inflated and three were conservative relative to the ex post figures. Two potential sources of variance are examined – visitor spending and organisational expenditure. The former was found to be more unpredictable when compiling a pre-event forecast. The group for which direct expenditure is most difficult to predict is spectators, with the most exaggerated forecasts associated with free-to-view events.

    Research limitations/implications - Neither input-output nor computable general equilibrium models were used to analyse secondary, indirect or induced impacts. Nonetheless, direct expenditure is the basis for modelling wider impacts and is therefore worthy of consideration in its own right.

    Practical implications - The findings of this study should enable public sector agencies to better understand the reliability of projected figures presented to them by organisers in exchange for securing financial support for their events.

    Originality/value - Economic impact forecasts are rarely subjected to post-event scrutiny. This research bridges the gap between ex ante and ex post figures and identifies areas where forecast accuracy can be improved.

    Item Type: Article
    Uncontrolled Keywords: UoA26
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Sport Industry Research Centre
    Identification Number: https://doi.org/10.1108/17582951211229726
    Page Range: 188-200
    Depositing User: Rebecca Jones
    Date Deposited: 22 May 2012 10:39
    Last Modified: 09 Oct 2018 09:22
    URI: http://shura.shu.ac.uk/id/eprint/5118

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