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Driver, Ciaran and Meade, Nigel (2019) 'Enhancing survey‐based investment forecasts.' Journal of Forecasting, 38 (3). pp. 236-255.

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Alternative Location: https://doi.org/10.1002/for.2567

Abstract

We investigate the accuracy of capital investment predictors from a national business survey of South African manufacturing. Based on data available to correspondents at the time of survey completion, we propose variables that might affect the stability of their predictions. Having calibrated the survey predictors’ directional accuracy, we model the probability of a correct directional prediction using the proposed stability variables. For point forecasting, we compare the accuracy of rescaled survey forecasts with time series benchmarks and some survey/time series hybrid models. In addition, we model the magnitude of survey prediction errors using the stability variables. Directional forecast tests showed that three out of four survey predictors have value but are biased and inefficient. For shorter horizons we found survey forecasts, enhanced by time series data, significantly improved point forecasting accuracy. For longer horizons the survey predictors were as, or more, accurate than alternatives. The usefulness of the more accurate of the predictors examined is enhanced by auxiliary information: the probability of directional accuracy and the estimated error magnitude.

Item Type: Journal Article
SOAS Departments & Centres: Departments and Subunits > School of Finance & Management
ISSN: 02776693
Copyright Statement: © 2018 The Authors Journal of Forecasting Published by John Wiley & Sons, Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/)
DOI (Digital Object Identifier): https://doi.org/10.1002/for.2567
Date Deposited: 13 Dec 2018 10:16
URI: https://eprints.soas.ac.uk/id/eprint/30044
Funders: British Academy

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