Enhancing survey‐based investment forecasts

Driver, Ciaran; Meade, Nigel

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.

Citation

Driver, C., & Meade, N. (2019). Enhancing survey‐based investment forecasts. Journal of Forecasting, 38(3), 236-255. https://doi.org/10.1002/for.2567

• Journal Article Type: Article
• Acceptance Date: Dec 7, 2018
• Online Publication Date: Dec 7, 2018
• Publication Date: Apr 1, 2019
• Deposit Date: Dec 13, 2018
• Publicly Available Date: Dec 13, 2018
• Journal: Journal of Forecasting
• Print ISSN: 0277-6693
• Electronic ISSN: 1099-131X
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 38
• Issue: 3
• Pages: 236-255
• DOI: https://doi.org/10.1002/for.2567
• Publisher URL: https://doi.org/10.1002/for.2567