Searching for the picture: forecasting UK cinema admissions using Google Trends data

Abstract

This paper investigates whether Google Trends search information can improve forecasts of cinema admissions, over and above those based on seasonal patterns in the data. Using monthly data for the UK for the period 2004(1) to 2008(12) we examine various forecasting models that incorporate Google Trends search information. We find clear evidence that Google Trends data on searches relevant to cinema visits do have the potential to increase the accuracy of cinema admissions forecasting models. There is also some evidence to suggest that Google Trends indexes based on combined information from searches using a number of different search terms work better than those based on only a single keyword. The results also appear to confirm earlier findings that the UK cinema admissions series is more suitably modelled by the use of fixed seasonal dummies than through autoregressive formulations.

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