Abstract
Over the last few years, economic literature has used technology to try to improve forecasting. With Big Data and the vast amount of information regarding consumer habits, many sales forecasting models tried to exploit this feature. In this context, Google searches can provide valuable information regarding consumer preferences for a product. The purpose of this paper is to assess the contribution of Google searches in forecasting Ford car sales in Argentina. For this objective, we construct a model incorporating the Google Trend Index to capture search frequency in internet, and we compare this model with a standard model without said Index as an explanatory variable and assess the difference in performance between the two.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
