Using judgment to select and adjust forecasts from statistical models - Shari De Baets (Ghent University)

Wednesday 29 January 2020, 1:00pm to 2:00pm

Venue

Open to

Postgraduates, Public, Staff

Registration

Registration not required - just turn up

Event Details

Dr Shari De Baets from Ghent University will present a seminar to the Management Science Department

Abstract: Forecasting support systems allow users to choose different statistical forecasting methods. But how well do they make this choice? We examine this in two experiments. In the first one (N = 191), people selected the model that they judged to perform the best. Their choice outperformed forecasts made by averaging the model outputs and improved with a larger difference in quality between models and a lower level of noise in the data series. In a second experiment (N = 161), participants were asked to make a forecast and were then offered advice in the form of a model forecast. They could then re-adjust their forecast. Final forecasts were more influenced by models that made better forecasts. As forecasters gained experience, they followed input from high-quality models more readily. Thus, both experiments show that forecasters have ability to use and learn from visual records of past performance to select and adjust model-based forecasts appropriately.

Contact Details

Name Gay Bentinck
Email

g.bentinck@lancaster.ac.uk

Telephone number

+44 1524 592408