Destination choice with longitudinal data

Panel data and habits are often observed in travel behavior research, in route choice and car ownership. While moving from diary survey to location-aware technologies, recent data collection techniques provide panel data about location choice. Only few dynamic models of location choice exist in the literature, and none of them to our knowledge correct for serial correlation. We apply Wooldridge method to deal with the initial values problem on the choice of catering location on a campus from WiFi traces. Cross-validation and forecasting in the scenarios of cost increase and opening of a new catering location are presented. Predicted market shares of the new catering location correspond to point-of-sale data of the first week of opening.