Intertemporal data and travel cost analysis

This paper considers the use of multi-year data in travel cost analysis. To exploit the information embedded within intertemporal data, two broad approaches are examined: multiple year cross sections and panel models. Multiple year cross sections can be used to detect trends, and to test for stability of behavior. Panel models can be used to control for unobservable factors that are individual specific. Unfortunately, the low intertemporal variability of travel cost data sets weakens the power of panel estimators. Using aggregate data from the Boundary Waters Canoe Area, the stability of demand processes over the 1980–1986 period is investigated, as well as the problems inherent in using panel estimators in travel cost analysis.