Reduced Overestimation in Forecasting Telecommuting as a Travel Demand Management Policy

Abstract

Overestimated forecasts of the impacts of new policies, that is, over-prediction of the successes of the policies, are a well-known problem. Study of the effects of forecasting methods on potential bias may help modelers, planners, and policy makers better use forecasting tools. This paper addresses the overestimation of the success of telecommuting as a travel demand management policy. The research hypothesis underlying this study posits that overestimates of performance are virtually inevitable when the effects of new policies that aim to change travel behavior are forecast but that these biases eventually decline over time. The sources of overestimated forecasts are the prediction tools used and the ways in which modelers use these tools. The sources of the reduction in overestimation are the changes made to these tools and the knowledge and the data gained over time.

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