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Overestimation Reduction in Forecasting Telecommuting as a TDM Policy

Abstract

Overestimated forecasts of the impact of new policy, which over-predict policy success, are a well-known problem. Studying the effects of forecasting methods on potential biases may help modelers, planners and policy makers better use the forecasting tools. This paper addresses overestimation of telecommuting as a travel demand management (TDM) policy. The research hypothesis underlying this study posits that overestimates are virtually inevitable in forecasting the effect of new policies that aim to change travel behavior, but these biases eventually decline over time. The sources of overestimated forecast 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 the modeling tools results from knowledge and data gained over time.

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