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Overestimation Reduction in Forecasting Telecommuting as a TDM Policy

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  • Tal, Gil

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.

Suggested Citation

  • Tal, Gil, 2008. "Overestimation Reduction in Forecasting Telecommuting as a TDM Policy," Institute of Transportation Studies, Working Paper Series qt1qk959v1, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt1qk959v1
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    Cited by:

    1. Pengyu Zhu & Liping Wang & Yanpeng Jiang & Jiangping Zhou, 2018. "Metropolitan size and the impacts of telecommuting on personal travel," Transportation, Springer, vol. 45(2), pages 385-414, March.
    2. Tal, Gil & Cohen-Blankshtain, Galit, 2011. "Understanding the role of the forecast-maker in overestimation forecasts of policy impacts: The case of Travel Demand Management policies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(5), pages 389-400, June.

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    Keywords

    UCD-ITS-RP-08-32; Engineering;

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