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TRB 89th Annual Meeting (January 10-14, 2010)
Policy and Technology Advances in Transportation Demand Management and Parking Management
Jan 12 2010 7:30PM- 9:30PM
Hilton, International Center
Understanding the Role of Modeler in Overestimation Forecasts of Policy Impacts: Case of Travel Demand Management Policies (10-1897)
Forecasting the impacts of a proposed policy is an important component of the rational decision making process. Although forecasts often use scientific tools, biases and, more specifically, overestimations of the expected impact are often observed. This study explores possible correlations between forecaster characteristics and forecast bias. The study examines two transport-related policies aiming at the reduction of car use: telecommuting and carsharing. Both are Travel Demand Management (TDM) policies which attract much attention from transport experts. We test the extent to which the modeler's affiliation, the performing institute and the publication type (revealed characteristics) are correlated with the biases of the forecast. These characteristics are intuitively used by the forecast user as a tool to assess the 'objectivity' of the forecast. In addition, we test the extent to which the modeler's beliefs about the policy at stake (unrevealed characteristics) affect the forecast bias. While no association between the revealed characteristics and the forecast bias was found, the analysis found that optimistic modelers tend to have more biased forecasts compared with scientific skeptical modelers.
Tal, Gil , University of California, Davis
Cohen-Blankshtain, Galit , Hebrew University of Jerusalem, Israel
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