Understanding the role of the forecast-maker in overestimation forecasts of policy impacts: The case of Travel Demand Management policies

Forecasting the impacts of a proposed policy is an important component of the transportation planning and decision making process. Although scientific tools are often used in transportation forecasts, biases and, more specifically, overestimations of the expected impact are often observed. This study explores the correlations between forecast-maker’s characteristics and forecast bias creation and reduction. 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 tested the extent to which the forecast-maker’s beliefs about the policy at stake affected the forecast bias. We found that attitudes and beliefs associates not only with overestimation bias but also with its reduction over time. We also tested the extent to which the forecast-maker’s affiliation, the performing institute and the publication type were correlated with the biases of the forecast and with the forecaster attitudes and beliefs. These characteristics are intuitively used by the forecast user as tools to assess the ‘objectivity’ of the forecast, but our analysis found no association between these characteristics and the forecast bias.

Research highlights
► Forecasts of the impact of new TDM policies are often overestimated.
► Forecast-maker’s beliefs about the policy at stake affected the forecast bias.
► Forecast-maker’s affiliation, institute, and publication type not correlated with bias.
► Optimistic and skeptical core beliefs explain reduction in overestimation over time.