Demand forecasting errors and the ownership of infrastructure

Abstract

This article examines the argument that the introduction of more private sector expertise into public sector transportation demand forecasting will improve its accuracy. An examination of a number of pure public and public–private US highway investment traffic demand forecasts, however, finds no significance evidence that latter are more accurate.

Keywords:

• traffic forecasting
• infrastructure investment appraisal
• public–private financing

JEL Classification:

• C53
• L98
• R42

Acknowledgement

The authors would like to express their gratitude for the financial support from the Commonwealth of Virginia.

Notes

¹ There is also considerable evidence of serious underestimation of the outturn costs of major transportation investments (e.g. Flyvbjerg et al., 2004; Flyvbjerg, 2007), but this is not considered here.

² A classic case of the problem is highlighted by Dan McFadden (2001) in his Noble acceptance speech. McFadden deployed a disaggregate discrete mode split model to examine the impact of the construction of the Bay Rapid Transit System (BART) in the San Francisco area. While the conventional aggregate gravity model forecast a 15% modal share for BART, his disaggregate forecast was 6.3% and the actuality was 6.2%. Despite this, BART has never adopted disaggregate modelling as a policy tool.

³ In few cases where data for that time period is not complete, software was used for estimation interpolation.

⁴ There is an inevitable bias in this selection in that it misses out any projects that were rejected because traffic forecasts were inaccurately pessimistic.