Reference Class Forecasting for Hong Kong's Major Roadworks Projects

Bent Flyvbjerg, Chi-keung Hon, and Wing Huen Fok, 2016, "Reference Class Forecasting for Hong Kong’s Major Roadworks Projects," Proceedings of the Institution of Civil Engineers 169, November, Issue CE6, pp. 17-24, doi/10.1680/jcien.15.00075.

20 Pages Posted: 19 Sep 2017

See all articles by Bent Flyvbjerg

Bent Flyvbjerg

University of Oxford - Said Business School; IT University of Copenhagen; St Anne's College, University of Oxford

CK Hon

Government of the Hong Kong Special Administrative Region

WH Fok

Advisian Limited

Date Written: September 15, 2017

Abstract

Reference Class Forecasting (RCF) is a method to remove optimism bias and strategic misrepresentation in cost and time to completion forecasting of projects and programmes. In September 2012, the Development Bureau of the Government of the Hong Kong Special Administrative Region commissioned a study to test the feasibility of using RCF in Hong Kong, the first of its kind in the Asia-Pacific region.

This study comprises 25 roadwork projects. For these projects cost and time to completion forecast and actual data were retrieved. The analysis established and verified the statistical distribution of the forecasting accuracy at various stages of project development and benchmarked the projects against a sample of 863 similar projects.

The study contributes to the understanding of how to improve forecasts by (1) de-biasing early estimates, (2) explicitly consider the risk appetite of decision makers, and (3) safeguard public funding allocation by balancing exceedance and under-use of project budgets.

Suggested Citation

Flyvbjerg, Bent and Hon, CK and Fok, WH, Reference Class Forecasting for Hong Kong's Major Roadworks Projects (September 15, 2017). Bent Flyvbjerg, Chi-keung Hon, and Wing Huen Fok, 2016, "Reference Class Forecasting for Hong Kong’s Major Roadworks Projects," Proceedings of the Institution of Civil Engineers 169, November, Issue CE6, pp. 17-24, doi/10.1680/jcien.15.00075., Available at SSRN: https://ssrn.com/abstract=3037412

Bent Flyvbjerg (Contact Author)

University of Oxford - Said Business School ( email )

Oxford
Great Britain

IT University of Copenhagen ( email )

Copenhagen
Denmark

St Anne's College, University of Oxford ( email )

Oxford
United Kingdom

CK Hon

Government of the Hong Kong Special Administrative Region

Hong Kong

WH Fok

Advisian Limited ( email )

Hong Kong

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