Abstract
In this paper, a set of double-log multiple regression models is developed to examine the monthly tunnel traffic of six major toll tunnels in Hong Kong for a 22-year period from January 1979 to September 2000. Despite the much lower percentage of households with cars (12.3%) and the higher dependence of passenger trips on public transport (80.2%), the estimated automobile elasticities in Hong Kong are remarkably similar to those reported in New York, where car ownership is high and the automobile is the dominant mode of transport. The empirical elasticity range in Hong Kong is from —0.103 to —0.291. This is similar to estimates for the United States (—0.13 to —0.45), the United Kingdom (—0.14 to —0.36), and Australia (—0.09 to —0.52). The findings suggest that toll increases are likely to be effective in raising revenue for tunnel management authorities but ineffective in reducing or reallocating automobile traffic for transport planning purposes. Policywise, suburbanization or the redistribution of population could have a much stronger influence on the urban transport market than a ‘multifaceted pricing’ strategy of raising the total costs of vehicle ownership and usage (including high vehicle-registration fees, parking, and gasoline prices). Moreover, improvements to railway connectivity and enhancement of travel speed on public transit could be much more effective than toll increases in relieving urban transport congestion problems at critical bottlenecks, such as downtown and suburb–downtown tunnels and bridges. The inclusion of lagged effects into the analysis further strengthens the above policy recommendations.
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