A series of six models is presented in which the problem of determining the optimal capacity of a transportation facility under second-best conditions is considered. The models consider the problems of allocating land between urban and rural use, as well as the allocation between roads and residences. The special character of congestion arising in public transportation systems is considered. The basic theory of second-best capacity optimization is considered and related to the first-best case of optimal pricing. This theory is extended to the case of uncertain demand for transportation services. The final model considers the interaction between two alternative modes of travel in an urban spatial setting. The analysis discloses essentially that second-best conditions whether in the form of non-optimal pricing or uncertainty require an increase in transportation capacity above first-best levels for empirically relevant demand elasticities. The analysis further demonstrates that upriced road congestion does not necessarily provide an economic justification for the subsidy of public transportation as previously assumed.
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