A Regression Model of the Number of Taxicabs in U.S. Cities

Abstract

In cities that control the number of taxicabs by law or regulation, setting the number of cabs is one of the most important decisions made by taxicab regulators and elected officials. Licensing either too many or too few cabs can have serious deleterious effects on the availability and quality of service and the economic viability of the taxi business. Yet local officials often have difficulty quantifying the demand for taxi service or tracking changes in demand. Multiple regression modeling of the number of cabs in 118 U.S. cities identifies three primary demand factors: the number of workers commuting by subway, the number of households with no vehicles available, and the number of airport taxi trips. These results can be used to identify peer cities for further comparison and analysis and to guide regulators in measuring changes in local demand for cab service.

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