A novel methodology to estimate cruising for parking and related external costs

Abstract Practitioners need to know the level of cruising for parking when designing parking policies. Existing methodologies, such as counting, experiments, and survey, are either too expensive or infeasible to be undertaken on a large scale. Inci et al. (2017) introduce an instrumental-variables-based econometric methodology using administrative data to estimate the average level of cruising when parking is close to full occupancy. This paper introduces a novel methodology to estimate the marginal external cruising time (and thus cost) across time and space. Our methodology is easier to implement, requires even less data, estimates the whole distribution rather than the average, and does not require parking to be near full occupancy. It also allows for welfare evaluations of parking fees and supply. To illustrate all these, we apply our methodology to Melbourne, which generates rich policy insights. We also apply it to the same dataset that Inci et al. (2017) use for Istanbul and find consistent results, rendering confidence to both methodologies.