This paper analyzes the dynamic spatial equilibrium of taxicabs and shows how common taxi regulations lead to substantial inefficiencies as a result of search frictions and misallocation. To analyze the role of regulation on frictions and efficiency, I pose a dynamic model of spatial search and matching between taxis and passengers. Using a comprehensive dataset of New York City yellow medallion taxis, I use this model to compute the equilibrium spatial distribution of vacant taxis and estimate intraday demand given price and medallion regulations. My estimates show that the weekday New York market achieves about $5.7 million in daily welfare or about $25 per trip, but an additional 53 thousand customers fail to find cabs due to search frictions. Counterfactual analysis shows that implementing simple tariff pricing changes can enhance allocative efficiency and expand the market, offering daily net surplus gains of up to $460 thousand and 65 thousand additional daily taxi-passenger matches, a similar magnitude to the gains generated by adopting a perfect static matching technology.