I study the impact of credit constraints on gig economy penetration, capital allocation, and employment through the lens of Uber and Lyft. The low-income individuals for whom ride share driving is attractive often require financing to obtain cars. Exploiting the staggered entry of ride share across cities and within-city variation in income, I find that ride share entry coincides with sharp increases in auto loans, auto sales, employment, and vehicle utilization among low-income individuals. Within zip codes, these effects are concentrated among ride-share eligible vehicles. Using the exogenous removal of bankruptcy disclosures as a shock to credit availability, I find that financial constraints dampen these effects. Motivated by these facts, I build a structural model linking consumers' vehicle acquisition and utilization, ride share driving, and financing decisions. I quantify the distributional and welfare implications of changes in credit supply and market structure. An increase in financing costs forces finance-dependent low-income drivers from the market and replaces them with wealthier, less financially constrained drivers with significantly higher outside earning opportunities. After-interest driver income nearly doubles, but finance-dependent drivers do not capture these benefits. Introducing a frictionless rental market for cars allows drivers to utilize idle capital, increases ride quantities by 20%, and decreases ride prices by 35%. Organizing the industry around taxi companies that own cars has the opposite effect. Proposed policies to restrict the number of drivers impose significant welfare costs that fall primarily on riders rather than drivers. These results suggest that finance critically shapes the size and boundaries of the gig economy.