We propose a quantitative spatial model featuring heterogeneous worker groups and their travel to consume non-tradable goods and services. We consider the opening of the Downtown Line (DTL) in Singapore, which connected regions where high-income households have residential amenities to where non-traded sectors are productive. Leveraging transit farecard data, we show that high-income workers saw large welfare gains but low-income workers gained little. Everyone enjoyed improved access to consumption opportunities, but low-income jobs in non-tradables moved to less attractive workplaces. Abstracting from consumption travel understates the disparate impact across worker groups three-fold.

Consider firms that operate platforms matching buyers and sellers while selling goods themselves. By guiding consumers towards their own products through algorithmic recommendations, these firms could influence market outcomes - a regulatory concern. To investigate, we combine novel data about sales and recommendations on Amazon with a structural model that captures seller entry. Recommendations are highly price-elastic (-20), and many consumers (34%) only consider recommended offers. Hence, algorithmic recommendations raise the demand elasticity (from -8 to -11), intensify price competition, and increase the purchase rate. However, increased competition reduces entry (but the missing merchants are the least efficient). Focusing on self-preferencing: recommendations favor Amazon (equivalent to a 6% price discount), but this skew does not act as a barrier to entry or otherwise harm consumers. Indeed, since consumers prefer Amazon’s offers, “self-preferencing” slightly raises consumer surplus by $9 per product per month (assuming Amazon’s prices remain constant.)

We consider the design of a large-scale public housing program where consumers face dynamic tradeoffs over apartments rationed via lotteries and prices. We show, theoretically and empirically, that changing rules complements increasing supply. First, we present a motivating example in which supplying more housing leads households to strategically delay their applications. By waiting for “better” developments arriving tomorrow, households forgo mediocre developments available today, resulting in more vacancies. Turning to the data from the mechanism, we formulate a dynamic choice model over housing lotteries and estimate it. Under the existing mechanism, we find that increasing supply fails to lower wait times. However, when a strategyproof mechanism is implemented, vacancies and wait times fall, but prices on the secondary market rise. Under this new mechanism, building more apartments lowers wait times and reduces the upward pricing pressure on the secondary market.

How should the supply of a good be optimally designed, when the designer can determine the horizontal quality of the good? Although commonly used queuing mechanisms treat the supply of goods as exogenous, in practice designers often control the inflow of goods. We study a dynamic matching model where the designer minimizes a convex combination of mismatch count and unassignment. With endogenous supply, the optimal mechanism overproduces underdemanded goods relative to the proportional benchmark, and competition improves match quality. Batching applications artificially generates competition and is optimal when the planner places a high weight on match quality. We apply our results to the Singaporean housing allocation process, Build-To-Order. Following our dissemination, the Singaporean government increased batching.

We study vehicle population controls, their dynamic effects, alternative policy designs, and implications for efficiency and equity. We leverage data on the universe of vehicles in Singapore, the number of which is limited by the Vehicle Quota Scheme (VQS). Under the VQS, car registrations must be accompanied by permits allocated in fortnightly auctions; after ten years, car permits expire and may be renewed at the prevailing auction price. First, we observe that the effective tax on vehicle ownership fluctuates by as much as S$10,000 per year per vehicle, possibly mispricing the negative externalities of ownership and use. To explain these large fluctuations in permit prices, we formulate a dynamic equilibrium model of vehicle ownership and replacement by individuals and firms. This model will be taken to administrative microdata to evaluate welfare under the current and alternative designs.