Over the past decade, e-commerce has significantly transformed how we access con- sumption: with just a few clicks, consumers in many urban areas can purchase and have their orders delivered to their doorsteps within a day or two, sometimes even within just a few hours, without having to visit the stores. How does this experience shape our cities and what are the welfare implications of e-commerce? I study this question in the context of the United States, exploiting the staggered rollout of Amazon fulfillment cen- ters across metropolitan areas as a proxy for local e-commerce expansion. I find that, in the years following e-commerce expansion, neighborhoods that were previously less accessible to retail amenities experience an increase in home values, rents, and service amenities. This effect is not driven by gentrification or sorting of residents into these neighborhoods, nor is it explained by the spillover impacts of increased employment due to large warehouse openings. Building upon the reduced-form evidence, I employ a quantitative spatial model to assess the welfare and distributional consequences of e-commerce. The analysis shows that FC entry reduces the cost of online shopping by 58% and lowers the local retail price index by 0.6 points. Taken together, my quan- tification estimates that the average renter gains $113 per month, while the average homeowner benefits twice as much at $200 per month from e-commerce, thanks to cap- ital gains. Residents in historically less accessible locations enjoy higher surplus than those in more accessible locations, and residents in larger cities see the highest welfare gains. This result suggests that while e-commerce expansion induces a decentralization effect within cities, it amplifies the agglomeration benefits across cities.

How does Airbnb, or short-term rentals in general, impact neighborhoods? Does Airbnb gentrify neighborhoods or does it simply displace local, particularly low-income, residents? While these questions have important implications for urban policies, there are surprisingly limited research done by economists to answer them. By exploiting shift-share IV estimation strategy and using LA County public school enrollment and publicly available data to proxy for neighborhood demographic composition and quality, I find evidence that an increase in Airbnb penetration would lead to displacement of low-income residents while there is little evidence of gentrification in the sense that Airbnb-penetrated neighborhoods become highly desirable and attract new high-income residents. I suggest that the underlying displacement mechanism is Airbnb-induced rent increase due to supply-inelastic housing units being reallocated from the long-term to short-term rental markets, which would likely hurt low-income residents the most. My estimates are robust to alternative specifications, including quasi-experimental designs exploiting timing and spatial variation in the implementation of home-sharing ordinances across LA County cities. This paper, to the best of my knowledge, is the first to provide evidence on the displacement impacts of short-term rentals.

I just wanted to say thank you for a great semester! The TA sessions were helpful and overall I feel that I learned well in the class.

The most valuable aspect was being able to reach out for help.

The instruction and interactivity of the lessons really motivated me to do the work I was given.

I believe the practice problems we worked through in our discussion course were helpful in understanding the course material. Often times it is hard to understand the professor, Tri really helped me gain a more in depth understanding of the material.

Thank you for being my TA this semester. I could always tell you put a lot of effort into preparing for our discussions and appreciated that you would make them more interactive. Thanks again!

Very informative.