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Over the past two decades, the availability of non-tradable services has become an important feature explaining residential neighborhood choice and local economic performance. However, surprisingly little is known about the size of investments that are required to support a local service-based economy or how such investments affect the service demand of existing residents. This paper leverages the resorting of residential and employment locations induced by the widespread adoption of remote work following the COVID-19 pandemic to investigate how the supply of consumption amenities responds to changes in local density and demographics. We use credit card transactions to measure consumer expenditures and create a high-frequency panel of establishment openings and closures. We estimate both the elasticity of non-tradable service supply with respect to local customer density and the elasticity of non-tradable service demand with respect to establishment density. We use a model of retail demand to study the distributional effects of the growing suburbanization of consumption amenities in recent years.

SNAP benefits buy 14 cents of every dollar spent on food in U.S. supermarkets and are a large, volatile component of retail demand. However, the effect of SNAP on the prices charged by food retailers is far from clear; the only two studies examining this issue find opposite results. We use administrative data on SNAP transactions and scanner data on retail prices and household expenditures, along with state-level variation in the generosity of benefits along both the intensive and extensive margins that are plausibly exogenous to local macroeconomic trends. We find that prices tend to increase following an increase in the per-recipient generosity of SNAP benefits but decrease following an increase in the number of eligible households. We present a model of consumer store choice and retailer price-setting featuring travel costs and liquidity constraints that can rationalize these diverging price responses. We then test its predictions and estimate its key parameters to quantify the incidence and welfare effects of intensive and extensive margin program expansions, in terms of the surplus split by beneficiaries and retailers and their spillover effects on non-recipient households.