Consumption access and agglomeration: evidence from smartphone data

We provide new theory and evidence on the role of consumption access in understanding the agglomeration of economic activity. We combine smartphone data that records user location every 5 minutes of the day with economic census data on the location of service-sector establishments to measure commuting and noncommuting trips within the Greater Tokyo metropolitan area. We show that non-commuting trips are frequent, more localized than commuting trips, strongly related to the availability of nontraded services, and occur along trip chains. Guided by these empirical findings, we develop a quantitative urban model that incorporates travel to work and travel to consume non-traded services. Using the structure of the model, we estimate theoretically-consistent measures of travel access, and show that consumption access makes a sizable contribution relative to workplace access in explaining the observed variation in residents and land prices across locations. Undertaking counterfactuals for changes in travel costs, we show that abstracting from consumption trips leads to a substantial underestimate of the welfare gains from a transport improvement (because of the undercounting of trips) and leads to a distorted picture of changes in travel patterns within the city (because of the different geography of commuting and non-commuting trips).