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Consumption Access and Agglomeration: Evidence from Smartphone Data

Author

Listed:
  • Yuhei Miyauchi

    (Boston University)

  • Kentaro Nakajima

    (Hitotsubashi University)

  • Stephen J. Redding

    (Princeton University and CEPR and NBER)

Abstract
Using smartphone data for Japan, 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. We use the gravity equation predictions of the model to estimate theoretically-consistent measures of travel access. We show that consumption access makes a substantial contribution to the observed variation in residents and land prices and the observed impact of the opening of a new subway line.

Suggested Citation

  • Yuhei Miyauchi & Kentaro Nakajima & Stephen J. Redding, 2021. "Consumption Access and Agglomeration: Evidence from Smartphone Data," Working Papers 287, Princeton University, Department of Economics, Center for Economic Policy Studies..
    • Handle: RePEc:pri:cepsud:287
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    References listed on IDEAS

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    Cited by:

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    3. Gupta, Arpit & Mittal, Vrinda & Peeters, Jonas & Van Nieuwerburgh, Stijn, 2022. "Flattening the curve: Pandemic-Induced revaluation of urban real estate," Journal of Financial Economics, Elsevier, vol. 146(2), pages 594-636.
    4. Atsushi Yamagishi & Yasuhiro Sato, 2022. "Measuring Discrimination in Spatial Equilibrium: 100 Years of Japan's Invisible Race," CIRJE F-Series CIRJE-F-1188, CIRJE, Faculty of Economics, University of Tokyo.
    5. Natsuki Arai & Masashige Hamano & Munechika Katayama & Yuki Murakami & Katsunori Yamada, 2022. "Nightless City: Impacts of Policymakers’ Questions on Overtime Work of Government Officials," Working Papers 2125, Waseda University, Faculty of Political Science and Economics, revised Oct 2023.
    6. Barzin,Samira & Avner,Paolo & Maruyama Rentschler,Jun Erik & O’Clery,Neave, 2022. "Where Are All the Jobs ? A Machine Learning Approach for High Resolution Urban Employment Prediction inDeveloping Countries," Policy Research Working Paper Series 9979, The World Bank.
    7. Xiameng Pan & Chang Sun, 2023. "Internal Migration, Remittances and Economic Development," CESifo Working Paper Series 10623, CESifo.
    8. Su, Yichen, 2022. "Measuring the Value of Urban Consumption Amenities: A Time-Use Approach," Journal of Urban Economics, Elsevier, vol. 132(C).
    9. Su, Yichen, 2022. "Measuring the Value of Urban Consumption Amenities: A Time-Use Approach," MPRA Paper 113158, University Library of Munich, Germany.
    10. Federica Daniele & Mariona Segu & David Bounie & Youssouf Camara, 2022. "Bike-friendly cities: an opportunity for local businesses? Evidence from the city of Paris," THEMA Working Papers 2022-09, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.

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    More about this item

    Keywords

    agglomeration; urbanization; transportation; Japan;
    All these keywords.

    JEL classification:

    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R20 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - General
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General
    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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