IDEAS home Printed from https://ideas.repec.org/p/bca/bocawp/25-16.html

Incorporating Trip-Chaining to Measuring Canadians’ Access to Cash

Author

Listed:
  • Heng Chen
  • Hongyu Xiao

Abstract

Household mobility data can improve our measurement of access to cash. The existing literature typically assumes that households visit their nearest ABMs or financial institution branches from their homes, without combining cash withdrawals with other activities (i.e., on their way to shopping). However, the typical approach neglects two realistic features: The first is that, due to spatial agglomeration, cash access points could be co-located with popular points of interest, such as retail service centers; and, second, households could combine multiple trips, via trip-chaining, to reduce travel costs. Our paper employs smartphone data to construct an improved cash access metric by accounting for both spatial agglomeration and households’ travel patterns. We find that incorporating trip-chaining into the travel metric could show that travel costs are from 15% to 25% less than not incorporating trip-chaining and that the biggest decrease is driven by rural residents.

Suggested Citation

  • Heng Chen & Hongyu Xiao, 2025. "Incorporating Trip-Chaining to Measuring Canadians’ Access to Cash," Staff Working Papers 25-16, Bank of Canada.
  • Handle: RePEc:bca:bocawp:25-16
    DOI: 10.34989/swp-2025-16
    as

    Download full text from publisher

    File URL: https://doi.org/10.34989/swp-2025-16
    File Function: Abstract
    Download Restriction: no

    File URL: https://www.bankofcanada.ca/wp-content/uploads/2025/06/swp2025-16.pdf
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.34989/swp-2025-16?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Daniel Shoag & Stan Veuger, 2018. "Shops and the City: Evidence on Local Externalities and Local Government Policy from Big-Box Bankruptcies," The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 440-453, July.
    2. Heng Chen & Daneal O’Habib & Hongyu Xiao, 2024. "How do Canadians perceive access to cash?," Staff Analytical Notes 2024-24, Bank of Canada.
    3. Couture, Victor & Dingel, Jonathan I. & Green, Allison & Handbury, Jessie & Williams, Kevin R., 2022. "JUE Insight: Measuring movement and social contact with smartphone data: a real-time application to COVID-19," Journal of Urban Economics, Elsevier, vol. 127(C).
    4. Scott R. Baker & Stephanie Johnson & Lorenz Kueng, 2021. "Shopping for Lower Sales Tax Rates," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(3), pages 209-250, July.
    5. Helmut Stix, 2020. "A spatial analysis of access to ATMs in Austria," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue Q3/20, pages 39-59.
    6. Krüger, Malte & Seitz, Franz, 2025. "Costs of means of payment for consumers: Literature review and some sensitivity analyses," IMFS Working Paper Series 218, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuhei Miyauchi & Kentaro Nakajima & Stephen J Redding, 2025. "The Economics of Spatial Mobility: Theory and Evidence Using Smartphone Data," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(4), pages 2507-2570.
    2. Olivier Coibion & Yuriy Gorodnichenko & Dmitri Koustas, 2021. "Consumption Inequality and the Frequency of Purchases," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(4), pages 449-482, October.
    3. Klopack, Ben & Luco, Fernando, 2025. "JUE Insight: Measuring local consumption with payment cards and cell phone pings," Journal of Urban Economics, Elsevier, vol. 149(C).
    4. Giammatteo, Michele & Iezzi, Stefano & Zizza, Roberta, 2022. "Pecunia olet. Cash usage and the underground economy," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 107-127.
    5. Difang Huang & Ying Liang & Boyao Wu & Yanyi Ye, 2025. "Estimating the impact of social distance policy in mitigating COVID-19 spread with factor-based imputation approach," Empirical Economics, Springer, vol. 68(2), pages 585-601, February.
    6. Khondaker Golam Moazzem & Tamim Ahmed, 2021. "Implications of COVID-19 for Bangladesh’s Graduation from the LDC Status," CPD Working Paper 140, Centre for Policy Dialogue (CPD).
    7. Bernstein, Shai & Colonnelli, Emanuele & Giroud, Xavier & Iverson, Benjamin, 2019. "Bankruptcy spillovers," Journal of Financial Economics, Elsevier, vol. 133(3), pages 608-633.
    8. Winfried Koeniger & Peter Kress, 2024. "The Effect of Unconventional Fiscal Policy on Consumption -New Evidence based on Transactional Data," Swiss Finance Institute Research Paper Series 24-58, Swiss Finance Institute.
    9. Silke Hamann & Annekatrin Niebuhr & Duncan Roth & Georg Sieglen, 2023. "How does the Covid‐19 pandemic affect regional labor markets and why do large cities suffer most?," Journal of Regional Science, Wiley Blackwell, vol. 63(5), pages 1228-1250, November.
    10. Hakan Yilmazkuday, 2024. "Welfare costs of shopping trips," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 73(1), pages 241-264, June.
    11. Shoag, Daniel & Veuger, Stan, 2017. "Taking My Talents to South Beach (and Back)," Working Paper Series rwp17-019, Harvard University, John F. Kennedy School of Government.
    12. Makoto Sakuma & Kazushi Matsuo & Morito Tsutsumi & Toyokazu Imazeki, 2024. "Measuring office attendance during the COVID-19 pandemic with mobility data to quantify local trends and characteristics," Asia-Pacific Journal of Regional Science, Springer, vol. 8(1), pages 185-237, March.
    13. Kristian Behrens & Brahim Boualam & Julien Martin, 2020. "Are clusters resilient? Evidence from Canadian textile industries," Journal of Economic Geography, Oxford University Press, vol. 20(1), pages 1-36.
    14. Chenggang Wang, 2022. "Green Technology Innovation, Energy Consumption Structure and Sustainable Improvement of Enterprise Performance," Sustainability, MDPI, vol. 14(16), pages 1-21, August.
    15. Bernardino, Tiago & Gabriel, Ricardo Duque & Quelhas, João & Silva-Pereira, Márcia, 2025. "The full, persistent, and symmetric pass-through of a temporary VAT cut," Journal of Public Economics, Elsevier, vol. 248(C).
    16. Diego Daruich & Julian Kozlowski, 2023. "Macroeconomic Implications of Uniform Pricing," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(3), pages 64-108, July.
    17. Leung, Justin H. & Seo, Hee Kwon, 2023. "How do government transfer payments affect retail prices and welfare? Evidence from SNAP," Journal of Public Economics, Elsevier, vol. 217(C).
    18. Siddharth Sharma & Wilbur Chung, 2022. "Demand agglomeration economies, neighbor heterogeneity, and firm survival: The effect of HHGregg's bankruptcy," Strategic Management Journal, Wiley Blackwell, vol. 43(2), pages 370-401, February.
    19. Avetian, Vladimir & Pauly, Stefan, 2025. "You can’t sit with us: How locals and tourists compete for amenities in Paris," Journal of Urban Economics, Elsevier, vol. 148(C).
    20. Victoria Baudisch & Matthias Neuenkirch, 2023. "Costly, but (Relatively) Ineffective? An Assessment of Germany’s Temporary VAT Rate Reduction During the Covid-19 Pandemic," Research Papers in Economics 2023-04, University of Trier, Department of Economics.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • R22 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Other Demand
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bca:bocawp:25-16. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bocgvca.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.