IDEAS home Printed from https://ideas.repec.org/a/anr/reveco/v14y2022p47-67.html
   My bibliography  Save this article

Household Financial Transaction Data

Author

Listed:
  • Lorenz Kueng

    (Facoltà di Scienze Economiche, Università della Svizzera italiana, Lugano, Switzerland)

  • Scott R. Baker

    (Kellogg School of Management, Northwestern University, Evanston, Illinois, USA)

Abstract

The growth of the availability and use of detailed household financial transaction micro data has dramatically expanded the ability of researchers to understand both household decision making and aggregate economic fluctuations across a wide range of fields. This class of transaction data is derived from a myriad of sources, including financial institutions, FinTech apps, and payment intermediaries. We review how these detailed data have been utilized in finance and economics research and analyze both their benefits and limitations as compared to more traditional measures of income, spending, and wealth. Finally, we discuss the future potential of this flexible class of data in firm-focused research, real-time policy analysis, and macro statistics.

Suggested Citation

  • Lorenz Kueng & Scott R. Baker, 2022. "Household Financial Transaction Data," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 47-67, August.
  • Handle: RePEc:anr:reveco:v:14:y:2022:p:47-67
    DOI: 10.1146/annurev-economics-051520-023646
    as

    Download full text from publisher

    File URL: https://doi.org/10.1146/annurev-economics-051520-023646
    Download Restriction: Full text downloads are only available to subscribers. Visit the abstract page for more information.

    File URL: https://libkey.io/10.1146/annurev-economics-051520-023646?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
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ali B. Barlas & Seda Guler Mert & Berk Orkun Isa & Alvaro Ortiz & Tomasa Rodrigo & Baris Soybilgen & Ege Yazgan, 2024. "Big data financial transactions and GDP nowcasting: The case of Turkey," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 227-248, March.
    2. Guttman-Kenney, Benedict & Firth, Chris & Gathergood, John, 2023. "Buy now, pay later (BNPL) ...on your credit card," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    3. Nemeczek, Fabian & Radermacher, Jan, 2022. "Personality-augmented MPC: Linking survey and transaction data to explain MPC heterogeneity by Big Five personality traits," SAFE Working Paper Series 348, Leibniz Institute for Financial Research SAFE.

    More about this item

    Keywords

    transaction data; financial account data; household finance; linked accounts; payments data;
    All these keywords.

    JEL classification:

    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • G51 - Financial Economics - - Household Finance - - - Household Savings, Borrowing, Debt, and Wealth
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • H31 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Household

    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:anr:reveco:v:14:y:2022:p:47-67. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: http://www.annualreviews.org (email available below). General contact details of provider: http://www.annualreviews.org .

    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.