IDEAS home Printed from https://ideas.repec.org/a/eee/pacfin/v87y2024ics0927538x24002324.html
   My bibliography  Save this article

Political uncertainty, bank loans, and corporate behavior: New investigation with machine learning

Author

Listed:
  • Qian, Yilei
  • Wang, Feng
  • Zhang, Muyang
  • Zhong, Ninghua

Abstract

This paper investigates how uncertain term length, a novel source of political uncertainty, affects the behaviors of banks and firms using a machine-learning approach. China's local authorities do not have a fixed term, creating an ideal environment for studying how economic agents react to their perception of political uncertainty without an actual political turnover. We implement a machine-learning method to predict the term length of city leaders by observing others with similar backgrounds. Combining this new measurement of political uncertainty and bank- and firm-level data, we find an inverted U-shaped relationship between city leaders' predicted remaining term length and bank loans, corporate liabilities, and investment, which matches the change of political uncertainty over the term. We also record the potential adverse consequences of the politically motivated loan and investment expansion, such as a loss of corporate efficiency and a disruption in market order.

Suggested Citation

  • Qian, Yilei & Wang, Feng & Zhang, Muyang & Zhong, Ninghua, 2024. "Political uncertainty, bank loans, and corporate behavior: New investigation with machine learning," Pacific-Basin Finance Journal, Elsevier, vol. 87(C).
  • Handle: RePEc:eee:pacfin:v:87:y:2024:i:c:s0927538x24002324
    DOI: 10.1016/j.pacfin.2024.102480
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927538X24002324
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.pacfin.2024.102480?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 search for a different version of it.

    More about this item

    Keywords

    Political uncertainty; Uncertain term length; Bank loans; Corporate investment; Machine learning;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies

    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:eee:pacfin:v:87:y:2024:i:c:s0927538x24002324. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/pacfin .

    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.