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How Forced Switches Reveal Switching Costs: Evidence from the Loan Market

Published online by Cambridge University Press:  04 October 2023

Karolis Liaudinskas Open the ORCID record for Karolis Liaudinskas [Opens in a new window]
Karolis Liaudinskas*
Affiliation:
Research unit of the monetary policy department, Norges Bank
*
karolis.liaudinskas@norges-bank.no
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Abstract

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This article proposes a novel way to estimate consumer switching costs and uses Lithuanian credit register data and two bank closures to provide this estimate for the loan market. I show that when a distressed bank’s closure forced firms to switch, they started borrowing at lower interest rates instantly and permanently and that this drop revealed the lower bound of firms’ ex ante switching costs. A healthy bank’s closure showed no such effect. The article’s findings suggest that distressed banks hold up and overcharge firms and that by closing and resolving such banks with good-bank/bad-bank separation regulators can improve firm financing.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , First View , pp. 1 - 41
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

I thank Nicola Pavanini (the referee) and George G. Pennacchi (the editor) for detailed comments that greatly improved this article. I also thank Puriya Abbassi, Shantanu Banerjee, Vicente Bermejo, Arnoud Boot, Santiago Carbó, Mihnea Constantinescu, Aurelijus Dabušinskas, Hans Degryse, Ruben Durante, Michael Ehrmann, Randall K. Filer, Xavier Freixas, Gergely Ganic, Tomas Garbaravičius, Galina Hale, Veronica Harrington, Guillermo Hausmann, Juan F. Imbet, Vasso Ioannidou, Filippo Ippolito, Artūras Juodis, Marius Jurgilas, Eglė Karmazienė, Stephen Karolyi, Luc Laeven, Povilas Lastauskas, Maria-Teresa Marchica, Albert J. Menkveld, Gaizka Ormazábal, Joe Peek, José-Luis Peydró, Andrea Polo, Aurelija Proškutė, Rafael Repullo, Kasper Roszbach, João A.C. Santos, Enrico Sette, Linas Tarasonis, Victoria Vanasco, Romain Veyrune, Paul Wachtel, Christian Wagner, and Alminas Žaldokas for their comments. I thank seminar participants and discussants at Norges Bank, Bank of Lithuania, National Bank of Ukraine, Universitat Pompeu Fabra, VU Amsterdam, University of Copenhagen, Manchester Business School, University of Glasgow, CUNEF, WU Vienna, CPB Netherlands Bureau for Economic Policy Analysis, European Winter Meeting of the Econometric Society 2019, 16th Corporate Finance Day, 25th International Panel Data Conference, 25th Dubrovnik Economics Conference, 2nd Baltic Economics Conference, and 15th CIREQ PhD Students’ Conference. I especially thank Kristina Grigaitė for arranging access to the Lithuanian credit register and making this research possible. The views expressed in this article are those of the author and do not necessarily reflect those of an affiliated institution.

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