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Backscratching in banks: political cycles in bank manager appointments

Published online by Cambridge University Press:  28 December 2020

Jonas Markgraf*
Affiliation:
Department of Politics and International Relations, University of Oxford, Oxford, UK
*
Corresponding author. Email: jonas.markgraf@politics.ox.ac.uk

Abstract

Close ties between politicians and businesses affect firms’ performance and political outcomes, and while direct political control over firms has been curtailed by tightened regulation, political connections remain ubiquitous in many countries. Yet, it is unclear through which channels these linkages are maintained in strictly regulated environments. I speculate that one such channel of political control over firms is politicians’ ability to influence corporate appointment decisions. To test the claim, I employ survival models that analyze chairpersons’ turnovers in 90 Spanish savings banks between 1985 and 2010 and find strong evidence for electoral appointment cycles: bank chairpersons are more likely to lose office shortly after regional elections and when new governments enter office.

Type
Research Note
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press on behalf of the European Political Science Association

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References

Bortolotti, B and Faccio, M (2008) Government control of privatized firms. Review of Financial Studies 22(8), 29072939.10.1093/rfs/hhn077CrossRefGoogle Scholar
Boubakri, N, Cosset, J-C and Saffar, W (2008) Political connections of newly privatized firms. Journal of Corporate Finance 14, 654673.10.1016/j.jcorpfin.2008.08.003CrossRefGoogle Scholar
Box-Steffensmeier, J and Jones, B (2004) Event History Modeling: A Guide for Social Scientists. New York: Cambridge University Press.10.1017/CBO9780511790874CrossRefGoogle Scholar
Box-Steffensmeier, J and Zorn, C (2001) Duration models and proportional hazards in political science. American Journal of Political Science 45(4), 972988.10.2307/2669335CrossRefGoogle Scholar
Cunat, V. and Garicano, L. (2010). Did Good Cajas Extend Bad Loans? Governance, Human Capital and Loan Portfolios. unpublished manuscript. http://www.vicentecunat.com/cajas.pdfGoogle Scholar
Earle, JS and Gehlbach, S (2015) The productivity consequences of political turnover: firm-level evidence from Ukraine's Orange revolution. American Journal of Political Science 59(3), 708723.10.1111/ajps.12170CrossRefGoogle Scholar
Englmaier, F and Stowasser, T (2017) Electoral cycles in savings bank lending. Journal of European Economic Association 15(2), 296354.10.1093/jeea/jvw005CrossRefGoogle Scholar
Faccio, M (2006) Politically connected firms. American Economic Review 96(1), 369386.10.1257/000282806776157704CrossRefGoogle Scholar
Faccio, M, Masulis, RW and Mcconnell, JJ (2006) Political connections and corporate bailouts. The Journal of Finance 61(1), 25972635.10.1111/j.1540-6261.2006.01000.xCrossRefGoogle Scholar
Fisman, R (2001) Estimating the value of political connections. American Economic Review 91(4), 10951102.10.1257/aer.91.4.1095CrossRefGoogle Scholar
Grambsch, P and Therneau, T (1994) Proportional hazards tests and diagnostics based on weighted residuals. Biometrika 81(3), 515526.10.1093/biomet/81.3.515CrossRefGoogle Scholar
Illueca, M, Norden, L and Udell, G (2014) Liberalization and risk-taking: evidence from government-controlled banks. Review of Finance 18(4), 12171257.10.1093/rof/rft023CrossRefGoogle Scholar
Jin, S and Boehmke, F (2017) Proper specification of nonproportional hazards corrections in duration models. Political Analysis 25(1), 138144.10.1017/pan.2016.16CrossRefGoogle Scholar
Keele, L (2010) Proportionally difficult: testing for nonproportional hazards in Cox models. Political Analysis 18(2), 189205.10.1093/pan/mpp044CrossRefGoogle Scholar
Khwaja, AI and Mian, A (2005) Do Lenders Favor politically connected firms? Rent provision in an emerging financial market. Quarterly Journal of Economics 120(4), 13711411.10.1162/003355305775097524CrossRefGoogle Scholar
La Porta, R, Lopez-de Silanes, F and Shleifer, A (2002) Government ownership of banks. The Journal of Finance 57(1), 265301.10.1111/1540-6261.00422CrossRefGoogle Scholar
Lavezzolo, S. and Illueca, M. (2017). Political Lending Cycles in Government-Controlled Banks: Evidence from Corporate Debt. unpublished manuscript. https://goo.gl/5Bteh4Google Scholar
Licht, AA (2011) Change comes with time: substantive interpretation of nonproportional hazards in event history analysis. Political Analysis 19(2), 227243.10.1093/pan/mpq039CrossRefGoogle Scholar
Markgraf, J and Rosas, G (2019) On board with banks: do banking connections help politicians win elections?. The Journal of Politics 81(4), 13571370.10.1086/704435CrossRefGoogle Scholar
McGilchrist, CA and Aisbett, C (1991) Regression with frailty in survival analysis. Biometrics 47(2), 461466.10.2307/2532138CrossRefGoogle ScholarPubMed
Nguyen, BD (2011) Ownership structure and board characteristics as determinants of CEO turnover in French-listed companies. Finance 32(2), 5389.10.3917/fina.322.0053CrossRefGoogle Scholar
Sagarra, M, Mar-Molinero, C and García-Cestona, M (2015) Spanish savings banks in the credit crunch: could distress have been predicted before the crisis? A multivariate statistical analysis. European Journal of Finance 21(2), 195214.10.1080/1351847X.2013.784208CrossRefGoogle Scholar
Sapienza, P (2004) The effects of government ownership on bank lending. Journal of Financial Economics 72(2), 357384.10.1016/j.jfineco.2002.10.002CrossRefGoogle Scholar
Therneau, TM, Grambsch, PM and Shane Pankratz, V (2003) Penalized survival models and frailty penalized survival models and frailty. Journal of Computational and Graphical Statistics 12(1), 156175.10.1198/1061860031365CrossRefGoogle Scholar
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