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Employment and branch network effects on the efficiency of Polish cooperative banks

Abstract

Objective: The article aims to evaluate the influence of the employment structure and branch network on the capability of large cooperative banks in Poland (possessing assets exceeding PLN 1 billion) to sustain an optimal equilibrium between operational efficiency and liquidity. This article also seeks to identify the causes for the declining efficiency of cooperative banks in Poland in recent years and to evaluate the possibility of implementing solutions to enhance this efficiency.

Research Design & Methods: We used static panel models with data suitable for unit and time series analysis. The sample consisted of large cooperative banks operating in Poland (assets over 1 billion PLN). Statistical analysis involved diagnostic tests, collinearity analysis via VIF, and winsorisation at the first percentile to reduce outlier impact. We used Driscoll-Kraay standard errors to estimate the panel model.

Findings: We established that a high number of employees in a cooperative bank can negatively affect the return on assets (ROA) and lead to an increase in the cost-to-income (CtI) ratio. Similarly, an extensive branch network can lead to a decrease in the efficiency of assets used (ROA) and an increase in the CtI ratio. On the other hand, a higher bank’s total assets-to-employee ratio is associated with a lower CtI ratio, suggesting improved cost efficiency. Moreover, banks with higher assets per branch achieve higher profitability (higher ROA) and better cost efficiency (lower CtI).

Implications & Recommendations: The results of our study imply that optimising the staffing structure and branch network is crucial to achieve a balance between profitability and cost efficiency in cooperative banks. The solution to the problem could be employment restructuring, the implementation of process automation technologies, precise staff planning, and investment in the development of employee competence. We also suggest optimising costs related to the branch network, implementing modern technologies, and performing operational restructuring. Cooperative banks should strive to increase the efficiency of asset allocation.

Contribution & Value Added: The article comprehensively analyses of impact of the employment structure and the branch network on the efficiency and liquidity of large cooperative banks, which complements previous research focusing mainly on financial aspects. We provided empirical evidence of the complex nature of the relationship between organisational factors and the financial performance of cooperative banks in Poland.

Keywords

cooperative banks, efficiency, liquidity, employment, branch network

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Author Biography

Mateusz Folwarski

Mateusz Folwarski, PhD, professor at UEK, research and teaching associate in the Department of Banking and Global Financial System at the Krakow University of Economics. His research interests include cooperative banking, FinTech innovations.

Michał Boda

Michał Boda, Ph.D., Research and Teaching Assistant Professor in the Department of Banking and Global Financial System at the Krakow University of Economics. His research interests include banking, risk management, and mortgage loans.

Bartłomiej Balawejder

Bartłomiej Balawejder, MA, Research and Teaching Assistant in the Department of Banking and Global Financial System at the Krakow University of Economics. His research interests include banking, risk management, mortgage loans and international finance.


References

  1. Arellano, M., & Bond. S. (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. The Review of Economic Studies, 58(2), 277-297. https://doi.org/10.2307/2297968
  2. Barra, C., Papaccio, A. & Ruggiero, N. (2025). Management Cost Efficiency and Technology Gap: Cooperative vs. Non-Cooperative Credit Banks. Journal of the Knowledge Economy. https://doi.org/10.1007/s13132-025-02612-0
  3. Bernini, C., & Brighi, P. (2017). Bank branches expansion, efficiency and local economic growth. Regional Studies, 52(10), 1332-1345. https://doi.org/10.1080/00343404.2017.1380304
  4. Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87. https://doi.org/10.1016/S0304-4076(98)00009-8
  5. Bossler, M., & Schild, C-J. (2016).The employment structure of cooperative banks – a test of institutional hypotheses. European Economics: Labor & Social Conditions eJournal, 87(1). https://doi.org/10.1111/apce.12084
  6. Coccorese, P., & Shaffer, S. (2018). Cooperative Banks and Local Economic Growth. CAMA Working Paper, 11/2018. Available at SSRN: https://ssrn.com/abstract=3125909 or https://doi.org/10.2139/ssrn.3125909
  7. Dańska-Borsiak, B. (2011). Dynamiczne modele panelowe w badaniach ekonomicznych. Łódź, Wydawnictwo Uniwersytetu Łódzkiego.
  8. Driscoll, J.C., & Kraay, A. (1998). Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data. The Review of Economics and Statistics, MIT Press, 80(4). https://doi.org/10.1162/003465398557825
  9. Drukker, D.M. (2003). Testing for serial correlation in linear panel-data models. Stata Journal, 3(2). https://doi.org/10.1177/1536867X0300300206
  10. Kil, K., Folwarski, M. & Walitza, A. (2020). Optymalne ścieżki dojścia do zbudowania efektywności banków spółdzielczych. Warszawa, WIB.
  11. Groeneveld, H. (2023). European Co-operative Banks in 2022: A Concise Assessment (October 30, 2023). Available at SSRN. https://doi.org/10.2139/ssrn.4641319
  12. GUS (2025). Retrieved from https://stat.gov.pl/wskazniki-makroekonomiczne/ on March 12, 2025.
  13. Hesse, H., & Cihak, M. (2007). Cooperative Banks and Financial Stability. IMF Working Paper, 07(02). Retrieved from SSRN: https://ssrn.com/abstract=956767 on March 12, 2025.
  14. Hoechle, D. (2007). Robust standard errors for panel regressions with cross-sectional dependence. The Stata Journal, 7. https://doi.org/10.1177/1536867X0700700301
  15. Juszczyk, S., Balina, R., & Kowalski, O. (2015). Efficiency Determinants of Cooperative Banks in Poland in 2005-2012. Krakow Review of Economics and Management Zeszyty Naukowe Uniwersytetu Ekonomicznego W Krakowie, 10(934), 35-50. https://doi.org/10.15678/ZNUEK.2014.0934.1003
  16. Lang, F., Signore, S., & Gvetadze, S. (2016). The role of cooperative banks and smaller institutions for the financing of SMEs and small midcaps in Europe. EIF Working Paper, 2016(36).
  17. Migliorelli, M., & Lamarque, E. (2022). Contemporary Trends in European Cooperative Banking. Palgrave Macmillan. (No. hal-03665298).
  18. Nisha, & Rani, R. (2024). Co-operative Banks – A Helping Hands for Small and Medium Entrepreneurs in Saharanpur District. Integrated Journal for Research in Arts and Humanities, 4(2). https://doi.org/10.55544/ijrah.4.2.3
  19. Pacelli, V., Pampurini, F., & Sylos Labini, S. (2019). The peculiarity of the cooperative and mutual model: evidence from the European banking sector. Journal of Financial Management, Markets and Institutions, 07(01). https://doi.org/10.1142/S2282717X19400012
  20. Pesaran, M.H. (2003). A Simple Panel Unit Root Test in the Presence of Cross Section Dependence. University of Cambridge, Cambridge Working Papers in Economics, 0346. https://doi.org/10.2139/ssrn.457280
  21. Pesaran, M.H. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. CESIFO Working Papers Series, 1229, IZA Discusion Paper 1240. https://doi.org//10.2139/ssrn.572504
  22. Piasecki, P. (2024). The influence of training, membership and employee age on turnover intention in co-operative financial institutions. International Journal of Contemporary Management, 6(1), 109-124. https://doi.org/10.2478/ijcm-2024-0005
  23. Poli, F. (2019). Co-operative banking networks in Europe. Cham: Palgrave Macmillan.
  24. Ramcharan, R., Verani S., & Skander J. (2016). From Wall Street to Main Street: The Impact of the Financial Crisis on Consumer Credit Supply. The Journal of Finance, 71(3), 1323-1356. https://doi.org/10.1111/jofi.12209
  25. Roodman, D. (2009). How to do xtabond2: An introduction to difference and system GMM in Stata. Stata Journal, 9. https://doi.org/10.1177/1536867X0900900106
  26. Rzońca, A., Ciżkowicz, P., & Albinowski, M. (2013). Links between the trust in the ECB and its interest rate policy. Warsaw, Economic Institute, NBP Working Paper, 158. Retrieved from https://static.nbp.pl/publikacje/materialy-i-studia/158_en.pdf on March 12, 2025.
  27. Sztaudynger, M. (2018). Czynniki makroekonomiczne a spłacalność kredytów konsumpcyjnych. Gospodarka Narodowa, 4(296). https://doi.org/10.33119/GN/102228
  28. Venanzi, D., & Matteucci, P. (2021). The largest cooperative banks in Continental Europe: a sustainable model of banking. International Journal of Sustainable Development & World Ecology, 29(1), 84-97. https://doi.org/10.1080/13504509.2021.1919784
  29. Wooldridge, J.M. (2003). Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press, https://doi.org/10.1007/s00712-003-0589-6

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