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Productivity growth in network models: An application to banking during the financial crisis

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  • Stavros A. Kourtzidis
  • Roman Matousek
  • Nickolaos G. Tzeremes

Abstract

We construct Malmquist Productivity indices for two-stage processes. A two-stage data envelopment analysis model with an additive efficiency decomposition is used for the modelling of the two-stage process. We incorporate prior information into the analysis using the Weight Assurance Region model. This model offers advantages such as the weights representing the contribution of each stage to the overall process are always positive and we also can restrict them into a region given the available prior information. We extend this model from efficiency analysis to productivity analysis and we calculate Malmquist Productivity indices using four alternative decomposition approaches. The model is applied to a panel of banks in Central and Eastern European countries and productivity change is evaluated for three periods of the financial crisis. The alternative decompositions allow us to examine the various sources of productivity change during the financial crisis. Convergence patterns are also examined.

Suggested Citation

  • Stavros A. Kourtzidis & Roman Matousek & Nickolaos G. Tzeremes, 2019. "Productivity growth in network models: An application to banking during the financial crisis," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(1), pages 111-124, January.
    • Handle: RePEc:taf:tjorxx:v:70:y:2019:i:1:p:111-124
    DOI: 10.1080/01605682.2017.1421851
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    Cited by:

    1. Gulati, Rachita, 2022. "Bank ownership and governance quality in India: Evolution and detection of convergence clubs," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    2. Doumpos, Michalis & Zopounidis, Constantin & Gounopoulos, Dimitrios & Platanakis, Emmanouil & Zhang, Wenke, 2023. "Operational research and artificial intelligence methods in banking," European Journal of Operational Research, Elsevier, vol. 306(1), pages 1-16.
    3. Wanke, Peter & Tsionas, Mike G. & Chen, Zhongfei & Moreira Antunes, Jorge Junio, 2020. "Dynamic network DEA and SFA models for accounting and financial indicators with an analysis of super-efficiency in stochastic frontiers: An efficiency comparison in OECD banking," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 456-468.
    4. Lamers, Martien & Present, Thomas & Vander Vennet, Rudi, 2022. "European bank profitability: The great convergence?," Finance Research Letters, Elsevier, vol. 49(C).
    5. Henriques, C.O. & Marcenaro-Gutierrez, O.D., 2021. "Efficiency of secondary schools in Portugal: A novel DEA hybrid approach," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    6. Mosab I. Tabash & Suhaib Anagreh & Bilal Haider Subhani & Mamdouh Abdulaziz Saleh Al-Faryan & Krzysztof Drachal, 2023. "Tourism, Remittances, and Foreign Investment as Determinants of Economic Growth: Empirical Evidence from Selected Asian Economies," Economies, MDPI, vol. 11(2), pages 1-15, February.
    7. Khosro Soleimani-Chamkhorami & Saeid Ghobadi, 2021. "Cost-efficiency under inter-temporal dependence," Annals of Operations Research, Springer, vol. 302(1), pages 289-312, July.

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