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Merger and Acquisitions in South African Banking: A Network DEA Model

Author

Listed:
  • Peter Wanke

    (COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Rio de Janeiro)

  • Andrew Maredza

    (School of Economics and Decision Science, North West University, South Africa)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria)

Abstract

Banking in South Africa is known for its small number of companies that operate as an oligopoly. This paper presents a strategic fit assessment of mergers and acquisitions (M and A) in South African banks. A network DEA (Data Envelopment Analysis) approach is adopted to compute the impact of contextual variables on several types of efficiency scores of the resulting virtual merged banks: global (merger), technical (learning), harmony (scope), and scale (size) efficiencies. The impact of contextual variables related to the origin of the bank and its type is tested by means of a set of several robust regressions to handle dependent variables bounded in 0 and 1: Tobit, Simplex, and Beta. The results reveal that bank type and origin impact virtual efficiency levels. However, the findings also show that harmony and scale effects are negligible due to the oligopolistic structure of banking in South Africa.

Suggested Citation

  • Peter Wanke & Andrew Maredza & Rangan Gupta, 2016. "Merger and Acquisitions in South African Banking: A Network DEA Model," Working Papers 201665, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201665
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    4. Yung‐ho Chiu & Tai‐Yu Lin & Tzu‐Han Chang & Yi‐Nuo Lin & Shih‐Yung Chiu, 2021. "Prevaluating efficiency gains from potential mergers and acquisitions in the financial industry with the Resample Past–Present–Future data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(2), pages 369-384, March.
    5. Abreu, Emmanuel Sousa de & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2019. "What is going on with studies on banking efficiency?," Research in International Business and Finance, Elsevier, vol. 47(C), pages 195-219.
    6. Chang, Tsung-Sheng & Lin, Ji-Gang & Ouenniche, Jamal, 2023. "DEA-based Nash bargaining approach to merger target selection," European Journal of Operational Research, Elsevier, vol. 305(2), pages 930-945.
    7. Bayiley, Yitbarek Takele & Redae, Haben Mehari, 2022. "Domestic Bank Merger and Acquisition in Ethiopia: a prudent strategy for efficiency and synergy gain," Ethiopian Journal of Economics, Ethiopian Economics Association, vol. 26(1), April.
    8. Pinto, Claudio, 2019. "Model and measure the relative efficiency of a four-stage production process. An NDEA multiplier relational model under different systems of resource distribution preferences between sub-processes," MPRA Paper 92617, University Library of Munich, Germany.
    9. Shirasu, Yoko, 2018. "Long-term strategic effects of mergers and acquisitions in Asia-Pacific banks," Finance Research Letters, Elsevier, vol. 24(C), pages 73-80.
    10. Petridis, Konstantinos & Tampakoudis, Ioannis & Drogalas, George & Kiosses, Nikolaos, 2022. "A Support Vector Machine model for classification of efficiency: An application to M&A," Research in International Business and Finance, Elsevier, vol. 61(C).
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    More about this item

    Keywords

    Banks; South Africa; Merger and Acquisitions; Network; DEA; Robust Regression Analysis;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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