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Banking Efficiency Determinants in India: A Two-stage Analysis

Author

Listed:
  • Rishabh Goswami
  • Farah Hussain

    (Farah Hussain is at the Tezpur University, Assam, India, e-mail: farah@tezu.ernet.in)

  • Manish Kumar

    (Manish Kumar is at the Tezpur University, Assam, India, e-mail: manish@tezu.ernet.in)

Abstract

This study aims at measuring the technical efficiency of banks in India and examining its determinants. Efficiency is said to be achieved if a bank is able to maximise its output subject to limited inputs. To obtain technical efficiency score, input-oriented Malmquist Data Envelopment Analysis is applied on two outputs and three input variables, based on a VRS (variable returns to scale) assumption. Three foreign banks—namely, A B Bank Ltd, Bank of Ceylon, and Citibank N A—and two Indian banks—namely, HDFC Bank and State Bank of India—are found to be most efficient during the study period. The efficiency scores when subsequently used as the dependent variable along with independent variables—bank size, capitalisation, liquidity risk, returns on assets, interest rate, credit risk, market concentration and gross domestic product (GDP)—in a panel regression analysis found the fixed effect model to be more appropriate in explaining the determinants. The results reveal that liquidity risk, returns on assets, credit risk, market concentration and GDP have a significant effect on the technical efficiency, while banks size, interest rate and level of capitalisation are found to be insignificant variables. JEL Classification: G21, C13, C60

Suggested Citation

  • Rishabh Goswami & Farah Hussain & Manish Kumar, 2019. "Banking Efficiency Determinants in India: A Two-stage Analysis," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 13(4), pages 361-380, November.
  • Handle: RePEc:sae:mareco:v:13:y:2019:i:4:p:361-380
    DOI: 10.1177/0301574219868373
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    References listed on IDEAS

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    Cited by:

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    2. Clement Olalekan Olaniyi & Titus Ayobami Ojeyinka & Xuan Vinh Vo & Mamdouh Abdulaziz Saleh Al‐Faryan, 2023. "Do business strategies vary across firms in the banking industry? New perspectives from the bank size–profitability nexus," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(1), pages 525-544, January.
    3. Maria Elisabete Neves & Catarina Proença & António Dias, 2020. "Bank Profitability and Efficiency in Portugal and Spain: A Non-Linearity Approach," JRFM, MDPI, vol. 13(11), pages 1-19, November.
    4. Ayobami Ojeyinka, Titus & Enisan Akinlo, Anthony, 2021. "Does Bank Size Affect Efficiency? Evidence From Commercial Banks In Nigeria," Ilorin Journal of Economic Policy, Department of Economics, University of Ilorin, vol. 8(1), pages 79-100, June.
    5. Proença, Catarina & Augusto, Mário & Murteira, José, 2023. "The effect of earnings management on bank efficiency: Evidence from ECB-supervised banks," Finance Research Letters, Elsevier, vol. 51(C).
    6. Ather Hassan Dar & Somesh Kumar Mathur & Sila Mishra, 2021. "The Efficiency of Indian Banks: A DEA, Malmquist and SFA Analysis with Bad Output," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 653-701, December.
    7. Wasi Ul Hassan Shah & Gang Hao & Nan Zhu & Rizwana Yasmeen & Ihtsham Ul Haq Padda & Muhammad Abdul Kamal, 2022. "A cross-country efficiency and productivity evaluation of commercial banks in South Asia: A meta-frontier and Malmquist productivity index approach," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-17, April.

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    More about this item

    Keywords

    Banks; Efficiency Determinants; Malmquist DEA; Balanced Panel; Fixed Effect Estimation;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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