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Developments in the efficiency of the Thailand banking sector: a DEA approach

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  • Fadzlan Sufian
  • Muzafar Shah Habibullah

Abstract

Purpose - The purpose of the present paper is to empirically analyze the efficiency of the Thailand banking sector during the period of 1999‐2008. Design/methodology/approach - The efficiency estimates of individual banks are evaluated by using the data envelopment analysis approach. The central tendency and parametric method based on the Tobit regression is employed to investigate the Thailand banking sector's production efficiency while controlling for the potential effects of internal (bank‐specific characteristics) and external (macroeconomic and industry specific) contextual variables. As a robustness check, following Banker and Natarajan among others, the second‐stage regression is also estimated by using the ordinary least square regression method, while the standard errors are calculated by using White's specification to adjust for cross‐section heteroskedasticity. Findings - During the period under study, the empirical findings indicate that scale inefficiency outweighs pure technical inefficiency in determining the Thailand banking sector's technical efficiency. The results from the multivariate regression analysis suggest that banks with higher loans intensity and better capitalized tend to exhibit higher efficiency levels. On the other hand, credit risk is negatively related to bank efficiency. The empirical findings suggest that the recent global financial crisis exerts negative impact on the efficiency of Thailand banks. The results indicate that the domestic banks have exhibited higher TE compared to their foreign bank counterparts. Research limitations/implications - Owing to its limitations, the paper could be extended in a variety of ways. First, the scope of this study could be further extended to investigate changes in cost, allocative, and technical efficiencies over time. Second, future research into the efficiency of the Thailand banking sector efficiency could also consider the production function along with the intermediation function. Finally, investigation of changes in productivity over time as a result of technical change or technological progress or regress by employing the Malmquist total factor productivity index could yet be another extension to the paper. Originality/value - Although the literature examining the efficiency of financial institutions with parametric and/or non‐parametric frontier techniques has expanded rapidly in recent times, these studies have been confined to the US banking sector or the banking sectors in the Western and developed countries. However, empirical evidences on the developing countries banking sectors in general and of the ASEAN countries in particular are relatively sparse. The present paper attempted to fill a demanding gap in that case by providing new empirical evidence on the sources and determinants of the Thailand banking sector's efficiency.

Suggested Citation

  • Fadzlan Sufian & Muzafar Shah Habibullah, 2010. "Developments in the efficiency of the Thailand banking sector: a DEA approach," International Journal of Development Issues, Emerald Group Publishing Limited, vol. 9(3), pages 226-245, September.
    • Handle: RePEc:eme:ijdipp:v:9:y:2010:i:3:p:226-245
    DOI: 10.1108/14468951011073316
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    5. Mustapha A. Akinkunmi, 2017. "Regulatory Impact of Bank Performance in Nigeria: Application of Stochastic Frontier Analysis," Applied Economics and Finance, Redfame publishing, vol. 4(4), pages 32-43, July.
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    7. Ebenezer Fiifi Emire Atta Mills & Mavis Agyapomah Baafi & Fangbiao Liu & Kailin Zeng, 2021. "Dynamic operating efficiency and its determining factors of listed real‐estate companies in China: A hierarchical slack‐based DEA‐OLS approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3352-3376, July.
    8. Mohamed Mehdi Jelassi & Ezzeddine Delhoumi, 2021. "What explains the technical efficiency of banks in Tunisia? Evidence from a two-stage data envelopment analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    9. Shirong Zhao, 2020. "Shadow Prices of Non-performing Loans for Chinese Banks in the Post-Crisis Era," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(6), pages 1-8.
    10. Atta Mills, Ebenezer Fiifi Emire & Zeng, Kailin & Fangbiao, Liu & Fangyan, Li, 2021. "Modeling innovation efficiency, its micro-level drivers, and its impact on stock returns," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    11. Hasanul Banna & Syed Karim Bux Shah & Abu Hanifa Md Noman & Rubi Ahmad & Muhammad Mehedi Masud, 2019. "Determinants of Sino-ASEAN Banking Efficiency: How Do Countries Differ?," Economies, MDPI, vol. 7(1), pages 1-23, February.
    12. Abdul Latif Alhassan & Michael Lawer Tetteh, 2017. "Non-Interest Income and Bank Efficiency in Ghana: A Two-Stage DEA Bootstrapping Approach," Journal of African Business, Taylor & Francis Journals, vol. 18(1), pages 124-142, January.

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