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Environmental Factors Affecting Hong Kong Banking: A Post-Asian Financial Crisis Efficiency Analysis

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Abstract

Within the banking efficiency analysis literature there is a dearth of studies which have considered how banks have ‘survived’ the Asian financial crisis of the late 1990s. Considering the profound changes that have occurred in the region’s financial systems since then, such an analysis is both timely and warranted. This paper examines the evolution of Hong Kong’s banking industry’s efficiency and its macroeconomic determinants through the prism of two alternative approaches to banking production based on the intermediation and services-producing goals of bank management over the post-crisis period. Within this research strategy we employ Tone’s (2001) Slacks-Based Model (SBM) combining it with recent bootstrapping techniques, namely the non-parametric truncated regression analysis suggested by Simar and Wilson (2007) and Simar and Zelenyuk’s (2007) group-wise heterogeneous sub-sampling approach. We find that there was a significant negative effect on Hong Kong bank efficiency in 2001, which we ascribe to the fallout from the terrorist attacks in America in 9/11 and to the completion of deposit rate deregulation that year. However, post 2001 most banks have reported a steady increase in efficiency leading to a better ‘intermediation’ and ‘production’ of activities than in the base year of 2000, with the SARS epidemic having surprisingly little effect in 2003. It was also interesting to find that the smaller banks were more efficient than the larger banks, but the latter were also able to enjoy economies of scale. This size factor was linked to the exportability of financial services. Other environmental factors found to be significantly impacting on bank efficiency were private consumption and housing rent.

Suggested Citation

  • Karligash Kenjegalieva & Maximilian J. B. Hall & Richard Simper, 2008. "Environmental Factors Affecting Hong Kong Banking: A Post-Asian Financial Crisis Efficiency Analysis," Discussion Paper Series 2008-01, Department of Economics, Loughborough University, revised Jun 2008.
  • Handle: RePEc:lbo:lbowps:2008-01
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    File URL: http://www.lboro.ac.uk/departments/ec/RePEc/lbo/lbowps/MHKKRS.pdf
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    2. Imad Bou-Hamad & Abdel Latef Anouze & Denis Larocque, 2017. "An integrated approach of data envelopment analysis and boosted generalized linear mixed models for efficiency assessment," Annals of Operations Research, Springer, vol. 253(1), pages 77-95, June.
    3. Ohene-Asare, Kwaku & Turkson, Charles & Afful-Dadzie, Anthony, 2017. "Multinational operation, ownership and efficiency differences in the international oil industry," Energy Economics, Elsevier, vol. 68(C), pages 303-312.
    4. Gulati, Rachita, 2022. "Global and local banking crises and risk-adjusted efficiency of Indian banks: Are the impacts really perspective-dependent?," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 23-39.
    5. Özlem O. Akdeniz & Hussein A. Abdou & Ali I. Hayek & Jacinta C. Nwachukwu & Ahmed A. Elamer & Chris Pyke, 2024. "Technical efficiency in banks: a review of methods, recent innovations and future research agenda," Review of Managerial Science, Springer, vol. 18(11), pages 3395-3456, November.
    6. Zhenni Yang & Christopher Gan & Zhaohua Li, 2019. "Role of Bank Regulation on Bank Performance: Evidence from Asia-Pacific Commercial Banks," JRFM, MDPI, vol. 12(3), pages 1-25, August.

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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