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A Geographically Weighted Approach in Measuring Efficiency in Panel Data: the Case of US Saving Banks

Author

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  • Benjamin M. Tabak
  • Rogério B. Miranda
  • Dimas M. Fazio
Abstract
The objective of this article is to discuss a new approach to control for the environment when one estimates efficiency by the stochastic frontier model. By introducing geographical weights and estimating local frontiers for each US saving bank for 2001-09, we find that bank technical performance is higher for most banks in comparison to a fixed-effects approach. This result highlights the importance of explicitly considering local environment and constraints while analyzing banks' behavior. All in all, this model has been proved very promising and viable for future empirical studies.

Suggested Citation

  • Benjamin M. Tabak & Rogério B. Miranda & Dimas M. Fazio, 2012. "A Geographically Weighted Approach in Measuring Efficiency in Panel Data: the Case of US Saving Banks," Working Papers Series 275, Central Bank of Brazil, Research Department.
    • Handle: RePEc:bcb:wpaper:275
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    Cited by:

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    5. Glass, Anthony J. & Kenjegalieva, Karligash & Weyman-Jones, Thomas, 2020. "The effect of monetary policy on bank competition using the Boone index," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1070-1087.
    6. 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.
    7. Francisco Javier Sáez-Fernández & Andrés J. Picazo-Tadeo & Mercedes Beltrán-Esteve & Caroline Elliott, 2015. "Assessing the performance of the Latin American and Caribbean banking industry: Are domestic and foreign banks so different?," Cogent Economics & Finance, Taylor & Francis Journals, vol. 3(1), pages 1006976-100, December.
    8. Shiyi Chen & Wolfgang K. Härdle & Li Wang, 2020. "Estimation and determinants of Chinese banks’ total factor efficiency: a new vision based on unbalanced development of Chinese banks and their overall risk," Computational Statistics, Springer, vol. 35(2), pages 427-468, June.
    9. Vaneet Bhatia & Sankarshan Basu & Subrata Kumar Mitra & Pradyumna Dash, 2018. "A review of bank efficiency and productivity," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 557-600, November.
    10. Angelo Marsiglia Fasolo, 2012. "A Note on Particle Filters Applied to DSGE Models," Working Papers Series 281, Central Bank of Brazil, Research Department.
    11. Xiaoping Zhou & Zhenyang Qin & Yingjie Zhang & Linyi Zhao & Yan Song, 2019. "Quantitative Estimation and Spatiotemporal Characteristic Analysis of Price Deviation in China's Housing Market," Sustainability, MDPI, vol. 11(24), pages 1-28, December.
    12. Johann Burgstaller, 2020. "Retail‐bank efficiency: Nonstandard goals and environmental determinants," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 91(2), pages 269-301, June.
    13. Waldyr Areosa & Marta Areosa, 2012. "Information (in) Chains: information transmission through production chains," Working Papers Series 286, Central Bank of Brazil, Research Department.
    14. Tri Rahayu, Siti Aisyah & Mulyaningsih, Tri & Cahyadin, Malik, 2019. "Determinants of Credit Market in Indonesian Banking Industry," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 53(3), pages 11-21.
    15. Chen, Ting-Hsuan & Lee, Chien-Chiang, 2020. "Spatial analysis of liquidity risk in China," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    16. Carmelo Algeri & Luc Anselin & Antonio Fabio Forgione & Carlo Migliardo, 2022. "Spatial dependence in the technical efficiency of local banks," Papers in Regional Science, Wiley Blackwell, vol. 101(3), pages 685-716, June.
    17. repec:hum:wpaper:sfb649dp2014-068 is not listed on IDEAS
    18. Zhao, Bingquan & Tian, Yuan & Kenjegalieva, Karligash & Wood, Justine, 2024. "Measuring the productivity of urban commercial banks in China," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 477-489.

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    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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