中国商业银行贷款地理分布对银行利润效率的影响

doi:10.11821/dlxb201506009

Abstract

Abstract:

The regional development research on commercial banks has always been the focus of financial geography research. At present, there is still debate on whether the geographical decentralization level of commercial bank loan can positively influence bank performance. This paper uses the loan data of 13 listed commercial banks in China releasing to each province during 2007-2013 to analyze the loan releasing geographical distribution characteristics of large-sized commercial banks and small and medium-sized commercial banks and the geographic variation trend of non-performing loans. On such basis, it uses stochastic frontier analysis (SFA) and the basic model of Battese and Collie (1995) to build the trans-log profit function model to conduct empirical analysis of the influence of geographical decentralization level of commercial bank loan on the efficiency of bank profits. Research results show that: (1) Increasing the geographical decentralization level of loan can boost the revenue and profit efficiency for commercial banks in the process of banking operation; (2) Large-sized commercial banks, due to the effect of national policies, cover broader loan releasing areas, and the loan releasing proportion in the central and western regions is significantly higher than that of the small and medium-sized commercial banks, and the average profit efficiency has always been higher than that of the small and medium-sized commercial banks. However, in recent years, with the gradually increasing geographical decentralization level of small and medium-sized commercial banks loan, the gap of profit efficiency between the two has been narrowed; (3) At present, the loan business of some small and medium-sized commercial banks in China still belongs to the relationship loan, and raising the geographical decentralization level of loan will lower their profit efficiency. Therefore, the diversified business operation should be carefully handled and cannot blindly follow it.

Key words: geography of finance, commercial banks, loan, geographic distribution, efficiency, China

Zhimin DAI, Liyan ZHU. The influence of geographical distribution of commercial bank loan on the bank profit efficiency in China[J].Acta Geographica Sinica, 2015, 70(6): 955-964.

Figures/Tables 7

Fig. 1

Fig. 2

Tab. 1

Tab. 2

Selection and description of variables

变量	具体变量描述与衡量
投入变量(P)
在职职工数量(P₁)
可贷资金额(P₃)	存款+中央银行借款+同业及金融机构存入及拆入
产出变量(Y)
利息收入额(Y₁)
非利息收入额(Y₂)	手续费及佣金收入+投资收益+其他业务收入
影响变量
贷款地理分散程度(Z₁)	$DIV = 1 - (Loa n i ∑ Loan) 2$ ; Loan_i：银行在某一地区的贷款投放额; ∑Loan：银行当年的贷款总额。
所有制形式(Z₂)	国有控股银行=0; 中小股份制银行=1。
收益变量
税后净利润(TP)

Tab. 2

Tab. 3

Tab. 4

The result of stochastic frontier analysis

		coefficient	standard-error	t-ratio
利润函数
	常数项	-81.91194	0.94370	-86.79862
	lnP₁	-3.96060	0.84378	-4.69388*
	lnP₂	11.94231	0.69423	17.20230*
	lnY₁	4.06477	0.68306	5.95082*
	lnY₂	-5.74492	0.16387	-35.05868*
	lnP₁*lnP₁	-0.43525	0.05852	-7.43753*
	lnP₁*lnP₂	0.35610	0.18209	1.95561*
	lnP₁*lnY₁	0.53582	0.20919	2.56138*
	lnP₁*lnY₂	-0.14641	0.12101	-1.20990
	lnP₂*lnP₂	-0.52401	0.10103	-5.18671*
	lnP₂*lnY₁	0.02267	0.43317	0.05233
	lnP₂*lnY₂	0.35344	0.15764	2.24201*
	lnY₁*lnY₁	-0.37189	0.36045	-1.03176
	lnY₁*lnY₂	0.14001	0.25277	0.55391
	lnY₂*lnY₂	-0.06447	0.09956	-0.64755
效率函数
	常数项	2.07661	0.28482	7.29100
	Z₁	-2.63906	0.59032	-4.47057*
	Z₂	-0.64578	0.15141	-4.26512*
方差参数
	$Δ 2$	0.09671	0.00884	10.94371
	$γ$	0.99543	0.00073	1361.41720*
其他信息
	LR	50.67
	平均技术效率	80.00%

Tab. 4

Tab. 5

References 34

[1]	Porteous D J.The geography of finance: Spatial dimensions of intermediary behaviour. Aldershot: Avebury, 1995: 1-230.
[2]	Martin R.Money and the Space Economy. London: John Wiley and Sons, 1999: 1-337.
[3]	Dow S C.The stages of banking development and the spatial evolution of financial systems//Martin R, Money and the Space Economy. London: John Wiley and Sons, 1999: 31-48.
[4]	Li Xiaojian, Zhou Xiongfei, Wei Chunjiang, et al.Locational changes of banking services in the less developed region of China since 1980: The case of Henan province. Acta Geographica Sinica, 2006, 61(4): 414-424.
	[李小建, 周雄飞, 卫春江, 等. 发展中地区银行业空间系统变化: 以河南省为例. 地理学报, 2006, 61(4): 414-424.]
[5]	Fan Xiangmei, Qiu Zhaoxiang, Zhang Xiaoyun. An empirical of the geographical diversification benefits and risks of small and medium sized banks in China. Management World, 2010(10): 171-173.
	[范香梅, 邱兆祥, 张晓云. 中国中小银行地域多元化风险与收益的实证分析. 管理世界, 2010(10): 171-173.]
[6]	He Canfei, Fu Rong.An empirical study on the locational choices of foreign banks in China. Acta Geographica Sinica, 2009, 64(6): 701-712.
	[贺灿飞, 傅蓉. 外资银行在中国的区位选择. 地理学报, 2006, 64(6):701-712.]
[7]	Kevin J S.Do community banks benefit from diversification? Journal of Financial Services Research, 2004, 25: 135-160.
[8]	Liang N, Rhoades S A.Geographic diversification and risk in banking. Journal of Economics and Business, 1988, 40(4): 271-284.
[9]	Laderman E, Schmidt R, Zimmerman G.Location, branching and bank portfolio diversification: The case of agricultural lending. Federal Reserve Bank of San Francisco Economic Review, 1991: 24-38.
[10]	Economides N, Hubbard R G, Palia D.The political economy of branching restrictions and deposit insurance: A model of monopolistic competition among small and large banks. Journal of Law and Economics, 1996, 39(2): 667-704.
[11]	Pilloff S J.Performance changes and shareholder wealth creation associated with mergers of publicly traded banking institutions. Journal of Money, Credit and Banking, 1996, 28: 294-310.
[12]	Houston F J, Christopher M J, Michael D Ryngaert.Where do merger gains come from? Bank mergers from the perspectives if insiders and outsiders. Journal of Financial Economics, 2001, 60: 285-331.
[13]	Penas P M, Haluk U.Gains in bank mergers: Evidence from bond markets. Journal of Financial Economics, 2004: 1-31.
[14]	Acharya V, Hasan I, Anthony S. The effects of focus and diversification on bank risk and return: Evidence from individual bank loan portfolios. Mimeo, New Jersey Institute of Technology, 2002(3): 15.
[15]	Claudia M B, John C D, Charlotte O.Cross-border diversification in bank asset portfolios. Working Paper, 2004.
[16]	Deng S, Elyasiani E.Diversification and performance of the U.S. commercial banks. Working Paper, 2005.
[17]	Cao Fengqi.Market orientation of city commercial banks. Rural Finance Research, 2006(4): 34-37.
	[曹凤岐. 城市商业银行的市场定位. 农村金融研究, 2006(4): 34-37.]
[18]	Wei Shijie.Business diversification, spatial diversification and performance of commercial banks-empirical study of China [D]. Tianjin: Nankai University, 2010.
	[魏世杰. 业务分散、空间分散与商业银行绩效: 基于中国的实证研究[D]. 天津: 南开大学, 2010.]
[19]	Frame W S, Srinivasan A, Woosley L.The effect of credit scoring on small business lending. Journal of Money, Credit and Banking, 2001, 33: 813-825.
[20]	Berger A N, DeYoung R. The effects of geographic expansion on bank efficiency. Journal of Financial Services Research, 2001, 19: 163-184.
[21]	Berger A N, Udell G F.Small business credit availability and relationship lending: The importance of bank organizational structure. Economic Journal, 2002, 112: 32-53.
[22]	Berger A N, Hasan I, Zhou Mingming.Bank ownership and efficiency in China: What will happen in the world's largest nation? Journal of Banking and Finance, 2009, 33(1): 113-130.
[23]	Wang Pan, Wu Wei, Huang Juan.Cross-regional business of city commercial banks: Credit expansion, risk level and bank performance. Journal of Financial Research, 2012, 379(1): 141-153.
	[王攀, 吴玮, 黄娟. 城市商业银行跨区域经营: 信贷扩张、风险水平及银行绩效. 金融研究, 2012, 379(1): 141-153.]
[24]	Berger A N, Humphrey D B.Efficiency of financial institutions: International survey and directions for future research. European Journal of Operation Research, 1997, 98: 175-212.
[25]	Battese G E, Coelli T J.A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics, 1995, 20: 325-332.
[26]	Berger A N, Hancock D, Humphrey D B.Bank efficiency derived from the profit function. Journal of Banking and Finance, 1993, 13: 317-347.
[27]	Maudos J, Pastor J M, Perez F, et al.Cost and profit efficiency in European banks. Journal of International Financial Markets Institutions and Money, 2002, 12: 33-58.
[28]	Godfrey Y, He Canfei, Liu Hao.Centralization and marginalization: The Chinese banking industry in reform. Applied Geography, 2012, 32: 854-867.
[29]	Li Xiaojian.A theoretical review of financial geography and study of financial geography in China. Economic Geography, 2006, 26(5): 721-730.
	[李小建. 金融地理学理论视角及中国金融地理研究. 经济地理, 2006, 26(5): 721-730.]
[30]	Wu Wei, Liu Weidong, Liu Yi.Regional differences of local banking systems in China. Acta Geographica Sinica, 2007, 62(12): 1235-1243.
	[武巍, 刘卫东, 刘毅. 中国地区银行业金融系统的区域差异. 地理学报, 2007, 62(12): 1235-1243.]
[31]	Lu Yuanquan, Zhang Degang.The research on the measurement of regional financial efficiency and its difference. Economic Geography, 2012, 32(1): 96-101.
	[陆远权, 张德钢. 中国区域金融效率测度及效率差异研究. 经济地理, 2012, 32(1): 96-101.]
[32]	Li Zhishan, Huang Guangqing, Chen Fenggui, et al.The geographic distribution characteristics research of Chinese joint-stock commercial bank. Economic Geography, 2014, 34(2): 19-27.
	[李智山, 黄光庆, 陈凤桂, 等. 中国全国性股份制商业银行地理分布特征研究. 经济地理, 2014, 34(2): 19-27.]
[33]	Qiu Zhaoxiang, Zhang Lei. The research of commercial bank profit efficiency evaluation after risk adjustment. Journal of Financial Research, 2007(3): 98-110.
	[邱兆祥, 张磊. 经过风险调整的商业银行利润效率评价研究. 金融研究, 2007(3): 98-110.]
[34]	Chen Dong, Fan Jie.Interregional capital flows and regional development gap: Analysis of the inter-bank credit flows. Acta Geographica Sinica, 2011, 66(6): 723-731.
	[陈东, 樊杰. 区际资本流动与区域发展差距: 对中国银行间信贷资本流动的分析. 地理学报, 2011, 66(6): 723-731.]

年份	不良贷款率前五名	不良贷款率后五名
2007	四川、吉林、黑龙江、山西、青海	浙江、上海、江苏、福建、北京
2008	四川、西藏、山西、青海、吉林	浙江、宁夏、重庆、上海、福建
2009	黑龙江、海南、吉林、河南、西藏	宁夏、重庆、北京、福建、江苏
2010	西藏、青海、四川、山西、甘肃	宁夏、福建、上海、内蒙、北京
2011	西藏、青海、山西、辽宁、四川	内蒙、上海、重庆、福建、北京
2012	浙江、青海、辽宁、江西、新疆	重庆、海南、北京、广西、内蒙
2013	浙江、江西、江苏、福建、辽宁	重庆、西藏、海南、北京、甘肃

	税后净利润(万元)	在职职工人数(人)	可贷资金(万元)	利息收入(万元)	非利息收入(万元)	HHI
平均值	5 453 724	135 458	430 688 014	19 335 934	3 128 344	0.76
中位数	2 852 000	40 340	240 045 300	10 844 700	1 358 000	0.75
最大值	26 296 500	478 980	1 589 080 400	76 711 100	15 208 400	0.84
最小值	61 404	8 573	31 630 604	1 804 390	103 370	0.69

	2007	2008	2009	2010	2011	2012	2013	平均值
中小型商业银行
平安银行	88.78	16.30	96.43	85.88	91.16	71.01	67.40	73.85
上海浦东发展银行	56.99	86.74	71.57	76.33	87.78	94.29	93.02	80.96
招商银行	96.68	98.12	70.29	78.35	88.24	94.65	86.01	87.48
华夏银行	54.07	59.72	44.98	53.45	62.64	66.00	71.06	58.85
兴业银行	97.99	98.65	84.50	75.70	80.58	79.58	80.22	85.32
民生银行	61.93	64.64	77.75	75.46	93.30	85.19	92.74	78.71
光大银行	64.00	76.44	57.85	74.93	82.62	79.09	82.85	73.97
中信银行	73.24	87.32	64.31	75.07	79.14	74.65	74.39	75.45
大型商业银行
工商银行	91.15	94.33	92.34	98.69	98.60	97.47	95.58	95.45
建设银行	97.91	89.14	86.46	88.64	98.87	92.53	92.49	92.29
农业银行	97.71	79.49	92.30	92.99	86.68	88.54	96.15	90.55
中国银行	92.50	73.50	81.43	88.14	74.44	72.93	74.24	79.60
交通银行	73.09	70.00	63.70	66.48	74.26	63.24	61.62	67.49
平均值
中小型商业银行	74.21	73.49	70.96	74.40	83.18	80.56	80.96
大型商业银行	90.47	81.29	83.24	86.99	86.57	82.94	84.02

The influence of geographical distribution of commercial bank loan on the bank profit efficiency in China

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