3 (, 250001 ;, 250100) : DEA,,, ;, U, : ; ;DEA ; :F830 :A :1002-7246(2005) 01-0091 - 11,, (,2004), (,2004),, 25 DEA,,, ; DEA, ;, ; :2004-11 - 20 : (1970 - ),,,,, (1968 - ),,,, 3 [ ] ( :02BJ Y127) 91
,, ( ) ( ) Farell (1957),, (2003) (1999) DEA DEA, 14 (2000) DEA 1993-1999, (2001) (2001) 5 (2002) DEA Malmquist, 1994-1999, (2003) (2003) DEA (2004) DEA SFC 47 (2004) SFC Bankscope 1995-2001 22,,, (2004), 1997-2001 14,,,, DEA,,
,,,,,, Berger and Humphrey (1997), ;, Ferrier and Lovell (1990),, Berger Humphrey (1997), Berger and Humphrey(1997) 130, (Parametric Method) ; (Non - Parametric Method),, (Berger and Humphrey,1997) ;,,,,, ;, DEA ( X - ) (1998),, (SFA) (DFA) ( TFA) (DEA) ( FDH) DEA (Data Envelopment Analysis),DEA, ( Input Orientated Model) (Output Orientated Model) (1999),, DEA DEA, Charnes et al1 (1978) Farell (1957) Farrell 1957 Debreu (1957) Koopmans(1957), : (1) (technical efficiency, TE), ; (2) (allocative efficiency, AE),, X - (, Farrell ) CRS( ) Charnes, Cooper
, BCC, CRS, (pure technical efficiency, PTE), (TE) (PTE) (SE) Sherman and Gold (1985) Coelli (1996) ( y 1, y 2, x) ( x 1, x 2, y) ( ) ( ) : : TE o = OA/ OB, TE i = OQ/ OP, A E o = OB/ OC, A E i = OR/ OQ, EE o = OA/ OC = TE o A E o EE i = OR/ OP = TE i A E i, ZZ,A( OC, ),AA P, EE i, EE o, TE, : DEA, Max,, s1 t1 y i + Y Ε 0, x i - X Φ0,
i Ε 0 i, i, ; y i i ; x i i (2000) (2002),,, 3, DEA, 1,,, 1 DEA DEA 100 C 100 C 100 C 100 C 100 C 98173 I 100 C 97138 I 100 D 95186 I 100 I 95159 I 100 I 92168 I 100 I 84124 I 100 I 80135 D 100 D 78155 D 100 C 75 D 100 C 4814 D 100 C : C D I Harker and Zenios(2000) ; X ; ( ) Frei et al1(2000) Maudos et al1 (1998)
,, : 11,,, 21,, 8 %,, (,2001) 31,,, 41,, ( ) (,2001), 51,,,, 40-60 %, ( ),, 61, : (1) Shleifer and Vishny(1986), La Porta et al1(1998,1999) Claessens et al1(2002) ; (2) Burkart, Gromb and Panunzi (1997),, ; (3),,
(Demsetz and Lehn,1985), (active monitoring hypothesis), (Friend and Lang, 1988),,, (Shleifer and Vishny,1986) 71 (Shleifer and Vishny, 1997) (2001),, ;,,, Jensen and Meckling(1976) Ang, Cole and Lin(2000) Singh and Davidson(2003) Ang, Cole and Lin(2000) ( / ) ;Singh and Davidson(2003) 3 ( / ),,,, Jensen and Meckling(1976),,, ;, 8,,, 2 2 OPE, 1, 0 ITR INO ( - ) INS
LIT DIS GOV S 1 1 HS 10 10, 3,, 1 10 20186 % 56137 %, ;, 27177 % ; 3185 % 2192 % ;, 28161 %, 3 DEA ITR S 1 HS 10 INO INS LIT DIS GOV 92191 712385 012086 015637 012777 010385 012861 113950 010292 100100 710147 011500 015327 013135 010362 012328 113612 010054 100100 917193 110000 110000 015543 010835 111772 117405 011428 48140 418760 010644 012599-014881 010206 010054 111220 010000 13105 114679 012064 011699 011986 010139 012875 011583 010396 3, DEA,, 4,, 1 10, 015, S 1 SH 10 OPE ITR,,,, 4 :
OPE 11000 ITR 018197 110000 S 1 012488 013392 110000 HS 10-010982 - 011261 017303 110000 INO - 014058-013357 - 017381-014655 110000 INS - 014048-013424 - 011425 010387 010196 110000 LIT - 011565 010754-013953 - 012037 012747 011579 110000 DIS - 012497-010926 - 011261-011180 013920 010143-011687 110000 GOV - 010344 011595 015705 014013-014953 011114-011883 010799 110000 DEA = C + a 1 OPE + a 2 HS 10 + a 3 INS + a 4 LIT + a 5 DIS + a 6 GOV (1) DEA = C + a 1 OPE + a 2 S 1 + a 3 INS + a 4 LIT + a 5 DIS (2) DEA = C + a 1 ITR + a 2 HS 10 + a 3 INS + a 4 LIT + a 5 DIS + a 6 GOV (3) DEA = C + a 1 OPE + a 2 HS 10 + a 3 INO + a 4 INS + a 5 LIT + a 6 DIS + a 7 GOV (4), (1) - (4), 5, 1 10, 3 1 10 0, ;,,,,,,, U,,,, 5 (1) (2) (3) (4) C 2814603 (019397) 4818113 (117090) 1711006 (015615) 2813662 (019045) OPE 1011037 (117950) 319364 (016809) 1013855 (115607) ITR 117986 (212274) 3
S 1 015134 (219385) 3 HS 10 015286 (311824) 3 015541 (314607) 3 015347 (218854) 3 INO 117821 (010876) INS 6614682 (013337) 11210339 (015419) 9514390 (015002) 6915382 (013326) LIT 15651104 (019857) 23231882 (113555) 56610170 (013759) 15301017 (019047) DIS 2013654 (112671) 1916014 (111838) 1513151 (110444) 1916502 (110605) GOV - 15510877-19517823 - 15114776 ( - 212140) 3 ( - 217793) 3 ( - 118164) 3 3 R 2 014652 014314 015118 014655 A - R 2 012513 012040 013165 011983 D1W1 118035 118469 118919 117980 : T, 3 1 %, 3 3 5 %, 3 3 3 10 %,, 1 10, ;, ;, 25 DEA,, U,
1, Malmquist,2002 5 2,,2001 7 3,,1998 11 4,,,2004 2 5,,2003 3 6, :SFC DEA,,2004 1 7,,2002 1 8,,,2001 4 9,,2002 3 10,,,2000 3 11,,1999 1 12,,2004 8 13, :,,2003 14, DEA 1997-2001,,200313 15, :,,2003 12 16,,2003 4 17,,2003 4 18,,2000 6 19,,2001 1 20,,2004 2 21 Avkiran, 19991The evidence of efficiency gains : The role of mergers and the benefits to the public1 Journal of Banking and Finance Vol1 231pp1991-10131 22 Casu and Molyneux, Acomparative study of efficiency in European banking, University of Wales,Working Papers,20001 23 Coelli, T1 J1,1996, A Guide to DEAP Version 211 : A Data Envelopment Analysis(Computer) Program1 Center for Efficien2 cy and Productivity Analysis(CEPA) working papers1 24 Jackson and Fethi, Evaluating the technical efficiency of Turkish commercial banks : an application of DEA and Tobit analy2 sis,university of Queensland, Working Papers,20001 25 Sathye, Efficiency of banks in a developing economy : the case of India, European Journal of Operational Research, 2003, Vol1148,pp1662-6711 Abstract : This article estimates the efficiency of state - owned and local as well as joint - stock commercial banks with 25 samples by using DEA method, makes statistically empirical analysis on several factors affectingbank s effi2 ciency. The result shows that there is no evident difference in the efficiency among state - owned banks, joint - stock banks and urban commercial banks. However, centralized ownership structure and corporate governance mechanism are the key factors affecting the efficiency of commercial banks in China. With the centralization of the ownership structure, the bank s efficiency has a trend of reversed U. In addition ; it is also found that the expansion of bank size helps to enhance its efficiency. Key words : commercial Banks, efficiency, DEA, corporate governance. ( : ) ( :FY)