: 3 :,,,,,, : : 1992 6,,1992 2003, 8156 %,,: (1) ; (2) () ; (3),, (1994) (2004) 267, (2004), (2005) (2005),1992 2002,,,,,, :, ;; 3,, : gunaihua @126. com ;,, :510275, :lijf @scnu. edu. cn ( :05BJL015) 985, 46
2006 1 (),,,,;, 1992 2003, (Π, ),1992 7376, 2003 13461, 5162 %, 1992 1913 2003 6121 U 1992 01259,2000 01497,,1992,1992 2003, : 9305 18940 ;5707 10113 ; 6240 8569,3599 3065-534,8827 10371 1544, 1992 1163 1149 0191,2003 1187 2121 1118?,,,, (,Capital Intensity),,,: K t = K t - 1 + I t - K t - 1 (1) (1) (), (2004),,,28 (1990 ) :1952 1995 :1996 2002, Hall Jones (1999), 10 (6 % ),, 1990,,,: 50,, (,2002),,, ; ; () Hall Jones(1999) 127 47
:,1992, 1978,14 :1978 1992,1993 2002 ; 1992 1992,0163, OLS, 01866 1 1992 2002,,, 20 90,,,70 %,,, 1 1992 2002 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 (Π) 23525 24948 25779 27829 31679 36173 41761 48303 54286 60640 66359 (Π) 9469 10099 10255 10942 12674 14409 17147 20798 24202 27626 31398 (Π) 15364 15697 14856 15161 16877 20473 25677 29847 33684 37810 42534 Π 2148 2147 2151 2154 2150 2151 2144 2132 2124 2120 2111 Π 1153 1159 1174 1184 1188 1177 1163 1162 1161 1160 1156 Π 0162 0164 0169 0172 0175 0170 0167 0170 0172 0173 0174 : (Π) : (),,,,,X,;,,,,,,,, 1 : 48 1, ( Y2 - Y1) B A (2), Y2 - Y1 = ( Y1 3 - Y1) + ( Y1 3 3 - Y1 3 ) + ( Y2 - Y1 3 3 ) = { ( Y1 3 - Y1) - ( Y2 3 3 - Y2) } + ( Y1 3 3 - Y1 3 ) + ( Y2 3 3 - Y1 3 3 ) = ( TE1 - TE2) + TP +YK (2)
2006 1 (2), ( TE1 - TE2) TPYK A B, B A YK, ( TE1 - TE2) TP,, B A,, B A,( TE1 - TE2) TP,B A,,,,, (Wu,2000),,,,,,,,,,,,,,,,,,,,,,, : (1),,, 1,,,,,,,, ( ) ( ),,, 49
:, (2),,,,,,,,,,,,,,,,,,,,,,,(),,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,: (1), (2),, (3),,, (4), (5),, 50
2006 1,, () Farrel 1957,, (,2004),, ;,,,,,,,,,:,,; (Panel Data),,, Battese Coelli 1995 (Stochastic Frontier Approach,SFA),C2D,: ln y it = b 0 + t + ln k it + V it - U it (3), i t ; y k ; b 0 ; ; ( V it - U it ) ; V it ( ), N (0, 2 V ), U it ; U it t i,n ( M it, 2 U) M it, e - M it i t, Mit,,, : M it = 0 + 1 t + 2 east i + 3 middle i + W it (4), i t ; east middle, 0 1 ; 0 ; 1,, ; 2 3,, 2 3 ( ), 2 3 ( ) ; W it,n (0, 2 W),,,,M it 0, 1,, 1, 51
:,,,, (4) : M it = < 0 + < 1 t + < 2 mar it + < 3 edu it + W it (5), i t W it ; < 0 ; < 1 1 ; mar edu ; < 2 < 3,,,(3), (6) 0,, (OLS), ;1, U it, 2 U = (0 1) (6) 2 U + 2 V (LR), LR : LR = - 2{ln[ L ( H 0 )ΠL ( H 1 ) ]} = - 2{ln[ L ( H 0 ) ] - ln[ L ( H 1 ) ]} (7), L ( H 0 ) L ( H 1 ) H 0 H 1 (Log ) LR, LR,,Kodde Palm(1986),,,,,, (),, (2001,2003,2004), ( mar),,,,,,,: (1) ; (2), ; (3), 2,1998 2002,,, 52
2006 1,, ( edu) 2 1998 2002, :1998 2002, : 0,6,9, 12,14, 16, 19,,, 1998 1999 2000 2001 2002 6195 6193 7123 7114 7153 5167 5134 5144 4149 4172 4115 4114 4139 3195 4103 5169 5156 5178 5128 5152 1150 1143 1141 1168 1182 0126 0126 0124 0132 0133 :,, (1999 2000 ), :2000 2001 2004,, () 1992 2002 28,, ( GLS), 01572 01434, 01998Wald, 1 2 01275,015998, 1, C2D Frontier 41 1, (3) (4) (3) (5) (1 2), Frontier 41 1 LR, 3 4,,, 1992 2002,1998 2002 1 2,: ;(1992 2002), ;, ;,,, 1 %,(3) (4) (3) (5),1,01912, 90 %,,,5 % 5 %01023,1992 2002 GLS, 53
: 213 %,40 % 1992,,,01033,, 313 % : (1),,,,,,,,,,,, (2),,,,,,, 3 1 2 t t 41827 3 3 3 211608 31565 3 3 3 111046 01023 3 3 3 41072 01027 3 3 11852 01434 3 3 3 181872 01566 3 3 3 171859 01151 11491 11149 3 3 3 21902 01033 3 3 3 31128 01064 11136-01829 3 3 3-41092 - 01125 3 3-21121 - 01075 3 3-11771 - 01104 3 3-11856 2 01079 3 3 3 41636 01092 3 3 3 31752 01912 3 3 3 361021 11000 3 3 3 2341606 Log 90158 3 3 3 47152 3 3 3 308 140 11 5 28 28 : 3 3 3 3 3 3 1 % 5 %10 %;, 54 2,,
2006 1, - 01075, B A 1,, B A 715 %,A 715 % - 01104,,B A 1, A 1014 %,, - 01829-01125, 8219 %1215 % 4 Log LR H 1 :412 413 90158 5 % 1 % 1 1 H 0 : 0 = 1 = 2 = 3 == 0 21113 138190 5 101371 141325 2 H 0 := 0 40116 100184 1 21706 51412 3 H 0 : 1 = 0 39146 102124 1 21706 51412 4 H 0 : 2 = 3 = 0 30131 120154 2 51138 81273 H 1 :412 414 47152 2 1 H 0 : < 0 = < 1 = < 2 = < 3 == 0 18140 58124 5 101371 141325 2 H 0 := 0 44133 6138 1 21706 51412 3 H 0 : < 1 = 0 38157 1719 1 21706 51412 4 H 0 : < 2 = < 3 = 0 39128 16148 2 51138 81273 :5 %1 %Kodde D. and F. Palm,1986,Wald Criteria for Jointly Testirg Equality and Inequality Restrictions, Econometrica,Vol. 54, p. 1246 1,,1992, 01926,01846 01761,,,2002,01908, 01681 01609,75 % 67 %,2002 8, 11 12,01964 01959,,, (),01414 01426,,,,, 55
:,:, ;,,,,,,,,,,,,2005 :,3,2004 :, 9,2004 ::, 1,1994 :, 3,2004 : :, 7,2004 :,3,2002 :, 12 :2004 ::1952 2000, 10 Battese and Coelli, 1995,A Model for Technical Inefficiency Effects in a Stochastic Production Frontier for Panel Data, Empirical Economics, Vol. 20, pp. 325 32. 253 81. Farrell M J., 1957,The Measurement of Production Efficiency, Journal of the Royal Statistical Society. Series A ( General),120(3),pp. Hall. R. and Charles Jones,1999,Why do Some Countries Produce so much More Output per worker than Others?, The Quarterly Journal of Economics, Feb. pp. 83 115. 48. Kodde D. and F. Palm,1986,Wald Criteria for Jointly Testing Equality and Inequality Restrictions,Econometrica, Vol. 54, pp. 1243 Wu Yanrui,2000,Is China s Economic Growth Sustainable? A Productivity Analysis, China Economic Review, Vol. 11, pp. 278 96. An Empirical Analysis on the Regional Disparity of Technical Efficiency Realized in China s Service Industries Gu Naihua and Li Jiangfan (School of Business,China Center for Services Sector Research,Sun Yat2Sen University) Abstract : The objective of this paper is threefold. First, to describe the regional disparity of productivity of labor realized in China s service sector over the period 1992 2003. Secondly, to discuss the regional disparity of technical efficiency in China s service sector and its influence on the productivity of labor, using SFA and panel data. Thirdly, to find the factors which affect the technical efficiency. The main results show that the regional disparity of technical efficiency in China s service sector do exist, which is the main cause of the regional disparity of productivity of labor. Moreover, the degree of marketization and the education of employees appear to exert a depressive effect on technical efficiency. At last, the paper gives some suggestions on shortening the regional development disparity of service sector. Key Words :Service Sector ; Technical Efficiency ; Regional Disparity JEL Classification :L890, O140 56 ( :) ( : )