2006 2,??,, 20,, : T ( Theil index) L ( Theil second measure) : (1) (transfer principle Pigou2Dalton condition),, ; (2) ( mean independence),, ; (3) (

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1 Ξ,, L ucas (1988),,, 1969,, ( ) ;, 1981, ( ),,,,,,,,, (),, ;,,, Ξ ( ) ( 02J AZJD790022), :, , ;,, :, ; :, ; :, http : / / www. huaans. com. cn/ info/ TitleCont. jsp? id =

2 2006 2,??,, 20,, : T ( Theil index) L ( Theil second measure) : (1) (transfer principle Pigou2Dalton condition),, ; (2) ( mean independence),, ; (3) (pop ulation2size independence),, ; (4) (decomposability),,,,,, 1990,,,,,, , ; , ( ), :,, ;,,, 1. : Jonna P. Estudillo, Income Inequality In The Philippines, , T he Developing Economies, :, :, ; :,2004,,, 68,,,,,,,,,,, Yi, Wi ;,, Wi, Yi

3 : G = n n- 1 Yi + 2 i = 1Wi i = 1 Wi (1 - Vi) - 1 (1), Wi ; Yi, ; Vi Yi i = 1 i, Vi = Y1 + Y2 + Y3 + + Yi 2. : (coefficient of variance, CV) (relative standard deviation) : CV = (s/ gx) 100 (2), s = ; gx = 3. ( T) : T = 1 yi n i yi log m m, yi i ; n ; m 4. (L) : L = 1 n log m i yi, n m yi 3 5. : V = i (logm 3 - logyi) 2 / n (5), n yi 3, m 3,,,,,,,, (),,,, () ;, (3) (4),,,, 0 1, 0, ;, ; 1, : 012 ; ; ; ; 015 ( 67 ), 69

4 (), (, ) ( A. F. Shorrocks), :, i yi yiki k : yi = k yik,i = 1,,N ;y = (y1,,yn ) ;yk = (y1k,,ynk) (6), 6,, s, : sk = COV (yk,y) 2 (y), s. t. sk = 1 (7) k, s, ;, 1990,, (),,,,,,,,,,, :, 31,,,,,,,, ( R. L ucas),, Evidence from Rural China, T he Economic J ournal, 2002, 112, pp : (1) ; (2) ; (3) ; (4) 70 Jonathan Morduch, Terry Sicular, Rethinking Inequality Decomposition, with ; (5) ; (6), Guass s A. F. Shorrocks, The Class of Additive Decomposable Inequality Measures, Economet rica, 1980, 48, pp ; A. F. Shorrocks, Decomposition Procedures for Distributional Analysis : A Unified Framework Based on the Shapley Value, 1999, mimeo, University of Essex ; M. Sastre and A. Trannoy, Shapley Inequality Decomposition by Factor Component s : Some Methodological Issues, J ournal of Economics, Supplement 9, 2002, pp

5 ,,,, (),, , 1990 ; % %,,,,,,,,,, ( ), , : yi i ; n ( , 31) ; m ; m : ( T) (L) : ( ) 1,,, 1990,, 1990 : (2004),,, ,, ; 71

6 2006 2, s : 2 s : ( ) 2,,,,,, (, ),,,,,,,,,,,,,,, (), 9, 15 7, , 1 % ( 3), , ;, ;,, (2004)

7 (2000 ), 3/ () : (2004),,,, 2001, 522, 10 % 96 %, 64 % %, 500, 1/ % 7812 %6210 %, 21, 50 % 3, 1 : ( ), 2 : ( ), : 2003,,, 8899, 492 ;, 21265, 5316 ;, 35233, : (2004) 73

8 ;, 23488, 42756, 819 %, 015 % ; 2113 %, 513 % ; 3512 %, 3313 % ; 2315 %, 4218 %, 1 4 1,,, 1999, (2001 ) 1993,, 1999, 2001 (2) 8 %, 50 % 60 % (3), 1999,,,,,,, 1995, 1999, 40 % ( 4) 3 : ( ), 4 : ( ),, ( 3),,,, 10 9 ;,,, 8,, %, % %, 0131 % = : (2004), 74

9 ,? (, )?,, 1950 (J. Mincer), , 1980,,,,,, : Yt = A K [ u (t) h (t) N (t) ] 1 - h (8), Yt t, K, N, u, h, A, h (8) : Log Yt = Log Kt + LogA + (1 - ) [Logu + LogN ] + (1 - ) Logh +Logh(9), : Log Yt / N = Log K/ N + (1 - ) Logu + LogA + (1 - ) Logh +Logh (10) Yt / N y, K/ N k (10), A u,, : y = k + (1 - )h + h (11) 28 ( ),, 2002 (11) y, ,, 2003, (11),,, ,,,,, 1997,, 1997,, 75

10 2006 2, ( ) , h, ( ),, h,, /, 2001, :,,, 6,, 3 : =, Ip, Ij ; p, p (1 )h = p Ip + j Ij (12) (3) y = k + p Ip + j Ij +h (13), Ip =, Ij 6 (13), 2002, 2001, 2001 (, ) 2002,,,,,,, H1 H2 (4),,,,, 76,,,

11 ,,, H1 = 1, H1 = 0 ;, H2 = 1, H2 = 0, y = k + p Ip + h1 H1 Ip + h2 H2 Ip + hap (14) y = k + j Ij + 1 H1 Ij + 2 H2 Ij + haj (15) 4 (, 95 %) y (1) (2) (3) (4) k Ip Ij ha H1 Ip H2 Ip H1 Ij H2 Ij (01 082) [ , ] (01 003) [ , ] (01 064) [01 744, ] (01 004) [ , ] (01 003) [ , ] (01125) [01404, ] (01399) [ , ] (01075) [01132, ] (01348) [ , ] (01311) (01084) [ , ] (01001) [ , ] (01065) [01716, ] (01 114) [01 429, ] (01 313) [ , ] (01 071) [01 136, ] [ , ] DW gr F ,,,,, () p j ;, H1 = 1, H2 = 0, p + h1 j + 1 ;, p + h2 j + 2 (, 77

12 2006 2,,, ) OL S (14) (15), 4 (1) (2) gr 2 95 %,, 5 %, F, 5 %, 4, 95 %, DW 2,, (14) (15) : H0 : h1 = 0, h2 = 0 H0 : 1 = 0, 2 = 0 : y =k + p Ip + hap (16) y =k + j Ij +hap (17) F, H0 4 (3) (4), (16) (17) F, : 4, :,,, ( 1),,,,,,,,, 1,, 3,,,,,,,,,,,, 2 4,,,,,,,,, 78

13 ,, ; ; ,,, ;,,,,,,,,,,,,,,,, () ( ),,,, ( ) ( ) ( ),,,,,,,, (),,, :, ;, ;,,,,,,,, : 79

14 In recent years, research on bot h t he asymmetry of t he effect of monetary policy and it s effect on inflation has raised great concern abroad in t he field of finance. Paolo Suricaπs (2004) belief t hat nonlinearity is a robust feat ure of U S monetary policy holds only for t he period before 1979 and wit h respect to the outp ut gap, and this implies an average inflation bias during t he 1960s and 1970s but a value not statistically different f rom zero over t he last two decades. With t he targeting f unction defined by the forward2looking struct ure of t he economy and non2quadratic lo ss f unctio n, we o btain t he optimal and no nlinear respo nse rules. By using t he Generalized Met hod of Moment s ( GMM), we contrast t he result s of reduced2form and struct ural estimates of central bank first order condition ( Eular equation) under t he framework of asymmetric preference and nonlinear response rules. inflatio n bias. Through a simple device, t his paper provides a discussion of t he The result indicates cent ral bank asymmet ric p reference and no nlinear mo netary policy response rules contribute to t he inflation bias. (5) Chinaπs Regional Differences in Technical Eff iciency and the Decomposition of Total Factor Productivity Growth ( ) W an g Zhi gan g Gong L i utang Chen Yuy u 55 Empirical study is conducted to test Chinaπs provincial dataset s ( ), using a translog p roduction f unction in a general stochastic frontier specification. The findings of this st udy show t hat t he eastern regio n is t he mo st efficient while t he western regio n is t he least efficient, and t he difference between t hem is significant and almo st co nstant during t he recent year s. St ro nger market forces and human capital are important facto rs for efficiency imp rovement and may decrease production uncertainty, while a higher government spending ratio is harmf ul to efficiency and increases production uncertainty. Finally, the st udy finds that TFP ( Total Factor Productivit y) has been decreasing since 1995, but t he reaso ns behind t his call for f urt her research. Technological progress is the main driving force for TFP, and more effort s should be made to improve technical efficiency in t he f ut ure. (6) The Income Gap and the Accumulation of Human Capital in Rural China Zou W ei Zhan g Fen 67 The income gap between rural and urban areas, and among different rural areas in China has drawn wide attention. This st udy attempt s to explain t he income gap in rural China f rom t he perspective of human capital ( particularly t he level of educatio n). In analyzing t he growing income gap trend among different rural areas, the aut hors of this article specify income gap s by so urces of inco me and undertake met rological research. According to t heir st udy, t he wage income gap in rural areas present s as a major factor contributing to growing income gap s. Wage income in rural areas is mainly co2related wit h farmersπ level of education. Finally, t he article analyses t he effect s of education on income gap s in rural areas with the extended model by L ucas (1988), and co ncludes t hat t here is a significant correlatio n between rural inco me gap s and farmer sπ level of educatio n. Therefore, t he key to narrowing rural inco me gap s lies in imp rovement of educatio n (particularly elementary and seco ndary educatio n) in rural areas. (7) Integration of Trade and Disintegration of Production : An Empirical Study Based on Two 206

CHIPS Oaxaca - Blinder % Sicular et al CASS Becker & Chiswick ~ 2000 Becker & Chiswick 196

CHIPS Oaxaca - Blinder % Sicular et al CASS Becker & Chiswick ~ 2000 Becker & Chiswick 196 2015 3 179 2015 5 Comparative Economic & Social Systems No. 3 2015 May 2015 2001 ~ 2011 F812 A 1003-3947 2015 03-0020-14 Wu & Perloff 2004 Benjamin et al. 2004 Sicular et al. 2007 1998 2003 40% 1985 2.