Ξ,, L ucas (1988),,, 1969,, ( 430072) ;, 1981, ( 430072),,,,,,,,, (),, ;,,, Ξ ( 70203008) ( 02J AZJD790022), :, 1998 4, ;,, :, 1998 8 ; :, 2004 8 ; :, http : / / www. huaans. com. cn/ info/ TitleCont. jsp? id = 518176 67
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,,,,,, 1988 1995, ; 1995 1999, ( ), :,, ;,,, 1. : Jonna P. Estudillo, Income Inequality In The Philippines, 1961 91, T he Developing Economies, 1997 1988 1995 1999 :, 1997 9 :, 1997 10 ; :,2004,,, 68,,,,,,,,,,, Yi, Wi ;,, Wi, Yi
: 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 ; 01 2 01 3 ; 013 014 ; 014 01 5 ; 015 ( 67 ), 69
2006 2 (), (, ) ( 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, pp193 106 : (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. 613 625 ; 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. 51 89
,,,, (),, 1978 13316 2003 262212, 1990 ; 1978 6717 %2003 451 6 %,,,,,,,,,, 1995 2003 1996 2004 ( ), 1995 1996, : yi i ; n ( 1995 1996 30, 31) ; m ; m 3 1 1 : 1995 2003 ( T) (L) 1995 013398 451633451 01089418308 141771367 0114986355 1996 013298 421471465 01079540165 151158042 0113866841 1997 013312 421300984 01076756476 151309844 0113512197 1998 013307 411067451 01072587535 151414201 0112760012 1999 013391 411620473 01074605582 151446204 0113055172 2000 013575 431362346 01079999322 151492533 0113651078 2001 013648 441426047 01083780811 151590533 0114239994 2002 01366 441838023 01085015312 151704495 0114357425 2003 0134 431741159 01083040329 151853928 0113983761 : (1996 2004) 1,,, 1990,, 1990 : (2004),,, 2004 7 18 1997,, ; 71
2006 2, s : 2 s 1995 0169 01 23 0105 0103 1996 0173 01 21 0104 0103 1997 0175 01 18 0104 0103 1998 0178 01 15 0104 0103 1999 018 01 12 0105 0103 2000 0179 01 13 0104 0103 2001 0181 01 11 0103 0105 2002 0181 01 09 0105 0105 2003 018 01 09 0105 0106 : (1996 2004) 2,,,,,, (, ),,,,,,,,,,,,,,, (), 9, 15 7, 3 15 64, 1 % ( 3), 13 8500 72, ;, ;,, (2004)
(2000 ), 3/ 4 1000 3 () 1994 141 68 37119 38159 8151 0182 0121 1995 131 47 36162 40111 8161 0196 0124 1996 111 23 35152 42183 8191 1120 0131 1997 101 10 35112 44130 8191 1124 0133 1998 91 56 34149 44199 9115 1146 0137 1999 81 96 33165 46105 9138 1157 0140 2000 81 09 32122 48107 9131 1183 0148 2001 71 69 31114 48188 9165 2102 0161 : (2004),,,, 2001, 522, 10 % 96 %, 64 %2001 75 %, 500, 1/ 4 8310 % 7812 %6210 %, 21, 50 % 3, 1 : (1994 2002), 2 : (1994 2002), : 2003,,, 8899, 492 ;, 21265, 5316 ;, 35233, : (2004) 73
2006 2 33266 ;, 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 : (1994 2002), 4 : (1994 2002),, 1994 2001 8 ( 3),,,, 10 9 ;,,, 8,, 2001 20117 %, 39184 % 34148 %, 0131 % = : (2004), 74
,? (, )?,, 1950 (J. Mincer), 20 60 70, 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 2002,, 2003, (11),,, 1999 2000,,,,, 1997,, 1997,, 75
2006 2, (2003 2004) 2000 10111, 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,,,
,,, 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) 01 073 01663 01099 01 663 k Ip Ij ha H1 Ip H2 Ip H1 Ij H2 Ij (01 082) [ - 01097, 01 244 ] - 010068 (01 003) [ - 01014, 01 000 ] 01 877 (01 064) [01 744, 11010 ] 010069 (01 004) [ - 01001, 01 015 ] 010063 (01 003) [ - 01001, 01 013 ] (01125) [01404, 01 922 ] 01334 (01399) [ - 01492, 11160 ] 01287 (01075) [01132, 01 442 ] 01268 (01348) [ - 01452, 01989 ] 01304 (01311) (01084) [ - 01 075, 01272 ] 0100073 (01001) [ - 01 003, 01002 ] 01849 (01065) [01716, 01983 ] (01 114) [01 429, 01897 ] 01 574 (01 313) [ - 01070, 11 219 ] 01 282 (01 071) [01 136, 01429 ] [ - 01340, 01948 ] DW 21 153 21263 21199 21 199 gr 2 981 9 9517 9818 951 9 F 5121167 1261824 7961 763 2191705,,,,, () p j ;, H1 = 1, H2 = 0, p + h1 j + 1 ;, p + h2 j + 2 (, 77
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
,, 010001 01602 ; - 010005 01638 ; - 010068 01334,,, ;,,,,,,,,,,,,,,,, () ( ),,,, ( ) ( ) ( ),,,,,,,, (),,, :, ;, ;,,,,,,,, : 79
2006 2 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 ( 1978 2003) W an g Zhi gan g Gong L i utang Chen Yuy u 55 Empirical study is conducted to test Chinaπs provincial dataset s ( 1978 2003 ), 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