: 3 ( 11625) :, (25) :1993 1 24 2,,, Tergsvirta, T2O2 O, : LSTR,,,,(25), LSTR LM :1993 1 24 2,,,, (25),,,,,, (,25),(24) MV = PY,,, VECM,, 3 24 : (:747312),, 25 7 17 18,,,! 9
25 12 MWALD,M 1 M 2 ;M 1 M 2 P2T,,,,,,,, STR,, (),STR, (, ) ( y t ) x t, G(, c ; s t ),,,STR, (25),?,?,, Tergsvirta (1998),,, logistic,tergsvirta (1994), ; cal (1995), ; cal Osborn (2) (T2O2O ),, STR ; ;STR ;, STR ;,(25), 1993 1 24 2 GDP ( ln GDP) ( ln i) M 2,( ln rbal), ln GDP ln i ln rbal ADF,5 %,,, (I(1) ), ln GDP ln i ln rbal,, STR : y t = x t < + ( x t ) G(, c ; s t ) + u t, t = 1,L, T (1), <,{ u t }, u t ln GDP, x t, : x t = (1, x 1 t,l, x pt ) = (1, y t - 1,L y t - k ; z 1 t,l, z mt ), y t k 91
: m, p = k + m ln GDP,k = 8, ln i ln rbal, m 2,p = 1 G(, c ; s t ) [,1 ], s t,, x t, G( ), Granger Tergsvirta (1993) STR, LSTR ESTR LSTR G( ) : G(, c ; s t ) = [1 + exp ( - ( s t - c) ) ] - 1,> (2),G( ) s t,> 1, c,,, ESTR G( ) : G(, c ; s t ) = 1 - exp ( - ( s t - c) 2 ),> (3),s t c, G( ),, c,> ;, s t = c y t = x t + u t y t = x t ( + ) + u t ;, STR,Luukkonen Saikkonen Tergsvirta (1988) logistic : G 3 (, c ; s t ) = + 1 s t + 2 s 2 t + 3 s 3 t + R (, c ; s t ) (4), R (, c ; s t ) (4) (1) : y t = x t + ( x t Πs t ) 1 + ( x t Πs 2 t ) 2 + ( x t Πs 3 t ) 3 + u 3 t (5), u 3 t = u t + ( x t ) R (, c ; s t ), Var ( u 3 t ) = Var ( u t ) = 2, x t = ( x 1 t,l, x pt ),, STR, G( ),[,1 ],,,,, G( ) c,, (, + ),c,,,tergsvirta (1994) G( ),; cal (1995), ; cal Osborn (2) T2O2O STR,STAR ; cal (1995) STAR STR,,(25) :,, G( ) logistic, exponential,, Tergsvirta (1998), (5) j, j = 1,2,3, : H 4 3 = ; H 3 2 = 3 = ; H 2 1 = 2 = 3 =, H 3 p2, exponential, 92
25 12 ESTR ;,LSTR, (1) : 8 y t = < + i = 1 < i y t - i + 2 j = 1 8 j z jt + ( < 1 + i = 1 < 1 i y t - i + 2 j = 1 1 j z jt ) G V (, c ; s t ) + u t (6), t = 1,2,L, T, G V (, c ; s t ), (2) (3), : G V 1 (, c ; s t ) = [1 + exp ( - ( s t - c)π^( s t ) ) ] - 1,> (7) G V 2 (, c ; s t ) = 1 - exp ( - ( s t - c) 2 Π^ 2 ( s t ) ),> (8), (6),,,, T2O2O G ( ), (6), :,c, 1 15 ; = 15,,15 2 c s t,4 c,,4 c,g( ),, G( ),,Tergsvirta (1994),,,,, ; = 15,,,,,[1,15 ],15,299 ; c s t 1Π4,4 c (6),,, c,,,,,, AIC,,,, (6) STR, ln rbal ln i (6),STR,STR Sensier Osborn ; cal (22) STR,,, Sensier 196 1994, 14, 5,46,,STR, (25) F, ln rbal ln rabl ( - 5) ln i ln i ( - 1) 1 ln rbal,h 4 H 3 H 2 F131594 3151431143 93
: p 2,,1 H 4 H 3 H 2 F logistic, ln rbal ( - 5) ln i ln i ( - 1), s t H 4 H 3 H 2 ln rbal 13. 594 3. 5143 1. 43 H 4 H 3 H 2 F 1, logistic ln rbal ( - 5) 14. 63 6. 588 1. 94 ln i 5. 793 1. 9953. 21 logistic,, c, ln rbal,: ln i ( - 1) 6. 5752 2. 991. 428 G 1 ( s t ) = [1 + exp{ - 915 ( s t - 183264)Π183623} ] - 1 (9) G 2 ( s t ) = [1 + exp{ - 1 ( s t - 183264)Π183623} ] - 1 (1) (9) (1),,, (1), ln rbal (1) 1 ln rbal ( - 5),: 1 G 2 ( s t ) G 3 ( s t ) = [1 + exp{ - 215 ( s t - 148192)Π183623} ] - 1 (11) (11) (1),,c, (11) (1), ( 2) 2 G 3 ( s t ) c (1), (11) 1 1 2,,,(11) (1) ln i,: g 1 ( s t ) = [1 + exp{ - 1615 ( s t - 13849)Π198291} ] - 1 (12) GAUSS61 94
25 12 g 2 ( s t ) = [1 + exp{ - 17 ( s t - 13849)Π198291} ] - 1 (13) g 3 ( s t ) = [1 + exp{ - 6515 ( s t - 1855)Π198291} ] - 1 (14), (12) (13) 15,, (14),,, lni, (14) ( 3) ln i ( - 1),: 3 g 3 ( s t ) g 4 ( s t ) = [1 + exp{ - 3 ( s t + 15346)Π198291} ] - 1 (15) g 5 ( s t ) = [1 + exp{ - 315 ( s t + 15346)Π198291} ] - 1 (16) g 6 ( s t ) = [1 + exp{ - 215 ( s t + 15346)Π198291} ] - 1 (17),,(15) (15) (16) (4 5) 4 g 4 ( s t ) 5 g 5 ( s t ), (15) (16),,, 2 2,,,,,, 95
:,,, 2 s t c ln rbal ln rbal ( - 5) ln i ln i ( - 1) = 915. 83264 8. 654 % = 1. 83264 8. 654 % = 215. 48192 4. 919 % = 6515. 855. 859 % = 3 -. 5346-5. 26 % = 315 -. 5346-5. 26 % 2,,, 81654 % ;,, 311 %,,= 15 = 1, = 6515 ;,1, 5,,, STR,Sensier Osborn ; cal (22) Sensier Osborn ; cal (22) STR,,,,,, (9) (1) (11) (14) (15) (16) (6),,, AIC, AIC 3, t2p R 2 3,:, (25), lnrbal ln rbal ( - 5),, ln rbal ( - 5), ln rbal ln GDP( - 1) ln GDP( - 6) ln rbal 2,,,,,,, ln rbal ( - 5), 96
25 12 3 ln GDP( - 1) ln rbal STR ln rbal ( - 5) ln i ln i ( - 1) = 915 = 1 = 215 = 6515 = 3 = 315 -. 39628. 37 -. 38248. 395 ln GDP( - 2) ln GDP( - 3) ln GDP( - 4) -. 648975. 129. 545987. 2. 926934. 32. 949531. 18. 166935. 16 ln GDP( - 5) ln GDP( - 6). 275447. 5. 27682. 4. 184151. 35 ln GDP( - 7). 911911. 392 -. 74627. 46. 87642. 436 -. 72591. 47-1. 13966. 1-1. 96991. 2 ln GDP( - 8) ln rbal -. 129478. 269 -. 13292. 225-1. 345343. 5 ln i G ln GDP( - 1) G ln GDP( - 2) G ln GDP( - 3) G ln GDP( - 4) G ln GDP( - 5) 4. 7545. 2. 988334. - 1. 692183. 31-1. 16428. 149 -. 49812. 5 5. 56943. 2 1. 31388. - 1. 838642. 23-1. 27942. 13 -. 53385. 3. 764864. 268-1. 66627. - 1. 9591. 17 -. 988467. 32 G ln GDP( - 6) G ln GDP( - 7) G ln GDP( - 8). 633176. 24-1. 182293.. 671782. 18-1. 256776. G ln rbal -. 174243. 9 1. 185694. 11 -. 32. 18 -. 29147. 123 12. 475. 62-2. 26713. 129 46. 43439. 38-24. 54342. 85 41. 2597. 48-4. 15666. 42-41. 37238. 37 G ln i CONSTANT. 25517. 4. 25358. 3 G. 18995. 316. 58311. 8. 13775. 233 1. 19171. 85-1. 9827. 44 1. 162637. 18 1. 94219.. 568373. 36. 22496. 3-1. 16729. 449 1. 1557. 16 1. 827893.. 53571. 42. 22666. 3 R 2. 836682. 83989. 877649. 76667. 783495. 7835 97
:,STR (6),, s t = ln rbal, ln GDP ;s t = ln i,,, ln GDP ( - 4), G ln GDP( - 1) G ln GDP ( - 5) G ln i, 1,,,,,;, ln rbal ( - 5),,,,,,,,,, ;,,,,,,,,3,STR,VAR 15 16,, 175,,, 183,,,STR, STR 8 9,,,,,,,c >, < G() 1, s t > c,,,, s t = ln i,,s t = ln i ( - 1),,, ln rbal ln i, R1 R2,,, 1 ;- 1 ;( 6) 6 R1 R2 :1993 3 4,1997 3 4,1998 2 3 4,2 3 4,22 3 4, 24 1 2 4 rbal i ;,, 98
25 12 4 1993 rbal i 3 -. 21868. 24112 4. 65569. 13389 6 R1 R2 ln rbal ln rbal ( - 5) ln i ln i ( - 1) = 915 = 1 = 215 = 6515 = 3 = 315-1. 841 % - 2. 971 %. 985-1. 841 % - 2. 971 %. 886-7. 158 % 1. 6379 %. 9781 23. 2512 % 1. 4799 %. 9595 29. 3 %. 9997 6. 54 %. 8847 29. 3 %. 9999 6. 54 %. 9151 1997 3. 54474 -. 21955 4. 67371 -. 118738-3. 266 %. 322-1. 9169 %. 1168-3. 266 %. 27-1. 9169 %. 163. 5284 %. 7741 1. 8181 %. 9854-3. 545 % - 12. 733 % 3. 1 %. 7219-6. 67 %. 974 3. 1 %. 7527-6. 67 %. 693 1998 2. 488626 -. 191359 3. 55167 -. 2314 4. 286 % 1-3. 1373 %. 346 4. 286 % 1-3. 1373 %. 292 43. 9436 % 1. 5977 %. 81-19. 995 % - 23. 869 % - 13. 9 %. 78-17. 8 %. 17-13. 9 %. 35-17. 8 %. 6 2 4. 4929 -. 94348 3. 22761 -. 11335-4. 5611 %. 76-6. 3779 %. 1-4. 5611 %. 59-6. 3779 %. 7 -. 8261 %. 1259-2. 6429 %. 19-1. 294 % - 1. 9925 % - 4. 23 %. 1989 4. 7 %. 7831-4. 23 %. 1645 4. 7 %. 8172 22 4. 13879. 22448 3. 319-7. 2661 %. 4-5. 464 %. 28-7. 2661 %. 3-5. 464 %. 21-3. 5311 %. 2-1. 729 %. 167 1. 3858 %. 9999 -. 859 %. 33 7. 45 %. 996 5. 21 %. 8364 7. 45 %. 9367 5. 21 %. 873 24 4. 38162 1. 44642 -. 121729-4. 8378 %. 56-4. 1898 %. 113-4. 8378 %. 43-4. 1898 %. 9-1. 128 %. 697 -. 4548 %. 2563 -. 859 %. 33-13. 32 % 5. 21 %. 8364-6. 97 %. 887 5. 21 %. 873-6. 97 %. 619 2. 2516. 37278-6. 1434 %. 13-6. 1434 %. 9-2. 484 %. 34 2. 8688 % 1 8. 93 %. 9398 8. 93 %. 9611, 99
:, (1 5),1993 3 4,1997 3,1998 2,2 3 4, 24 2, 1998 2,,1997 4, ln rbal, ln rbal ( - 5). 9854,11998 2,1997,,,, 1997 1999,,,1998 1998 3 13 % 8 %, 1997 1 7. 2 % 1999 6 2. 7 % ;,9. 36 % 3. 78 %, 1998,,, 1998 1 1 % 2 % ;1999 9, 9 %,2 %3 %, STR,,,,,,,, 25 7 21 19, :,,,,25 :,,24 : VECM DSGE,,25 :, 2 Luukkonen, R., Saikkonen, P., Tergsvirta, T., 1988,Testing Linearity against Smooth Transition Autoregression, Biometrika, 75, 491 499. Granger,C. W.J.,Tergsvirta,T.,1993,Modeling Nonlinear Economic Relationships,Oxford University Press,Oxford. ; cal, N., 1995, Nonlinear Models for UK Macroeconomic Time Series. Discussion Paper 9526, School of Economic Studies. University of Manchester. ; cal, N., Osborn, D. R., 2, Business Cycle Non2linearities in UK Consumption and Production. Journal of Applied Econometrics, Vol. 15, pp. 27 43. Sensier, M., Osborn, D. R., Ocal, N., 22, Asymmetric Interest Rate Effects for the UK Real Economy. Oxford Bulletin of Economics and Statistics, Vol. 64, pp. 315 339. Tergsvirta, T., 1994, Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Statistical Association, 89, 28 218. 1 Journal of the American
25 12 Tergsvirta, T., 1998, Modeling Economic Relationships with Smooth Transition Regressions. In : Ullah, A., Giles, D. E. A. ( Eds. ). Handbook of Applied Economic Statistics. Statistics : Textbooks and Monographs, Vol. 155. Dekker, New York, Basel and Hong Kong, pp. 57 552. Measurement for the Breakpoints and Transition Functions for Monetary Policy Operation of China s Center Bank Zhao Jinwen and Min Jie (School of Statistics, Dongbei University of Finance and Economics) Abstract:The operation of monetary policy is an important instrument for the government to control the economy on the macro scope. Different country, different region and different period of economic progress have great difference in their impact and characteristics of the monetary policy. The research of Zhao jinwen and Minjie (25) indicates that the effect of China s monetary policy shows an obvious asymmetry and strong nonlinearity during the period of the first quarter of 1993 to the second quarter of 24. On the basis of the previous research, this paper determined the type of the transition function for the central bank monetary policy operation by the Tergsvirta test in the first place. Then, the breakpoints of China s monetary policy operation and specific form of the transition function will be determined through the advanced and complicated T2O2O grid search. The conclusion has significant and direct implications for the improvement of China s macro2control policy and the persistent, fast, healthy and harmonious development of national economy. Key Words :Monetary Policy ;LSTR Model ; Breakpoints ;Transition Functions ; Grid Search JEL Classification : E52,E63,C51 ( :) ( :) ( 14 ) Equality for the Sake of Gro wth : The Nexus of Inequality, Investment, Education and Gro wth in China Lu Ming, Chen Zhao and Wan Guanghua ( Fudan University) (Development Economics Reserarch Center,UN) Abstract :This paper incorporates distribution2lag model into a system of equations to study the nexus of inequality, investment, education and growth in China. The major findings are : (1) Inequality has strong instant negative effect on investment. The effect turns to be positive and then falls down gradually until weakly negative. In the long run, the cumulative effect of inequality on investment is negative. (2) Inequality has moderate effect on education, and the cumulative effect is positive. (3) The effect of inequality on investment overweighs its effect on education, so inequality has a strong indirect effect on growth instantaneously. The effect turns positive and then weakly negative. The cumulative effect of inequality on growth is always negative. Besides, we also find growth reduces inequality. Therefore, narrowing inequality enhances growth, and conversely mitigates inequality. Equality and growth can be achieved simultaneously. Key Words : Inequality ; Investment ; Education ; Growth JEL Classification :D63,J21,O4 ( :) ( : ) 11