2012 12 * CPI FAVAR CPI 5 2010 2011 134% CPI 2001 CPI 2002 2002Q2-1. 1 2002 2004Q3 5. 3 2006Q1 1. 2 8 2008Q1 8 2009Q2-1. 5 2011 7 6. 5% CPI 2008 2009 2011 2008 2009 2010 * 430074 wangspi@ sina. com 430074 zhumanzhou@ 126. com Fxkjhss@ vip. 163. com 29
CPI Facor-Augmened Vecor Auoregressive FAVAR Sargen & Sims 1977 Giannone e al. 2004 Sock & Wason 2002a Bai & Ng 2006 Bernanke e al. 2005 FAVAR Boivin e al. 2009 FAVAR FAVAR 2008 2009 CPI 2009 FAVAR 2011 2011 2012 FAVAR GDP CPI FAVAR FAVAR FAVAR CPI CPI 2005Q1 2007Q3 M2 14% 18. 5% 22. 8% 25. 7% CPI 2. 8% 6. 1% M2 2008 CPI 2009Q3-1. 3 2009Q3 2010Q4 M2 18. 46% 29. 31% 30% 2010Q1 2010Q4 25% CPI 2009Q3-1. 3% 2010Q4 4. 7% 2011Q3 6. 3% 2007 2010 2011 CPI CPI FAVAR Sims 1980 VAR Y = Ψ( L) Y -1 + v 1 Y M 1 L Ψ ( L) Sims 1992 Y Y = y π m R ' y π m R Sims 1 30
2012 12 price puzzle Sims 1 1 VAR X N x ~ I 0 0 1 X X k - 1 F R X CPI R F k C = F' R ' X X = ΛC + e 2 Λ N k C k k = N N 1 VAR C = Φ( L) C -1 + v 3 2 3 FAVAR 1 3 R F VAR 2 F Λ FAVAR CPI π i e π i = λ' i C + e i 4 λ' i Λ CPI 4 π i λ' i C e i λ' i C CPI Boivin e al. 2009 Reis & Wason 2010 CPI CPI FAVAR X Bai Ng 2002 Bernanke e al. 2005 Bernanke e al. 2005 1 1 R C 2 4 CPI F 2 4 F k - 1 F CPI k - 1 F k FAVAR 2 3 2 F^ Λ^ e^ Sock & Wason 2002a Bai & Ng 2006 F^ 3 F OLS 3 Φ^ ( L) v^ CPI 81 X 1 GDP 2 3 31
CPI 4 5 6 7 PPI CPI 1 8 M0 M1 M2 9 9 81 81 2001 1 2011 3 CEIC X - 12 FAVAR ~ I 0 0 1 X x X 1 X CPI 2 3 4 R R ~ I 0 ADF PP X I 0 FAVAR 1. X F 7 R 8 C = F' R ' X R Boivin e al. 2009 F FAVAR 2 3 1 X 7 F F 0 a X R X F ( 0) R R λ^ 0 R b X ~ 0 0 = X - λ^ R R X R c X ~ 0 7 F F 1 F 1 R d X ~ 0 F 1 1 50 F^ F^ R 2 OLS Λ e 2 F^ 3 3 F AIC 3 OLS ^ Φ ( L) v^ 121 7 81 8 Λ 1B 5 7 4 1 F^ F1 F4 0 32 1 2000 12
2012 12 I 0 1 F1 2007 2008 2011 M2 PPI F2 10 2001 2002 2004 2008 2009 2010 2011 F3 F4 F1 F2 Bernanke e al. 2005 R 2 i var λ^ ' i C^ λ^ ' = var x i = i C^ 2 2 ( x ) var 1 r 2 1 F1 F2 F6 1 i 5 CPI PPI 0. 82 0. 03 0. 55 0. 001 0. 61 0. 02 0. 17 0. 001 0. 80 0. 03 0. 2 0. 01 0. 87 0. 001 0. 05 0. 08 0. 76 0. 43 0. 05 0. 13 0. 71 0. 15 0. 001 0. 001 0. 71 0. 17 0. 22 0. 02 A A 7 M1 M2 0. 86 0. 14 0. 01 0. 03 0. 86 0. 18 0. 01 0. 06 0. 90 0. 61 0. 01 0. 06 0. 42 0. 24 0. 07 0. 01 R 2 0. 39 0. 24 0. 03 0. 03 r 2 1 C 0. 82 0. 61 0. 8 0. 87 CPI PPI 0. 71 0. 90 0. 86 M1 M2 0. 42 0. 39 0. 54 r 2 0. 001 0. 02 0. 02 0. 54 0. 01 0. 28 0 33
CPI 5 X 81 R 2 0. 57 M1 M2 0. 61 0. 24 0. 24 PPI 0. 55 2. CPI 1 CPI CPI FAVAR 2 CPI 4 2 2 CPI F 1 F 2 F 3 F 4 F 5 F 6 F 7 R CPI - 0. 69-0. 11 0. 67 0. 59 0. 31 0. 03-0. 09-0. 18-1. 34-0. 37 1. 43 1. 55 0. 79-0. 11-0. 74-0. 35-0. 23-0. 04 0. 07 0. 03 0. 07-0. 19 0. 16-0. 05-0. 18 0. 17 0. 03 0. 12 0. 04-0. 14 0. 38-0. 05-0. 23 0. 06 0. 18-0. 16 0. 11-0. 53 0. 13-0. 02-0. 18 0. 08 0. 12 0. 00 0. 20-0. 36 0. 34-0. 08-0. 46-0. 31 0. 22 0. 48-0. 04 0. 10 0. 24-0. 16-0. 19-0. 47 0. 39-0. 12 0. 10 0. 50-0. 16-0. 06-0. 58 0. 56 0. 63 0. 24-0. 25 0. 28 0. 47-0. 07 R CPI - 0. 18 FAVAR 4 CPI λ' i C e i CPI 2 2 2004 2 2004M02 CPI 1. 09 CPI - 1. 06 2008M02 1. 72 1 2009M02-0. 93-1. 26 34
2012 12 0. 41 0. 34 0. 22 71% 29% 2005 2007 M2 17. 6% 16. 9% 16. 7% 2008M02 1. 72 1 2008M12-0. 87-0. 88 100% M2 2009M03 25. 5% 2009M11 29. 74% 2A 2008M11-0. 85-0. 70 0. 23 0. 33 140% 3. CPI Boivin e al. 2009 w = ρ( L) w -1 + ε 6 6 ρ( L) L AIC 1-7 ρ ( 1) 3 3 CPI 0. 41 0. 34 0. 51 3 0. 77 4 0. 11 1 1. 04 0. 76 0. 14 1 0. 72 4 0. 13 1 0. 19 0. 17 0. 93 4 0. 94 2 0. 48 2 0. 30 0. 20 0. 08 2 0. 47 3 0. 07 2 0. 34 0. 24-0. 36 1 0. 19 5-0. 16 1 0. 45 0. 39 0. 66 1 0. 87 1 0. 15 1 2 4 CPI CPI CPI CPI CPI CPI CPI CPI 2 4 CPI > 0 CPI < 0 CPI CPI 3 0. 77 0. 72 0. 51 0. 14 0. 11 0. 13 6 CPI 35
CPI 6 Wold 6 AR MA w = δ( L) ε MA CPI MA MA 3 3A 3C CPI CPI 0. 41 0. 3B 3C CPI 3 3C CPI 2-3 3B CPI 2 3A CPI 1 3 CPI CPI CPI CPI 2005M01 2006M03 2A 1 2-0. 08 M2 15% 2. 25% 1. 43% GDP 9% M2 0. 05 M2 CPI - 0. 3 0. 6 47% 50% 53% CPI 50% CPI M2 4 36
2012 12 4 CPI 1 CPI CPI 05M01-06M03-0. 08-0. 04-0. 04 47% 2005Q1-0. 35-0. 10-0. 25 30% 2006Q1 0. 14 0. 00 0. 14-2% 0. 05 0. 01 0. 04 16% CPI 03M10-04M09 0. 21 0. 12 0. 09 57% 2003 0. 51 0. 24 0. 27 48% 2004 0. 25 0. 22 0. 03 88% - 0. 10-0. 03-0. 08 25% CPI 06M10-08M06 0. 32 0. 27 0. 05 83% 2007 0. 76 0. 59 0. 17 78% 2008 0. 20 0. 27-0. 07 135% 06M10-08M10 0. 23 0. 22 0. 01 95% CPI 08M07-09M06-0. 35-0. 41 0. 06 118% 2008-0. 57-0. 78 0. 20 135% 2009-0. 75-0. 73-0. 02 98% 08M11-09M10-0. 11-0. 09-0. 03 76% CPI 09M10-11M03 0. 17 0. 23-0. 06 134% 2010 0. 28 0. 40-0. 12 142% 2011 0. 26 0. 31-0. 05 121% 10M01-11M03 0. 13 0. 14-0. 01 109% M2CPI A B M2 0. 05 15. 99% - 0. 03 17. 77% 0. 23 17. 46% 0. 38 15. 88% 0. 18 21. 43% 1. A < 0. 1 2. B < 50% 1. 0. 1 < A < 0. 2 2. 50% < B < 80% 1. A > 0. 2 2. 80% < B < 100% 1. A < - 0. 2 2. B > 100% 1. A > 0. 2 2. B > 100% 4 2005Q1 2006Q1 5 47% 57% 83% 118% 134% 1. CPI 31% CPI CPI CPI 50% CPI 2006M10 2008M06 0. 27 83% 17% CPI CPI 2A 2006M04 M10 CPI CPI 80% 1 M2 2008M07 ~ 2009M06 2008M11 M2 14. 8% 2009M03 25. 5% 2009 2009 M2 37
CPI CPI 2003M10 2004M09 57% CPI M2 2003Q2 20. 8% 2008 2 2008M08 2009M02-1. 26 4 0. 27-0. 41 83% 118% 2008Q3 2008Q4 69% 115% 1 2009 2010 M2 27. 7% 19. 7% 2009 35% 0. 23 134% 2010Q3 2010Q4 2011Q1 42% 86% 185% 4 CPI 2003 2004 2010 2011 CPI 0. 21 0. 17 CPI 0. 12 0. 23 57% 134% 2010 2011 2003 2004 2. CPI CPI CPI 2005Q1 2006Q1 53% CPI 2003M10 2004M09 43% CPI CPI 0. 27 CPI CPI 2006M10 2008M06 17% CPI 0. 17 2008 100% 2008 19% 2010 38
2012 12 CPI 3. 2005M01 2006M03 M2 0. 05 M2 CPI 2006M10 2008M06 M2 0. 23 M2 83% M2 0. 38 2008M07 2009M06 M2 2008M07 16. 4% 14. 8% 2008M12 17. 8% 2009M06 28. 46% 2009M10 2010M12 M2 0. 18 M2 3 4 FAVAR 1 1. 3 v^ Σ v Σ v Choleski R * 2. R * FAVAR 3 FAVAR 3 VMA C h C ~ h 3. λ' i C ~ h λ' i - 0. 25 4 ~ π ~ π 4 CPI h R - 1 R h = 4A 2 R CPI 1 2 FAVAR Boivin e al. 2009 A Boivin e al. 2009 4A CPI Boivin e al. 2009 39
CPI 0 6 7 20 0 4A FAVAR CPI 4B 6 8 4C 6 15 17 6 CPI 81 81 7 FAVAR CPI 1 81 7 8 82% 80% 87% CPI PPI 71% 71% 86% 86% 81 57% 2 FAVAR 2005M01 2006M03 2003M10 2004M09 2006M10 2008M06 2008M07 2009M06 2009M10 2011M03 5 47% 57% 83% 118% 134% CPI GDP 47% 53% CPI CPI CPI 57% CPI 83% 118% 134% 3 CPI CPI CPI 2 3 CPI 2 CPI 40 R
2012 12 CPI FAVAR CPI FAVAR 4 FAVAR FAVAR FAVAR FAVAR 2012 1 2008 8 2009 9 1 2011 7 2008 7 2011 2 2010 7 2009 11 2009 1 2011 9 2008 2 2009 CPI 11 2011 5 Bai J. and S. Ng 2002 Deermining he Number of Facors in Approximae Facor Models Economerica Vol. 70 191 221. Bai J. and S. Ng 2006 Confidence Inervals for Diffusion Index Forecass and Inference for Facor-Augmened Regressions Economerica Vol. 74 1133 1150. Bernanke B. S. J. Boivin and P. Eliasz 2005 Measuring he Effecs of Moneary Policy A Facor-Augmened Vecor Auoregressive FAVAR Approach Quarerly Journal of Economics Vol. 120 387 422. Boivin J. M. P. Giannoni and I. Mihov 2009 Sicky Prices and Moneary Policy Evidence from Disaggregaed US Daa American Economic Review Vol. 99 350 384. Giannone D. L. Reichlin and L. Sala 2004 Moneary Policy in Real Time NBER Macroeconomics Annual 2004 161 200. Reis R. and M. W. Wason 2010 Relaive Goods Prices Pure Inflaion and he Phillips Correlaion American Economic Journal Macroeconomics Vol. 2 128 157. Sargen T. J. and C. A. Sims 1977 Business Cycle Modeling Wihou Preending o Have Too Much A-Priori Economic Theory New Mehods in Business Cycle Research ed. Federal Reserve Bank of Minneapolis. Sims C. A. 1980 Macroeconomics and Realiy Economerica Vol. 48 1 48. Sims C. A. 1992 Inerpreing he Macroeconomic Time Series Facs The Effecs of Moneary Policy European Economic Review Vol. 36 975 1000. Sock J. H. and M. W. Wason 1996 Evidence on Srucural Insabiliy in Macroeconomic Time Series Relaions Journal of Business and Economic Saisics Vol. 14 11 30. Sock J. H. and M. W. Wason 1999 Forecasing Inflaion Journal of Moneary Economics Vol. 44 293 335. Sock J. H. and M. W. Wason 2002a Forecasing Using Principal Componens from a Large Number of Predicors Journal of he 41
CPI American Saisical Associaion Vol. 97 1167 1179. Sock J. H. and M. W. Wason 2002b Macroeconomic Forecasing Using Diffusion Indexes Journal of Business and Economic Saisics Vol. 20 147 162. Macroeconomic Componen and Macroeconomic Shocks of China s CPI Index Wang Shaoping Zhu Manzhou and Hu Shuoshang Huazhong Universiy of Science and Technology Absrac This paper exracs seven common facors from Chinese macroeconomic informaion se and esablishes a facoraugmened vecor auoregressive model FAVAR by he seven facors and moneary facor. We decompose he flucuaions in China s CPI index ino macroeconomic componen ha are due o macroeconomic facors and idiosyncraic shocks which come from disaggregae prices variaions. Then we conduc some ypical impulse response of he CPI index o macroeconomic shocks. Our main finding is ha he eigh macroeconomic facors do capure imporan dimensions of Chinese macroeconomic movemens. The analysis of macroeconomic componen and is mean s raio o he mean of inflaion rae iself provides a new sigh for properies and sources of Chinese inflaion in he differen ime periods. Typically he raio is 134% in he 2010 2011 period of inflaion which shows his is a serious inflaion and is driven by macroeconomic facors. The effecs of macroeconomic shocks imply ha ighening of boh moneary and demand raher han only moneary iself will effecively sabilize he inflaion. Key Words Inflaion Macroeconomic Componen Idiosyncraic Shock Facor-augmened Vecor Auoregressive JEL Classificaion C32 E31 E52 檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵 14 Realizaion Mechanism of China s Moneary Policy Targes 2001 2010 Wang Guogang Insiue of Finance and Banking Chinese Academy of Social Sciences Absrac This aricle explores he realizaion mechanism for he final and inerim arges of China s moneary policy from 2001 o 2010. I finds ha he hree significan price surges in he en years were no he resuls of loose moneary policy. While keeping he rapid economic growh China avoided he inflaion linked wih excess money issuance. The inroducion of loan incremen in he inerim arges also showed he mauring of China s moneary policy arge sysem. To improve China s moneary operaion hree measures need o be aken firsly basing sabilizing moneary policy on he rend of non-food price index in CPI secondly readjusing he definiion of money according o he differen characerisics of ransacion money and sorage money hirdly including RMB exchange raes ino he inerim arges of moneary policy. Key Words Moneary Policy Targe Realizaion Mechanism JEL Classificaion E51 E52 42