金融加速器效应区域差异性研究_以房地产业对货币政策的传导为例

[]2009-06-22[](1970-),,,,,(,510275)[]19992008,VAR,:23,7;16,,,[];;[]F830.572[]A[]1007-9556(2009)08-0102-07AreaDifferenceofFinancialAcceleratorEffectofHousingCreditMarketinChinaBasedonRealEstateIndustrytoMonearyPolicyYUANShen-Guo(LingnanCollege,SunYat-senUniversity,Guangzhou510275,China)Abstract:Thepapermakesuseofthemonthlydatumfrom1999to2008,analyzingtheareadifferenceoffinancialacceleratoreffectofhousingcreditmarketinChinabyVARandpulseresponsefunction.Itconcludesthat,among23investigationobjects,thereare7provincesdonotexistdistinctthiseffect,whileamongother16provinces,Shanghaicityhasthebiggesteffect,thefollowingareJiangxiandYunnanprovinces,LiaoningandShanxiprovinceshavethesmallesteffect.Theseconclusionswillhelpmonetaryauthoritiestosetdownadaptivemone2tarypolicyandcreditpolicy.KeyWords:monetarypolicy;FinancialAcceleratorEffect;areadifferenceBernankeGertlerGilchrist(1989[1],1994[2]),,,,BernankeGertlerandGilchrist(1998)[3],GertlerGilchristandNatalucci(2003)[4],Ao2kiProudmanandVlieghe(2004)[5],H.Almeida,M.CampelloandC.Liu(2006)[6],(2007)[7],,GertlerGilchrist(1991)[8],BenankeGertlerGilchrist(1994)[2],(2007)[9],(2009)[10],,30,,,,20120098318///////JournalofShanXiFinanceandEconomicsUniversityAug.,2009Vol.31No.8(,2007)[11],,,,,,(2006)[12],(2006)[13],(2007)[14],,,,,,,,,,,,,,,,,M,R,P,N,L,IY,IY,,,:MRPNLIY,M,R,P,N,L,IY,:MRPNLIY,,,,,,,,,,1998,,M2,,,,,;,,,,14M22001320082,M2,,1,M23,,2004420054,1M230120098318///////JournalofShanXiFinanceandEconomicsUniversityAug.,2009Vol.31No.8234M2,,19982007M2,,M2,,56,,,(2007),6,5M26,1M21,M20.87,,M20.87,0.94,0.92,0.97,,12001320082M2M2M210.8810.870.9410.870.950.971:M2,;40120098318///////JournalofShanXiFinanceandEconomicsUniversityAug.,2009Vol.31No.8,,,,,,,,,,,Bernanke(),,VARVAR,,VAR,,:Yt=0C+PK=1AKYt-K+t,tiid(0,),Yt=[M2,N,L,I](1)M2NLI,C,,PVAR,A,VAR,VAR,23,5,24VARVAR,,,VAR:M2NiLiIi,i=1,,24,i=1VAR,i=22423VAR()1999120088,1,,,,,X-12VAR,,,VAR,DFADF,,ADFADF,22(C,T,K)ADF(C,T,K)ADF5%M2(0,0,0)-0.381D(M2)(0,0,0)-13.231-1.944N(C,T,12)-2.987D(N)(C,T,12)-4.347-3.454L(0,0,11)-1.768D(L)(0,0,11)-2.967-1.944I(C,T,4)-3.147D(I)(C,T,4)-8.178-3.451:(C,T,K),0,5%,I(1),Johansen,VAR1,,SCHQ1,LRFPEAIC3,,3,VAR1,33M2NLIJohansen1%1%0330.24977.6860.1632.29133.24130.20245.3941.0725.39826.8120.11719.9924.6013.99620.2030.0526.0012.955.99712.97:3331%5%;50120098318///////JournalofShanXiFinanceandEconomicsUniversityAug.,2009Vol.31No.8WalterEndersAppliedEconometricTimeSeries3,5%,VAR12,,Granger,44GrangerFM2Granger1141.39260.2074Granger1143.94750.0221Granger1143.31390.0401,M2,20%,Granger,5%,Granger,Granger:,,7NM2Cholesky8LNCholesky9ILCholeskyVAR,,,,VAR17979,Cholesky25.8%,,9-0.9%,Cholesky14.6%,21.3%,35.2%,15,Cholesky12.4%,0%,31.6%,10,VAR1,18.1%,23.3%,4.4%,,18.1%23.3%4.4%=0.18%,:118.1%,123.3%,14.4%,1,0.18%60120098318///////JournalofShanXiFinanceandEconomicsUniversityAug.,2009Vol.31No.8,,,,VAR,,,,AICSCLRFPEHQVAR,,,VARP,:P=T1/4(,2008),T,,VAR3,VAR(3),23VAR5%,,23,55,7,M2,,,,,;,;,,7,,,,716,,,1.69%;,1.52%;,1.06%;,0.01%;110.02%0.96%,,,,,Cholesky,89.1%;,75.9%60.5%;,0.2%0.9%;,2.4%56.9%5NM2LNIL()(%)(%)()(%)(%)()(%)(%)(%)279.1(1)27.6179.9(1)7.2225.9(1)18.30.362514.4(1)17.91510.7(1)10.0308.1(3)44.60.802018.6(1)27.11712.7(1)29.1173.3(4)12.20.962314.7(1)7.9117.3(2)13.9266.5(3)15.10.17913.3(1)37.0136.2(3)20.7153.9(1)10.60.81306.8(5)60.5177.9(1)5.778.5(1)9.40.32308.4(2)56.9148.4(2)31.7132.7(1)1.50.271213.8(2)35.81513.0(4)17.51511.0(1)24.31.52268.7(2)0.2710.3(2)19.8176.0(4)28.90.013016.2(1)75.91380.7(1)54.3133.0(5)4.11.69257.0(5)5.42718.0(2)18.9175.9(1)3.90.042822.1(2)0.91716.2(4)42.1123.4(1)3.00.011647.4(1)89.11222.9(3)6.7338.1(1)4.80.29307.2(3)2.41617.2(1)38.2111.4(3)1.80.021122.6(4)48.4930.8(1)7.2447.4(1)30.31.061617.8(1)50.5246.3(3)1.4303.0(1)22.00.163014.9(1)-15.8129.6(2)32.8112.4(5)4.3-0.223018.2(1)-50.42237.5(1)78.43013.4(3)12.8-5.061111.3(1)24.612-20.0(3)-52.8122.7(4)3.7-0.48126.1(3)4.32312.9(1)-30.3304.6(1)-5.10.07274.5(1)-31.2117.6(2)-3.71110.8(1)13.60.161518.8(2)47.4162.1(2)-8.72116.3(1)43.2-1.78304.9(3)29.719-14.7(2)-46.31711.9(1)23.1-3.18:NM2LNIL;30;,Cholesky70120098318///////JournalofShanXiFinanceandEconomicsUniversityAug.,2009Vol.31No.8,54.3%42.1%38.2%;,1.4%;5.7%31.7%,,,Cholesky44.6%;,30.3%28.9%;1.5%24.3%,,5235689,,,,,,,,,,,,:(1);(2)31,16,7(8);(3)16,,,,,1.69%1.52%1.06%,130.01%0.96%;(4)16:(1),,,,;(2),[][1]B.S.Bernake&M.Gertler.Agencycost,networth,andbusinessfluctuations[J].AmericanEconomicReview,1989,79:14-31.[2]B.S.Bernake,M.Gertler&S.Gilchrist.Thefinancialacceleratorandtheflighttoquality.NBERworkingpaper,1994,No.4789.[3]B.S.Bernake,M.Gertler&S.Gilchrist.Thefinancialacceleratorinaquantitativebusinesscycleframework.NBERwork2ingpaper,1998,No.6455.[4]MarkGertler,SimonGilchrist,FabioM.Natalucci.Ex2ternalconstraintsonmonetarypolicyandthefinancialaccelerator.2003.[5]KosukeAoki,JamesProudman,GertjanVlieghe.Houseprices,consumption,andmonetarypolicy:afinancialacceleratorapproach[J].JournalofFinancialIntermediation,2004,414-435.[6]H.Almeida,M.CampelloandC.Liu.Thefinancialac2celerator:evidencefromiInternationalhousingmarkets[J].ReviewofFinance,200