计量经济学案例分析第七章

1、第七章案例分析【案例7.1为了研究19551974年期间美国制造业库存量Y和销售额X的关系,我们在例7.3中采用了经验加权法估计分布滞后模型.尽管经验加权法具有一些优点,但是设置权数的主观随意性较大,要求分析者对实际问题的特征有比拟透彻的了解.下面用阿尔蒙法估计如下有限分布滞后模型：Yt0XtiXt12Xt23Xt3Ut将系数i(i=0,1,2,3)用二次多项式近似,即001012202142303192那么原模型可变为2Z2tUtXt33其中YtZ0t0Z0t1Z1XtXtXt2XtXt223XtZ2tXt14Xt29Xt3在Eviews工作文件中输入X和Y的数据,在工作文件窗口中点击“Ge

2、nr工具栏,出现对话框,输入生成变量Z0t的公式,点击“OK；类似,可生成Z1t、Z2t变量的数据.进入EquationSpecification对话栏,键入回归方程形式YCZ0Z1Z2点击“OK,显示回归结果(见表7.2).表7.2匚日pmnd日门Yanabl?Method:LoaGtSquare;Datft：03/101)6Tirti支1之D2Sampl机招uct口町195B1974IrcludedoDsenaiiofia17BfleradjustngendpartcVjnaJoCudnctcrrJzmrrStjtu:icroo.CZOZ1Z2-；1401541-92ARH-350Q94O

3、0.003306E124901HS48O39959470.C01.090204=0409131J067090口00460七生D166464-25960053.0222R-squsrdMeanCBpendsnl何er-90AdjusltdR-squaredn-winS.D.叫wde再啕r275.914S.Eofrecre$ion5745aAkaiksinfocriterion6.773106SjumgquafpHreidldQ15.25dSchwaizcritprioriB9691SBLoglikdlihond7OJ57143F-：atitlk13的J63gDurbih-WatECin为就1.8

4、43X2Prato(F-etati&tlc)O.OOCOO：表中Z0、Z1、Z2对应的系数分别为0、1、2的估计值？0、？1、？2.将它们代入?分布滞后系数的阿尔蒙多项式中,可计算出.、1、2、3的估计值为：?040.661248?0?20.6612480.902049(0.432155)1.131142?02?4?20.66124820.9020494(0.432155)0.736725?03?9?20.66124830.9020499(0.432155)-0.522从而,分布滞后模型的最终估计式为：Yt6.4196010.630281Xt1.15686Xt10.76178Xt20.5549

5、5Xt3在实际应用中,Eviews提供了多项式分布滞后指令“PDL用于估计分布滞后模型.下面结合本例给出操作过程：在Eviews中输入X和丫的数据,进入EquationSpecification对话栏,键入方程形式YCPDL(X,3,2)其中,“PDL指令表示进行多项式分布滞后(PolynomialDistributedLags)模型的估计,括号中的3表示X的分布滞后长度,2表示多项式的阶数.在EstimationSettings栏中选择LeastSquares(最小二乘法),点击OK,屏幕将显示回归分析结果(见表7.3).表7.3Depend?TtVariably;Me：had:三qLare

6、sO3/19X)STi-na.12.25Ship胤的u*苣d,195gIBMIndudMDbMmwtions17喃卅adjustingencfpoints“an曲kInFfficiPrrS+iJErrorl-Slsteslicp曲C-71ig.gaaa-35H2941JUQ3jPDLDI1.1311420179991&2342?OlOOOOPDLB2a0377390庇西7口2期英O.QBf-POUJ3Q43JI660I5E464工诙疏0222R-5qLarEdQ99G797Meaindepenenlvar810GOTAcjuecA-squaradJ996058S.D匚阵电n#nt用279.91

7、74B.E.rfregression17.57430AkdikeinloErrte-ionaminsSumsqtared40】心“Sc隔海iscriterion8.969159Loglikilhoud-70.571J2,U4IMl1343G39Du.rbirWflinnqlit1期田叱nring口LagDistributiana1XCaelficenlStdErrorT-Statistir1、D136B12S016C40m更胆IA11.131U口.17期62S443J_.2a73E73Q164201.J64E2T3D5ZmnJ34R1W7231NSun耐LagszDtvnOlhcJO31,70

8、65需要指出的是,用“PDL估计分布滞后模型时,Eviews所采用的滞后系数多项式变换不是形如(7.4)式的阿尔蒙多项式,而是阿尔蒙多项式的派生形式.因此,输出结果中PDL01、PDL02、PDL03对应的估计系数不是阿尔蒙多项式系数.、八2的估计.但同前面分步计算的结果相比,最终的分布滞后估计系数式?军？公Z是相同的.【案例7.2】货币主义学派认为,产生通货膨胀的必要条件是货币的超量供给.物价变动与货币供给量的变化有着较为密切的联系,但是二者之间的关系不是瞬时的,货币供给量的变化对物价的影响存在一定时滞.有研究说明,西方国家的通货膨胀时滞大约为23个季度.在中国,大家普遍认同货币供给的变化对

9、物价具有滞后影响,但滞后期究竟有多长,还存在不同的熟悉.下面采集19962.5年全国广义货币供给量和物价指数的月度数据见表7.4对这一问题进行研究.表7.41996-2005年全国广义货币供给量及物价指数月度数据月度广义货币M2千亿元广义货币增长量M2z千亿元居民消费价格同比指数tbzs月度广义货币M2千亿元广义货币增长量M2z千亿元居民消费价格同比指数tbzsJan-9658.401Oct-00129.522-0.9518100Feb-9663.7785.377109.3Nov-00130.99411.4721101.3Mar-9664.5110.733109.8Dec-00134.6103

10、3.6162101.5Apr-9665.7231.212109.7Jan-01137.54362.9333101.2May-9666.881.157108.9Feb-01136.2102-1.3334100Jun-9668.1321.252108.6Mar-01138.74452.5343100.8Jul-9669.3461.214108.3Apr-01139.94991.2054101.6Aug-9672.3092.963108.1May-01139.0158-0.9341101.7Sep-9669.643-2.666107.4Jun-01147.80978.7939101.4Oct-967

11、3.15223.5092107Jul-01149.22871.419101.5Nov-9674.1420.9898106.9Aug-01149.94180.7131101Dec-9676.09491.9529107Sep-01151.82261.880899.9Jan-9778.6482.5531105.9Oct-01151.4973-0.3253100.2Feb-9778.9980.35105.6Nov-01154.08832.59199.7Mar-9779.8890.891104Dec-01158.30194.213699.7Apr-9780.8180.929103.2Jan-02159.

12、63931.337499May-9781.1510.333102.8Feb-02160.93561.2963100Jun-9782.7891.638102.8Mar-02164.06463.12999.2Jul-9783.460.671102.7Apr-02164.57060.50698.7Aug-9784.7461.286101.9May-02166.0611.490498.9Sep-9785.8921.146101.8Jun-02169.60123.540299.2Oct-9786.6440.752101.5Jul-02170.85111.249999.1Nov-9787.590.9461

13、01.1Aug-02173.25092.399899.3Dec-9790.99533.4053100.4Sep-02176.98243.731599.3Jan-9892.21141.2161100.3Oct-02177.29420.311899.2Feb-9892.024-0.187499.9Nov-02179.73632.442199.3Mar-9892.015-0.009100.7Dec-02185.00735.27199.6Apr-9892.6620.64799.7Jan-03190.48835.481100.4May-9893.9361.27499Feb-03190.1084-0.37

14、99100.2Jun-9894.6580.72298.7Mar-03194.48734.3789100.9Jul-9896.3141.65698.6Apr-03196.13011.6428101Aug-9897.2990.98598.6May-03199.50523.3751100.7Sep-9899.7952.49698.5Jun-03204.93145.4262100.3Oct-98100.87521.080298.9Jul-03206.19311.2617100.5Nov-98102.2291.353898.8Aug-03210.59194.3988100.9Dec-98104.4985

15、2.269599Sep-03213.56712.9752101.1Jan-99105.51.001598.8Oct-03214.46940.9023101.8Feb-99107.7782.27898.7Nov-03216.35171.8823103Mar-99108.4380.6698.2Dec-03221.22284.8711103.2Apr-99109.2180.7897.8Jan-04225.101933.87913103.2May-99110.0610.84397.8Feb-04227.050721.94879102.1Jun-99111.3631.30297.9Mar-04231.6

16、5464.60388103Jul-99111.4140.05198.6Apr-04233.627861.97326103.8Aug-99112.8271.41398.7May-04234.84241.21454104.4Sep-99115.0792.25299.2Jun-04238.427493.58509105Oct-99115.390.31199.4Jul-04234.8424-3.58509105.3Nov-99116.5591.16999.1Aug-04239.729194.88679105.3Dec-99119.8983.33999Sep-04243.7574.02781105.2J

17、an-00121.221.32299.8Oct-04243.74-0.017104.3Feb-00121.58340.3634100.7Nov-04247.135583.39558102.8Mar-00122.58070.997399.8Dec-04253.20776.07212102.4Apr-00124.12191.541299.7Jan-05257.752834.54513101.9May-00124.0533-0.0686100.1Feb-05259.35611.60327103.9Jun-00126.60532.552100.5Mar-05264.58895.2328102.7Jul

18、-00126.3239-0.2814100.5Apr-05266.992662.40376101.8Aug-00127.791.4661100.3May-05269.22942.23674101.8Sep-00130.47382.6838100数据来源：中国经济统计数据库,为了考察货币供给量的变化对物价的影响,我们用广义货币M2的月增长量M2Z作为解释变量,以居民消费价格月度同比指数TBZS为被解释变量进行研究.首先估计如下回归模型TBZSt0M2Ztut得如下回归结果表7.5.表7.5DependentVariable:TBZSMethod:LeastSquaresDate:07/03/05

19、Time:17:10Sample(adjusted):1996:022005:05Includedobservations:112afteradjustingendpointsVariableCoefficientStd.Errort-StatisticProb.C101.43560.397419255.23580.0000M2Z0.0683710.1518720.4501900.6535R-squared0.001839Meandependentvar101.5643AdjustedR-squared-0.007235S.D.dependentvar2.911111S.E.ofregress

20、ion2.921623Akaikeinfocriterion4.999852Sumsquaredresid938.9472Schwarzcriterion5.048396Loglikelihood-277.9917F-statistic0.202671Durbin-Watsonstat0.047702Prob(F-statistic)0.653460从回归结果来看,M2Z的t统计量值不显著,说明当期货币供给量的变化对当期物价水平的影响在统计意义上不明显.为了分析货币供给量变化影响物价的滞后性,我们做滞后个月的分布滞后模型的估计,在Eviews工作文档的方程设定窗口中,输入TBZSCM2ZM2Z

21、(-1)M2Z(-2)M2Z(-3)M2Z(-4)M2Z(-5)M2Z(-6)结果见表7.6.表7.6DependentVariable:TBZSMethod:LeastSquaresDate:07/03/05Time:17:09Sample(adjusted):1996:082005:05Includedobservations:106afteradjustingendpointsVariableCoefficientStd.Errort-StatisticProb.C100.04920.584318171.22400.0000M2Z-0.0110370.140613-0.0784930.9

22、376M2Z(-1)0.0161690.1379980.1171660.9070M2Z(-2)0.0530440.1368080.3877230.6991M2Z(-3)0.0286790.1431550.2003330.8416M2Z(-4)0.1308250.1391830.9399510.3496M2Z(-5)0.1377940.1425020.9669650.3359M2Z(-6)0.2487780.1433941.7349240.0859R-squared0.055557Meandependentvar101.1377AdjustedR-squared-0.011904S.D.depe

23、ndentvar2.347946S.E.ofregression2.361879Akaikeinfocriterion4.629264Sumsquaredresid546.6902Schwarzcriterion4.830278Loglikelihood-237.3510F-statistic0.823546Durbin-Watsonstat0.094549Prob(F-statistic)0.570083从回归结果来看,M2Z各滞后期的系数逐步增加,说明当期货币供给量的变化对物价水平的影响要经过一段时间才能逐步显现.但各滞后期的系数的t统计量值不显著,因此还不能据此判断滞后期究竟有多长.为此

24、,我们做滞后12个月的分布滞后模型的估计,结果见表7.7.表7.7DependentVariable:TBZSMethod:LeastSquaresDate:07/03/05Time:17:09Sample(adjusted):1997:022005:05Includedobservations:100afteradjustingendpointsVariableCoefficientStd.Errort-StatisticProb.C98.356680.467897210.21020.0000M2Z-0.1676650.121743-1.3772030.1720M2Z(-1)-0.03206

25、50.111691-0.2870840.7747M2Z(-2)-0.0009950.111464-0.0089250.9929M2Z(-3)0.0042430.1138150.0372760.9704M2Z(-4)0.1065810.1127270.9454800.3471M2Z(-5)0.0432170.1131610.3819080.7035M2Z(-6)0.1175810.1184600.9925750.3237M2Z(-7)0.1404180.1155711.2149880.2277M2Z(-8)0.2208750.1143681.9312710.0567M2Z(-9)0.140875

26、0.1153541.2212470.2253M2Z(-10)0.1804970.1158951.5574100.1230M2Z(-11)0.2469110.1255431.9667520.0524M2Z(-12)0.3923590.1300583.0167980.0034R-squared0.317136Meandependentvar100.7830AdjustedR-squared0.213913S.D.dependentvar1.890863S.E.ofregression1.676469Akaikeinfocriterion4.000434Sumsquaredresid241.7072

27、Schwarzcriterion4.365158Loglikelihood-186.0217F-statistic3.072325Durbin-Watsonstat0.265335Prob(F-statistic)0.000906表7.7显示,从M2Z至ijM2Z(-11),回归系数都不显著异于零,而M2Z(-12)的回归系数t统计量值为3.016798,在5%显著性水平下拒绝系数为零的原假设.这一结果说明,当期货币供给量变化对物价水平的影响在经过12个月(即一年)后明显地显现出来.为了考察货币供给量变化对物价水平影响的持续期,我们做滞后18个月的分布滞后模型的估计,结果见表7.8.表7.8D

28、ependentVariable:TBZSMethod:LeastSquaresDate:07/03/05Time:17:08Sample(adjusted):1997:082005:05Includedobservations:94afteradjustingendpointsVariableCoefficientStd.Errort-StatisticProb.C97.414110.370000263.28150.0000M2Z-0.0836490.094529-0.8849000.3791M2Z(-1)-0.1167440.093984-1.2421610.2181M2Z(-2)-0.1

29、199390.094428-1.2701560.2080M2Z(-3)-0.0929930.095720-0.9715090.3345M2Z(-4)-0.0329120.095823-0.3434680.7322M2Z(-5)-0.0238910.097813-0.2442560.8077M2Z(-6)0.0172900.1006450.1717940.8641M2Z(-7)0.0282880.0975700.2899290.7727M2Z(-8)0.0487080.0958770.5080210.6129M2Z(-9)0.0259950.0975690.2664220.7907M2Z(-10

30、)0.1182470.0967641.2220210.2256M2Z(-11)0.1574080.1025581.5348150.1291M2Z(-12)0.2712810.1123162.4153260.0182M2Z(-13)0.3257600.1092172.9826840.0039M2Z(-14)0.3962420.1070463.7016010.0004M2Z(-15)0.3354820.1067763.1419410.0024M2Z(-16)0.2708110.1072222.5256970.0137M2Z(-17)0.2000240.1092781.8304150.0712M2Z(-18)0.1696960.1015471.6711140.0989R-squared0.610520Meandependentvar100.6085AdjustedR-squared0.510519S.D.dependentvar1.795733S.E.ofregression1.256348Akaikeinfocriterion3.480597Sumsquaredresid116.8024Schwarzcriterion4.021724Loglikelihood-143.5881F-statistic6.105105Durbin-Watsonsta