Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 121.22 121.5834 122.5807 124.1219 124.0533 126.6053 126.3239 127.79 130.4738 1.322 0.3634 0.9973 1.5412 -0.0686 2.552 -0.2814 1.4661 2.6838 99.8 100.7 99.8 99.7 100.1 100.5 100.5 100.3 100 Oct-04 Nov-04 Dec-04 Jan-05 Feb-05 Mar-05 Apr-05 May-05 243.74 247.13558 253.2077 257.75283 259.3561 264.5889 266.99266 269.2294 -0.017 3.39558 6.07212 4.54513 1.60327 5.2328 2.40376 2.23674 104.3 102.8 102.4 101.9 103.9 102.7 101.8 101.8 数据来源：中国经济统计数据库，http://db.cei.gov.cn/。 为了考察货币供应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
TBZSt????0M2Zt?ut
得如下回归结果（表7.5）。
表7.5
Dependent Variable: TBZS Method: Least Squares Date: 07/03/05 Time: 17:10 Sample(adjusted): 1996:02 2005:05 Included observations: 112 after adjusting endpoints Variable C M2Z R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat Coefficient 101.4356 0.068371 Std. Error 0.397419 0.151872 t-Statistic 255.2358 0.450190 Prob. 0.0000 0.6535 0.001839 Mean dependent var 101.5643 -0.007235 S.D. dependent var 2.921623 Akaike info criterion 938.9472 Schwarz criterion -277.9917 F-statistic 0.047702 Prob(F-statistic) 2.911111 4.999852 5.048396 0.202671 0.653460 从回归结果来看，M2Z的t统计量值不显著，表明当期货币供应量的变化对当期物价水平的影响在统计意义上不明显。为了分析货币供应量变化影响物价的滞后性，我们做滞后6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
TBZS C M2Z M2Z(-1) M2Z(-2) M2Z(-3) M2Z(-4) M2Z(-5) M2Z(-6)
结果见表7.6。
表7.6
Dependent Variable: TBZS Method: Least Squares Date: 07/03/05 Time: 17:09 Sample(adjusted): 1996:08 2005:05 Included observations: 106 after adjusting endpoints Variable C M2Z M2Z(-1) M2Z(-2) M2Z(-3) M2Z(-4) M2Z(-5) M2Z(-6) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat Coefficient 100.0492 -0.011037 0.016169 0.053044 0.028679 0.130825 0.137794 0.248778 Std. Error 0.584318 0.140613 0.137998 0.136808 0.143155 0.139183 0.142502 0.143394 t-Statistic 171.2240 -0.078493 0.117166 0.387723 0.200333 0.939951 0.966965 1.734924 Prob. 0.0000 0.9376 0.9070 0.6991 0.8416 0.3496 0.3359 0.0859 0.055557 Mean dependent var 101.1377 -0.011904 S.D. dependent var 2.361879 Akaike info criterion 546.6902 Schwarz criterion -237.3510 F-statistic 0.094549 Prob(F-statistic) 2.347946 4.629264 4.830278 0.823546 0.570083 从回归结果来看，M2Z各滞后期的系数逐步增加，表明当期货币供应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，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7.7
Dependent Variable: TBZS Method: Least Squares Date: 07/03/05 Time: 17:09 Sample(adjusted): 1997:02 2005:05 Included observations: 100 after adjusting endpoints Variable C M2Z M2Z(-1) M2Z(-2) M2Z(-3) M2Z(-4) M2Z(-5) M2Z(-6) M2Z(-7) M2Z(-8) M2Z(-9) M2Z(-10) M2Z(-11) M2Z(-12) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat Coefficient 98.35668 -0.167665 -0.032065 -0.000995 0.004243 0.106581 0.043217 0.117581 0.140418 0.220875 0.140875 0.180497 0.246911 0.392359 Std. Error 0.467897 0.121743 0.111691 0.111464 0.113815 0.112727 0.113161 0.118460 0.115571 0.114368 0.115354 0.115895 0.125543 0.130058 t-Statistic 210.2102 -1.377203 -0.287084 -0.008925 0.037276 0.945480 0.381908 0.992575 1.214988 1.931271 1.221247 1.557410 1.966752 3.016798 Prob. 0.0000 0.1720 0.7747 0.9929 0.9704 0.3471 0.7035 0.3237 0.2277 0.0567 0.2253 0.1230 0.0524 0.0034 0.317136 Mean dependent var 100.7830 0.213913 S.D. dependent var 1.676469 Akaike info criterion 241.7072 Schwarz criterion -186.0217 F-statistic 0.265335 Prob(F-statistic) 1.890863 4.000434 4.365158 3.072325 0.000906 表7.7显示，从M2Z到M2Z(-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。这一结果表明，当期货币供应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。为了考察货币供应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7.8
Dependent Variable: TBZS Method: Least Squares Date: 07/03/05 Time: 17:08 Sample(adjusted): 1997:08 2005:05 Included observations: 94 after adjusting endpoints Variable C M2Z M2Z(-1) M2Z(-2) M2Z(-3) M2Z(-4) M2Z(-5) M2Z(-6) M2Z(-7) M2Z(-8) M2Z(-9) M2Z(-10) M2Z(-11) M2Z(-12) M2Z(-13) M2Z(-14) M2Z(-15) M2Z(-16) M2Z(-17) M2Z(-18) R-squared Coefficient 97.41411 -0.083649 -0.116744 -0.119939 -0.092993 -0.032912 -0.023891 0.017290 0.028288 0.048708 0.025995 0.118247 0.157408 0.271281 0.325760 0.396242 0.335482 0.270811 0.200024 0.169696 Std. Error 0.370000 0.094529 0.093984 0.094428 0.095720 0.095823 0.097813 0.100645 0.097570 0.095877 0.097569 0.096764 0.102558 0.112316 0.109217 0.107046 0.106776 0.107222 0.109278 0.101547 t-Statistic 263.2815 -0.884900 -1.242161 -1.270156 -0.971509 -0.343468 -0.244256 0.171794 0.289929 0.508021 0.266422 1.222011 1.534815 2.415326 2.982684 3.701601 3.141941 2.525697 1.830415 1.671114 Prob. 0.0000 0.3791 0.2181 0.2080 0.3345 0.7322 0.8077 0.8641 0.7727 0.6129 0.7907 0.2256 0.1291 0.0182 0.0039 0.0004 0.0024 0.0137 0.0712 0.0989 0.610520 Mean dependent var 100.6085