1、Mussa)、考霍(PKouri)、比尔森(JBilson)等人。它是在1975年瑞典斯德哥尔摩附近召开的关于“浮动汇率与稳定政策”的国际研讨会上被提出来的。弹性货币法的一个基本思想:汇率是两国货币的相对价格,而不是两国商品的相对价格,因此汇率水平应主要由货币市场的供求状况决定。2弹性货币法的论述重要假设:(1) 稳定的货币需求方程,即货币需求同某些经济变量存在着稳定的关系;(2) 购买力平价持续有效。S=(y*-y)+(i-i*)+(Ms-Ms*) 从模型中我们可以看出,本国与外国之间实际国民收入水平、利率水平以及货币供给水平通过对各自物价水平的影响而决定了汇率水平。本国利率上升会降低货币需
2、求,在原有的价格水平与货币供给水平上,这会造成支出的增加、物价的上升,从而通过购买力平价关系造成本国货币的贬值相关数据收集在中经网中我们找到了1985年到2002年美国,中国各自的官方汇率,实际国民收入,实际利率,货币供给M1,M2。现在的问题是M1,M2都是衡量货币供给的指标,应当选哪个?我们选择了M2.因为在Frederic S. Mishkin(米什金)的The Economics of Money, Banking, and Financial Market书我们找到了m1,m2的定义,而且书中明确指出,M2由于其速率远比M1稳定,因而在衡量货币供给方面比M1更好。在P57给出了M1,
3、M2的定义:M1=Currency +Travelers checks +Demand deposits + Other checkable depositsM2= M1 + Small denomination time deposits + savings deposits and money market deposit accounts + Money market mutual fund shares作者在p560写道:”The relative stability of M2 velocity suggests that money demand functions in whic
4、h the money supply is defined as M2 might performed substantially better than those in which the money supply is defined as M1.”原始数据如下:年 度 中国汇率S 美国国民收入Y* 中国国民收入Y 中国实际利率I 美国实际利率I* 美国M2* 中国M21985 2.94 55985.65 12133 -2.02 6.52 28010.48 4874.91986 3.45 57264.02 13413.65 3.17 5.97 30980.83 6348.61987 3.
5、72 59578.44 15097.47 2.72 5.01 31939.3 7957.41988 3.72 62681.01 16958.06 -2.79 5.7 33946.54 9602.11989 3.77 64121.72 17739.94 2.33 6.79 35906.38 11393.11990 4.78 64915.73 18598.37 3.49 5.87 37674.36 14681.91991 5.32 65061.65 20405.99 1.79 4.65 38900.36 18598.91992 5.51 66602.99 23502.67 0.68 3.72 39
6、547.64 24327.31993 5.76 68257.01 26798.67 -3.12 3.52 40137.58 35680.81994 8.62 71056.98 30525.25 -7.44 4.96 40153.51 46920.31995 8.35 73322 33496.5 -0.99 6.51 42418.03 60743.51996 8.31 75932.52 36830.48 3.93 6.2 45010.02 76095.31997 8.29 79473.88 40400.25 7.76 6.36 47968.64 91867.811998 8.28 83736.6
7、5 43205.3 9 7.02 52809.77 105560.111999 8.28 87407.58 46178.05 8.22 6.45 57122.22 121042.062000 8.28 91182.21 49249.8 4.86 6.98 61088.86 135960.232001 8.28 91502.37 52826.99 4.61 4.44 69677.66 156411.932002 8.28 93332.11 57512.11 5.62 3.47 72688.63 186790.54由于模型中s , y, I Ms是指汇率,实际国民收入,货币供给量的自然对数值,于是
8、作如下数据处理:( s=lnS, y=lnY, i=I, m=lnM)年 度 s y*-y i-i* m-m*1985 1.078409581 2.607576 -0.0854 -2.826891986 1.238374231 2.689774 -0.028 -2.823511987 1.313723668 2.68649 -0.0229 -2.703461988 1.313723668 2.621039 -0.0849 -2.576531989 1.327075001 2.61204 -0.0446 -2.474981990 1.564440547 2.814457 -0.0238 -2.5
9、0681991 1.671473303 2.83098 -0.0286 -2.409371992 1.706564623 2.7482 -0.0304 -2.192471993 1.750937475 2.685865 -0.0664 -1.868641994 2.154085085 2.999013 -0.124 -1.998341995 2.122261539 2.905681 -0.075 -1.763171996 2.117459609 2.840979 -0.0227 -1.592361997 2.115049969 2.791642 0.014 -1.465251998 2.113
10、842968 2.775557 0.0198 -1.421261999 2.113842968 2.75192 0.0177 -1.36292000 2.113842968 2.729797 -0.0212 -1.313812001 2.113842968 2.663186 0.0017 -1.305232002 2.113842968 2.598012 0.0215 -1.17004平稳性检验:单位根检验:y一阶差分,滞后0 期 ADF Test Statistic -4.485774 1% Critical Value* -4.67125% Critical Value -3.734710
11、% Critical Value -3.3086*MacKinnon critical values for rejection of hypothesis of a unit root.Augmented Dickey-Fuller Test EquationDependent Variable: D(Y,2)Method: Least SquaresDate: 06/14/05 Time: 09:35Sample(adjusted): 1987 2002Included observations: 16 after adjusting endpointsVariable Coefficie
12、nt Std. Error t-Statistic Prob. D(Y(-1) -1.211682 0.270117 -4.485774 0.0006C 0.056801 0.065830 0.862841 0.4039TREND(1985) -0.006505 0.006251 -1.040761 0.3170R-squared 0.607580 Mean dependent var -0.009211Adjusted R-squared 0.547208 S.D. dependent var 0.165921S.E. of regression 0.111648 Akaike info c
13、riterion -1.379568Sum squared resid 0.162049 Schwarz criterion -1.234707Log likelihood 14.03654 F-statistic 10.06389M的单位根检验:滞后期为0,2阶差分ADF Test Statistic -6.098875 1% Critical Value* -4.73155% Critical Value -3.761110% Critical Value -3.3228 D(M,3)36 1988 2002 15 after adjusting endpointsVariable Coe
14、fficient Std. Error t-Statistic Prob.I的单位根检验滞后期为1,2阶差分ADF Test Statistic -4.409217 1% Critical Value* -4.80255% Critical Value -3.792110% Critical Value -3.3393 D(I,3)29 1989 2002 14 after adjusting endpointsE一阶差分滞后1期ADF Test Statistic -3.415388 1% Critical Value* -4.7315 D(E,2)13D(E(-1) -1.480432 0
15、.433459 -3.415388 0.0058D(E(-1),2) 0.297192 0.285576 1.040677 0.3204C 0.204362 0.098391 2.077042 0.0620TREND(1985) -0.011981 0.007830 -1.530147 0.1542R-squared 0.610438 Mean dependent var -0.005023Adjusted R-squared 0.504194 S.D. dependent var 0.168304S.E. of regression 0.118509 Akaike info criterio
16、n -1.204485Sum squared resid 0.154487 Schwarz criterion -1.015671Log likelihood 13.03364 F-statistic 5.745612Durbin-Watson stat 2.071058 Prob(F-statistic) 0.012930因果关系检验:E 与m2 互为因果Pairwise Granger Causality Tests23Sample: 1985 2002Lags: 2Null Hypothesis: Obs F-Statistic ProbabilityM does not Granger
17、 Cause E 16 14.0385 0.00094E does not Granger Cause M 6.99392 0.01097E与 y:互不为因果28 1Y does not Granger Cause E 17 0.93813 0.34920E does not Granger Cause Y 0.09072 0.76769E与 I 互不为因果 06/15/05 Time: 11:50 3I does not Granger Cause E 15 0.44195 0.72943E does not Granger Cause I 0.83104 0.51325参数的估计最小二乘回
18、归得 E 05/18/04 Time: 21:02 18C -0.617765 0.246003 -2.511204 0.0249Y 1.290026 0.085334 15.11731 0.0000I -0.142262 0.263086 -0.540744 0.5972M 0.575430 0.018366 31.33085 0.0000R-squared 0.993250 Mean dependent var 1.780155Adjusted R-squared 0.991804 S.D. dependent var 0.385816S.E. of regression 0.034928
19、 Akaike info criterion -3.677909Sum squared resid 0.017080 Schwarz criterion -3.480048Log likelihood 37.10118 F-statistic 686.7379Durbin-Watson stat 1.371224 Prob(F-statistic) 0.000000线性关系显著(由F统计量得知), R2=0.993250说明拟合优度很好,但是由I的T检验中t=-0.540744,其绝对值小于2,可以看出,I 作为解释变量不是很合理经济意义检验:回归所得的I的系数符号与经济意义不符 ,其他变量经
20、济意义符合计量经济学检验重共线性检验相关系数矩阵:的确存在多重线性,并且I的t统计量不显著I Y MI 1.000000 -0.238763 0.526896Y -0.238763 1.000000 0.176456M 0.526896 0.176456 1.000000逐步回归得: 13:08Variable Coefficient Std. Error t-Statistic Prob.C -3.269684 2.051116 -1.594100 0.1305Y 1.841804 0.747527 2.463862 0.0255R-squared 0.275054 Mean depende
21、nt var 1.780155Adjusted R-squared 0.229745 S.D. dependent var 0.385816S.E. of regression 0.338608 Akaike info criterion 0.776491Sum squared resid 1.834484 Schwarz criterion 0.875421Log likelihood -4.988419 F-statistic 6.070615Durbin-Watson stat 0.115207 Prob(F-statistic) 0.025456C 1.887803 0.112636
22、16.76017 0.0000I 3.322453 2.184643 1.520822 0.1478R-squared 0.126299 Mean dependent var 1.780155Adjusted R-squared 0.071693 S.D. dependent var 0.385816S.E. of regression 0.371728 Akaike info criterion 0.963132Sum squared resid 2.210912 Schwarz criterion 1.062063Log likelihood -6.668192 F-statistic 2
23、.312898Durbin-Watson stat 0.271065 Prob(F-statistic) 0.147820C 2.998507 0.128513 23.33228 0.0000M 0.613007 0.062182 9.858300 0.0000R-squared 0.858640 Mean dependent var 1.780155Adjusted R-squared 0.849805 S.D. dependent var 0.385816S.E. of regression 0.149523 Akaike info criterion -0.858295Sum squared resid 0.357714 Schwarz criterion -0.759365Log likelihood 9.724656 F-statistic 97.18608Durbin-Watson stat 1.194219 Prob(F-statistic) 0.000000选M为第一个解释变量 05/1
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