我自己做的VEC得出的结果：<br/> Vector Error Correction Estimates <br/> Date: 04/14/09 Time: 04:08 <br/> Sample (adjusted): 1983 2008 <br/> Included observations: 26 after adjustments <br/> Standard errors in ( ) &amp; t-statistics in [ ] <br/> <br/>Cointegrating Eq: CointEq1 <br/> <br/>LNEX(-1) 1.000000 <br/> <br/>LNGDPUS(-1) -2.200673 <br/> (1.23799) <br/> [-1.77762] <br/> <br/>LNRER(-1) 9.124482 <br/> (2.88902) <br/> [ 3.15833] <br/> <br/>C 7.613669 <br/> <br/>Error Correction: D(LNEX) D(LNGDPUS) D(LNRER)<br/> <br/>CointEq1 0.046128 -0.004730 -0.043198<br/> (0.02214) (0.00238) (0.01953)<br/> [ 2.08379] [-1.98982] [-2.21133]<br/> <br/>D(LNEX(-1)) -0.194024 -0.015547 0.074694<br/> (0.18246) (0.01959) (0.16101)<br/> [-1.06339] [-0.79345] [ 0.46389]<br/> <br/>D(LNEX(-2)) -0.367242 -0.009885 0.128460<br/> (0.15828) (0.01700) (0.13968)<br/> [-2.32020] [-0.58156] [ 0.91968]<br/> <br/>D(LNGDPUS(-1)) 3.931582 0.260889 -0.473816<br/> (1.81680) (0.19511) (1.60328)<br/> [ 2.16401] [ 1.33715] [-0.29553]<br/> <br/>D(LNGDPUS(-2)) -4.213310 -0.237105 -0.285885<br/> (1.63023) (0.17507) (1.43864)<br/> [-2.58449] [-1.35434] [-0.19872]<br/> <br/>D(LNRER(-1)) 0.214156 -0.033186 0.115644<br/> (0.27073) (0.02907) (0.23891)<br/> [ 0.79104] [-1.14144] [ 0.48405]<br/> <br/>D(LNRER(-2)) 0.041634 0.046911 -0.237709<br/> (0.24232) (0.02602) (0.21384)<br/> [ 0.17181] [ 1.80266] [-1.11161]<br/> <br/>C 0.206257 0.058216 0.054925<br/> (0.14568) (0.01564) (0.12856)<br/> [ 1.41584] [ 3.72117] [ 0.42724]<br/> <br/> R-squared 0.702891 0.668130 0.423501<br/> Adj. R-squared 0.587349 0.539070 0.199308<br/> Sum sq. resids 0.196439 0.002265 0.152979<br/> S.E. equation 0.104467 0.011219 0.092189<br/> F-statistic 6.083411 5.176881 1.888997<br/> Log likelihood 26.61911 84.63250 29.86979<br/> Akaike AIC -1.432239 -5.894808 -1.682292<br/> Schwarz SC -1.045132 -5.507701 -1.295185<br/> Mean dependent 0.128116 0.057133 0.025916<br/> S.D. dependent 0.162624 0.016524 0.103026<br/> <br/> Determinant resid covariance (dof adj.) 1.05E-08 <br/> Determinant resid covariance 3.48E-09 <br/> Log likelihood 142.4962 <br/> Akaike information criterion -8.884322 <br/> Schwarz criterion -7.577837 <br/> <br/>我通过EVIEWS得出他的公式是：D(LNEX) = 0.0461276779119*( LNEX(-1) - 2.20067330942*LNGDPUS(-1) + 9.12448159075*LNRER(-1) + 7.61366881265 ) - 0.194023900788*D(LNEX(-1)) - 0.367241614385*D(LNEX(-2)) + 3.93158195018*D(LNGDPUS(-1)) - 4.21330986898*D(LNGDPUS(-2)) + 0.214155956101*D(LNRER(-1)) + 0.0416343905002*D(LNRER(-2)) + 0.206257225034<br/><br/>D(LNGDPUS) = - 0.00473028901525*( LNEX(-1) - 2.20067330942*LNGDPUS(-1) + 9.12448159075*LNRER(-1) + 7.61366881265 ) - 0.0155470858135*D(LNEX(-1)) - 0.00988526473703*D(LNEX(-2)) + 0.260888549756*D(LNGDPUS(-1)) - 0.237105439231*D(LNGDPUS(-2)) - 0.0331856192752*D(LNRER(-1)) + 0.0469105440561*D(LNRER(-2)) + 0.0582156837724<br/><br/>D(LNRER) = - 0.0431979188658*( LNEX(-1) - 2.20067330942*LNGDPUS(-1) + 9.12448159075*LNRER(-1) + 7.61366881265 ) + 0.0746935802748*D(LNEX(-1)) + 0.128459956365*D(LNEX(-2)) - 0.473815868896*D(LNGDPUS(-1)) - 0.285884707825*D(LNGDPUS(-2)) + 0.115644013884*D(LNRER(-1)) - 0.237708912649*D(LNRER(-2)) + 0.0549245116526<br/><br/><br/>但是我看别人写的文章，他们的主要公式好像并没有这么长，他的公式是<meta content="text/html; charset=utf-8" http-equiv="Content-Type"></meta><meta content="Word.Document" name="ProgId"></meta><meta content="Microsoft Word 12" name="Generator"></meta><meta content="Microsoft Word 12" name="Originator"></meta><link href="file:///C:%5CDOCUME%7E1%5CQQW%5CLOCALS%7E1%5CTemp%5Cmsohtmlclip1%5C01%5Cclip_filelist.xml" rel="File-List"></link><link href="file:///C:%5CDOCUME%7E1%5CQQW%5CLOCALS%7E1%5CTemp%5Cmsohtmlclip1%5C01%5Cclip_themedata.thmx" rel="themeData"></link><link href="file:///C:%5CDOCUME%7E1%5CQQW%5CLOCALS%7E1%5CTemp%5Cmsohtmlclip1%5C01%5Cclip_colorschememapping.xml" rel="colorSchemeMapping"></link><!--Element not supported - Type: 8 Name: #comment--><!--Element not supported - Type: 8 Name: #comment--><style>
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<p align="left" class="MsoNormal" style="text-align: left;"><span style="font-family: 宋体;">△</span><span lang="EN-US">lnEX</span><sub><span lang="EN-US" style=";">t</span></sub><span lang="EN-US">=0.02+0.28</span><span style="font-family: 宋体;">△</span><span lang="EN-US">lnEX</span><sub><span lang="EN-US" style=";">t-1</span></sub><span lang="EN-US">+1.94</span><span style="font-family: 宋体;">△</span><span lang="EN-US">lnGDPu</span><sub><span lang="EN-US" style=";">t-1</span></sub><span lang="EN-US">+0.03</span><span style="font-family: 宋体;">△</span><span lang="EN-US">lnRER</span><sub><span lang="EN-US" style=";">t-1</span></sub><span lang="EN-US">-0.04ecm</span><sub><span lang="EN-US" style=";">t-1</span></sub></p><p align="left" class="MsoNormal" style="text-align: left;">(t、t-1都是下标)，我想询问一下，这个公式是不是他自己简便后得出来的？那怎么简便？</p><p align="left" class="MsoNormal" style="text-align: left;">望大家伸出援手，谢谢！<br/><sub><span lang="EN-US" style=";"></span></sub><span lang="EN-US"><op></op></span></p>
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