求助：时间序列的EVIEWS的实现

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求助：在做非平稳的时间序列过程中，多解释变量的协整检验及误差修正模型怎样用EVIEWS实现呢？我不会操作怎么办！请指点或介绍有关详细操作的书籍！谢谢！

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关键词：EVIEWS Views Eview view 时间序列 EVIEWS 求助 时间 序列

在eviews的多变量窗口下（至少两个）点击view——》cointegretion, 然后，选择数据是否带有趋势项、平方项、常数，以及joganson模型中的变量滞后期数，ok后做出JJ检验的结果，误差修正模型需要点击proc＝》make vector autoregrssion =>vector error corection

万分感谢！我这就一试！

二楼的兄台可还在？我按你说的计算出两个表，第一个表是否说明没有协整方程，反正这两个我看不懂呀！怎么办？ Date: 04/11/08   Time: 09:10
Sample: 1985 2006
Included observations: 20
Test assumption: Linear deterministic trend in the data
Series: A LEX LIM
Lags interval: 1 to 1
					Likelihood	5 Percent	1 Percent	Hypothesized
Eigenvalue					Ratio	Critical Value	Critical Value	No. of CE(s)
0.670206					33.46726	29.68	35.65	None *
0.358742					11.28153	15.41	20.04	At most 1
0.112860					2.395057	3.76	6.65	At most 2
*(**) denotes rejection of the hypothesis at 5%(1%) significance level
L.R. test indicates 1 cointegrating equation(s) at 5% significance level
Unnormalized Cointegrating Coefficients:
A					LEX	LIM
2.315103					-0.363764	-0.148466
0.234168					0.624851	-0.703826
0.598596					0.064298	-0.374174
Normalized Cointegrating Coefficients: 1 Cointegrating Equation(s)
A					LEX	LIM	C
1.000000					-0.157126	-0.064129	-11.50421
					(0.04609)	(0.05192)
Log likelihood					16.24725
Normalized Cointegrating Coefficients: 2 Cointegrating Equation(s)
A					LEX	LIM	C
1.000000					0.000000	-0.227706	-11.46000
						(0.01634)
0.000000					1.000000	-1.041055	0.281378
						(0.07734)
Log likelihood					20.69049

Date: 04/11/08   Time: 09:19
Sample(adjusted): 1987 2006
Included observations: 20 after adjusting endpoints
Standard errors & t-statistics in parentheses
				A	LEX	LIM
A(-1)				1.005394	4.759920	2.750155
				(0.23692)	(2.45395)	(2.86976)
				(4.24352)	(1.93970)	(0.95832)
A(-2)				-0.244743	-1.571345	0.512643
				(0.22219)	(2.30133)	(2.69127)
				(-1.10151)	(-0.68280)	(0.19048)
LEX(-1)				0.042331	0.452862	0.020553
				(0.03058)	(0.31673)	(0.37040)
				(1.38428)	(1.42980)	(0.05549)
LEX(-2)				-0.024543	-0.406753	-0.156812
				(0.02648)	(0.27426)	(0.32074)
				(-0.92686)	(-1.48307)	(-0.48891)
LIM(-1)				-0.000938	0.077395	0.383941
				(0.02876)	(0.29788)	(0.34835)
				(-0.03263)	(0.25982)	(1.10216)
LIM(-2)				0.028582	0.127901	-0.091913
				(0.03061)	(0.31706)	(0.37078)
				(0.93371)	(0.40340)	(-0.24789)
C				2.889795	-36.05601	-36.02240
				(1.26210)	(13.0722)	(15.2872)
				(2.28967)	(-2.75822)	(-2.35638)
R-squared				0.989716	0.948890	0.921116
Adj. R-squared				0.984970	0.925301	0.884707
Sum sq. resids				0.027956	2.999037	4.101468
S.E. equation				0.046373	0.480307	0.561692
F-statistic				208.5176	40.22557	25.29966
Log likelihood				37.34991	-9.404360	-12.53490
Akaike AIC				-3.034991	1.640436	1.953490
Schwarz SC				-2.686484	1.988942	2.301996
Mean dependent				14.01144	11.31654	11.17714
S.D. dependent				0.378249	1.757362	1.654235
Determinant Residual Covariance					2.25E-05
Log Likelihood					21.88802
Akaike Information Criteria					-0.088802
Schwarz Criteria					0.956717