ls et1 c x2 et1(-1) 回归方程et1=0.824785et1(-1)
Y－0.824785Yt-1=(1－0.824785)p1＋（Xt－0.824785Xt-1）p2+vt
ls lny-0.824785*lny(-1) c lnx2-0.824785*lnx2(-1)
Dependent Variable: Y-0.824785*Y(-1) Method: Least Squares Date: 11/01/10 Time: 13:03 Sample (adjusted): 1986 2007
Included observations: 22 after adjustments
Variable C
X2-0.824785*X2(-1) R-squared
Coefficient
14784.99 0.722670
Std. Error
1699.579 0.055449
t-Statistic
8.699208 13.03305
Prob.
0.0000 0.0000
31999.94 15083.71 19.96536 20.06455 169.8604 0.000000
0.894659 Mean dependent var 0.889392 S.D. dependent var 5016.499 Akaike info criterion 5.03E+08 Schwarz criterion -217.6190 F-statistic 0.782158 Prob(F-statistic)
Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat
N=22 , k=1 , dL=1.239 dU=1.429 DW=0.782158 正相关
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