In this example, the Grunfeld series are estimated using different estimation methods. Refer to Maddala (1977) for details of the Grunfeld investment data set. For comparison, the Yule-Walker method, ULS method, and maximum likelihood method estimates are shown. With the DWPROB option, the p-value of the Durbin-Watson statistic is printed. The Durbin-Watson test indicates the positive autocorrelation of the regression residuals. The DATA and PROC steps follow:
title 'Grunfeld''s Investment Models Fit with Autoregressive Errors'; data grunfeld; input year gei gef gec; label gei = 'Gross investment GE' gec = 'Lagged Capital Stock GE' gef = 'Lagged Value of GE shares'; datalines; 1935 33.1 1170.6 97.8 ... more lines ...
proc autoreg data=grunfeld; model gei = gef gec / nlag=1 dwprob; model gei = gef gec / nlag=1 method=uls; model gei = gef gec / nlag=1 method=ml; run;
The printed output produced by each of the MODEL statements is shown in Output 8.2.1 through Output 8.2.4.
Output 8.2.1: OLS Analysis of Residuals
Grunfeld's Investment Models Fit with Autoregressive Errors |
Dependent Variable | gei |
---|---|
Gross investment GE |
Ordinary Least Squares Estimates | |||
---|---|---|---|
SSE | 13216.5878 | DFE | 17 |
MSE | 777.44634 | Root MSE | 27.88272 |
SBC | 195.614652 | AIC | 192.627455 |
MAE | 19.9433255 | AICC | 194.127455 |
MAPE | 23.2047973 | HQC | 193.210587 |
Durbin-Watson | 1.0721 | Regress R-Square | 0.7053 |
Total R-Square | 0.7053 |
Parameter Estimates | ||||||
---|---|---|---|---|---|---|
Variable | DF | Estimate | Standard Error |
t Value | Approx Pr > |t| |
Variable Label |
Intercept | 1 | -9.9563 | 31.3742 | -0.32 | 0.7548 | |
gef | 1 | 0.0266 | 0.0156 | 1.71 | 0.1063 | Lagged Value of GE shares |
gec | 1 | 0.1517 | 0.0257 | 5.90 | <.0001 | Lagged Capital Stock GE |
Estimates of Autocorrelations | |||
---|---|---|---|
Lag | Covariance | Correlation | -1 9 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 1 |
0 | 660.8 | 1.000000 | | |********************| |
1 | 304.6 | 0.460867 | | |********* | |
Preliminary MSE | 520.5 |
---|
Output 8.2.2: Regression Results Using Default Yule-Walker Method
Estimates of Autoregressive Parameters | |||
---|---|---|---|
Lag | Coefficient | Standard Error |
t Value |
1 | -0.460867 | 0.221867 | -2.08 |
Yule-Walker Estimates | |||
---|---|---|---|
SSE | 10238.2951 | DFE | 16 |
MSE | 639.89344 | Root MSE | 25.29612 |
SBC | 193.742396 | AIC | 189.759467 |
MAE | 18.0715195 | AICC | 192.426133 |
MAPE | 21.0772644 | HQC | 190.536976 |
Durbin-Watson | 1.3321 | Regress R-Square | 0.5717 |
Total R-Square | 0.7717 |
Parameter Estimates | ||||||
---|---|---|---|---|---|---|
Variable | DF | Estimate | Standard Error |
t Value | Approx Pr > |t| |
Variable Label |
Intercept | 1 | -18.2318 | 33.2511 | -0.55 | 0.5911 | |
gef | 1 | 0.0332 | 0.0158 | 2.10 | 0.0523 | Lagged Value of GE shares |
gec | 1 | 0.1392 | 0.0383 | 3.63 | 0.0022 | Lagged Capital Stock GE |
Output 8.2.3: Regression Results Using Unconditional Least Squares Method
Estimates of Autoregressive Parameters | |||
---|---|---|---|
Lag | Coefficient | Standard Error |
t Value |
1 | -0.460867 | 0.221867 | -2.08 |
Algorithm converged. |
Unconditional Least Squares Estimates | |||
---|---|---|---|
SSE | 10220.8455 | DFE | 16 |
MSE | 638.80284 | Root MSE | 25.27455 |
SBC | 193.756692 | AIC | 189.773763 |
MAE | 18.1317764 | AICC | 192.44043 |
MAPE | 21.149176 | HQC | 190.551273 |
Durbin-Watson | 1.3523 | Regress R-Square | 0.5511 |
Total R-Square | 0.7721 |
Parameter Estimates | ||||||
---|---|---|---|---|---|---|
Variable | DF | Estimate | Standard Error |
t Value | Approx Pr > |t| |
Variable Label |
Intercept | 1 | -18.6582 | 34.8101 | -0.54 | 0.5993 | |
gef | 1 | 0.0339 | 0.0179 | 1.89 | 0.0769 | Lagged Value of GE shares |
gec | 1 | 0.1369 | 0.0449 | 3.05 | 0.0076 | Lagged Capital Stock GE |
AR1 | 1 | -0.4996 | 0.2592 | -1.93 | 0.0718 |
Autoregressive parameters assumed given | ||||||
---|---|---|---|---|---|---|
Variable | DF | Estimate | Standard Error |
t Value | Approx Pr > |t| |
Variable Label |
Intercept | 1 | -18.6582 | 33.7567 | -0.55 | 0.5881 | |
gef | 1 | 0.0339 | 0.0159 | 2.13 | 0.0486 | Lagged Value of GE shares |
gec | 1 | 0.1369 | 0.0404 | 3.39 | 0.0037 | Lagged Capital Stock GE |
Output 8.2.4: Regression Results Using Maximum Likelihood Method
Estimates of Autoregressive Parameters | |||
---|---|---|---|
Lag | Coefficient | Standard Error |
t Value |
1 | -0.460867 | 0.221867 | -2.08 |
Algorithm converged. |
Maximum Likelihood Estimates | |||
---|---|---|---|
SSE | 10229.2303 | DFE | 16 |
MSE | 639.32689 | Root MSE | 25.28491 |
SBC | 193.738877 | AIC | 189.755947 |
MAE | 18.0892426 | AICC | 192.422614 |
MAPE | 21.0978407 | HQC | 190.533457 |
Log Likelihood | -90.877974 | Regress R-Square | 0.5656 |
Durbin-Watson | 1.3385 | Total R-Square | 0.7719 |
Observations | 20 |
Parameter Estimates | ||||||
---|---|---|---|---|---|---|
Variable | DF | Estimate | Standard Error |
t Value | Approx Pr > |t| |
Variable Label |
Intercept | 1 | -18.3751 | 34.5941 | -0.53 | 0.6026 | |
gef | 1 | 0.0334 | 0.0179 | 1.87 | 0.0799 | Lagged Value of GE shares |
gec | 1 | 0.1385 | 0.0428 | 3.23 | 0.0052 | Lagged Capital Stock GE |
AR1 | 1 | -0.4728 | 0.2582 | -1.83 | 0.0858 |
Autoregressive parameters assumed given | ||||||
---|---|---|---|---|---|---|
Variable | DF | Estimate | Standard Error |
t Value | Approx Pr > |t| |
Variable Label |
Intercept | 1 | -18.3751 | 33.3931 | -0.55 | 0.5897 | |
gef | 1 | 0.0334 | 0.0158 | 2.11 | 0.0512 | Lagged Value of GE shares |
gec | 1 | 0.1385 | 0.0389 | 3.56 | 0.0026 | Lagged Capital Stock GE |