The Durbin-Watson statistic is produced with every time-series regression estimated by least squares. To access the p-value associated with the test, which is computed using the Imhoff procedure, use the accessor $dwpval. An example based on the Phillips curve is:
1 open "@gretldirdatapoephillips_aus. gdt"
2 diff u
3 setinfo inf – d "Australian Inflation Rate" – n "Inflation Rate"
4 setinfo d_u – d "Change in Australian Civilian Unemployment Rate
5 (Seasonally adjusted)" – n "D. Unemployment Rate"
6 ols inf d_u const
7 scalar dw_p = $dwpval
8 print dw
The result, including the last line of the regression output that shows the estimated value of p and the DW statistic, is:
0.549882 Durbin-Watson 0.887289
dw_p = 2.1981736e-009
The DW statistic is 0.887 and its p-value is well below the 5% threshold, indicating significant autocorrelation. The GUI gives a slightly prettier result. It has to be called from the model window as Tests>Durbin-Watson p-value.