Use the data in TRAFFIC2.RAW for this exercise. These monthly data, on traffic accidents in California over the years 1981 to 1989, were used in Computer ExerciseC10.11.
(i) Using the standard Dickey-Fuller regression, test whether Itotacct, has a unit root. Can you reject a unit root at the 2.5% level?
(ii) Now, add two lagged changes to the test from part (i) and compute the augmented Dickey-Fuller test. What do you conclude?
(iii) Add a linear time trend to the ADF regression from part (ii). Now what happens?
(iv) Given the findings from parts (i) through (iii), what would you say is the best characterization of Itotacct. an I( 1) process or an 1(0) process about a linear time trend?
(v) Test the percentage of fatalities, prcfatt, for a unit root, using two lags in an ADF regression. In this case, does it matter whether you include a linear time trend?