The study looked at how the augmented Dickey-Fuller test works when checking for a unit root in data. They found that the test's accuracy is not affected by the specific type of data being analyzed, as long as the errors in the data have a continuous positive spectral density. The researchers also discovered that the test's ability to detect stationary data decreases as the number of variables used in the test increases. This is because more variables lead to them becoming more closely related as the number of variables approaches infinity.