Hi everyone.


I was trying to check my data to see if I have stationary or non stationary data. I am using annual data with no gaps and my dataset comprises 6 variables.

I started by running the regression using the command:

Code:
reg lco2 lgdp lpopd lpopg lfdi lper
then performed the Durbin-Watson d-statistic using the command

Code:
estat dwatson
My Rsquare ( 0.6740) is less than Durbin-Watson d-statistic (0.9382188) indicating that the series is stationary.

However I wanted to confirm this using ADF test. When I ran the ADF test, it showed that 2 of my variables where non stationary at all critical levels while 3 were not. I then created new variables at the first difference based on already transformed data (i.e. transformed to the logarithmic form) and performed the ADF again.

However, I noticed that some of my data points for the first differenced var had some negative values. see a short extract of the lco2 var which only shows one value as positive (12 points total with positive values and the rest negative for dco2 if you look at the entire timeline)
lco2 dco2
.2551924
.2537923 -.0087013
.2412684 -.0017993
.2140184 -.0014001
.1825199 -.0125239
.2224333 -.0272499
.2106815 -.0314985
.1640534 .0399134
.1612443 -.0117518
.1641062 -.0466281
.1662048 -.002809

The results of the ADF on the differenced var were also mixed. For the dependent var, the t stat in its absolute form was larger than the critical vales at all points, for one of my independent var, it is only larger at 5 and 10% critical value point and for another independent variable, the absolute value is not larger than any critical values at any points. for 3 of my control variables the absolute values of t sata is larger than all critical values at all point.

I want to run either a VAR, VECM or ARDL at the end.

1. How do I deal with the issue of these mixed results from the ADF and with the negative values in the differenced var?
2. should I just forgo the ADF given the result of the D.Wastson in the first regression result. When I ran regression before difference, 4/5 independent var showed to be statistically significant and have an effect on co2. however with the differenced vars, non are significant

Thank you all

Rose