I am currently doing some econometrics with, probably, nonstationary variables in a panel setting. I was hoping for cointegration, but, ADF-test on stationarity of residuals of a cointegrating regression performs rather bad. A regression using first differences performs even worse.
Nevertheless, I found out that including two lags of my dependent variable, when estimating in levels, yields very fine results (good R² and great results from autocorrelation tests). Can I trust these results or are they spurious? That is, are they unbiased and consistent? Should I fear the Nickel-bias?
Are there ways to deal with nonstationarity other than first differencing in the absence of cointegration?
I am using OLS in EViews and include cross-sectional fixed effects.