Some of my variables in my unbalanced panel dataset is non-stationary, and I was wondering if I can use this and not think about the data being non-stationary? Is it possible to take the difference so the data becomes stationary and then use the within estimation? Or how should I proceed?
I can't seem to find any information on this, all answers are appreciated.
Dear Arne Faaberg
When dealing with non-stationary variables in an unbalanced panel dataset, ignoring the issue can lead to spurious regression results where relationships appear significant even when they are not. Non-stationarity can inflate t-statistics and distort inference, making it crucial to address the problem before proceeding with estimation. While some estimators may be robust to certain forms of non-stationarity, it is generally advisable to test for and resolve stationarity issues to ensure the validity of your results.
Taking the difference of the non-stationary variables to achieve stationarity is a common approach, particularly if the variables are integrated of order one (I(1)). Once differenced, you can proceed with within estimation (fixed effects) if the transformed variables meet the stationarity assumptions. However, differencing removes long-run information, so if you are interested in long-term relationships, you might consider alternative methods like panel cointegration techniques. Alternatively, you could explore dynamic panel models or other specifications that account for non-stationarity while preserving the structure of your data. The choice depends on your research question and the nature of the non-stationarity in your dataset.
I hope this helps.
- Badges
- Science topic