Stationarity in panel data refers to whether the mean and variance of variables are constant over time across entities; many panel datasets are non-stationary, so tests like Levin–Lin–Chu, Im–Pesaran–Shin, or Fisher-ADF are used to check for unit roots before applying panel econometric models.

Thanks for your answer

What is your opinion on second generation panel unit root tests like pesaran's CADF? When do we use this test in panel data models?

Second-generation panel unit root tests, such as Pesaran's Cross-sectionally Augmented Dickey-Fuller (CADF) test, are a significant advancement over first-generation tests.

One uses the CADF test, and other second-generation tests, when there is a plausible theoretical basis or empirical evidence of cross-sectional dependence in the panel data. This is particularly relevant in cross-country studies of variables like GDP, inflation, or interest rates, where national economies are influenced by global factors.

Sónia Maria Aniceto Morgado Thank you for your reply.

ADF and Levin-Lin-Chu is perfect models, but you can apply other model from Stata, with trend or without trend.

Inder Kumar tnx for your reply.