Use the Arellano-Bond framework via the user-written xtabond2 command or the built-in xtdpdgmm command to implement Generalized Method of Moments (GMM).
In macro-panels (e.g., datasets covering multiple countries over many years), shocks like global financial crises can affect all entities simultaneously. This creates cross-sectional dependence. You can test for this using Pesaran’s CD test: xtcsd, pesaran abs Use code with caution.
Generate data (or import real data) do "generate_data.do" stata panel data
* Run your FE model first xtreg y x1 x2, fe
xtreg y x, fe vce(cluster id)
*
xtline gdp_growth, overlay legend(label(1 "Country 1") label(2 "Country 2")) You can test for this using Pesaran’s CD
Stata will output the panel variable name, the time variable name, and whether your panel is "balanced" (every entity has data for every time period) or "unbalanced" (some entities have missing time periods). 2. Exploring and Visualizing Panel Data
The choice of model depends on your assumptions about the individual-specific effects (the "unobserved" factors unique to each entity). Model Type Stata Command Description Fixed Effects (FE) xtreg y x, fe Exploring and Visualizing Panel Data The choice of
These require xtset first.