When cleaning panel data, you can use logical operators to include or exclude specific observations:
Running the data is only half the battle; presenting it effectively is equally important. Stop manually copying Stata output into Excel or Word.
How much the variable changes from person to person. If a variable like education has zero within variation, it means individuals in your sample did not change their schooling level during the study window. stata panel data exclusive
The Random Effects model assumes that unobserved individual effects are entirely uncorrelated with the explanatory variables. RE utilizes both within-unit and between-unit variation, making it more efficient than FE if its assumptions hold. xtreg y x1 x2 x3, re Use code with caution. 3. High-Level Diagnostics: Choosing the Right Model
Pooled OLS ignores the panel structure entirely, treating every observation as completely independent. This is rarely appropriate because it introduces severe omitted variable bias if αialpha sub i correlates with your explanatory variables. regress y x1 x2 x3, vce(cluster panelvar) Use code with caution. Fixed Effects (FE) When cleaning panel data, you can use logical
: Plots time-series trajectories for individual cross-sectional units, allowing for rapid visual detection of outliers or structural breaks. 2. Fixed Effects vs. Random Effects: The Selection Matrix
Panel data variation occurs across two dimensions: entities and within entities over time. Understanding which dimension holds the most variation dictates your modeling choices. xtsum (Panel Decomposition of Summary Statistics) If a variable like education has zero within
For panels with structural breaks, the xtbunitroot module allows testing with breakpoints.