Econometrics: Panel Data & Fixed Effects
Econometrics: Panel Data & Fixed Effects
💡 Key Takeaways
- Define panel data and explain its value for studying changes over time in humanities and social sciences.
- Describe the fixed effects model and how it controls for unobserved, time-invariant differences across entities.
- Understand when to use fixed effects vs pooled OLS or random effects and basic model selection criteria.
- Learn how to interpret fixed effects outputs, including the meaning of within-entity coefficients and key limitations.
❓ Frequently Asked Questions
What is panel data?
Panel data tracks the same units (e.g., people, firms, countries) across multiple time periods, enabling analysis of dynamics and controlling for stable, unobserved differences.
What are fixed effects, and why use them in panel data analysis?
Fixed effects capture all unobserved, time-invariant differences across units by allowing a separate intercept for each unit (or by demeaning). This helps isolate the impact of variables that change over time and reduces bias from omitted, stable factors.
How does the fixed effects model differ from pooled OLS and random effects?
Pooled OLS ignores the panel structure; random effects assumes unobserved effects are uncorrelated with regressors. Fixed effects allows correlation between unobserved, time-invariant traits and regressors, using only within-unit variation for estimation.
What is the within transformation (demeaning) in fixed effects estimation?
The within transformation subtracts the unit’s average from each variable, removing time-invariant factors so the regression analyzes how changes within each unit relate to changes in the outcome.