17 D2. Panel Data — Overview
17.1 About
This section introduces panel data econometrics — data combining \(N\) units observed over \(T\) periods. This structure allows controlling for unobserved time-invariant heterogeneity, a key advantage over pure cross-sections.
Topics: one-way error component model, Fixed Effects (within estimator), Random Effects (GLS), Hausman test, first-difference estimator, dynamic panels (Arellano-Bond).
17.2 Lecture Notes
17.3 Slides
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Note: Slides and notes are pending translation to English.
17.4 Overview
Panel data (also called longitudinal data) combines cross-sectional and time series dimensions: we observe \(N\) units (individuals, firms, countries) over \(T\) time periods. This structure allows us to control for unobserved heterogeneity that is constant within a unit — a key advantage over pure cross-sections.
Key topics covered
- The one-way error component model: \(y_{it} = x_{it}'\beta + \alpha_i + u_{it}\)
- Fixed Effects (FE) — within estimator, FWL theorem applied to panels
- Random Effects (RE) — GLS estimator, feasible GLS
- Hausman test: FE vs. RE
- First-difference estimator
- Clustered standard errors
- Dynamic panel models (GMM-based: Arellano-Bond)
More detail
See D3. Panel Data Theory for derivations and proofs.