Fixed effects models are statistical techniques used in panel data analysis that control for time-invariant characteristics of individuals or entities, allowing for the estimation of causal relationships while accounting for unobserved heterogeneity. These models focus on changes within an entity over time, thus minimizing bias from omitted variables that do not vary across time but may influence the outcome. By doing so, fixed effects models are particularly valuable in addressing selection bias and confounding factors in various contexts, including impact estimation and social protection evaluations.
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