Comparar métodos

	Investigación Causal-Comparativa Basada en Paneles	Modelo de efectos fijos
Campo	Diseño de investigación	Econometría
Familia	Process / pipeline	Regression model
Año de origen	1950s–1980s (formalized across educational and social science methodology literature)	1971–1978
Autor original	Building on causal-comparative tradition (John W. Best, 1959) extended to panel data structures in social and educational research	Mundlak (1978); Nerlove (1971); classical panel econometrics
Tipo	Quantitative observational research design	Panel regression estimator
Fuente seminal	Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2019). How to Design and Evaluate Research in Education (10th ed.). McGraw-Hill. ISBN: 978-1260087840	Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. ISBN: 978-3030538002
Alias	panel causal-comparative design, longitudinal ex post facto research, panel ex post facto study, repeated-measures causal-comparative study	FE model, within estimator, least squares dummy variable, LSDV regression
Relacionados	5	5
Resumen	Panel-based causal-comparative research is a quantitative observational design that tracks the same sample of participants or units across multiple time points and then compares pre-existing groups to identify differences in outcomes. By combining the temporal depth of a panel structure with the group-contrast logic of causal-comparative (ex post facto) methodology, it allows researchers to examine how naturally occurring conditions — such as treatment exposure, policy changes, or demographic characteristics — relate to outcomes over time, without experimental random assignment.	The fixed effects (FE) model is the workhorse estimator for panel data when unobserved unit-specific characteristics are suspected to correlate with the regressors. By absorbing each entity's time-invariant heterogeneity into a separate intercept, FE isolates the causal effect of within-unit variation and eliminates omitted-variable bias from time-constant confounders.