Salīdzināt metodes

	Strukturālās izmaiņas ar nejaušiem efektiem modelis	Modelis ar strukturālām pārtraukuma fiksētajām ietekmēm
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	1998–2000s	1998 (Bai-Perron); FE estimator classical
Autors	Bai & Perron (break detection); Baltagi (panel RE framework)	Bai & Perron (structural break testing); Mundlak / within-group estimator tradition
Tips	Panel regression with regime shifts	Panel regression with regime change
Pirmavots	Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78.	Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47-78.
Citi nosaukumi	RE model with structural breaks, break-adjusted random effects, random effects break model, panel RE with regime shifts	FE model with structural breaks, break-adjusted fixed effects, panel fixed effects with regime shifts, structural change fixed effects estimator
Saistītās	5	6
Kopsavilkums	The structural break random effects model extends standard panel RE estimation by allowing one or more breakpoints at which slope coefficients or error variances shift across time. It combines structural change detection (e.g., Bai-Perron) with the GLS-based random effects estimator, producing regime-specific parameter estimates while retaining the efficiency gains of pooling individual-level variation as random draws from a common distribution.	The structural break fixed effects model extends the standard within-group (FE) panel estimator by allowing the slope coefficients to shift at one or more detected break dates. Each unit's unobserved time-invariant heterogeneity is still removed by demeaning, but separate coefficient regimes are estimated for each sub-period, capturing policy shifts, crises, or technological transitions that would otherwise bias a single-regime FE estimate.