Salīdzināt metodes

	Modelis ar strukturālām pārtraukumiem dinamiskajos paneļu datos	Dinamiskais paneļa datu modelis
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	1991–1998	1988–1991
Autors	Bai & Perron (break detection); Arellano & Bond (dynamic panel GMM)	Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988)
Tips	Dynamic panel model with regime change	Dynamic regression / GMM estimation
Pirmavots	Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78.	Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277–297.
Citi nosaukumi	dynamic panel with breaks, panel dynamic model structural change, DPDSB, panel dynamic structural break estimator	dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model
Saistītās	6	5
Kopsavilkums	The structural break dynamic panel data model extends the standard dynamic panel framework by allowing regression coefficients or the autoregressive parameter to shift at one or more unknown break dates. It combines GMM-based dynamic panel estimation with formal structural change tests, enabling researchers to study how economic relationships evolve across distinct regimes while controlling for unobserved individual heterogeneity and endogeneity of the lagged dependent variable.	The dynamic panel data model extends standard panel regression by including a lagged value of the outcome variable as a regressor, capturing persistence and adjustment dynamics. Because the lagged dependent variable is correlated with the unit-specific fixed effect, ordinary OLS or within estimators are biased; GMM-based methods using internal instruments are the standard remedy.