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Нелинеен модел с фиксирани ефекти×Нелинеен модел със случайни отклонения×
ОбластИконометрияИконометрия
СемействоRegression modelRegression model
Година на възникване19841981–2010
СъздателGary ChamberlainHeckman (1981); Chamberlain (1984); further systematized by Wooldridge (2010)
ТипPanel data estimatorPanel data / nonlinear regression
Основополагащ източникChamberlain, G. (1984). Panel data. In Z. Griliches & M. D. Intriligator (Eds.), Handbook of Econometrics (Vol. 2, pp. 1247–1318). Elsevier. link ↗Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586
Други названияnonlinear FE model, NLFE, conditional fixed effects model, incidental parameters modelnonlinear RE model, NLRE model, random effects nonlinear panel model, mixed nonlinear panel model
Свързани51
РезюмеThe nonlinear fixed effects model extends fixed effects panel estimation to outcomes governed by nonlinear response functions — such as binary, count, or censored outcomes — while absorbing unobserved individual heterogeneity through unit-specific intercepts. Key special cases include conditional logit for binary outcomes and Poisson fixed effects for count data.The nonlinear random effects model extends classical random effects estimation to settings where the outcome variable is binary, count-based, censored, or otherwise non-continuously distributed across panel units. It accounts for unobserved individual heterogeneity by treating unit-specific effects as random draws from a distribution, then integrating them out to form a likelihood that can be maximised over the structural parameters.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Nonlinear Fixed Effects Model · Nonlinear Random Effects Model. Извлечено на 2026-06-17 от https://scholargate.app/bg/compare