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法玛-麦克贝回归×时变参数因子增强向量自回归模型×
领域计量经济学计量经济学
方法族Regression modelRegression model
起源年份19732005
提出者Eugene Fama and James MacBethBernanke, Boivin, and Eliasz
类型Cross-sectional regressionTime-varying system
开创性文献Fama, E. F., & MacBeth, J. D. (1973). Risk, return, and equilibrium: Empirical tests. Journal of Political Economy, 81(3), 607-636. DOI ↗Bernanke, B. S., Boivin, J., & Eliasz, P. S. (2005). Measuring monetary policy. Journal of Political Economy, 113(1), 161-208. link ↗
别名Two-step cross-sectional regressionDynamic factor model with time-varying parameters
相关33
摘要The Fama-MacBeth procedure is a two-step regression methodology for analyzing cross-sectional relationships while controlling for time-series structure. Introduced by Fama and MacBeth (1973), it first estimates time-series parameters for each cross-sectional unit, then regresses outcomes on those parameters across the cross-section, averaging results over time. This approach elegantly separates within-unit dynamics from cross-sectional heterogeneity and provides standard errors robust to panel structure.TVP-FAVAR is a hybrid framework combining factor-augmented VARs with time-varying parameter estimation via Kalman filtering. Introduced by Bernanke et al. (2005) and refined by Primiceri (2005), it extracts latent economic factors (e.g., a 'common monetary policy shock') from high-dimensional data while allowing VAR coefficients to evolve stochastically over time. This framework captures both reduced-dimensionality patterns and structural instability, making it ideal for studying evolving policy regimes and shock dynamics.
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ScholarGate方法对比: Fama-MacBeth Regression · TVP-FAVAR. 于 2026-06-19 检索自 https://scholargate.app/zh/compare