手法を比較

	時間変動係数VARモデル（TVP-VAR）	状態空間モデル（カルマンフィルタ）
分野	計量経済学	計量経済学
系統	Regression model	Regression model
提唱年	2005	1990
提唱者	Primiceri (2005); Cogley & Sargent (2001, 2005)	Harvey; Durbin & Koopman (state space treatment); Kalman filter
種類	Multivariate time-series model with drifting coefficients	State space time series model
原典	Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. Review of Economic Studies, 72(3), 821-852.	Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press.
別名	TVP-VAR, time-varying VAR, TV-VAR, drifting-coefficient VAR	state space, Kalman filter, unobserved components model, Durum Uzayı Modeli (State Space / Kalman Filter)
関連	6	4
概要	The Time-Varying Parameter VAR (TVP-VAR) model extends the standard vector autoregression by allowing the coefficients and error covariances to evolve gradually over time. Estimated via Bayesian methods and MCMC simulation, it captures how dynamic relationships between macroeconomic or financial variables shift across different economic regimes without requiring pre-specified break points.	A state space model is a general time series framework that describes a series through unobserved (latent) state variables linked by a measurement equation and a transition equation, with the states estimated in real time by the Kalman filter. Developed in the state space tradition of Harvey (1990) and Durbin & Koopman (2012), it nests ARIMA and exponential smoothing as special cases.