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Model dinamičkih panel podataka sa vremenski promenljivim parametrima×Model stanja prostora (Kalmanov filter)×
OblastEkonometrijaEkonometrija
PorodicaRegression modelRegression model
Godina nastanka1990s–2000s1990
TvoracHsiao, Pesaran, and related panel time-series literatureHarvey; Durbin & Koopman (state space treatment); Kalman filter
TipDynamic panel model with time-varying coefficientsState space time series model
Temeljni izvorCanova, F., & Ciccarelli, M. (2009). Estimating multicountry VAR models. International Economic Review, 50(3), 929-959. DOI ↗Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. DOI ↗
Drugi naziviTVP dynamic panel model, time-varying coefficient panel model, TVP-DPD model, state-space dynamic panel modelstate space, Kalman filter, unobserved components model, Durum Uzayı Modeli (State Space / Kalman Filter)
Srodne24
SažetakThe time-varying parameter dynamic panel data model combines lagged dependent variables with coefficients that evolve over time across panel units. It extends conventional dynamic panel models by allowing slope parameters to shift across periods, making it well-suited for studying structural change, heterogeneous adjustment dynamics, and parameter instability in macro-panels and cross-country datasets.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.
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ScholarGateUporedite metode: Time-varying parameter dynamic panel data model · State Space Model. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare