Regression modelEconometrics / time series

Time-Varying Parameter ARIMA Model (TVP-ARIMA)

The time-varying parameter ARIMA model extends the classical ARIMA framework by allowing its autoregressive and moving-average coefficients to evolve over time rather than remaining fixed. Cast in state-space form and estimated via the Kalman filter, it is designed for economic and financial time series whose dynamic structure shifts in response to structural breaks, policy changes, or regime transitions.

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Sources

  1. Harvey, A. C. (1989). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 9780521405737
  2. Cooley, T. F., & Prescott, E. C. (1976). Estimation in the Presence of Stochastic Parameter Variation. Econometrica, 44(1), 167–184. DOI: 10.2307/1911389

Related methods

Referenced by

ScholarGateTime-varying parameter ARIMA model (Time-Varying Parameter Autoregressive Integrated Moving Average Model). Retrieved 2026-06-04 from https://scholargate.app/en/econometrics/time-varying-parameter-arima-model