Regression modelEconometrics / time series

Time-Varying Parameter GLS (TVP-GLS)

Time-varying parameter GLS extends generalized least squares to settings where regression coefficients are not fixed constants but evolve over time according to a stochastic process. By embedding the model in a state-space framework and applying GLS corrections for non-spherical errors, it captures structural change, regime shifts, and gradually drifting relationships in time-series data.

EconMind ile uygulaSoonVideoSoon

Tam yöntemi oku

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Cooley, T. F., & Prescott, E. C. (1976). Estimation in the presence of stochastic parameter variation. Econometrica, 44(1), 167–184. DOI: 10.2307/1911389
  2. Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 9780521321969

Related methods

ScholarGateTime-varying parameter GLS (Time-Varying Parameter Generalized Least Squares). Retrieved 2026-06-04 from https://scholargate.app/tr/econometrics/time-varying-parameter-gls