A unified theory for ARMA models with varying coefficients: One solution fits all
M. Karanasos, A. Paraskevopoulos, T. Magdalinos, A. Canepa

TL;DR
This paper develops a comprehensive, explicit solution framework for TV-ARMA models, enabling analysis of their properties, forecasting, and stability, with practical application to U.S. inflation data.
Contribution
It introduces a unified, explicit solution representation for TV-ARMA models based on Hessenbergian matrices, advancing understanding of their properties and stability.
Findings
Inflation persistence increased after 1976
Persistence declined and stabilized post-1986
Theoretical results applied to real economic data
Abstract
For the large family of ARMA models with variable coefficients (TV-ARMA), either deterministic or stochastic, we provide an explicit and computationally tractable representation based on the general solution of the associated linear difference equation. Analogous representations are established for the fundamental properties of such processes, including the Wold-Cram\'{e}r decomposition and their covariance structure as well as explicit optimal linear forecasts based on a finite set of past observations. These results are grounded on the principal determinant, that is a banded Hessenbergian representation of a restriction of the Green function involved in the solution of the linear difference equation associated with TV-ARMA models, built up solely of the autoregressive coefficients of the model. The convergence properties of the model are a consequence of the absolute summability…
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Taxonomy
TopicsMonetary Policy and Economic Impact · Financial Risk and Volatility Modeling · Market Dynamics and Volatility
