Piecewise Linear Solutions for Non-Stationary Models

Mariano Kulish and Inna Tsener
Additional contact information
Mariano Kulish: Univeristy of Sydney
Inna Tsener: Universitat de les Illes Balears

No 387, Working Papers from Red Nacional de Investigadores en Economía (RedNIE)

Abstract: We assess the accuracy and efficiency of time-varying linear solution methods for non-stationary rational expectations models. These methods construct a sequence of local linear approximations, each with coefficients that vary over time, based on a set of expansion points. Benchmarking against globally accurate non-linear solutions, we show, both theoretically and numerically, that their accuracy depends critically on the choice of expansion points and on agents’ expectations about the future. Our results contribute to the literature on solving non-stationary stochastic models with rational expectations, spanning a wide range of sources of non-stationarity, including evolving structural parameters, changing policy regimes, and cases without a balanced growth path.

Keywords: piecewise linear solutions; approximation points; time-inhomogeneous models; non-stationary models; semi-Markov models; unbalanced growth; time-varying parameters; extended function path (search for similar items in EconPapers)
JEL-codes: C61 C63 C68 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2025-02
References: Add references at CitEc
Citations:

Downloads: (external link)
https://rednie.eco.unc.edu.ar/files/DT/387.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aoz:wpaper:387

Access Statistics for this paper

More papers in Working Papers from Red Nacional de Investigadores en Economía (RedNIE) Contact information at EDIRC.
Bibliographic data for series maintained by Laura Inés D Amato ().