Stationarity and ergodicity of vector STAR models

4Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

Abstract

Smooth transition autoregressive models are widely used to capture nonlinearities in univariate and multivariate time series. Existence of stationary solution is typically assumed, implicitly or explicitly. In this paper, we describe conditions for stationarity and ergodicity of vector STAR models. The key condition is that the joint spectral radius of certain matrices is below 1. It is not sufficient to assume that separate spectral radii are below 1. Our result allows to use recently introduced toolboxes from computational mathematics to verify the stationarity and ergodicity of vector STAR models.

References Powered by Scopus

Computationally efficient approximations of the joint spectral radius

112Citations
N/AReaders
Get full text

Computing the joint spectral radius

101Citations
N/AReaders
Get full text

Towards a unified approach for proving geometric ergodicity and mixing properties of nonlinear autoregressive processes

64Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Delayed Monetary Policy Effects in a Multi-Regime Cointegrated VAR(MRCIVAR)

7Citations
N/AReaders
Get full text

Correction to: A Smooth Transition Autoregressive Model for Matrix-Variate Time Series (Computational Economics, (2025), 65, 1, (429-458), 10.1007/s10614-024-10568-7)

0Citations
N/AReaders
Get full text

Evaluating the nonlinear association between PM<inf>10</inf> and emergency department visits

0Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Kheifets, I. L., & Saikkonen, P. J. (2020). Stationarity and ergodicity of vector STAR models. Econometric Reviews, 39(4), 407–414. https://doi.org/10.1080/07474938.2019.1651489

Readers over time

‘18‘20‘21‘2300.511.52

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 2

67%

Researcher 1

33%

Readers' Discipline

Tooltip

Computer Science 1

25%

Engineering 1

25%

Economics, Econometrics and Finance 1

25%

Mathematics 1

25%

Save time finding and organizing research with Mendeley

Sign up for free
0