Random autoregressive models: A structured overview

Marta Regis (Corresponding author), Paulo Serra, Edwin R. van den Heuvel

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

2 Citaten (Scopus)
4 Downloads (Pure)


Models characterized by autoregressive structure and random coefficients are powerful tools for the analysis of high-frequency, high-dimensional and volatile time series. The available literature on such models is broad, but also sector-specific, overlapping, and confusing. Most models focus on one property of the data, while much can be gained by combining the strength of various models and their sources of heterogeneity. We present a structured overview of the literature on autoregressive models with random coefficients. We describe hierarchy and analogies among models, and for each we systematically list properties, estimation methods, tests, software packages and typical applications.

Originele taal-2Engels
Pagina's (van-tot)207-230
Aantal pagina's24
TijdschriftEconometric Reviews
Nummer van het tijdschrift2
StatusGepubliceerd - apr. 2022

Bibliografische nota

Publisher Copyright:
© 2021 The Author(s). Published with license by Taylor and Francis Group, LLC.

Copyright 2021 Elsevier B.V., All rights reserved.


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