Random autoregressive models: A structured overview

P.J. de Andrade Serra, Marta Regis*, Edwin van den Heuvel

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


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 ran- dom coefficients. We describe hierarchy and analogies among models, and for each we systematically list properties, estimation methods, tests, soft- ware packages and typical applications.
Original languageEnglish
Pages (from-to)207-230
Number of pages24
JournalEconometric Reviews
Issue number2
Early online date5 Apr 2021
Publication statusPublished - 2022


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