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Testing for randomness in a random coefficient autoregression model

Horv�th, Lajos; Trapani, Lorenzo


Lajos Horv�th

Lorenzo Trapani


We propose a test to discern between an ordinary autoregressive model, and a random coefficient one. To this end, we develop a full-fledged estimation theory for the variances of the idiosyncratic innovation and of the random coefficient, based on a two-stage WLS approach. Our results hold irrespective of whether the series is stationary or nonstationary, and, as an immediate result, they afford the construction of a test for " relevant " randomness. Further, building on these results, we develop a randomised test statistic for the null that the coefficient is non-random, as opposed to the alternative of a standard RCA(1) model. Monte Carlo evidence shows that the test has the correct size and very good power for all cases considered.


Horváth, L., & Trapani, L. (2019). Testing for randomness in a random coefficient autoregression model. Journal of Econometrics, 209(2), 338-352.

Journal Article Type Article
Acceptance Date Jan 14, 2019
Online Publication Date Jan 24, 2019
Publication Date 2019-04
Deposit Date Jan 17, 2019
Publicly Available Date Jan 25, 2021
Journal Journal of Econometrics
Print ISSN 0304-4076
Electronic ISSN 1872-6895
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 209
Issue 2
Pages 338-352
Keywords Random Coefficient AutoRegression; WLS estimator; randomised test
Public URL
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Additional Information This article is maintained by: Elsevier; Article Title: Testing for randomness in a random coefficient autoregression model; Journal Title: Journal of Econometrics; CrossRef DOI link to publisher maintained version:; Content Type: article; Copyright: © 2019 Elsevier B.V. All rights reserved.


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