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Testing for randomness in a random coefficient autoregression model

Horv�th, Lajos; Trapani, Lorenzo

Authors

Lajos Horv�th

Lorenzo Trapani



Abstract

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.

Citation

Horváth, L., & Trapani, L. (2019). Testing for randomness in a random coefficient autoregression model. Journal of Econometrics, 209(2), 338-352. https://doi.org/10.1016/j.jeconom.2019.01.005

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 Mar 29, 2024
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
DOI https://doi.org/10.1016/j.jeconom.2019.01.005
Keywords Random Coefficient AutoRegression; WLS estimator; randomised test
Public URL https://nottingham-repository.worktribe.com/output/1479371
Publisher URL https://www.sciencedirect.com/science/article/pii/S0304407619300090
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: https://doi.org/10.1016/j.jeconom.2019.01.005; Content Type: article; Copyright: © 2019 Elsevier B.V. All rights reserved.

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