Testing for randomness in a random coefficient autoregression model

Horv�th, Lajos; Trapani, Lorenzo

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: 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
• 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.
• Contract Date: Jan 17, 2019