 Unbounded heteroscedasticity in autoregressive modelsNikolaos Kourogenis, Nikitas Pittis and Panagiotis Samartzis The Journal of Economic Asymmetries, 2024, vol. 29, issue C Abstract: This paper develops the asymptotic theory for stable autoregressive models in which the noise variance grows in a polynomial-like fashion. It is shown that the asymptotic distribution of the OLS estimator of the coefficient vector is multivariate normal with a covariance matrix that depends on the order, k, of the variance growth. A consistent estimator of k is proposed, which delivers heteroscedasticity-robust test statistics. The case of “variance decline” is studied as well. It is demonstrated that by means of a simple data transformation producing the time reversed image of the original series, the problem of “variance decrease” can be reformulated in terms of that of polynomial-like variance growth. Simulation evidence suggests that the new procedures work quite well in small samples. Finally, the new methods are used in order to measure potential asymmetries in business cycles dynamics among several OECD countries. Keywords: Polynomial-like noise variance; Limiting distribution; Order of variance growth; Modified t-statistic; Heteroscedasticity-robust t-statistic; Asymmetry (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:joecas:v:29:y:2024:i:c:s1703494923000634 DOI: 10.1016/j.jeca.2023.e00351 Access Statistics for this article The Journal of Economic Asymmetries is currently edited by A.G. Malliaris More articles in The Journal of Economic Asymmetries from Elsevier |
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