• Media type: E-Article
  • Title: Estimation and inference for the threshold model with hybrid stochastic local unit root regressors
  • Contributor: Chen, Chaoyi [VerfasserIn]; Stengos, Thanasēs [VerfasserIn]
  • imprint: 2022
  • Published in: Journal of risk and financial management ; 15(2022), 6 vom: Juni, Artikel-ID 242, Seite 1-15
  • Language: English
  • DOI: 10.3390/jrfm15060242
  • ISSN: 1911-8074
  • Identifier:
  • Keywords: hybrid local stochastic unit root ; threshold model ; Aufsatz in Zeitschrift
  • Origination:
  • Footnote:
  • Description: In this paper, we study the estimation and inference of the threshold model with hybrid local stochastic unit root regressors. Our main contribution is to propose an estimator that generalizes the threshold model with various forms of nonstationary regressors and to obtain its limiting distribution theory. In particular, our proposed model generalizes the threshold model with unit root, local-to-unity, and stochastic unit root regressors. We provide the estimation strategy for the least squares estimator and derive the asymptotic results for the proposed estimator. Depending on the diminishing rate of the threshold effect, we find that the limiting distribution of the threshold estimator takes different forms. Monte Carlo simulations are used to assess our proposed estimator's finite sample performance, which is found to perform well.
  • Access State: Open Access
  • Rights information: Attribution (CC BY)