Linearity and misspecification tests for vector smooth transition regression models
Timo Teräsvirta and
Yukai Yang
No 2014061, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)
Abstract:
In this paper, we derive Lagrange multiplier and Lagrange multiplier type specification and misspecification tests for vector smooth transition models. We report results from simulation studies in which the size and power properties of the proposed tests in small samples are considered. The results show that these asymptotic tests generally suffer from size distortion. We find that Wilks’s and Rao’s F statistic both have satisfactory size properties and can be recommended for empirical use. Bootstrapping the standard asymptotic LM statistic offers another solution to the problem.
Keywords: Vector STAR models; linearity test; misspecification test; vector nonlinear time series; serial correlation; parameter constancy; residual nonlinearity test (search for similar items in EconPapers)
JEL-codes: C12 C32 C52 (search for similar items in EconPapers)
Date: 2014-11-30
New Economics Papers: this item is included in nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (33)
Downloads: (external link)
https://sites.uclouvain.be/core/publications/coredp/coredp2014.html (application/pdf)
Related works:
Working Paper: Linearity and Misspecification Tests for Vector Smooth Transition Regression Models (2014) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:2014061
Access Statistics for this paper
More papers in LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) Voie du Roman Pays 34, 1348 Louvain-la-Neuve (Belgium). Contact information at EDIRC.
Bibliographic data for series maintained by Alain GILLIS ().