Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/179583 
Year of Publication: 
2015
Citation: 
[Journal:] EconomiA [ISSN:] 1517-7580 [Volume:] 16 [Issue:] 1 [Publisher:] Elsevier [Place:] Amsterdam [Year:] 2015 [Pages:] 1-21
Publisher: 
Elsevier, Amsterdam
Abstract: 
Nonlinear time series models, especially those with regime-switching and/or conditionally heteroskedastic errors, have become increasingly popular in the economics and finance literature. However, much of the research has concentrated on the empirical applications of various models, with little theoretical or statistical analysis associated with the structure of the processes or the associated asymptotic theory. In this paper, we derive sufficient conditions for strict stationarity and ergodicity of three different specifications of the first-order smooth transition autoregressions with heteroskedastic errors. This is essential, among other reasons, to establish the conditions under which the traditional LM linearity tests based on Taylor expansions are valid. We also provide sufficient conditions for consistency and asymptotic normality of the Quasi-Maximum Likelihood Estimator for a general nonlinear conditional mean model with first-order GARCH errors.
Abstract (Translated): 
Modelos não-lineares com múltiplos regimes e heterpcedasticidade condicional são muito populares em economia e finanças. Neste artigo derivamos condições de estacionaridade para modelos com transição suave e erros heterocedásticos. Além disso derivamos condições suficientes para consistência e normalidade assintótica do estimador de quase-máxima verossimilhança.
Subjects: 
Nonlinear time series
Regime-switching
Smooth transition
STAR
GARCH
Asymptotic theory
JEL: 
C22
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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