A low-dimension portmanteau test for non-linearity

Castle, Jennifer L.; Hendry, David F.

doi:10.1016/j.jeconom.2010.01.006

Cited by 49 publications

(43 citation statements)

References 27 publications

(40 reference statements)

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“…Castle and Hendry (2010) provide details of the test, in which principal components of the set of possible linear regressors are computed and their non-linear functions are jointly tested. Let x t denote the set of candidate regressors where…”

Section: Testing For Non-linearitymentioning

confidence: 99%

Semi-Automatic Nonlinear Model Selection

Castle¹,

Hendry²

2014

Essays in Nonlinear Time Series Econometrics

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We consider model selection for non-linear dynamic equations with more candidate variables than observations, based on a general class of non-linear-in-the-variables functions, addressing possible location shifts by impulse-indicator saturation. After an automatic search delivers a simplified congruent terminal model, an encompassing test can be implemented against an investigator's preferred non-linear function. When that is non-linear in the parameters, such as a threshold model, the overall approach can only be semi-automatic. The method is applied to re-analyze an empirical model of real wages in the UK over 1860-2004, updated and extended to 2005-2011 for forecast evaluation.JEL classifications: C51, C22.

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Section: Testing For Non-linearitymentioning

confidence: 99%

Semi-Automatic Nonlinear Model Selection

Castle¹,

Hendry²

2014

Essays in Nonlinear Time Series Econometrics

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“…For more discussion on principal components in solving the collinearity problem, see Castle and Hendry (2010).…”

Section: General Testmentioning

confidence: 99%

Testing the Granger Noncausality Hypothesis in Stationary Nonlinear Models of Unknown Functional Form

Péguin-Feissolle¹,

Strikholm²,

Teräsvirta³

2013

Communications in Statistics - Simulation and Computation

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may January 2012Abstract In this paper we propose a general method for testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form. These tests are based on a Taylor expansion of the nonlinear model around a given point in the sample space. We study the performance of our tests by a Monte Carlo experiment and compare these to the most widely used linear test. Our tests appear to be well-sized and have reasonably good power properties.

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“…[13,30] and generalizations based on polynomial and exponential functions, see [4,8] and references therein. Series expansions are rarely optimal for global approximation of functions, cf.…”

Section: Introductionmentioning

confidence: 99%

Semiparametric lag dependent functions

Lindström¹

2013

ams

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This paper introduces a suite of tests for linear and general nonlinear serial dependence. The problem is complex as the number of variations of realistic non-linear alternatives is very large.The alternative model is defined in terms of penalized truncated polynomial splines, making the approximation capable of accurately approximating a large class of linear and non-linear processes.The asymptotic distribution for the test statistic is derived, and we show using Monte Carlo simulations that one test is equivalent to the Ljung-Box test, other linear tests corresponds to ordinary or partial sample autocorrelation while the non-linear versions are capable of detecting non-linear effects, even when other tests fail to do so.

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A low-dimension portmanteau test for non-linearity

Cited by 49 publications

References 27 publications

Semi-Automatic Nonlinear Model Selection

Semi-Automatic Nonlinear Model Selection

Testing the Granger Noncausality Hypothesis in Stationary Nonlinear Models of Unknown Functional Form

Semiparametric lag dependent functions

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