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Testing nonlinearity: decision rules for selecting between logistic and exponential star models

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dc.affiliation.dptoUC3M. Departamento de Estadísticaes
dc.contributor.authorEscribano, Álvaro
dc.contributor.authorJordá, Óscar
dc.contributor.editorUniversidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned2009-12-23T10:18:17Z
dc.date.available2009-12-23T10:18:17Z
dc.date.issued1997-09
dc.description.abstractThis paper introduces new LM specification procedures to choose between Logistic and Exponential Smooth Transition Autoregressive (ST AR) models and to improve testing for nonlinearities. The selection procedures introduced here are simpler and have better consistency and power properties than those previously available in the literature. These improvements result from analyzing the properties ofthe Taylor approximations to the transition function. Monte-CarIo and empirical evidence are provided in support of the new procedures.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/10016/6216
dc.language.isoeng
dc.relation.ispartofseriesUC3M Working Papers. Statistics and Econometrics
dc.relation.ispartofseries97-63-24
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaEstadística
dc.subject.otherSmooth transtition nonlinear models
dc.subject.otherlinearity test,
dc.subject.otherlogistic versus exponential models
dc.subject.otherpower and size of the tests
dc.subject.otherindustrial production index
dc.titleTesting nonlinearity: decision rules for selecting between logistic and exponential star models
dc.typeworking paper*
dspace.entity.typePublication
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