Tests of Joint Hypotheses for Time Series Regression with a Unit Root
Pierre Perron ()
Cahiers de recherche from Universite de Montreal, Departement de sciences economiques
This Paper Studies Tests of Joint Hypotheses in Time Series Regression with a Unit Root in Which Weakly Dependent and Heterogeneously Distributed Innovations Are Allowed. We Consider Two Types of Regression: One with a Constant and Lagged Dependent Variable, and the Other with a Trend Added. the Statistics Studied Are the Regression "F-Test" Originally Analysed by Dickey and Fuller (1981) in a Less General Framework. the Limiting Distributions Are Found Using Functinal Central Limit Theory. New Test Statistics Are Proposed Which Require Only Already Tabulated Critical Values But Which Are Valid in a Quite General Framework (Including Finite Order Arma Models Generated by Gaussian Errors). This Study Extends the Results on Single Coefficients Derived in Phillips (1986A) and Phillips and Perron (1986).
Keywords: Time Series; Mathematical Analysis; Theory; Testing (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:mtl:montde:8632
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