Tests of Joint Hypotheses for Time Series Regression with a Unit Root
Article [Version of Record]
Is part ofCahier de recherche ; #8632
Publisher(s)Université de Montréal. Département de sciences économiques.
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).
Perron, P., «Tests of Joint Hypotheses for Time Series Regression with a Unit Root», Cahier de recherche #8632, Département de sciences économiques, Université de Montréal, 1986, 24 pages.