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

Abstract: 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)
Pages: 24P. pages
Date: 1986
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/1866/412 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mtl:montde:8632

Access Statistics for this paper

More papers in Cahiers de recherche from Universite de Montreal, Departement de sciences economiques Contact information at EDIRC.
Bibliographic data for series maintained by Sharon BREWER ().