Nothing Special   »   [go: up one dir, main page]

  EconPapers    
Economics at your fingertips  
 

Nearly Efficient Likelihood Ratio Tests of a Unit Root in an Autoregressive Model of Arbitrary Order

Samuel Brien (), Michael Jansson and Morten Nielsen

No 1429, Working Paper from Economics Department, Queen's University

Abstract: We study large sample properties of likelihood ratio tests of the unit root hypothesis in an autoregressive model of arbitrary order. Earlier research on this testing problem has developed likelihood ratio tests in the autoregressive model of order one, but resorted to a plug-in approach when dealing with higher-order models. In contrast, we consider the full model and derive the relevant large sample properties of likelihood ratio tests under a local to unity asymptotic framework. As in the simpler model, we show that the full likelihood ratio tests are nearly efficient, in the sense that their asymptotic local power functions are virtually indistinguishable from the Gaussian power envelopes. Extensions to sieve-type approximations and different classes of alternatives are also considered.

Keywords: Efficiency; Likelihood ratio test; Nuisance parameters; Unit root hypothesis (search for similar items in EconPapers)
JEL-codes: C12 C22 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2022-03
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.econ.queensu.ca/sites/econ.queensu.ca/files/wpaper/qed_wp_1429.pdf First version 2020 (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:qed:wpaper:1429

Access Statistics for this paper

More papers in Working Paper from Economics Department, Queen's University Contact information at EDIRC.
Bibliographic data for series maintained by Mark Babcock ().

 
Page updated 2024-12-17
Handle: RePEc:qed:wpaper:1429