Department of Economics and Business Economics

Asymptotics for the conditional-sum-of-squares estimator in multivariate fractional time series models

Research output: Working paperResearch

Documents

  • rp14_34

    Submitted manuscript, 490 KB, PDF document

  • Morten Ørregård Nielsen, Queens's University, Canada
This paper proves consistency and asymptotic normality for the conditional-sum-of-squares estimator, which is equivalent to the conditional maximum likelihood estimator, in multivariate fractional time series models. The model is parametric and quite general, and, in particular, encompasses the multivariate non-cointegrated fractional ARIMA model. The novelty of the consistency result, in particular, is that it applies to a multivariate model and to an arbitrarily large set of admissible parameter values, for which the objective function does not converge uniformly in probablity, thus making the proof much more challenging than usual. The neighborhood around the critical point where uniform convergence fails is handled using a truncation argument.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages32
Publication statusPublished - 6 Oct 2014
SeriesCREATES Research Papers
Number2014-34

See relations at Aarhus University Citationformats

Download statistics

No data available

ID: 81842527