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

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Author Info

  • Morten Ørregaard Nielsen

    ()
    (Queen's University and CREATES)

Abstract

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.

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File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_1259.pdf
File Function: First version 2011
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Bibliographic Info

Paper provided by Queen's University, Department of Economics in its series Working Papers with number 1259.

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Length: 31 pages
Date of creation: Jan 2011
Date of revision:
Handle: RePEc:qed:wpaper:1259

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Keywords: Asymptotic normality; conditional-sum-of-squares estimator; consistency; fractional integration; fractional time series; likelihood inference; long memory; nonstationary; uniform convergence; uniform convergence;

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Cited by:
  1. Søren Johansen & Morten Ørregaard Nielsen, 2012. "The role of initial values in nonstationary fractional time series models," CREATES Research Papers 2012-47, School of Economics and Management, University of Aarhus.
  2. Giuseppe Cavaliere & Morten Ørregaard Nielsen & A.M. Robert Taylor, 2013. "Bootstrap Score Tests for Fractional Integration in Heteroskedastic ARFIMA Models, with an Application to Price Dynamics in Commodity Spot and Futures Markets," Working Papers 1309, Queen's University, Department of Economics.

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