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Estimation and Testing for Fractional Cointegration

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  • Marcel Aloy

    ()
    (Aix-Marseille Université, Greqam)

  • Gilles de Truchis

    ()
    (Aix-Marseille Université, Greqam)

Abstract

Estimation of bivariate fractionally cointegrated models usually operates in two steps: the first step is to estimate the long run coefficient (\beta) whereas the second step estimates the long memory parameter (d) of the cointegrating residuals. We suggest an adaptation of the maximum likelihood estimator of Hualde and Robinson (2007) to estimate jointly \beta and d, and possibly other nuisance parameters, for a wide range of integration orders when regressors are I(1). The finite sample properties of this estimator are compared with various popular estimation methods of parameters \beta (LSE, ADL, DOLS, FMLS, GLS, MLE, NBLS, FMNBLS), and d (LPE,LWE,LPM,FML) through a Monte Carlo experiment. We also investigate the crucial question of testing for fractional cointegration (that is, d

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Bibliographic Info

Paper provided by Aix-Marseille School of Economics, Marseille, France in its series AMSE Working Papers with number 1215.

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Length: 30 pages
Date of creation: 05 Jun 2012
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Handle: RePEc:aim:wpaimx:1215

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Keywords: Fractional cointegration; Long memory; Monte Carlo experiment; Cointegration test.;

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