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      <record key="001" att1="001" value="175252" att2="175252">001   175252</record>
      <field key="037" subkey="x">englisch</field>
      <field key="050" subkey="x">Open Access</field>
      <field key="076" subkey="">Ökonomie</field>
      <field key="079" subkey="y">http://www.ihs.ac.at/publications/lib/oa11.pdf</field>
      <field key="079" subkey="z">Bauer, Dietmar - et al., Asymptotic Properties of Pseudo Maximum Likelihood Estimates for Multiple Frequency I(1) Processes (pdf)</field>
      <field key="100" subkey="">Bauer, Dietmar</field>
      <field key="103" subkey="">Institute for Econometrics, Operations Research and System Theory, TU Wien</field>
      <field key="104" subkey="a">Wagner, Martin</field>
      <field key="107" subkey="">Department of Economics, University of Bern</field>
      <field key="331" subkey="">Asymptotic Properties of Pseudo Maximum Likelihood Estimates for Multiple Frequency I(1) Processes</field>
      <field key="403" subkey="">1. Ed.</field>
      <field key="410" subkey="">Bern, Switzerland</field>
      <field key="412" subkey="">Volkswirtschaftliches Institut, Universität Bern</field>
      <field key="425" subkey="">2002, June</field>
      <field key="433" subkey="">45 pp.</field>
      <field key="451" subkey="">Diskussionsschriften; 02-05</field>
      <field key="451" subkey="i">Volkswirtschaftliches Institut, Universität Bern (Ed.)</field>
      <field key="544" subkey="">OA11</field>
      <field key="700" subkey="">C13</field>
      <field key="700" subkey="">C32</field>
      <field key="720" subkey="">State space representation</field>
      <field key="720" subkey="">Unit roots</field>
      <field key="720" subkey="">Cointegration</field>
      <field key="720" subkey="">Pseudo maximum likelihood estimation</field>
      <field key="753" subkey="">Abstract: In this paper we derive (weak) consistency and the asymptotic distribution of pseudo maximum likelihood estimates for</field>
      <field key="mul" subkey="t">iple frequency I(1) processes. By multiple frequency I(1) processes we denote processes with unit roots at arbitrary points</field>
      <field key="on" subkey="t">he unit circle with the integration orders corresponding to these unit roots all equal to 1. The parameters corresponding to</field>
      <field key="the" subkey="">cointegrating spaces at the different unit roots are estimated super-consistently and have a mixture of Brownian motions</field>
      <field key="lim" subkey="i">ting distribution. All other parameters are asymptotically normally distributed and are estimated at the standard square root</field>
      <field key="of" subkey="T">rate. The problem is formulated in the state space framework, using the canonical form and parameterization introduced by</field>
      <field key="Bau" subkey="e">r and Wagner (2002b). Therefore the analysis covers vector ARMA processes and is not restricted to autoregressive processes.;</field>
    </SEQUENTIAL>
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