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      <record key="001" att1="001" value="145030" att2="145030">001   145030</record>
      <field key="037" subkey="x">englisch</field>
      <field key="050" subkey="x">Forschungsbericht</field>
      <field key="076" subkey="">Ökonomie</field>
      <field key="079" subkey="y">http://www.ihs.ac.at/publications/eco/es-121.pdf</field>
      <field key="079" subkey="z">Kunst, Robert M., Decision Maps for Bivariate Time Series with Potential Threshold Cointegration (pdf)</field>
      <field key="079" subkey="y">http://ideas.repec.org/p/ihs/ihsesp/121.html</field>
      <field key="079" subkey="z">Institute for Advanced Studies. Economics Series; 121 (RePEc)</field>
      <field key="100" subkey="">Kunst, Robert M.</field>
      <field key="103" subkey="">University of Vienna and Department of Economics, Institute for Advanced Studies</field>
      <field key="331" subkey="">Decision Maps for Bivariate Time Series with Potential Threshold Cointegration</field>
      <field key="403" subkey="">1. Ed.</field>
      <field key="410" subkey="">Wien</field>
      <field key="412" subkey="">Institut für Höhere Studien</field>
      <field key="425" subkey="">2002, September</field>
      <field key="433" subkey="">28 pp.</field>
      <field key="451" subkey="">Institut für Höhere Studien; Reihe Ökonomie; 121</field>
      <field key="451" subkey="h">Kunst, Robert M. (Ed.) ; Fisher, Walter (Assoc. Ed.) ; Ritzberger, Klaus (Assoc. Ed.)</field>
      <field key="461" subkey="">Economics Series</field>
      <field key="517" subkey="c">from the Table of Contents: Introduction; Designing the simulation; Simulation results: the maps; Summary and conclusion;</field>
      <field key="App" subkey="e">ndix: Geometric ergodicity of threshold cointegrated models;</field>
      <field key="542" subkey="">1605-7996</field>
      <field key="544" subkey="">IHSES 121</field>
      <field key="700" subkey="">C11</field>
      <field key="700" subkey="">C18</field>
      <field key="700" subkey="">C32</field>
      <field key="720" subkey="">Model selection</field>
      <field key="720" subkey="">Bayes testing</field>
      <field key="720" subkey="">Nonlinear time series models</field>
      <field key="753" subkey="">Abstract: Bivariate time series data often show strong relationships between the two components, while both individual variables</field>
      <field key="can" subkey="">be approximated by random walks in the short run andare obviously bounded in the long run. Three model classes are considered</field>
      <field key="for" subkey="">a time-series model selection problem: stable vector autoregressions, cointegrated models, and globally stable threshold</field>
      <field key="mod" subkey="e">ls. It is demonstrated how simulated decision maps help in classifying observed time series. The maps process the joint</field>
      <field key="evi" subkey="d">ence of two test statistics: a canonical root and an LR--type specification statistic for threshold effects.;</field>
    </SEQUENTIAL>
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