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      <record key="001" att1="001" value="162469" att2="162469">001   162469</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-188.pdf</field>
      <field key="079" subkey="z">LeSage, James P. - et al., Incorporating Transportation Network Structure in Spatial Econometric Models of Commodity Flows (pdf)</field>
      <field key="079" subkey="y">http://ideas.repec.org/p/ihs/ihsesp/188.html</field>
      <field key="079" subkey="z">Institute for Advanced Studies. Economics Series; 188 (RePEc)</field>
      <field key="100" subkey="">LeSage, James P.</field>
      <field key="103" subkey="">Department of Economics, University of Toledo</field>
      <field key="104" subkey="a">Polasek, Wolfgang</field>
      <field key="107" subkey="">Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria</field>
      <field key="331" subkey="">Incorporating Transportation Network Structure in Spatial Econometric Models of Commodity Flows</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="">2006, May</field>
      <field key="433" subkey="">34 pp.</field>
      <field key="451" subkey="">Institut für Höhere Studien; Reihe Ökonomie; 188</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; The spatial econometric flow model; An empirical illustration; Conclusions; References;</field>
      <field key="542" subkey="">1605-7996</field>
      <field key="544" subkey="">IHSES 188</field>
      <field key="700" subkey="">R1</field>
      <field key="700" subkey="">R41</field>
      <field key="700" subkey="">L92</field>
      <field key="700" subkey="">C21</field>
      <field key="720" subkey="">Commodity flows</field>
      <field key="720" subkey="">Spatial autoregression</field>
      <field key="720" subkey="">Bayesian</field>
      <field key="720" subkey="">Maximum likelihood</field>
      <field key="720" subkey="">Spatial connectivity of origin-destination flows</field>
      <field key="753" subkey="">Abstract: We introduce a regression-based gravity model for commodity flows between 35 regions in Austria. We incorporate</field>
      <field key="inf" subkey="o">rmation regarding the highway network into the spatial connectivity structure of the spatial autoregressive econometric model</field>
      <field key=". W" subkey="e">find that our approach produces improved model fit and higher likelihood values. The model accounts for spatial dependence</field>
      <field key="in" subkey="t">he origin-destination flows by introducing a spatial connectivity matrix that allows for three types of spatial dependence in</field>
      <field key="the" subkey="">origins to destinations flows. We modify this origin-destination connectivity structure that was introduced by LeSage and</field>
      <field key="Pac" subkey="e">(2005) to include information regarding the presence or absence of a major highway/train corridor that passesthrough the</field>
      <field key="reg" subkey="i">ons. Empirical estimates indicate that the strongest spatial autoregressive effects arise when both origin and destination</field>
      <field key="reg" subkey="i">ons have neighboring regions located on the highway network. Our approach provides a formal spatial econometric methodology</field>
      <field key="tha" subkey="t">can easily incorporate network connectivity information in spatial autoregressive models.;</field>
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