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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Integrating the Garin-Lowry model with a Travel Demand Model</title>
      <link>https://trid.trb.org/View/1572636</link>
      <description><![CDATA[The earliest land use model is known to be the Garin-Lowry model (GL) which was introduced nearly fifty years ago. Since then, land use modelling has significantly improved to encompass dynamics of land use evolution, decision makers’ behaviour and the inherent stochasticity in people’s behaviour. Even though, the basic GL is a cross-sectional static model, the convenient matrix formulation of GL persuades practitioners to utilize GL despite its shortcomings. This study aims at revisiting GL to rectify its shortcomings while maintaining its simple structure. The objectives of this study include improving the transportation component of GL, adding behavioural models in GL’s activity distribution and lastly introduce an equilibrium framework between travel and activity location choices using the basic GL model as its core. With the preliminary results of the Greater Sydney region, the study shows that the proposed framework achieves a better match to the existing conditions of the region than the results of a basic GL model.]]></description>
      <pubDate>Fri, 01 Mar 2019 15:51:06 GMT</pubDate>
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      <title>Simulating deep CO₂ emission reduction in transport in a general equilibrium framework: The GEM-E3T model</title>
      <link>https://trid.trb.org/View/1523349</link>
      <description><![CDATA[Transport sector restructuring to achieve deep greenhouse gas (GHG) emission cuts has attracted much attention because transportation is important for the economy and inflexible in greenhouse gas emission reduction. The aim of this paper is to simulate transition towards low carbon transportation in the European Union until 2050 and to assess the ensuing macroeconomic and sectorial impacts. Transport restructuring is dynamically simulated using a new transport-oriented version of the computable general equilibrium model GEM-E3 which is linked with the PRIMES-TREMOVE energy and transport sectors model. The analysis draws from comparing a reference scenario projection for the EU member-states up to 2050 to alternative transport policy scenarios and sensitivities which involve deep cutting of CO₂ emissions. The simulations show that transport restructuring affects the economy through multiple channels, including investment in infrastructure, the purchasing and manufacturing of new technology vehicles, the production of alternative fuels, such as biofuels and electricity. The analysis identifies positive impacts of industrial activity and other sectors stemming from these activities. However, the implied costs of freight and passenger transportation are of crucial importance for the net impact on gross domestic product (GDP) and income. Should the transport sector transformation imply high unit costs of transport services, crowding out effects in the economy can offset the benefits. This implies that the technology and productivity progress assumptions can be decisive for the sign of GDP impacts. A robust conclusion is that the transport sector decarbonisation, is likely to have only small negative impacts on the EU GDP compared to business as usual.]]></description>
      <pubDate>Tue, 24 Jul 2018 10:05:52 GMT</pubDate>
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      <title>FINANCING ROAD INFRASTRUCTURE BY SAVINGS IN CONGESTION COSTS: A CGE ANALYSIS</title>
      <link>https://trid.trb.org/View/645056</link>
      <description><![CDATA[The aim of this paper is to model the aspects of bottlenecks in road infrastructure, of congestion costs, and of the effect of investment in infrastructure in a computable general equilibrium framework. A long-run 'business-as-usual' simulation will show how congestion and its costs develop over time. The increasing costs of congestion indicate a necessity to act. The authors therefore raise the fuel tax to partly finance infrastructure investment, and then compare the cost of the addition in infrastructure with the savings in congestion costs in order to see whether this policy measure is self-financing.]]></description>
      <pubDate>Fri, 09 May 2003 00:00:00 GMT</pubDate>
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