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Development of a Large-scale Single US Region CGE Model using IMPLAN Data: A Los Angeles County Example with a Productivity Shock Application


  • James Andrew Giesecke


This paper details the construction of a large-scale computable general equilibrium (CGE) model for a single US region. The model contains a detailed treatment of margins and taxes, features not typically given prominence in US regional CGE models. The starting point for the core of the CGE model's data base is information from IMPLAN, producers of regional I/O data at the US county and state levels. IMPLAN's I/O tables, however, are in producer prices with aggregated treatment of margins and taxes. The methods for reconfiguring the I/O data into basic price flows with direct allocation of imports and a disaggregated treatment of taxes and margins are described. The method is applied to construction of a Los Angeles County model. An illustrative simulation of a productivity improvement in the Los Angeles County economy is then discussed. Développement d'un modèle GCE (modèle d’équilibre général) à grande échelle pour une région unique des États-Unis, à l'aide de données IMPLAN: un exemple dans le comté de Los Angeles avec une application à choc de productivité R ésumé La présente communication illustre en détail la construction d'un modèle informatisé d’équilibre général (GCE) pour une région unique des États-Unis. Ce modèle contient un traitement détaillé de marges et taxes, des aspects auxquels on n'accorde généralement pas une importance prédominante dans les modèles GCE régionaux aux États-Unis. Le point de départ pour la partie essentielle de la base de données du modèle CGE se situe au niveau des informations provenant d'IMPLAN, des producteurs de données d'Entrée/Sortie régionaux à l’échelon du comté et de l’état, aux États-Unis. Toutefois, les tableaux d'entrée/sortie d'IMPLAN portent sur des prix de producteur avec traitement agrégé des marges et des taxes. Les méthodes de reconfiguration des données d'E/S dans des flux de prix de base, avec affectation directe des importations, et un traitement désagrégé de taxes et marges, sont décrits. La méthode est appliquée à la construction d'un modèle du comté de Los Angeles. Une simulation illustrative d'un renforcement de la productivité est ensuite discutée. Desarrollo de un modelo CGE a gran escala para una región estadounidense única utilizando datos IMPLAN: un ejemplo de Los Angeles County con una aplicación de choques de productividad E xtracto Este trabajo detalla la construcción de un equilibro general computable (CGE) a gran escala para una sola región estadounidense. El modelo contiene un tratamiento detallado de márgenes e impuestos, características que típicamente no reciben prominencia en los modelos CGE regionales estadounidenses. El punto inicial para el núcleo de la base de datos del modelo CGE es información procedente de IMPLAN, productores de datos I/O (input--output) regionales a los niveles de condado y estado estadounidenses. No obstante, las tablas I/O de IMPLAN aparecen en precios de productores con tratamiento agregado de márgenes e impuestos. Se describen los métodos para reconfigurar los datos I/O en flujos de precios básicos con asignación directa de importaciones y un tratamiento desagregado de impuestos y márgenes. El método se aplica a la construcción de un modelo de Los Angeles County. Seguidamente, se discute una simulación ilustrativa de la mejora de productividad en la economía de Los Angeles County.

Suggested Citation

  • James Andrew Giesecke, 2011. "Development of a Large-scale Single US Region CGE Model using IMPLAN Data: A Los Angeles County Example with a Productivity Shock Application," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(3), pages 331-350, April.
  • Handle: RePEc:taf:specan:v:6:y:2011:i:3:p:331-350 DOI: 10.1080/17421772.2011.586722

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    References listed on IDEAS

    1. Kym Anderson & James Giesecke & Ernesto Valenzuela, 2010. "How would global trade liberalization affect rural and regional incomes in Australia?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(4), pages 389-406, October.
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    Cited by:

    1. María Teresa Álvarez-Martínez & Michael L. Lahr, 2016. "Gaming, States, and Tax Revenues—the Tortoise or the Hare: A CGE Comparative Assessment of Casino Resorts and Games-Only Casinos," Growth and Change, Wiley Blackwell, vol. 47(2), pages 236-258, June.
    2. Hussain, Anwar & Munn, Ian A. & Holland, David W. & Armstrong, James & Spurlock, Stanley R., 2012. "Economic Impact of Wildlife-Associated Recreation Expenditures in the Southeast United States: A General Equilibrium Analysis," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 44(01), February.
    3. James A. Giesecke & John R. Madden, 2013. "Evidence-based regional economic policy analysis: the role of CGE modelling," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 6(2), pages 285-301.
    4. Nicholas Kilimani & Jan van Heerden & Heinrich Bohlmann & Louise Roos, 2016. "Counting the cost of drought induced productivity losses in an agro-based economy: The case of Uganda," Working Papers 616, Economic Research Southern Africa.
    5. J.A. Giesecke & W.J. Burns & A. Barrett & E. Bayrak & A. Rose & M. Suher, 2010. "Assessment of the Regional Economic Impacts of Catastrophic Events: CGE analysis of resource loss and behavioral effects of a RDD attack scenario," Centre of Policy Studies/IMPACT Centre Working Papers g-194, Victoria University, Centre of Policy Studies/IMPACT Centre.
    6. Plassmann, Florenz & Feltenstein, Andrew, 2016. "How large do multi-region models need to be?," Journal of Policy Modeling, Elsevier, vol. 38(1), pages 138-155.
    7. Giesecke, James A. & Madden, John R., 2013. "Regional Computable General Equilibrium Modeling," Handbook of Computable General Equilibrium Modeling, Elsevier.
    8. Gesualdo, Maria & Rosignoli, Stefano, 2013. "Building a computable general equilibium model (cge) on a regional sam: the case of Tuscany," MPRA Paper 81412, University Library of Munich, Germany.
    9. Esmedekh Lkhanaajav, 2016. "CoPS-style CGE modelling and analysis," Centre of Policy Studies/IMPACT Centre Working Papers g-264, Victoria University, Centre of Policy Studies/IMPACT Centre.
    10. Michael Lahr & Maria Alvarez, 2013. "Tortoise and the Hare Revisited? A CGE Analysis of Gaming and State Tax Revenues:," ERSA conference papers ersa13p191, European Regional Science Association.
    11. Peter B. Dixon & Michael Jerie & Maureen T. Rimmer & Glyn Wittwer, 2017. "Using a regional CGE model for rapid assessments of the economic implications of terrorism events: creating GRAD-ECAT (Generalized, Regional And Dynamic Economic Consequence Analysis Tool)," Centre of Policy Studies/IMPACT Centre Working Papers g-280, Victoria University, Centre of Policy Studies/IMPACT Centre.

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    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • R13 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General Equilibrium and Welfare Economic Analysis of Regional Economies
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods


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