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A Top-down Framework for Regional Historical Analysis


  • James Giesecke


Abstract Bottom-up regional computable general equilibrium (CGE) models have clear theoretical advantages over their top-down counterparts. However bottom-up models are data intensive. Hence they face practical difficulties in applications requiring high levels of regional and sectoral disaggregation, such as explaining regional economic outcomes, and regional forecasting and policy analysis. This paper develops a top-down framework for explaining recent economic history for many regions. This requires estimation of variables describing regional structural change. These variables have a further use in generating plausible regional forecasts. Such forecasts are a prerequisite for convincing regional policy analysis.

Suggested Citation

  • James Giesecke, 2008. "A Top-down Framework for Regional Historical Analysis," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(1), pages 45-87.
  • Handle: RePEc:taf:specan:v:3:y:2008:i:1:p:45-87 DOI: 10.1080/17421770701774930

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    References listed on IDEAS

    1. Peter B. Dixon & Maureen T. Rimmer & Marinos E. Tsigas, 2007. "Regionalising results from a detailed CGE model: Macro, industry and state effects in the U.S. of removing major tariffs and quotas," Papers in Regional Science, Wiley Blackwell, vol. 86(1), pages 31-55, March.
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    5. James A Giesecke & John R Madden, 2006. "Uncovering the Factors behind Comparative Regional Economic Performance: A Dynamic CGE Approach," Centre of Policy Studies/IMPACT Centre Working Papers g-165, Victoria University, Centre of Policy Studies/IMPACT Centre.
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    8. Madden, J R & Challen, D W & Hagger, A J, 1983. "The Grants Commission's Relativities Proposals: Effects on the State Economies," Australian Economic Papers, Wiley Blackwell, vol. 22(41), pages 302-321, December.
    9. Naqvi, Farzana & Peter, Matthew W, 1996. "A Multiregional, Multisectoral Model of the Australian Economy with an Illustrative Application," Australian Economic Papers, Wiley Blackwell, vol. 35(66), pages 94-113, June.
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    Cited by:

    1. 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.
    2. Glyn Wittwer & Mark Horridge, 2010. "Bringing Regional Detail to a CGE Model using Census Data," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(2), pages 229-255.
    3. Giesecke, James A. & Madden, John R., 2013. "Regional Computable General Equilibrium Modeling," Handbook of Computable General Equilibrium Modeling, Elsevier.
    4. Naranpanawa, Athula & Arora, Rashmi, 2014. "Does Trade Liberalization Promote Regional Disparities? Evidence from a Multiregional CGE Model of India," World Development, Elsevier, vol. 64(C), pages 339-349.

    More about this item


    Regional general equilibrium; regional forecasting; top-down model; D58; R11; R13;

    JEL classification:

    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R13 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General Equilibrium and Welfare Economic Analysis of Regional Economies


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