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Uncovering the Factors behind Comparative Regional Economic Performance: A Dynamic CGE Approach

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Author Info
James A Giesecke
John R Madden

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Abstract

Recently a new method has emerged for uncovering the factors driving regional disparities in growth performance. The method involves historical analysis with a multiregional computable general equilibrium model. This paper has three main aims. The first is to demonstrate the capacity of the CGE historical technique to decompose the causes of regional divergence into clearly-specified economic factors. The second is to provide a generic miniature model that can be used as a template for adapting any multiregional CGE model to give it the capacity for undertaking historical analysis. The third is to demonstrate that this same miniature model can be used to explain the regional results in terms of the major model mechanisms behind them.

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File URL: http://www.monash.edu.au/policy/ftp/workpapr/g-165.pdf
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Paper provided by Monash University, Centre of Policy Studies/IMPACT Centre in its series Centre of Policy Studies/IMPACT Centre Working Papers with number g-165.

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Date of creation: Dec 2006
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Handle: RePEc:cop:wpaper:g-165

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Related research
Keywords: Computable general equilibrium; Regional growth; Regional divergence; Multi-regional historical analysis;

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Find related papers by JEL classification:
D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
R13 - Urban, Rural, and Regional Economics - - General Regional Economics - - - General Equilibrium and Welfare Economic Analysis of Regional Economies

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  1. Suahasil Nazara & Geoffrey J.D. Hewings, 2004. "Spatial Structure and Taxonomy of Decomposition in Shift-Share Analysis," Growth and Change, Gatton College of Business and Economics, University of Kentucky, vol. 35(4), pages 476-490. [Downloadable!] (restricted)
  2. W. Jill Harrison & J. Mark Horridge & K.R. Pearson, 2000. "Decomposing Simulation Results with Respect to Exogenous Shocks," Computational Economics, Springer, vol. 15(3), pages 227-249, June. [Downloadable!]
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  3. Harrison, W Jill & Pearson, K R, 1996. "Computing Solutions for Large General Equilibrium Models Using GEMPACK," Computational Economics, Springer, vol. 9(2), pages 83-127, May.
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  4. Adams, Philip D. & Dixon, Peter B. & McDonald, Daina & Meagher, G. A. & Parmenter, Brian R., 1994. "Forecasts for the Australian economy using the MONASH model," International Journal of Forecasting, Elsevier, vol. 10(4), pages 557-571, December. [Downloadable!] (restricted)
  5. Maria Abreu Henri L. F. de Groot & Raymond J. G. M. Florax, 2005. "A Meta-Analysis of β-Convergence: the Legendary 2%," Journal of Economic Surveys, Blackwell Publishing, vol. 19(3), pages 389-420, 07. [Downloadable!] (restricted)
  6. James Giesecke, 2002. "Explaining regional economic performance: An historical application of a dynamic multi-regional CGE model," Papers in Regional Science, Springer, vol. 81(2), pages 247-278. [Downloadable!] (restricted)
  7. Dixon, Peter B. & Parmenter, B. R. & Powell, Alan A., 1984. "The role of miniatures in computable general equilibrium modelling : Experience from ORANI," Economic Modelling, Elsevier, vol. 1(4), pages 421-428, October. [Downloadable!] (restricted)
  8. Johan Lundberg, 2006. "Using spatial econometrics to analyse local growth in Sweden," Regional Studies, Taylor and Francis Journals, vol. 40(3), pages 303-316, May. [Downloadable!] (restricted)
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