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.
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