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In this article we use Bayesian classification and finite mixture models to extract information from Levine's (2002) cross-country database and reconsider the relationship between financial structure and long-run economic growth. Our methods, based on statistical similarities and multi-dimensional structures, allow for parameter heterogeneity across the countries in Levine's database and yield substantially different findings than Levine's regarding the relationship between financial structure and economic performance.
