This paper applies quantile regression and non-parametric density estimation techniques to international data on long-run economic growth. The approach reveals that previously identified drivers of growth vary in their impact across the conditional distribution of international growth. Specifically, these factors display disparate effects in conditional low-growth and high-growth contexts. The results suggest that there is a general bias underlying prior research. The incumbent drivers of growth exhibit relatively larger coefficients, in absolute value, on the upper tail of the conditional growth distribution. This set of stylized facts identifies factors that might alter the international distribution of growth. Copyright Blackwell Publishing Ltd and The Victoria University of Manchester, 2003.
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