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Recent research on growth empirics has focused on resolving model and variable uncertainty. The conventional approach has been to assume a linear growth process and then to proceed with investigating the relevant variables that determine cross‐country growth. This article questions the linearity assumption underlying the vast majority of such research and uses recently developed non‐parametric techniques to handle non‐linearities as well as select relevant variables. We show that inclusion of non‐linearities is necessary for determining the empirically relevant variables and uncovering key mechanisms of the growth process.