What is Really Good for Long-Term Growth? Lessons from a Binary ClassificationTree (BCT) Approach

Although the economic growth literature has come a long way since the Solow-Swan model of the fifties, there is still considerable debate on the ""real' or ""deep"" determinants of growth. This paper revisits the question of what is really important for strong long-term growth by using a Binary Classification Tree approach, a nonparametric statistical technique that is not commonly used in the growth literature. A key strength of the method is that it recognizes that a combination of conditions can be instrumental in leading to a particular outcome, in this case strong growth. The paper finds