Empirical studies provide evidence that economic freedom, as measured by the Economic Freedom of the World Index, is related to economic growth. None the less, identifying which aspects of economic freedom are more conducive to growth has proven difficult, due to multicollinearity among the index areas. A possible explanation is that certain countries score high in all areas, whereas others tend do bad in all of them, simply because the former are more freedom-friendly than the latter. However, it is also true that each country presents a combination of freedoms, and restrictions to freedom, at the level of the individual indicators that make up each area. If some regularity exists with respect to these combinations, empirical detection of the most popular policy combinations would alleviate the collinearity problem, when assessing growth effects. Our article explores this possibility by means of cluster analysis, which we conduct at the individual indicator level. We show that multicollinearity can indeed be reduced in this way and identify policy packages that seem to be more conducive to economic growth than others. Results further indicate that certain policy packages may have only a short-term effect on growth, whereas others seem to have an enduring one.