Modes, weighted modes, and calibrated modes: evidence of clustering using modality tests

We apply recent results from the statistics literature to test for multimodality of worldwide distributions of several (unweighted and population-weighted) measures of labor productivity. Specifically, we employ Silverman (Bump) and Dip modality tests, calibrated to correct for their incorrect asymptotic levels. We show that test results are sensitive to the test statistic employed and to population weighting. But regardless of the statistical criterion used, multimodality is present throughout, or emerges during, our sample period (1960-2000). We also examine (a) movements of economies between modal clusters and (b) relationships between certain key development factors and multimodality of the productivity distribution.