Daniel J. Henderson

a test for multimodality of regression derivatives with application to nonparametric growth regressions (replication data)

This paper presents a method to test for multimodality of an estimated kernel density of derivative estimates from a nonparametric regression. The test is included in a study of nonparametric growth regressions. The results show that in the estimation of unconditional ?-convergence the distribution of the partial effects is multimodal, with one mode in the negative region (primarily OECD economies) and possibly two modes in the positive region (primarily non-OECD economies) of the estimates. The results for conditional ?-convergence show that the density is predominantly negative and there is mixed evidence that the distribution is unimodal.

Data and Resources

Suggested Citation

Henderson, Daniel J. (2009): A test for multimodality of regression derivatives with application to nonparametric growth regressions (replication data). Version: 1. Journal of Applied Econometrics. Dataset. https://jda-test.zbw.eu/dataset/a-test-for-multimodality-of-regression-derivatives-with-application-to-nonparametric-growth-regress