You're currently viewing an old version of this dataset. To see the current version, click here.

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

This dataset has no data

Suggested Citation

Henderson, Daniel J. (2010): A test for multimodality of regression derivatives with application to nonparametric growth regressions (replication data). Version: 1. Journal of Applied Econometrics. Dataset. https://journaldata.zbw.eu/dataset/a-test-for-multimodality-of-regression-derivatives-with-application-to-nonparametric-growth-regress?activity_id=91eed127-e735-46fe-ba9d-62ec20647e27