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A test for multimodality of regression derivatives with application to nonparametric growth regressions

Listed author(s):
  • Daniel J. Henderson

    (Department of Economics, State University of New York at Binghamton, Binghamton, NY, USA)

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 β-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 β-convergence show that the density is predominantly negative and there is mixed evidence that the distribution is unimodal. Copyright © 2009 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/jae.1099
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File URL: http://qed.econ.queensu.ca:80/jae/2010-v25.3/
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 25 (2010)
Issue (Month): 3 ()
Pages: 458-480

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Handle: RePEc:jae:japmet:v:25:y:2010:i:3:p:458-480
DOI: 10.1002/jae.1099
Contact details of provider: Web page: http://www.interscience.wiley.com/jpages/0883-7252/

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