Penalized exponential series estimation of copula densities with an application to intergenerational dependence of body mass index Academic Article

abstract

• 2014, Springer-Verlag Berlin Heidelberg. We propose a penalized maximum likelihood estimator of copula densities that is based on the multivariate exponential series density estimator. We employ an approximate likelihood cross validation method to select the smoothing parameter. We demonstrate the usefulness of the proposed method via Monte Carlo simulations. We apply this method to estimate copula densities between childrens and parents body mass indices (BMI). Our results suggest that the dependence relationship is generally asymmetric and stronger for females. We also find a higher intergenerational BMI dependence for low income families.

authors

• Wu, Ximing
• Zhang, Yu (Yvette)

published proceedings

• EMPIRICAL ECONOMICS

author list (cited authors)

• Gao, Y., Zhang, Y. Y., & Wu, X.

citation count

• 5

complete list of authors

• Gao, Yichen||Zhang, Yu Yvette||Wu, Ximing

publication date

• February 2015

publisher

• Springer Nature  Publisher

published in

• Empirical Economics  Journal

keywords

• Body Mass Index
• Copula
• Exponential Series Estimator
• Penalized Maximum Likelihood

Digital Object Identifier (DOI)

• 10.1007/s00181-014-0858-y

start page

• 61

end page

• 81

volume

• 48

issue

• 1

URL

• http://dx.doi.org/10.1007/s00181-014-0858-y