A New Semiparametric Approach to Analysing Conditional Income Distributions
نویسندگان
چکیده
In this paper we explore the application of structured additive distributional regression for the analysis of conditional income distributions in Germany following the reunification. Using a bootstrapped Kolmogorov-Smirnov test we find that conditional personal income distributions can generally be modelled using the three parameter Dagum distribution. Additionally our results hint at an even more pronounced effect of skill-biased technological change than can be observed by standard mean regression. JEL-Classification: C13, C21, D31, J31
منابع مشابه
A new semiparametric approach to analysing
In this paper we explore the application of Generalised Additive Models of Location, Scale and Shape for the analysis of conditional income distributions in Germany following the reunification. We find that conditional income distributions can generally be modelled using the three parameter Dagum distribution and our results hint at an even more pronounced effect of skill-biased technological c...
متن کاملModeling inequality and spread in multiple regression
We consider concepts and models for measuring inequality in the distribution of resources with a focus on how inequality varies as a function of covariates. Lorenz introduced a device for measuring inequality in the distribution of income that indicates how much the incomes below the u quantile fall short of the egalitarian situation where everyone has the same income. Gini introduced a summary...
متن کاملA Direct Approach to Inference in Nonparametric and Semiparametric Quantile Regression Models
This paper makes two main contributions. First, we construct “density-free” confidence intervals and confidence bands for conditional quantiles in nonparametric and semiparametric quantile regression models. They are based on pairs of symmetrized k-NN quantile estimators at two appropriately chosen quantile levels. In contrast to Wald-type confidence intervals or bands based on the asymptotic d...
متن کاملBayesian semiparametric copula estimation with application to psychiatric genetics.
This paper proposes a semiparametric methodology for modeling multivariate and conditional distributions. We first build a multivariate distribution whose dependence structure is induced by a Gaussian copula and whose marginal distributions are estimated nonparametrically via mixtures of B-spline densities. The conditional distribution of a given variable is obtained in closed form from this mu...
متن کاملNonparametric conditional hazard rate estimation: A local linear approach
Parametric and semiparametric methods often fail to capture the right shape of the conditional hazard rate in survival analysis. In this paper we propose a new and intuitive nonparametric estimator for the conditional hazard rate, based on local linear estimation techniques. This estimator can deal with both censored and uncensored data. We show that the local linear hazard rate estimator is co...
متن کامل