Tilburg University

About: Tilburg University is a education organization based out in Tilburg, Noord-Brabant, Netherlands. It is known for research contribution in the topics: Population & Context (language use). The organization has 5550 authors who have published 22330 publications receiving 791335 citations.

The Trade-off Between Environmental Care and Long-term Growth — Pollution in Three Prototype Growth Models

Abstract: The effects of increased environmental care on optimal technology choice and long-term growth are studied for an economy in which pollution is a side-product of physical capital used in production. First, it is shown that in case of a standard neoclassical production structure, the result is a less capital-intensive production process whereas the long-run growth rate is not affected. Next, we introduce assumptions of the endogenous growth literature. When there are constant returns to physical capital, an increase in abatement activities crowds out investment and lowers the endogenous growth rate. When human capital accumulation is the engine of growth, physical capital intensity declines and the endogenous optimal growth rate is unaffected by increased environmental care or is even higher, depending on whether or not pollution influences agents' ability to learn.

Influence Functions of the Spearman and Kendall Correlation Measures

Abstract: Nonparametric correlation estimators as the Kendall and Spearman correlation are widely used in the applied sciences. They are often said to be robust, in the sense of being resistant to outlying observations. In this paper we formally study their robustness by means of their influence functions and gross-error sensitivities. Since robustness of an estimator often comes at the price of an increased variance, we also compute statistical efficiencies at the normal model. We conclude that both the Spearman and Kendall correlation estimators combine a bounded and smooth influence function with a high efficiency. In a simulation experiment we compare these nonparametric estimators with correlations based on a robust covariance matrix estimator.