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Grouped data in the form of income shares have conventionally been used to estimate income inequality due to the lack of individual records. We provide guidance on the choice between parametric and nonparametric methods and its estimation, for which we develop the GB2group R package. We present...
Persistent link: https://www.econbiz.de/10012671233
This paper is divided in two parts. The first one is dedicated to analyse the inequality of the income distribution in Spain during the convergence process to the European Monetary Union. To carry out this task, we propose two robust models based on the quantile functions. Specifically, we use...
Persistent link: https://www.econbiz.de/10011314704
Power laws appear widely in many branches of economics, geography, demography and other social sciences. In particular, the upper tail of city size distributions appear to follow power laws, as many researchers have shown for different countries and different periods of times. A crucial point in...
Persistent link: https://www.econbiz.de/10011332428
It is known that the classical ruin function under exponential claim-size distribution depends on two parameters, which are referred to as the mean claim size and the relative security loading. These parameters are assumed to be unknown and random, thus, a loss function that measures the loss...
Persistent link: https://www.econbiz.de/10013200486
This note revisits the ideas of the so-called semiparametric methods that we consider to be very useful when applying machine learning in insurance. To this aim, we first recall the main essence of semiparametrics like the mixing of global and local estimation and the combining of explicit...
Persistent link: https://www.econbiz.de/10013200567
There is a vast literature on the selection of an appropriate index of income inequality and on what desirable properties such a measure (or index) should contain. The Gini index is, of course, the most popular. There is a concurrent literature on the use of hypothetical statistical...
Persistent link: https://www.econbiz.de/10011819495