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...

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...

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...

This paper presents the first global and regional estimates of polarization and bipolarization spanning the period 1960-2020. The study relies on group data to implement a flexible parametric model to obtain the global income distribution and polarization estimates. The study introduces a...

Over the past two decades, research on the impacts of a diverse range of public policies and income inequality has seen rapid growth. Despite the large number of publications to date, there remain important lacunae in our understanding of how policy interventions might help to reduce income...

Monitoring health is key for identifying priorities in public health planning and improving healthcare services. Life expectancy has conventionally been regarded as a valuable indicator to compare the health status of different populations. However, this measure is simply the mean of the...

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...