The passing of Act 39/2006, of 14th December, on the Promotion of Personal Autonomy and Care for Dependent Persons (known as the Dependent Care Law) has created the fourth pillar of Welfare State in Spain. In order to achieve its efficient implementation, we need to know who and how many individuals should be attended and how much money is needed for the attention. However, the answers to these two questions given until now suggest that a lot of work is still to be done in order to reach the objectives proposed by the Law.
The passing of the Law 39/2006 has given to Spanish insurance companies the chance of offering products that cover the expenses associated to the risk of dependence. However, due to the lack of reliable statistic information about dependent population, it is extremely difficult to evaluate not only the frequency but also the cost. These two items make the pricing process with a big cloud of uncertainty. This paper proposes a methodology for premium calculation taking into account not only the availability of the data but also the current legal framework in Spain. Together to the theoretical approach, premium calculations for two possible versions are included. Finally, it is introduced a simulation model that pretends to evaluate the impact that a portfolio with these kind of contracts would have on the solvency of an insurance company.
The aging of population is perhaps the most important problem that developed countries must face in the near future. Dependency can be seen as a consequence of the process of gradual aging. In a health context, this contingency is defined as a lack of autonomy in performing basic activities of daily living that requires the care of another person or significant help. In Europe in general and in Spain in particular, this phenomena represents a problem with economic, political, social and demographic implications. The prevalence of dependency in the population, as well as its intensity and evolution over the course of a person’s life are issues of greatest importance that should be addressed. The aim of this work is the estimation of life expectancy free of dependency (LEFD) based on functional trajectories to enhance the regular estimation of health expectancy. Using information from the Spanish survey EDAD 2008, we estimate the number of years spent free of dependency for disabled people according to gender, dependency degree (moderate, severe, major) and the earlier or later onset of dependency compared to a central trend. The main findings are as follows: first, we show evidence that to estimate LEFD ignoring the information provided by the functional trajectories may lead to non-representative LEFD estimates; second, in general, dependency-free life expectancy is higher for women than for men. However, its intensity is higher in women with later onset on dependency; Third, the loss of autonomy is higher (and more abrupt) in men than in women. Finally, the diversity of patterns observed at later onset of dependency tends to a dependency extreme-pattern in both genders.
The interaction between mathematicians, statisticians and econometricians working in actuarial sciences and finance is producing numerous meaningful scientific results. This volume introduces new ideas, in the form of four-page papers, presented at the international conference Mathematical and Statistical Methods for Actuarial Sciences and Finance (MAF), held at Universidad Carlos III de Madrid (Spain), 4th-6th April 2018. The book covers a wide variety of subjects in actuarial science and financial fields, all discussed in the context of the cooperation between the three quantitative approaches. The topics include: actuarial models; analysis of high frequency financial data; behavioural finance; carbon and green finance; credit risk methods and models; dynamic optimization in finance; financial econometrics; forecasting of dynamical actuarial and financial phenomena; fund performance evaluation; insurance portfolio risk analysis; interest rate models; longevity risk; machine learning and soft-computing in finance; management in insurance business; models and methods for financial time series analysis, models for financial derivatives; multivariate techniques for financial markets analysis; optimization in insurance; pricing; probability in actuarial sciences, insurance and finance; real world finance; risk management; solvency analysis; sovereign risk; static and dynamic portfolio selection and management; trading systems. This book is a valuable resource for academics, PhD students, practitioners, professionals and researchers, and is also of interest to other readers with quantitative background knowledge.
In this paper we propose Bayesian specifications of four of the most widespread models used for mortality projection: Lee-Carter, Renshaw-Haberman, Cairns-Blake-Dowd, and its extension including cohort effects. We introduce the Bayesian model averaging in mortality projection in order to obtain an assembled model considering model uncertainty. We work with Spanish mortality data from the Human Mortality Database, and results suggest that applying this technique yields projections with better properties than those obtained with the individual models considered separately.
In this paper, a goodness-of-fit test for normality based on the comparison of the theoretical and empirical distributions is proposed. Critical values are obtained via Monte Carlo for several sample sizes and different significance levels.We study and compare the power of forty selected normality tests for a wide collection of alternative distributions. The new proposal is compared to some traditional test statistics, such as Kolmogorov-Smirnov, Kuiper, Cram´er-von Mises, Anderson-Darling, Pearson Chi-square, Shapiro-Wilk, Shapiro-Francia, Jarque-Bera, SJ, Robust Jarque-Bera, and also to entropy-based test statistics. From the simulation study results it is concluded that the best performance against asymmetric alternatives with support on the whole real line and alternative distributions with support on the positive real line is achieved by the new test. Other findings derived from the simulation study are that SJ and Robust Jarque-Bera tests are the most powerful ones for symmetric alternatives with support on the whole real line, whereas entropy-based tests are preferable for alternatives with support on the unit interval.
In this paper we study a goodness-of-fit test based on the maximum correlation coefficient, in the context of randomly censored data. We construct a new test statistic under general right-censoring and prove its asymptotic properties. Additionally, we study a special case, when the censoring mechanism follows the well-known Koziol-Green model. We present an extensive simulation study on the empirical power of these two versions of the test statistic, showing their advantages over the widely used Pearson-type test. Finally, we apply our test to the head-and-neck cancer data.
In this paper, two new statistics based on comparison of the theoretical and empirical distribution functions are proposed to test exponentiality. Critical values are determined by means of Monte Carlo simulations for various sample sizes and different significance levels. Through an extensive simulation study, 50 selected exponentiality tests are studied for a wide collection of alternative distributions. From the empirical power study, it is concluded that, firstly, one of our proposals is preferable for IFR (increasing failure rate) and UFR (unimodal failure rate) alternatives, whereas the other one is preferable for DFR (decreasing failure rate) and BFR (bathtub failure rate) alternatives and, secondly, the new tests can be considered serious and powerful competitors to other existing proposals, since they have the same (or higher) level of performance than the best tests in the statistical literature.
Disability and dependence (lack of autonomy in performing common everyday actions) affect health status and quality of life; therefore they are significant public health issues. The main purpose of this study is to use classicalmulti-dimensional scaling techniques to design dependence profiles for Spanish children between 3 and 6 years old. The data come from the Survey about Disabilities, Personal Autonomy and Dependence situations, 2008.Two distance (or dissimilarity) functions between individuals are considered: the classical approach using Gower’s similarity coefficient and weighted related metric scaling. Both approaches can cope with different types of information (quantitative, multistate categorical and binary variables). However, the Euclidean configurations that are obtained via weighted related metric scaling present a higher percentage of explained variability and higher stability.
This research tries to assess the dependents and Long Term Care costs for next years in Spain. To do this, it has been taken account data from the Survey on Disabilities, Impairments and Health Status and population forecasts estimated by INE, the legal rules passed between 2006 and 2008, and some former studies about individual costs of long term care. The key point in this study is the concept of cost per point of scale. Once calculated, forecasts till 2050 have been estimated. Finally, the results have been compared with those included in the Long Term Care Act.
Disability and dependency (lack of autonomy in performing common everyday actions) affect health status and quality of life, therefore they are significant public health issues. The main purpose of this study is to establish the existing relationship among different variables (continuous, categorical and binary) referred to children between 3 and 6 years old and their functional dependence in basic activities of daily living. We combine different types of information via weighted related metric scaling to obtain homogeneous profiles for dependent Spanish children. The redundant information between groups of variables is modeled with an interaction parameter that can be optimized according to several criteria. In this paper, the goal is to obtain maximum explained variability in an Euclidean configuration. Data comes from the Survey about Disabilities, Personal Autonomy and Dependence Situations, EDAD 2008, (Spanish National Institute of Statistics, 2008)
The aging of population is perhaps the most important problem that developed countries must face in the near future. In fact, one of the eight tackling societal challenges of the European program Horizon 2020 is concerned with it. Dependency can be seen as a consequence of the process of gradual aging. Therefore, its prevalence on the population, its intensity and evolution over the course of a person's life have relevant economic, political and social implications. From data base EDAD 2008 the authors constructed a pseudo panel that registers personal evolution of the dependency scale according to the Spanish legislation and obtained individual dependency curves. In this work, our aim is to estimate life expectancy free of dependency using categorical data and the functional information contained in these trajectories. © 2014 Springer International Publishing Switzerland. All rights are reserved.
La aprobación y puesta en marcha de la Ley de Dependencia ha supuesto un nuevo campo de actuación para las políticas públicas. De acuerdo a dicha Ley, son las Comunidades Autónomas las responsables de ofrecer los servicios. Por ello parece oportuno plantearse si el impacto será igual en todas ellas. Este trabajo trata de evaluar el número de personas dependientes con derecho a ayudas públicas en cada territorio y el coste asociado a su atención, tanto en el instante actual como hasta 2015, año en el que el sistema público de atención estará plenamente desarrollado