Search results for "Econometric"
showing 10 items of 3780 documents
Dans quelle mesure les préférences individuelles contraignent-elles le développement du marché de l'assurance dépendance ?
2015
Dans un contexte de vieillissement de la population, différents scenarii sont envisagés pour réformer l’organisation et le financement de la prise en charge des personnes âgées dépendantes. La place de la prévoyance individuelle dans le financement de la dépendance est à ce titre largement débattue. À l’heure actuelle, malgré des restes à charge potentiellement conséquents, peu d’individus disposent d’une couverture assurantielle. Cet article vise à enrichir la littérature existante en évaluant dans quelle mesure les préférences observées dans la population limitent cette couverture. Nous mobilisons pour cela l’enquête Patrimoine et préférences vis-à-vis du temps et du risque (Pater) de 201…
Assessing implicit hypotheses in life table construction
2016
AbstractMortality figures are of capital importance for policy-making and public planning, as in forecasting financial provisions in public pension systems. General population life tables are constructed from aggregated statistics, an issue that usually entails adopting some (implicit) assumptions in their construction, such as the hypothesis of closed demographic system or the hypotheses of uniform distributions of death counts (and migration events) by age and calendar year. As microdata have become more abundant and reliable, these hypotheses could be assessed and more assumption-free estimators employed. Using a real database from Spain, we show that the above hypotheses are not appropr…
The Age Structure of Human Capital and Economic Growth
2018
This paper shows that the age structure of human capital is a relevant characteristic to take into account when analysing the role of human capital in economic growth. The effect of an increase in the education of the population aged 40–49 years is found to be an order of magnitude larger than an increase in the education attained by any other age cohort. The results are unlikely to be driven by the age structure of the population, as we find that the effects on growth of the age structure of education and the age structure of population are distinct. The findings are robust across specifications and remain unchanged when we control for long‐delayed effects in human capital or for the exper…
Ruin probabilities in the presence of heavy tails and interest rates
1997
Abstract We study the infinite time ruin probability for the classical Cramer-Lundberg model, where the company also receives interest on its reserve. We consider the large claims case, where the claim size distribution F has a regularly varying tail. Hence our results apply for instance to Pareto, loggamma, certain Benktander and stable claim size distributions. We prove that for a positive force of interest δ the ruin probability ψδ (u) ∼ κδ (1 - F(u)) as the initial risk reserve u→∞. This is quantitatively different from the non-interest model, where ψ(u) ∼ κ (1 – F(y)) dy.
Local Spatial Log-Gaussian Cox Processes for seismic data
2022
AbstractIn this paper, we propose the use of advanced and flexible statistical models to describe the spatial displacement of earthquake data. The paper aims to account for the external geological information in the description of complex seismic point processes, through the estimation of models with space varying parameters. A local version of the Log-Gaussian Cox processes (LGCP) is introduced and applied for the first time, exploiting the inferential tools in Baddeley (Spat Stat 22:261–295, 2017), estimating the model by the local Palm likelihood. We provide methods and approaches accounting for the interaction among points, typically described by LGCP models through the estimation of th…
Bayesian joint modeling for assessing the progression of chronic kidney disease in children.
2016
Joint models are rich and flexible models for analyzing longitudinal data with nonignorable missing data mechanisms. This article proposes a Bayesian random-effects joint model to assess the evolution of a longitudinal process in terms of a linear mixed-effects model that accounts for heterogeneity between the subjects, serial correlation, and measurement error. Dropout is modeled in terms of a survival model with competing risks and left truncation. The model is applied to data coming from ReVaPIR, a project involving children with chronic kidney disease whose evolution is mainly assessed through longitudinal measurements of glomerular filtration rate.
Bayesian hierarchical Poisson models with a hidden Markov structure for the detection of influenza epidemic outbreaks
2015
Considerable effort has been devoted to the development of statistical algorithms for the automated monitoring of influenza surveillance data. In this article, we introduce a framework of models for the early detection of the onset of an influenza epidemic which is applicable to different kinds of surveillance data. In particular, the process of the observed cases is modelled via a Bayesian Hierarchical Poisson model in which the intensity parameter is a function of the incidence rate. The key point is to consider this incidence rate as a normal distribution in which both parameters (mean and variance) are modelled differently, depending on whether the system is in an epidemic or non-epide…
Bayesian Markov switching models for the early detection of influenza epidemics
2008
The early detection of outbreaks of diseases is one of the most challenging objectives of epidemiological surveillance systems. In this paper, a Markov switching model is introduced to determine the epidemic and non-epidemic periods from influenza surveillance data: the process of differenced incidence rates is modelled either with a first-order autoregressive process or with a Gaussian white-noise process depending on whether the system is in an epidemic or in a non-epidemic phase. The transition between phases of the disease is modelled as a Markovian process. Bayesian inference is carried out on the former model to detect influenza epidemics at the very moment of their onset. Moreover, t…
Bayesian joint ordinal and survival modeling for breast cancer risk assessment
2016
We propose a joint model to analyze the structure and intensity of the association between longitudinal measurements of an ordinal marker and time to a relevant event. The longitudinal process is defined in terms of a proportional-odds cumulative logit model. Time-to-event is modeled through a left-truncated proportionalhazards model, which incorporates information of the longitudinal marker as well as baseline covariates. Both longitudinal and survival processes are connected by means of a common vector of random effects. General inferences are discussed under the Bayesian approach and include the posterior distribution of the probabilities associated to each longitudinal category and the …
An autoregressive approach to spatio-temporal disease mapping
2007
Disease mapping has been a very active research field during recent years. Nevertheless, time trends in risks have been ignored in most of these studies, yet they can provide information with a very high epidemiological value. Lately, several spatio-temporal models have been proposed, either based on a parametric description of time trends, on independent risk estimates for every period, or on the definition of the joint covariance matrix for all the periods as a Kronecker product of matrices. The following paper offers an autoregressive approach to spatio-temporal disease mapping by fusing ideas from autoregressive time series in order to link information in time and by spatial modelling t…