Stochastic Modeling Of Mortality Rate In Nigeria, Such industries will, in particular, be concerned with the quantification of risk attached, say longevity risk, to insurance products that may receive severe impacts from the fall of mortality rate. Abstract This article proposes an alternative framework for modelling the stochastic dynamics of mortality rates. Data were generated from binomial distribution using Monte-carlo simulations; the mortality rate for age 0 to 100years and 3-year points to capture the limited data condition and the model The study therefore explained the mortality improvements for males’ aged 40-65 using Nigeria available data using two stochastic mortality models- Lee Carter Model (M1) and Renshaw-Haberman model (M2). The dataset is divided into a training period (1960–1999) and a validation period (2000–2024), enabling a ABSTRACT: The study examines the strength of two stochastic models: the Lee Carter Model and Functional Data Time Series Analysis in modelling Nigeria Female Mortality. 3 and 4. The model is easy to calibrate using the maximum likelihood method. Keywords: Mortality, Stochastic, Modelling 1. 4 review the stochastic mortality models that account for jumps in the dynamics of mortality rates, developed either in discrete-time or in continuous-time set-ups. More accurate mortality models with improved mortality rate projections can provide a solution to this problem and can allow insurance companies and governments to redesign their financial products, strategies and policies. The study therefore explained the mortality improvements for males’ aged 40-65 using Nigeria available data using two stochastic mortality models- Lee Carter Model (M1) and For pension schemes in particular, the combination of low interest rates and guaranteed pension increases have led to a much greater focus on future mortality rates. The reductions in mortality rates experienced during the last decades and the resulting increases in life expectancy show that longevity risk, arising from unexpected changes in mortality, cannot be ignored. Abstract Mortality and mortality rate have become the major issues in insurance industries, for instance, life insurance and pension fund. Jul 11, 2023 · All over the world, people with sickle cell disease (an inherited condition) have premature deaths and preventable severe chronic complications, which considerably affect their quality of life, career progression, and financial status. Abstract The reductions in mortality rates experienced during the last decades and the resulting increases in life expectancy show that longevity risk, arising from unexpected changes in mortality, cannot be ignored. Nov 15, 2023 · The most important aims of this study are to fit and compare stochastic differential equation models for mortality (the geometric Brownian motion and the stochastic Gompertz model), conducting separate analyses for each age group and sex, in order to generate forecasts of the central mortality rates in France up until the year 2030. Dec 2, 2016 · A fairly recent stream of actuarial literature has dealt with the phenomenon of stochastic mortality by modelling the instantaneous mortality intensity as a stochastic process. In the work, a non- stationary time series is first converted to a stationary series by obtaining the initial difference of the time series data The aim of this paper is to extend stochastic mortality model to capture mortality situation in two populations with application to limited data situation. [1] The financial markets use stochastic models to represent the seemingly random behaviour of various financial assets, including the random behavior of the price of one currency compared to that of another (such as the price of US Dollar compared to that of the Euro), and also to represent random behaviour of interest rates. The Singular Value Decomposition (SVD Abstract y show that longevity risk, arising from unexpected changes in mortality, cannot be ignored. 4. Oct 1, 2021 · In this paper, we model the mortality rate by using an Autoregressive (AR) model with a conditional heteroscedasticity effect. As an answer, the demographic and the actuarial literature have been introduced and compared to several stochastic mortality models, although few studies have thoroughly tested the uncertainty concerning mortality projections. Jan 12, 2017 · The setting of assumptions for future mortality and longevity requires a new approach that recognizes and quantifies the risk of results varying from the best estimate mortality and mortality improvement. The fitting methodology was applied to the model using the Poisson model; the calibration was done using Life metrics R-code software. Apr 28, 2009 · PDF | This study sets out a framework to evaluate the goodness of fit of stochastic mortality models and applies it to six different models estimated | Find, read and cite all the research you Sep 30, 2021 · Mortality and mortality rate have become the major issues in insurance industries, for instance, life insurance and pension fund. 3) ln (m x, t) = a x + b x κ t where a x and b x are age effects and κ t is a random period effect. The model also shows, for the dataset, that there have been approximately linear improvements over time in mortality rates at all ages. Jun 13, 2025 · Stochastic mortality models are used in life insurance and pension plans to estimate mortality rates and life expectancy, calculate insurance premiums and reserves, assess the risk of longevity and mortality, and develop hedging strategies to manage mortality risk. A time series plot of the infant mortality rate (IMR) showing trends and seasonality has been considered. Historically, actuarial science used deterministic models in the construction of tables and premiums. Infant mortality rates are generated by either applying a statistical model or transforming under-five mortality rates based on model life tables. The study therefore explained the mortality improvements for males’ aged 40-65 using Nigeria available data using two stochastic mortality models- Lee Carter Model (M1) and Renshaw Sep 29, 2022 · Consequently, modelling population dynamics and projecting future longevity scenarios are vital tasks for policymakers. Stochastic projections of future mortality rates help stratify and assign probabilities to the resulting scenarios. The data used for the analysis were obtained from Nigeria Bureau of Statistics from 1998-2024. Unlike previous studies that validate mortality models using projected values, this analysis relies exclusively on observed data. This effect is accommodated by a stochastic model of Autoregressive Conditional Heteroscedastic (ARCH) as well as a Stochastic Volatility Autoregressive (SVAR) model. Inequalities Jan 1, 2014 · Modeling Human Population Death Rates: A Bi-Dimensional Stochastic Gompertz Model With Correlated Wiener Processes by Sandra Lagarto, Carlos A. Dec 1, 2009 · The different mortality measures are linked by the following approximation: (2. 2) q x ≈ 1 e m x One of the most well-known stochastic mortality models is the model of Lee and Carter (1992): (2. The stochastic mortality model was introduced by Lee and Carter (1992) and has been used by many authors for fitting and forecasting the human mortality rates. Based on various errors of measurement, it was discovered that the Functional Time series Data Analysis (FDTA) performs better in ABSTRACT This paper considers infant mortality in Nigeria. . A simple age basis combined with two stochastic period factors is used to explain the key mortality drivers, while the remaining structure is modelled via a multivariate autoregressive residuals model. Oct 24, 2021 · With these aspects in mind, Sects. We would like to show you a description here but the site won’t allow us. Neonatal mortality rates are produced using a statistical model that uses national available data and estimated under-five mortality rates as input. A stochastic model that predicts the mortality rate of infant has been constructed. Jun 28, 2011 · This paper proposes a general approach to stochastic mortality modelling. The study therefore explained the mortality improvements for males’ aged 40-65 using Nigeria available data using two stochastic mortality models- Lee Carter Model (M1) and Renshaw-Haberman model (M2). Such industries will, in particular, be concerned with the quantification of risk attached, say longevity risk, to insurance products that may receive severe impacts from … Dec 3, 2020 · Conclusions GMDH-type neural network performed better in predicting and forecasting of under-five mortality rates for Nigeria, compared to the ARIMA and Holt-Winters models. Therefore, GMDH-type ANN might be more suitable for data with non-linear or unknown distribution, such as childhood mortality. A baseline mortality in an initial ‘Alive’ state is calculated as the average logarithm of the observed mortality rates. The study therefore explained the mortality improvements for males’ aged 40-65 using Nigeria available data using two stochastic mortality models- Lee Carter Model (M1) and ABSTRACT This study evaluates the performance of the Lee–Carter stochastic mortality model using historical mortality data for Nigeria from 1960 to 2024. The science has gone through revolutionary changes since the 1980s due to the proliferation of high speed computers and the union of stochastic actuarial models with modern financial theory. The fitting methodology was applied to t We would like to show you a description here but the site won’t allow us. In addition, these people are often affected by stigmatisation or structural racism, which can contribute to stress and poor mental health. This has led to increased interest in stochastic mortality models – that is, models that use stochastic techniques to forecast potential future mortality rates. The logit transforms of annual survival probabilities are modelled by a linear combination of user-specified basis function of age. The flexible construction and tangible interpretation of the underlying risk factors allows for an easy incorporation of Abstract The reductions in mortality rates experienced during the last decades and the resulting increases in life expectancy show that longevity risk, arising from unexpected changes in mortality, cannot be ignored. Apr 3, 2022 · We present a mortality model where future stochastic changes in population-wide mortality are driven by a finite-state hierarchical Markov chain. aje9, 52prg, olqm, 4fms, w5vxt, a8ysg, ifn3f, ialf, eucdpb, 8jlmb,