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Estimation of Mortality Rates in Stage-Structured Population

Estimation of Mortality Rates in Stage-Structured Population
Author: Simon N. Wood
Publisher: Springer Science & Business Media
Total Pages: 113
Release: 2013-03-08
Genre: Social Science
ISBN: 3642499791

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The stated aims of the Lecture Notes in Biomathematics allow for work that is "unfinished or tentative". This volume is offered in that spirit. The problem addressed is one of the classics of statistical ecology, the estimation of mortality rates from stage-frequency data, but in tackling it we found ourselves making use of ideas and techniques very different from those we expected to use, and in which we had no previous experience. Specifically we drifted towards consideration of some rather specific curve and surface fitting and smoothing techniques. We think we have made some progress (otherwise why publish?), but are acutely aware of the conceptual and statistical clumsiness of parts of the work. Readers with sufficient expertise to be offended should regard the monograph as a challenge to do better. The central theme in this book is a somewhat complex algorithm for mortality estimation (detailed at the end of Chapter 4). Because of its complexity, the job of implementing the method is intimidating. Any reader interested in using the methods may obtain copies of our code as follows: Intelligible Structured Code 1. Hutchinson and deHoog's algorithm for fitting smoothing splines by cross validation 2. Cubic covariant area-approximating splines 3. Cubic interpolating splines 4. Cubic area matching splines 5. Hyman's algorithm for monotonic interpolation based on cubic splines. Prototype User-Hostile Code 6. Positive constrained interpolation 7. Positive constrained area matching 8. The "full method" from chapter 4 9. The "simpler" method from chapter 4.


The Stochastic Mortality Modeling and the Pricing of Mortality/longevity Linked Derivatives

The Stochastic Mortality Modeling and the Pricing of Mortality/longevity Linked Derivatives
Author: Shuo-Li Chuang
Publisher:
Total Pages: 316
Release: 2013
Genre:
ISBN:

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The Lee-Carter mortality model provides the very first model for modeling the mortality rate with stochastic time and age mortality dynamics. The model is constructed modeling the mortality rate to incorporate both an age effect and a period effect. The Lee-Carter model provides the fundamental set up currently used in most modern mortality modeling. Various extensions of the Lee-Carter model include either adding an extra term for a cohort effect or imposing a stochastic process for mortality dynamics. Although both of these extensions can provide good estimation results for the mortality rate, applying them for the pricing of the mortality/ longevity linked derivatives is not easy. While the current stochastic mortality models are too complicated to be explained and to be implemented, transforming the cohort effect into a stochastic process for the pricing purpose is very difficult. Furthermore, the cohort effect itself sometimes may not be significant. We propose using a new modified Lee-Carter model with a Normal Inverse Gaussian (NIG) Lévy process along with the Esscher transform for the pricing of mortality/ longevity linked derivatives. The modified Lee-Carter model, which applies the Lee-Carter model on the growth rate of mortality rates rather than the level of iv mortality rates themselves, performs better than the current mortality rate models shown in Mitchell et al (2013). We show that the modified Lee-Carter model also retains a similar stochastic structure to the Lee-Carter model, so it is easy to demonstrate the implication of the model. We proposed the additional NIG Lévy process with Esscher transform assumption that can improve the fit and prediction results by adapting the mortality improvement rate. The resulting mortality rate matches the observed pattern that the mortality rate has been improving due to the advancing development of technology and improvements in the medical care system. The resulting mortality rate is also developed under a martingale measure so it is ready for the direct application of pricing the mortality/longevity linked derivatives, such as q-forward, longevity bond, and mortality catastrophe bond. We also apply our proposed model along with an information theoretic optimization method to construct the pricing procedures for a life settlement. While our proposed model can improve the mortality rate estimation, the application of information theory allows us to incorporate the private health information of a specific policy holder and hence customize the distribution of the death year distribution for the policy holder so as to price the life settlement. The resulting risk premium is close to the practical understanding in the life settlement market.


Research Ethics in Complex Humanitarian Emergencies

Research Ethics in Complex Humanitarian Emergencies
Author: National Research Council
Publisher: National Academies Press
Total Pages: 28
Release: 2002-08-13
Genre: Social Science
ISBN: 0309169178

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Situations involving conflict and forced migration have become increasingly commonplace in today's world. The need to understand the causes, consequences, and characteristics of these situations is creating a burgeoning field of research. But given the nature of complex emergency settings, traditional research guidelines may be inappropriate. The research and policy community has recognized this problem and has begun to address issues surrounding the ethics of doing research in emergency settings and among conflict-affected and displaced populations. The Roundtable on the Demography of Forced Migration, under the aegis of the Committee on Population of the National Research Council, held a workshop to examine some of these issues. This report to the roundtable summarizes the workshop presentations and discussion.


Demographic Forecasting

Demographic Forecasting
Author: Federico Girosi
Publisher: Princeton University Press
Total Pages: 294
Release: 2008-08-24
Genre: Social Science
ISBN: 9780691130958

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Demographic Forecasting introduces new statistical tools that can greatly improve forecasts of population death rates. Mortality forecasting is used in a wide variety of academic fields, and for policymaking in global health, social security and retirement planning, and other areas. Federico Girosi and Gary King provide an innovative framework for forecasting age-sex-country-cause-specific variables that makes it possible to incorporate more information than standard approaches. These new methods more generally make it possible to include different explanatory variables in a time-series regression for each cross section while still borrowing strength from one regression to improve the estimation of all. The authors show that many existing Bayesian models with explanatory variables use prior densities that incorrectly formalize prior knowledge, and they show how to avoid these problems. They also explain how to incorporate a great deal of demographic knowledge into models with many fewer adjustable parameters than classic Bayesian approaches, and develop models with Bayesian priors in the presence of partial prior ignorance. By showing how to include more information in statistical models, Demographic Forecasting carries broad statistical implications for social scientists, statisticians, demographers, public-health experts, policymakers, and industry analysts. Introduces methods to improve forecasts of mortality rates and similar variables Provides innovative tools for more effective statistical modeling Makes available free open-source software and replication data Includes full-color graphics, a complete glossary of symbols, a self-contained math refresher, and more


Functional Linear Models for Mortality Forecasting

Functional Linear Models for Mortality Forecasting
Author: Farah Yasmeen
Publisher:
Total Pages: 428
Release: 2010
Genre:
ISBN:

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Over the last two decades, a number of approaches have been developed for modeling and forecasting mortality rates. However, using these models for two or more groups leads to inconsistent results, and various approaches have been proposed to resolve this problem.In this thesis, I present two new classes of functional linear models for analyzing, modeling and forecasting multiple time series corresponding to age-specific mortality rates of two or more groups within similar populations, which have related dynamics. Such groups might be males and females in the same population, different parts of a country (e.g. different provinces and states), races within a country (such as African American, White and Hispanic women in the United States), or different countries within a particular geographical region (for example, countries in the G7 group). The definition of "group" here depends on the forecaster's judgement. It is desirable for the disaggregated forecaststo be coherent with the overall forecast. In particular, a common restriction is that thesub-group forecasts should not diverge in the long run, and that the relative mortalityrates of the sub-groups should be approximately the same in the forecast period as in the historical period.This thesis is concerned with both theoretical and methodological developments of coherent mortality forecasting and the practical application of these new methods to various problems of real and current interest. I develop methods that are suitable for forecasting not only all-cause mortality data, but also cause-specific mortality, such as mortality ratesof chronic diseases, in contrast to the traditional age-period-cohort models.The first contribution of this thesis is to obtain age-related predictions of black and white breast cancer mortality rates in the United States. To the best of my knowledge, this is the first such study. I have successfully applied functional time series models to the breast cancer mortality data, as an alternative to the widely used APC models. I have shown that these models not only provide a basis for modeling age-specific mortality rates, but canalso be used to provide mortality forecasts and prediction intervals.A new method for the coherent forecasting of two or more functional time series ofmortality rates is proposed in chapter 4. This method is based on modelling the products and ratios of mortality rates from each individual group, rather than modelling the mortality rates themselves. The proposed method simplifies the modelling proceduregreatly, and provides a convenient and interpretable way of imposing coherence on the resulting forecasts. Relative to other recent proposals for coherent forecasting, the new approach is simpler to apply, is more flexible in allowing different types of dynamics, and produces more accurate forecasts.In this thesis, I relate some of the model extensions proposed by Hyndman & Ullah (2007), to the common principal components (CPC) and partial common principal components(PCPC) models introduced by Flury (1988). I combine the ideas of functional principalcomponents and CPC analysis with time series, and call the resulting models commonfunctional principal component (CFPC) models. I then use these models for the coherent forecasting of mortality rates. Although Hyndman & Ullah (2007) proposed these models, they did not discuss how they might be estimated or implemented. I therefore provide the methods for parameter estimation and forecasting using these models. I propose a sequential procedure to estimate the common and non-common/specific components, and use vector error correction models (VECM) to forecast the specific time series coefficients.I have applied the new methods to several types of disaggregated mortality rate data(disaggregated by sex, by region and by race). The newly developed functional linearmodels allow for non-divergence constraints to be imposed simply and naturally.Through the application of these new forecasting methods to the breast cancer mortalitydata of black and white women in the United States, I have found that the breast cancer mortality rates for both races are expected to decline, with the mortality rates of blacks remaining higher than those of whites for all age-groups. My analysis suggests that black women do not benefit equally from mammography and screening programs, and that a Forecasting disparity between the breast cancer mortality rates of the two races is expected to continueinto the future.


An Application of the James-Stein Estimation Method in Modeling of Mortality Rates

An Application of the James-Stein Estimation Method in Modeling of Mortality Rates
Author: Jinjin (Summer) Shan
Publisher:
Total Pages: 0
Release: 2023
Genre:
ISBN:

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It is known that the James-Stein estimation method outperforms the Maximum Likelihood Estimation method when we estimate a p−dimension independently distributed random variable with p ≥ 3. In this project, an explicit formula based on a modified James-Stein estimation is first derived to forecast a p−dimension random variable. Then the modified James-Stein estimator is applied to forecasting of mortality rates for 10, 20 and 30 years for six populations (both genders of the U.S., the U.K., and Japan). Moreover, some underlying mortality models (the Lee-Carter model, the Cairns-Blake-Dowd model, the M6 and M7 models, and the Renshaw-Haberman model) are also used in the forecasting of mortality rates to compare their forecast performances with the modified James-Stein estimation method. The results show that the modified James-Stein estimation method has the lowest overall average estimation error compared to all other mortality models. Finally, the shrinkage effect of the modified James-Stein estimate is studied with numerical illustrations for six populations and three forecasting years.


From Death to Birth

From Death to Birth
Author: National Research Council
Publisher: National Academies Press
Total Pages: 438
Release: 1998-01-12
Genre: Social Science
ISBN: 0309058961

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The last 35 years or so have witnessed a dramatic shift in the demography of many developing countries. Before 1960, there were substantial improvements in life expectancy, but fertility declines were very rare. Few people used modern contraceptives, and couples had large families. Since 1960, however, fertility rates have fallen in virtually every major geographic region of the world, for almost all political, social, and economic groups. What factors are responsible for the sharp decline in fertility? What role do child survival programs or family programs play in fertility declines? Casual observation suggests that a decline in infant and child mortality is the most important cause, but there is surprisingly little hard evidence for this conclusion. The papers in this volume explore the theoretical, methodological, and empirical dimensions of the fertility-mortality relationship. It includes several detailed case studies based on contemporary data from developing countries and on historical data from Europe and the United States.


Quantitative Fish Dynamics

Quantitative Fish Dynamics
Author: Terrance J. Quinn
Publisher: Oxford University Press, USA
Total Pages: 561
Release: 1999
Genre: Fish populations
ISBN: 0195076311

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The fields of fish population dynamics and stock assessment have seen major advances in the 1980s and 1990s, creating the need for a new synthesis. This text attempts that synthesis by presenting a contemporary approach for quantitative fisheries science that incorporates modern statistical and mathematical techniques. It emphasizes the link between biology and theory by explaining the assumptions inherent in the quantitative methods and models. The book covers key topics that are often overlooked in other texts, such as optimal harvesting, migratory stocks, and complex age and size-structured models. Quantitative Fish Dynamics is an ideal textbook for graduate and undergraduate courses in fish population dynamics and stock assessment. It is an indispensable reference work for fisheries scientists and others interested in conservation biology, fish and wildlife management, population ecology, and statistical applications.