Optimal Neighborhood Selection for AR-ARCH Random Fields with Application to Mortality

This article proposes an optimal and robust methodology for model selection. The model of interest is a parsimonious alternative framework for modeling the stochastic dynamics of mortality improvement rates introduced recently in the literature. The approach models mortality improvements using a random field specification with a given causal structure instead of the commonly used factor-based decomposition framework. It captures some well-documented stylized facts of mortality behavior including: dependencies among adjacent cohorts, the cohort effects, cross-generation correlations, and the conditional heteroskedasticity of mortality. Such a class of models is a generalization of the now widely used AR-ARCH models for univariate processes. A the framework is general, it was investigated and illustrated a simple variant called the three-level memory model. However, it is not clear which is the best parameterization to use for specific mortality uses. In this paper, we investigate the optimal model choice and parameter selection among potential and candidate models. More formally, we propose a methodology well-suited to such a random field able to select thebest model in the sense that the model is not only correct but also most economical among all thecorrectmodels. Formally, we show that a criterion based on a penalization of the log-likelihood, e.g., the using of the Bayesian Information Criterion, is consistent. Finally, we investigate the methodology based on Monte-Carlo experiments as well as real-world datasets.

Growing Income-Based Inequalities in Old-Age Life Expectancy in Sweden, 2006–2015

Sweden is known for high life expectancy and economic egalitarianism, yet in recent decades it has lost ground in both respects. This study tracked income inequality in old-age life expectancy and life span variation in Sweden between 2006 and 2015, and examined whether patterns varied across levels of neighborhood deprivation. Income inequality in remaining life expectancy at ages 65, 75, and 85 increased. The gap in life expectancy at age 65 grew by more than a year between the lowest and the highest income quartiles, for both men (from 3.4 years in 2006 to 4.5 years in 2015) and women (from 2.3 to 3.4 years). This widening income gap in old-age life expectancy was driven by different rates of mortality improvement: individuals with higher incomes increased their life expectancy at a faster rate than did those with lower incomes. Women with the lowest incomes experienced no improvement in old-age life expectancy. Furthermore, life span variation increased in the lowest income quartile, while it decreased slightly among those in the highest quartile. Income was found to be a stronger determinant of old-age life expectancy than neighborhood deprivation.

Coherent Mortality Forecasting for Less Developed Countries

This paper proposes a coherent multi-population approach to mortality forecasting for less developed countries. The majority of these countries have witnessed faster mortality declines among the young and the working age populations during the past few decades, whereas in the more developed countries, the contemporary mortality declines have been more substantial among the elders. Along with the socioeconomic developments, the mortality patterns of the less developed countries may become closer to those of the more developed countries. As a consequence, forecasting the long-term mortality of a less developed country by simply extrapolating its historical patterns might lead to implausible results. As an alternative, this paper proposes to incorporate the mortality patterns of a group of more developed countries as the benchmark to improve the forecast for a less developed one. With long-term, between-country coherence in mind, we allow the less developed country’s age-specific mortality improvement rates to gradually converge with those of the benchmark countries during the projection phase. Further, we employ a data-driven, threshold hitting approach to control the speed of this convergence. Our method is applied to China, Brazil, and Nigeria. We conclude that taking into account the gradual convergence of mortality patterns can lead to more reasonable long-term forecasts for less developed countries.

Mortality evolution in Algeria: What can we learn about data quality?

Mortality in Algeria has declined significantly since the country declared its independence in 1962. This trend has been accompanied by improvements in data quality and changes in estimation methodology, both of which are scarcely documented, and may distort the natural evolution of mortality as reported in official statistics. In this paper, our aim is to detect these methodological and data quality changes by means of the visual inspection of mortality surfaces, which represent the evolution of mortality rates, mortality improvement rates and the male-female mortality ratio over age and time. Data quality problems are clearly visible during the 1977–1982 period. The quality of mortality data has improved after 1983, and even further since the population census of 1998, which coincided with the end of the civil war. Additional inexplicable patterns have also been detected, such as a changing mortality age pattern during the period before 1983, and a changing pattern of excess female mortality at reproductive ages, which suddenly appears in 1983 and disappears in 1992.

Mandatory annuitization and money's worth: evidence from Singapore

This paper examines the impact of uncertainties in the future trends of mortality on annuity values in Singapore's compulsory purchase market. We document persistent population mortality improvement trends over the past few decades, which underscores the importance of longevity risk in this market. Using the money's worth framework, we find that the life annuities delivered expected payouts valued at 1.019–1.185 (0.973–1.170) per dollar of annuity premium for males (females). Even in a low mortality improvement scenario, the annuities provide an expected value exceeding 0.950. This suggests that participants in the national annuity pool have access to attractively priced annuities, regardless of sex, product, and premium invested.

Resuscitative Endovascular Balloon Occlusion of Aorta: A Systematic Review

BackgroundThe data on resuscitative endovascular balloon occlusion of the aorta (REBOA) use continue to grow with its increasing use in trauma centers. The data in her last 5 years have not been systematically reviewed. We aim to assess current literature related to REBOA use and outcomes among civilian trauma populations.MethodsA literature search using PubMed, EMBASE, and JAMA Network for studies regarding REBOA usage in civilian trauma from 2016 to 2020 is carried out. This review followed preferred reporting items for systematic reviews and meta-analysis guidelines.ResultsOur search yielded 35 studies for inclusion in our systematic review, involving 4073 patients. The most common indication for REBOA was patient presentation in hemorrhagic shock secondary to traumatic injury. REBOA was associated with significant systolic blood pressure improvement. Of 4 studies comparing REBOA to non-REBOA controls, 2 found significant mortality benefit with REBOA. Significant mortality improvement with REBOA compared to open aortic occlusion was seen in 4 studies. In the few studies investigating zone placement, highest survival rate was seen in patients undergoing zone 3. Overall, reports of complications directly related to overall REBOA use were relatively low.ConclusionREBOA has been shown to be effective in promoting hemodynamic stability in civilian trauma. Mortality data on REBOA use are conflicting, but most studies investigating REBOA vs. open occlusion methods suggest a significant survival advantage. Recent data on the REBOA technique (zone placement and partial REBOA) are sparse and currently insufficient to determine advantage with any particular variation. Overall, larger prospective civilian trauma studies are needed to better understand the benefits of REBOA in high-mortality civilian trauma populations.Study TypeSystematic Review.Level of evidenceIII- Therapeutic.

Mortality Forecasting with an Age-Coherent Sparse VAR Model

This paper proposes an age-coherent sparse Vector Autoregression mortality model, which combines the appealing features of existing VAR-based mortality models, to forecast future mortality rates. In particular, the proposed model utilizes a data-driven method to determine the autoregressive coefficient matrix, and then employs a rotation algorithm in the projection phase to generate age-coherent mortality forecasts. In the estimation phase, the age-specific mortality improvement rates are fitted to a VAR model with dimension reduction algorithms such as the elastic net. In the projection phase, the projected mortality improvement rates are assumed to follow a short-term fluctuation component and a long-term force of decay, and will eventually converge to an age-invariant mean in expectation. The age-invariance of the long-term mean guarantees age-coherent mortality projections. The proposed model is generalized to multi-population context in a computationally efficient manner. Using single-age, uni-sex mortality data of the UK and France, we show that the proposed model is able to generate more reasonable long-term projections, as well as more accurate short-term out-of-sample forecasts than popular existing mortality models under various settings. Therefore, the proposed model is expected to be an appealing alternative to existing mortality models in insurance and demographic analyses.

Analysis of Mortality Improvement on the Pension Cost Due to Aging Population

Aging is a good indicator in demographic and health areas as the lifespanof the elderly population increases. Based on the government’s Economic Outlook 2019,it was found that an aging population would increase the government pension paymentsas the pensioners and their beneficiaries have longer life expectancy. Due to mortalityrates decreasing over time, the life expectancy tends to increase in the future. Theaims of this study are to forecast the mortality rates in the years 2020 and 2025 usingthe Heligman-Pollard model and then analyse the effect of mortality improvement onthe pension cost (annuity factor) for the Malaysian population. However, this studyonly focuses on estimating the annuity factor using life annuities through the forecastedmortality rates. The findings indicated that the pension cost is expected to increase ifthe life expectancy of the Malaysian population increases due to the aging population inthe near future. Thus, to reduce pension costs and help the pensioners from insufficientfinancial income, the government needs to consider an extension of the retirement age infuture.

Modeling County-Level Spatio-Temporal Mortality Rates Using Dynamic Linear Models

The lifestyles and backgrounds of individuals across the United States differ widely. Some of these differences are easily measurable (ethnicity, age, income, etc.) while others are not (stress levels, empathy, diet, exercise, etc.). Though every person is unique, individuals living closer together likely have more similar lifestyles than individuals living hundreds of miles apart. Because lifestyle and environmental factors contribute to mortality, spatial correlation may be an important feature in mortality modeling. However, many of the current mortality models fail to account for spatial relationships. This paper introduces spatio-temporal trends into traditional mortality modeling using Bayesian hierarchical models with conditional auto-regressive (CAR) priors. We show that these priors, commonly used for areal data, are appropriate for modeling county-level spatial trends in mortality data covering the contiguous United States. We find that mortality rates of neighboring counties are highly correlated. Additionally, we find that mortality improvement or deterioration trends between neighboring counties are also highly correlated.