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The work proposes a mathematical model of the process of COVID-19 epidemic as it evolved in New Zealand. The model uses a system of differential equations which emanate from natural assumptions on some probability measure and evolution of this measure on evolving family of simplexes. The authors tried to create the model which, at one hand, is simple and easy to follow. and, at the other hand, reflects the observed epidemic process correctly. The practical aim was to come to justifiable estimations of important parameters like the rate of infection as function of time, thus quantifying effectiveness of the Government measures. Another parameters estimated were the probability distribution of detection times and recovery times. [ FROM AUTHOR] Copyright of Journal of Applied Statistics is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Inspired by the double-debt problem in Japan where the mortgagor has to pay the remaining loan even if their house was destroyed by a catastrophic event, we model the lender's cash flow, by an expo...

There is a significant potential demand around the world for a flexible product to manage individual longevity risk. However, annuity markets remain thin, driven by factors including lack of pricin...

Insurers are increasingly embracing the InsurTech ecosystem. The most important InsurTech-related trend in automobile insurance is usage-based insurance (UBI), which enables insurers to access and ...

This study investigates risk-seeking and optimal decisions of annuity providers. On the basis of a sample of U.S. life and annuity (L/A) insurers between 1997 and 2016, the results show clear performance-dependent risk attitudes. Specifically, insurers with returns below aspiration levels take more risks, whereas those with returns above reference levels decrease their risk-seeking, which supports the basic propositions of the cumulative prospect theory (CPT). Given initial evidence of mixed risk preferences in the L/A insurance industry, we derive an annuity insurer’s optimal investment and business strategies in a CPT decision-making framework. We show that changing risk preferences considerably affect an annuity provider’s decisions. We further illustrate how risk management changes an annuity insurer’s optimal strategies. Our results suggest that risk management lowers downside risk and allows a loss-averse decision-maker to assume more risk and achieve a higher level of utility.

In many countries, the decline in interest rates has reduced the interest in traditional participating life insurance contracts with investment guarantees and has led to a shift to unit-linked policies without guarantees. We design a novel mixed insurance contract splitting premium payments between a participating and a unit-linked fund. An additional guarantee fee is applied on the unit-linked return in order to increase the investment guarantee of the participating fund. In a utility-based framework, using power utility and prospect theory as preference functions, we show that the mixed product is usually perceived more attractive than a full investment in either the unit-linked or the participating contract. The guarantee fee is beneficial for conservative investors interested in a stronger protection against losses. This is also interesting from a marketing perspective: By the increase of the guarantee in the participating product, zero or negative guaranteed rates can be avoided.

This paper develops a valuation model of vulnerable American put options incorporating the correlated credit risk. The dynamics of the underlying asset, the counterparty assets and corporate liabil...

This paper develops a contingent claim model of a risk-averse life insurer’s equity with various borrowing-firm credit risk features. The insurer’s lending function with various financial technolog...

Collegiate Recovery Program (CRP) growth is dependent upon research that addresses the value of CRPs. Given that CRP research is relatively new, there are barriers related to justifying the establi...

The risk of incurring financial losses from fraudulent claims is an issue concerning all insurance companies. The detection of such claims is not an easy task. Moreover, a number of old-school meth...

The Consolidated Omnibus Reconciliation Act of 1985 (COBRA) contained provisions granting individuals the opportunity to continue employment-based insurance coverage following qualifying events whi...

Numerous eligible German students do not apply for heavily subsidized student aid (BAfoG). Our theoretical model shows how imperfect information, risk aversion, debt aversion, and student income ca...

Institutions of higher education are relying on philanthropy and fundraising at a greater level than ever before seen. This increased focus has led scholars to investigate various predictors regard...

In human population surveys, respondents are not likely to participate or give honest and truthful answers when the stigmatized issues are asked. To reduce the response biases RRT was developed. Th...

Alternative risk premia (ARP) are designed to provide low-cost exposures to long–short risk premia often embedded in hedge fund returns. This article describes the performance of the ARP market in ...

In the UK Listing Review it is suggested that the LSE should allow companies with dual class share (DCS) structures to list on the Premium segment. In this paper, we discuss this proposal. First, w...

Mortality data play an important role on the fields such as health, epidemiology and national planning. Most mortality models mainly focus on providing a perfect fitting, to the detriment of an exact forecasting result. In this paper, we fit the Bernstein polynomial to mortality data based on maximum likelihood based inference through the simulated annealing method. The proposed method utilizes the derivative of Bernstein polynomials to describe the pattern of mortality rates. The asymptotic behavior of the proposed model is also given on general results. The performance of the proposed method is evaluated by simulated examples and illustrated through applications to datasets provided from the Human Mortality Database (www.mortality.org). The simulated examples and real data analysis show that the proposed approach is quite satisfactory in forecasting the short-term mortality trends.

Refereed/Peer-reviewed The highest estimates of the prevalence of commercial contract cheating in Australia come from self-report surveys, which suggest that around 2% of students engage in commercial contract cheating during their higher education studies. However, self-report surveys are limited in that participants under-report socially-undesirable behaviours. In this study, we used an incentivised truth-telling method and surveyed 4098 students from six universities and six independent higher education providers in Australia. We found that 2.46 times more students admitted to commercial contract cheating, via submitting ghost-written assessments, when truth-telling was incentivised (via a Bayesian Truth Serum methodology) rather than when normal self-report survey instructions were used. Using prevalence estimation formulae that are combined with the incentivised truth-telling method, we estimate that 7.9% of students buy and submit assignments from commercial contract cheating services. Additionally, 11.4% outsource assessments via obtaining pre-written work from commercial file-sharing sites. These are substantially higher percentages of commercial contract cheating than self-reports suggest. Furthermore, having a first language other than English was the strongest demographic predictor of Australian students’ engagement in commercial contract cheating. We conclude that commercial contract cheating is a more common problem than suggested by self-report surveys. We argue that academic integrity researchers should consider methods beyond standard self-reports to estimate the prevalence of academic misconduct and that efforts to curb commercial contract cheating must be increased.

Open banking (OB) creates an opportunity for financial institutions to oer more personalised services by better differentiating between a specific customer (reference subject) and similar customers (comparison group). We propose the time-varying comparative mean value as a statistical method that learns about the dynamics governing how the response of a reference subject differs from that of a comparison group, defined via covariate truncation. The proposed model can be regarded as a time-varying truncated covariate regression model of which a smooth version is devised by resorting to local polynomial regression. The simulation study suggests that our estimators accurately recover the true time-varying comparative mean value in a variety of scenarios. We showcase our methods using OB-type data from a financial service provider in the UK, with the dataset containing detailed information on customers' accounts across 70 UK financial institutions. By contrasting a specific customer against similar customers, our method offers interesting diagnostics that can be used by financial institutions to recommend personalised services.

This paper investigates how the risk and the collateral values are jointly affecting the credit rationing. We propose a credit rationing model of continuous default risk and collateral values and s...

We study canonical consumption-savings problems of an individual involving uninsurable biometric risk. These problems are important in many applications from insurance economics and actuarial science. Since biometric risk is uninsurable, closed-form solutions do not exist and thus the problems must be approached by numerical methods. We propose a powerful approach where the solution is obtained by optimizing over a parametrized family of consumption strategies. In settings with mortality risk, critical illness risk, and habit formation, our solution method outperforms the well-established finite-difference approach both in run time and in precision. Our method also delivers a precision measure and closed-form representations of the optimal controls.

In determining whether a new permissible exposure limit is technologically feasible, the Occupational Safety and Health Administration (OSHA) and various courts have used poorly defined criteria such as whether "most employers most of the time" are able to comply with a standard. This vague definition creates problems when employers try to determine the best way to protect their workers and estimate the costs to remain in compliance with the permissible exposure limit. This article proposes a more rigorous approach to determine feasibility. By utilizing the best available statistical methods, employers and rule makers can better understand the variability within existing exposure data to determine the feasibility of new exposure limits. There are several readily available statistical tools that can be used for this purpose. To illustrate these techniques, a subset of data from the foundry industry and analysis from the OSHA respirable crystalline silica rulemaking proceeding are compared to methods published by the National Institute for Occupational Safety and Health in 1977 and a more sophisticated Bayesian approach. The results of this analysis suggest that complying with a new permissible exposure limit is more challenging than what is implied by OSHA's analysis, and calls into question its method of determining compliance. In the same vein, OSHA should move away from assessing compliance based on individual measurements and instead use a statistical approach to determine if a workplace is in compliance. These changes will encourage employers to better characterize occupational exposures, and will ultimately lead to better protection for employees while also providing employers protection from violations due to one-off overexposures.

Considering the effects of mortality risk awareness and idiosyncratic mortality force on economic decision-making of a retiree, we study the optimal post-retirement consumption and portfolio proble...

This is an accepted manuscript of an article published by Taylor & Francis in Housing Policy Debate on 10/08/2021, available online: https://doi.org/10.1080/10511482.2021.1931932 The accepted version of the publication may differ from the final published version.

The insurance industry is built on risk classification, grouping insureds into homogeneous classes. Through actions such as underwriting, pricing, and so forth, it differentiates, or discriminates, among insureds. Actuaries have responsibility for pricing insurance risk transfers and are intimately involved in other aspects of company actions and so have a keen interest in whether or not discrimination is appropriate from both company and societal viewpoints. This article reviews social and economic principles that can be used to assess the appropriateness of insurance discrimination. Discrimination issues vary by the line of insurance business and by the country and legal jurisdiction. This article examines social and economic principles from the vantage of a specific line of business and jurisdiction;these vantage points provide insights into principles. To sharpen understanding of the social and economic principles, this article also describes discrimination considerations for prohibitions based on diagnosis of COVID-19, the pandemic that swept the globe in 2020. Insurance discrimination issues have been an important topic for the insurance industry for decades and are evolving in part due to insurers’ extensive use of Big Data;that is, the increasing capacity and computational abilities of computers, availability of new and innovative sources of data, and advanced algorithms that can detect patterns in insurance activities that were previously unknown. On the one hand, the fundamental issues of insurance discrimination have not changed with Big Data;one can think of credit-based insurance scoring and price optimization as simply forerunners of this movement. On the other hand, issues regarding privacy and use of algorithmic proxies take on increased importance as insurers’ extensive use of data and computational abilities evolve. © 2021 The Author(s). Published with license by Taylor & Francis Group, LLC.

Zhiguang Li,1 Xu Si,1 Zhiyuan Ding,1 Xiao Li,1 Shuai Zheng,1 Yuxin Wang,1 Hua Wei,1 Yige Guo,2 Wei Zhang3 1School of Economics and Management, Anhui University of Chinese Medicine, Hefei, Anhui, People’s Republic of China; 2King’s Business School, King’s College London, London, UK; 3School of Information Engineering, Anhui University of Chinese Medicine, Hefei, Anhui, People’s Republic of ChinaCorrespondence: Hua WeiSchool of Economics and Management, Anhui University of Chinese Medicine, Hefei, Anhui, People’s Republic of ChinaTel +86 551-68129006Email weihua@ahtcm.edu.cnWei ZhangSchool of Information Engineering, Anhui University of Chinese Medicine, Hefei, Anhui, People’s Republic of ChinaTel +86 551-68129224Email zhangwei900316@163.comPurpose: This paper aims to measure the operating efficiency of China’s basic pension insurance from 2014 to 2019 in 31 provinces.Methods: The three-stage DEA model was used to evaluate the operating efficiency of basic pension insurance in 31 provinces.Results: On the whole, the operating efficiency of China’s basic pension insurance was at a high level, but there was still room for improvement. GDP, urbanization level and scale of government public expenditure had a positive impact on the operating efficiency of regional basic pension insurance. In contrast, the old-age dependency ratio had a significant negative effect. There were noticeable regional differences in the operating efficiency of China’s basic pension insurance, which showed a pattern of Central (0.742) >Eastern (0.689) >Western (0.505) after removing the influence of environmental variables.Conclusion: This study systematically analyzes the impact of external environmental regulations on China’s basic pension insurance’s operating efficiency and provides decision-making references for further improving the operating efficiency of China’s basic pension insurance. In order to further optimize the allocation of basic endowment insurance, this paper proposes the following countermeasures and suggestions: (1) broaden investment channels and improve the investment efficiency; (2) increase supervision of social security departments and strengthen information disclosure; (3) unify the management of social basic pension insurance.Keywords: three-stage DEA, China’s pension insurance, operating efficiency, technical efficiency

The study explores the borrowers’ credit risk factors, perception towards repayment interventions, and the problems of moral hazard affecting delinquency in uncollateralized loans issued by the Mic...

Existing compartmental-logistics models in epidemics control are limited in terms of optimizing the allocation of vaccines and treatment resources under a risk-averse objective. In this paper, we present a data-driven, mean-risk, multi-stage, stochastic epidemics-vaccination-logistics model that evaluates various disease growth scenarios under the Conditional Value-at-Risk (CVaR) risk measure to optimize the distribution of treatment centers, resources, and vaccines, while minimizing the total expected number of infections, deaths, and close contacts of infected people under a limited budget. We integrate a new ring vaccination compartment into a Susceptible-Infected-Treated-Recovered-Funeral-Burial epidemics-logistics model. Our formulation involves uncertainty both in the vaccine supply and the disease transmission rate. Here, we also consider the risk of experiencing scenarios that lead to adverse outcomes in terms of the number of infected and dead people due to the epidemic. Combining the risk-neutral objective with a risk measure allows for a trade-off between the weighted expected impact of the outbreak and the expected risks associated with experiencing extremely disastrous scenarios. We incorporate human mobility into the model and develop a new method to estimate the migration rate between each region when data on migration rates is not available. We apply our multi-stage stochastic mixed-integer programming model to the case of controlling the 2018-2020 Ebola Virus Disease (EVD) in the Democratic Republic of the Congo (DRC) using real data. Our results show that increasing the risk-aversion by emphasizing potentially disastrous outbreak scenarios reduces the expected risk related to adverse scenarios at the price of the increased expected number of infections and deaths over all possible scenarios. We also find that isolating and treating infected individuals are the most efficient ways to slow the transmission of the disease, while vaccination is supplementary to primary interventions on reducing the number of infections. Furthermore, our analysis indicates that vaccine acceptance rates affect the optimal vaccine allocation only at the initial stages of the vaccine rollout under a tight vaccine supply.

In this paper, we compare different spatial models for modelling the risk premium for water damage insurance on the level of the policyholder. We evaluate four models that take the spatial variabil...

According to SAMHSA (2014), 1 of the 10 domains of a trauma-informed approach to child welfare relates to universal screening; however, costs of installation and implementation models are often unc...

This study examines relationships between the location of supply chain disruptions (SCDs) within the supply chain, a firm’s experience with SCDs, and the disruption severity. Using organizational learning theory, we propose that an organization’s prior experience with SCDs will reduce the negative influence of future disruptions. However, the location of disruption occurrence (internal to the firm vs. external to the firm) also plays a vital role in the severity of future disruptions. We consider two measures of SCD severity to quantify the extent of negative influence on firms: (1) the initial loss of return on assets (ROA) and (2) the total loss of ROA over time. We empirically evaluate the performance of 262 publicly traded U.S. firms that experienced an SCD. Our study shows that the influence of internal and external SCDs on firms can be different when firms do and do not have experience with similar events. More specifically, the results show that when firms have not experienced a similar event in the past, internal SCDs are associated with a higher disruption severity than are external SCDs. The results also show that prior experience significantly decreases the disruption severity suffered by firms after internal SCDs.

Pharmaceutical inventory management is critical because insufficient pharmaceutical items and their misusage affect the lives of humans and cause financial losses. Conversely, deteriorating items a...

In this paper, we define a new multivariate conditional Value-at-Risk (MCVaR) risk measure. This MCVaR considers both individual risks and the aggregate risk of a portfolio, but prioritizes the agg...

We develop a two-stage contingent claim model to evaluate a life insurer’s equity. The model sequentially determines the optimal guaranteed rate and the optimal technology choice for strategic asse...

In this study, we identify the relationship between Medicaid expansion and emergency department use based on the data from Oregon Health Program. Among the relevant studies, Taubman et al. (2014) p...

Objective Missing data can produce biased estimates in interrupted time series (ITS) analyses. We reviewed recent ITS investigations on health topics for determining 1) the data management strategies and statistical analysis performed, 2) how often missing data were considered and, if so, how they were evaluated, reported and handled. Study design and setting This was a scoping review following standard recommendations from the PRISMA Extension for Scoping Reviews. We included a random sample of all ITS studies that assessed any intervention relevant to health care (eg, policies or programmes) with individual-level data, published in 2019, with abstracts indexed on MEDLINE. Results From 732 studies identified, we finally reviewed 60. Reporting of missing data was rare. Data aggregation, statistical tools for modelling population-level data and complete case analyses were preferred, but these can lead to bias when data are missing at random. Seasonality and other time-dependent confounders were rarely accounted for and, when they were, missing data implications were typically ignored. Very few studies reflected on the consequences of missing data. Conclusion Handling and reporting of missing data in recent ITS studies performed for health research have many shortcomings compared with best practice.

This study aims to determine the most appropriate warranty period and policy with the lowest warranty cost from the manufacturer/seller point of view. The warranty policy to be put forward and the warranty period to be offered under this policy should ensure customer satisfaction while at the same time causing a minimum cost to the manufacturer/seller. For this reason, the optimum warranty period within the scope of Free-Replacement Warranty (FRW) policy, Pro-Rata Warranty (PRW) policy, and Combined FRW/PRW policy which was the combination of those two warranty policies were tried to be determined. In the study which was done to determine the most appropriate warranty period, economic benefit and the benefit function obtained from warranty cost and dissatisfaction cost functions were used. While obtaining necessary formulas, exponential distribution, which was widely used in life tests as density function and gamma and inverse-gamma functions as prior distribution of the exponential distribution were used. To demonstrate the applicability and flexibility of the model, some typical sales models and numerical values for exponential lifetime distribution were used, and an algorithm was created to find the optimal solution. When all of the results were analyzed it was seen that Combined FRW/PRW policy was the most appropriate warranty cost as a result of testing the models obtained and it was also found that the warranty cost was almost 3% of the sale price. Within the frame of these obtained results, Combined FRW/PRW policy was suggested for the warranty service to be served with the product to the manufacturer/seller. If the warranty period number of revolutions were chosen almost g1=0.054., g2=0.120. the warranty cost will be in the minimum level and it will be almost 3% of the product sale price. The validity and accuracy of the proposed strategy was verified by a case study with a numerical sample providing a scientific basis. WOS:000665658800001 2-s2.0-85108637834

The present study analyzes the effectiveness (exhaustivity and mutual exclusivity) of a taxonomy for classifying animals into the categories of pet, pest, and profit (PPP), as well as variables tha...

In this paper, we mainly focus on the valuation for the risk-based premium of private pension plan with termination provided by the Pension Benefit Guaranty Corporation (PBGC). The dynamics for ass...

This paper proposes an innovative retirement product with a focus on longevity risk sharing, a contract we refer to as tail index-linked annuity (TILA). Specifically, the proposed TILA pays out variable annual payments, which will be equal to a regular nominal amount when a reference survival index is lower than a predetermined threshold (i.e., normal evolution of longevity risk), and a reduced, index-dependent payment when the threshold is passed (i.e., highly unfavorable evolution of longevity risk). The proposed TILA aims at not only improving the benefits of the policyholders, which has been the focus in recent literature on innovative retirement products, but also reducing the longevity risk exposure of the insurer, particularly for advanced retirement ages. Using real-world mortality data and stochastic multi-population mortality model, we find that the proposed TILA leads to higher expected lifetime utility than regular annuities for policyholders with different degrees of risk aversions. Meanwhile, numerical analysis shows that the proposed TILA could greatly mitigate the solvency risk of the insurer, leading to substantially lower loss probability and expected (tail-) loss than regular annuities in the presence of longevity shock, and therefore could reduce the insurer's required solvency capital under latest solvency regulations.

Objectives. There is little understanding of the optimal technical performance characteristics associated with winning matches in netball and how these might vary between competition levels and between each quarter of the game. This study aims to identify and compare team technical performance characteristics between elite domestic and international-level matches and among different quarters. Design. A retrospective cohort study was used. Methods. Netball data sets were analysed, containing quarter-level and overall match statistics from the professional league in Australia and international tournaments (n = 1,296 records, 648 matches). Permutation resampling tests were used to compare technical variables between domestic and international matches, and between winning and losing teams at both the match and (non-cumulative) quarter levels. Machine learning methods were used to model match outcome and to rank technical characteristics. Results. Differences in team technical characteristics were observed between domestic and international matches, relating to penalties, and score-related actions. There are a variety of team technical characteristics that vary between winning and losing performances, and their importance varies slightly between quarters within a match. A K-Nearest Neighbour classifier explained match outcome with a high accuracy which demonstrates that there are enough data available in elite netball to apply machine learning methods for more complex analyses in the future. Conclusions. Team technical performance varies between winning and losing performances, at elite domestic and international levels. Minimising undesirable technical actions such as penalties and errors appears to be the most important difference between winning and losing teams.

A designing methodology to determine the optimal multiple deferred state repetitive group sampling plan for assuring Birnbaum–Saunders distributed both mean and median life of the products is propo...