Relationships between migration and the fiscal sustainability of the pension system in China

There are a few existing studies on whether domestic migration improves China's pension system's fiscal sustainability in the context of rapid urbanization and industrialization. In this paper, we systematically investigate the impact of migration on the solvency of the worker's old-age insurance for urban employees by constructing actuarial and econometric models. We use panel data from 2002 to 2018, collected from 31 provinces in China. The results show that the association between migration and the solvency of pensions is an inverted-U shape along the urbanization process. Further regional comparison showed that the above-stated inverted-U curve is more pronounced in the central and western regions. We also established that the number of participants and the contribution base are the main contributors to these results. Our conclusions are important for future population policies and public pension systems in China.

[Rare diseases from a life insurance perspective]

A rare disease is defined as a disease that affects a maximum of 5 in 10,000 people. As of today there are roughly 7000 different rare diseases known. On account of this one can say that "rare diseases are rare, but people affected by them are common". For Germany this amounts to: 4 million people that are affected by a rare disease. Diagnosis, therapeutic options and prognosis have substantially improved for some of the rare diseases. Besides the general medical advances--especially in the area of genetics--this is also due to networking and sharing information by so-called Centres of Competence on a national and international scale. This results in a better medical care for the corresponding group of patients. Against this backdrop, the number of people applying for life assurance who are suffering from a complex or rare disease has risen steadily in the last years. Due to the scarce availability of data regarding long-term prognosis of many rare diseases, a biomathematical, medical and actuarial expertise on the part of the insurer is necessary in order to adequately assess the risk of mortality and morbidity. Furthermore there is quite a focus on the issue of rare diseases from not only politics but society as well. Therefore evidence based medical assessment by insurers is especially important in this group of applicants--thinking of legal compliance and reputational risk.

Actuarial considerations of medical malpractice evaluations in M&As

To best project an actuarial estimate for medical malpractice exposure for a merger and acquisition, a organization's leaders should consider the following factors, among others: How to support an unbiased actuarial estimation. Experience of the actuary. The full picture of the organization's malpractice coverage. The potential for future loss development. Frequency and severity trends.

Population forecasts for Bangladesh, using a Bayesian methodology

Population projection for many developing countries could be quite a challenging task for the demographers mostly due to lack of availability of enough reliable data. The objective of this paper is to present an overview of the existing methods for population forecasting and to propose an alternative based on the Bayesian statistics, combining the formality of inference. The analysis has been made using Markov Chain Monte Carlo (MCMC) technique for Bayesian methodology available with the software WinBUGS. Convergence diagnostic techniques available with the WinBUGS software have been applied to ensure the convergence of the chains necessary for the implementation of MCMC. The Bayesian approach allows for the use of observed data and expert judgements by means of appropriate priors, and a more realistic population forecasts, along with associated uncertainty, has been possible.

The efficiency of a group-specific mandated benefit revisited: the effect of infertility mandates

This paper examines the labor market effects of state health insurance mandates that increase the cost of employing a demographically identifiable group. State mandates requiring that health insurance plans cover infertility treatment raise the relative cost of insuring older women of child-bearing age. Empirically, wages in this group are unaffected, but their total labor input decreases. Workers do not value infertility mandates at cost, and so will not take wage cuts in exchange, leading employers to decrease their demand for this affected and identifiable group. Differences in the empirical effects of mandates found in the literature are explained by a model including variations in the elasticity of demand, moral hazard, ability to identify a group, and adverse selection.

Selection in insurance markets: theory and empirics in pictures

Government intervention in insurance markets is ubiquitous and the theoretical basis for such intervention, based on classic work from the 1970s, has been the problem of adverse selection. Over the last decade, empirical work on selection in insurance markets has gained considerable momentum. This research finds that adverse selection exists in some insurance markets but not in others. And it has uncovered examples of markets that exhibit "advantageous selection"—a phenomenon not considered by the original theory, and one that has different consequences for equilibrium insurance allocation and optimal public policy than the classical case of adverse selection. Advantageous selection arises when the individuals who are willing to pay the most for insurance are those who are the most risk averse (and so have the lowest expected cost). Indeed, it is natural to think that in many instances individuals who value insurance more may also take action to lower their expected costs: drive more carefully, invest in preventive health care, and so on. Researchers have taken steps toward estimating the welfare consequences of detected selection and of potential public policy interventions. In this essay, we present a graphical framework for analyzing both theoretical and empirical work on selection in insurance markets. This graphical approach provides both a useful and intuitive depiction of the basic theory of selection and its implications for welfare and public policy, as well as a lens through which one can understand the ideas and limitations of existing empirical work on this topic.

A time series modeling approach in risk appraisal of violent and sexual recidivism

For over half a century, various clinical and actuarial methods have been employed to assess the likelihood of violent recidivism. Yet there is a need for new methods that can improve the accuracy of recidivism predictions. This study proposes a new time series modeling approach that generates high levels of predictive accuracy over short and long periods of time. The proposed approach outperformed two widely used actuarial instruments (i.e., the Violence Risk Appraisal Guide and the Sex Offender Risk Appraisal Guide). Furthermore, analysis of temporal risk variations based on specific time series models can add valuable information into risk assessment and management of violent offenders.

ANTEROCOD: actuarial survival curves applied to medical coding support for chronic diseases

For the practitioner, choosing diagnosis codes is a non-intuitive operation. Mistakes are frequent, causing severe consequences on healthcare performance evaluation and funding. French physicians have to assign a code to all their activities and are frequently prone to these errors. Given that most of the time and particularly for chronic diseases indexed information is already available, we propose a tool named AnterOcod, in order to support the medical coding task. It suggests the list of most relevant plausible codes, predicted from the patient's earlier hospital stays, according to a set of previously utilized diagnosis codes. Our method applies the estimation of code reappearance rates, based on an equivalent approach to actuarial survival curves. Around 33% of the expected correct diagnosis codes were retrieved in this manner, after evaluating 998 discharge abstracts, significantly improving the coding task.

Actuarial assessment of violence risk in hospital-based partner assault clinics

Hospital-based partner assault clinics are a relatively recent addition to the community response to partner violence. In this study, 66% of 111 women attending hospital clinics for partner assault were physically injured and 43% reported death threats. Few concurrently used other services (shelters or police) and most relied on female friends and relatives for help. Many participants who currently lived with the perpetrator were contemplating leaving but only a third had made plans to do so. Participants faced an unusually high risk of future assault, according to both victim interview using the ODARA actuarial risk assessment and their own perceptions. Findings imply an important role for partner assault clinics and the feasibility of the victim service sector's using the same actuarial risk assessments as the criminal justice system.

[Decision analysis--a novel approach for calculating the cost-efficiency of medical tests]

Before issuing an insurance policy (e.g. life, disability, critical illness), insurers will usually carry out a medical risk assessment in order to prevent adverse selection. Often, the health questions in the application form will not be sufficient for this purpose since most applicants are not well-versed in medical science and terminology. If the insurer needs additional medical information such as a private medical attendant's report or current laboratory tests, however, costs will be incurred, which usually have to be paid by the insurer. What is the minimum sum insured which makes it worthwhile for the insurer to conduct certain screening tests, for example? Both the costs of medical screening and the associated savings are difficult to measure and involve a variety of different factors. Moreover, most parameters can only be estimated with limited accuracy. Therefore, we have developed a new calculation model using a decision-analysis approach. The new model makes it possible to analyse complex situations while taking into account the uncertainty of parameter estimation. Our findings show that in Germany, for instance, current sum thresholds for older applicants could in many cases be lowered and would still be cost-effective.

Risk and safety assessment in child welfare: instrument comparisons

The assessment of risk is a critical part of child welfare agency practice. This review of the research literature on different instruments for assessing risk and safety in child welfare focuses on instrument reliability, validity, outcomes, and use with children and families of color. The findings suggest that the current actuarial instruments have stronger predictive validity than consensus-based instruments. This review was limited by the variability in definitions and measures across studies, the relatively small number of studies examining risk assessment instruments, and the lack of studies on case decision points other than the initial investigation.

Unguided clinical and actuarial assessment of re-offending risk: a direct comparison with sex offenders in Denmark

Meta-analyses suggest that actuarial risk assessments outperform unguided clinical judgment for prediction of recidivism in criminal offenders. However, there is a lack of direct comparisons of the predictive accuracy of clinical judgment and actuarial risk scales for sexual offenders. We followed up 121 male sex offenders (> or =18 years) subjected to pre-trial forensic psychiatric assessment in Denmark in 1978-1992 (mean post-detainment time = 16.4 years) to compare the predictive validity of unstructured clinical judgment of recidivism risk with that of the well-established Static-99 (Hanson and Thornton, Law and Human Behavior 24:119-136, 2000) and an extension of the Static-99, the Static-2002 (Hanson and Thornton, Notes on the development of Static-2002 (Rep. No. 2003-01), Public Safety and Emergency Preparedness Canada, Ottawa, Canada, 2003). The predictive accuracy of unguided judgment did not exceed chance for any sexual, severe sexual or any violent (sexual or non-sexual) reconviction (AUCs of the ROC curve = 0.52, 95%CI = 0.41-0.63; 0.50, 95%CI = 0.34-0.67; and 0.57, 95%CI = 0.40-0.73, respectively). In contrast, all three outcomes were predicted significantly better than chance by the Static-99 (AUC = 0.62, 95%CI = 0.52-0.72; 0.72, 95%CI = 0.59-0.84; and 0.71, 95%CI = 0.56-0.86) and the Static-2002 (AUC = 0.67, 95%CI = 0.57-0.77; 0.69, 95%CI = 0.56-0.83; and 0.70, 95%CI = 0.55-0.86). Static-99 outperformed clinical judgment for sexual recidivision (chi(2) = 5.11, df = 1, p < .05). The Static-2002 was significantly more accurate for the prediction of any sexual recidivism as compared to unguided clinical judgment but its advantage fell just short of statistical significance for severe sexual recidivism (chi(2) = 3.56, df = 1, p = 0.06). When tested for recidivism within 2 years, none of the three prediction methods yielded results significantly better than chance for any outcome. This direct trial of the unguided clinical method argues against its continued use for risk assessment of sexual offenders.

Pivot tables for mortality analysis, or who needs life tables anyway?

Actuarial life-table analysis has long been used by life insurance medical directors for mortality abstraction from clinical studies. Ironically, today's life actuary instead uses pivot tables to analyze mortality. Pivot tables (a feature/function in MS Excel) collapse various dimensions of data that were previously arranged in an "experience study" format. Summary statistics such as actual deaths, actual and expected mortality (usually measured in dollars), and calculated results such as actual to expected ratios, are then displayed in a 2-dimensional grid. The same analytic process, excluding the dollar focus, can be used for clinical mortality studies. For raw survival data, especially large datasets, this combination of experience study data and pivot tables has clear advantages over life-table analysis in both accuracy and flexibility. Using the SEER breast cancer data, we compare the results of life-table analysis and pivot-table analysis.

Predictive medical information and underwriting

Medical underwriting involves the application of actuarial science by analyzing medical information to predict the future risk of a claim. The objective is that individuals with like risk are treated in a like manner so that the premium paid is proportional to the risk of future claim.

The factor structure of static actuarial items: its relation to prediction

Principal components analysis was conducted on items contained in actuarial instruments used with adult sex offenders, including: the Rapid Assessment of Sex Offender Risk for Recidivism (RASORR), the Static-99, the Violence Risk Appraisal Guide (VRAG), the Sex Offender Risk Appraisal Guide (SORAG), and the Minnesota Sex Offender Screening Tool-Revised (MnSOST-R). In a data set that included child molesters and rapists (N = 311), six interpretable components were identified: Antisocial Behavior, Child Sexual Abuse, Persistence, Detached Predatory Behavior, Young and Single, and Male Victim(s). The RRASOR was highly correlated with Persistence, and the VRAG and SORAG were highly correlated with Antisocial Behavior. Antisocial Behavior was a significant predictor of violent recidivism, while Persistence and Child Sexual Abuse were significant predictors of sexual recidivism.

Comparison of two risk assessment instruments for sexual offenders

The current research examines the predictive validity of the Static-99 and the SORAG in predicting sexual and violent recidivism among a sample of 258 treated high-risk sexual offenders. While the SORAG was found to have moderate predictive accuracy for both sexual and violent recidivism over a 5-year follow-up period, the Static-99 was found to only predict sexual recidivism. As well, the actual recidivism rates in the current sample were compared to the published risk percentages for each of the instruments. For both the Static-99 and the SORAG the current sample re-offended at a lower rate than expected. Possible explanations for this finding are discussed.

Evaluation of the SORAG and the Static-99 on Belgian sex offenders committed to a forensic facility

This study evaluated the convergent and predictive validity of the Sex Offender Risk Appraisal Guide (SORAG; V. L. Quinsey, G. T. Harris, M. E. Rice, & C. A. Cormier, 1998) and the Static-99 (R. K. Hanson & D. Thornton, 1999, 2000) among 147 male sex offenders committed to a high-security hospital in Belgium (Centre de Défense Sociale "Les Marronniers"). Of the sample, 63.8% were child abusers (victims under 14 years of age), 24.6% were rapists (victims aged 14 years or more), and 11.5% were mixed-victim offenders (victims less than 14 years of age and victims aged 14 years or more). After an average follow-up period of 4.2 years (SD = 3.4 years), the sexual recidivism rate was 25.2%, the violent recidivism rate was 17.1%, and the general (any) recidivism rate was 33.1%. The SORAG and the Static-99 were moderately correlated with each other (r = .55), and both showed strong predictive validity for general and violent recidivism (ROC AUC's ranging from .68 to .72 for the total sample). Both instruments showed moderate predictive validity for sexual recidivism (AUC of .64 for SORAG and .66 for Static-99).

[Which cancerous diseases are significant for the risk assessment when underwriting life insurance?]

Cancer is the most important cause of death in life insurance and not cardiovascular disease! Life insurance is bought by persons aged between 15 and 65 years with an average of about 35 years. Therefore mortality statistics for the total population cannot be transferred to life insurance. In that segment cancer ranks before cardiovascular diseases. In females, cancer is even more important than in males because they are less prone to cardiovascular diseases in the age groups under consideration. Tumor mortality rises after age 40 and reaches its peak in males at age 70, in females the curve is moved towards higher ages and peaks at age 80.

Clinical-economic appropriateness of drug treatments: designing a method that combines evidence-based information and cost assessments to construct league tables accounting for the potential number of patients

This paper presents a method to assess drug treatment appropriateness, based on an original combination of economic analysis, pharmacoepidemiological techniques and evidence-based information. This method generates an index of clinical-economic appropriateness for the treatment under examination, by comparing the theoretically expected health gain (EHG) to the yearly national expenditure (EXPEND) on that drug and the amount of health that is thought to be gained in the 'real' patients (RHG). This paper reviews all the analyses conducted so far using this method, and discusses their main results. The primary aim of this article is to suggest a ranking approach for allocating the drug budgets of national health systems.

Conversion of mortality ratios to a numerical rating classification for life insurance underwriting-revisited

This is a commentary requested by the J Insur Med Editor to accompany a reprinting in this 2004 issue of my 1988 article on "Conversion of Mortality Ratios to a Numerical Rating Classification for Life Underwriting" (J Insur Med 1988;20:54-61). Topics discussed in this commentary include the distinction between short-term and long-term mortality follow-up in certain conditions, the format and the introductory text of the US Decennial Life Tables, the distinction between mortality rate and mortality probability, averaging mortality rates over a period of years, and the great value of the exemplary follow-up study used in the 1988 article.

Actuarial assessment of risk among sex offenders

The appraisal of risk among sex offenders has seen recent advances through the advent of actuarial assessments. Statistics derived from Relative Operating Characteristics (ROCs) permit the comparison of predictive accuracies achieved by different instruments even among samples that exhibit different base rates of recidivism. Such statistics cannot, however, solve problems introduced when items from actuarial tools are omitted, when reliability is low, or when there is high between-subject variability in the duration of the follow-up. We present empirical evidence suggesting that when comprehensive actuarial tools (VRAG and SORAG) are scored with high reliability, without missing items, and when samples of offenders have fixed and equal opportunity for recidivism, predictive accuracies are maximized near ROC areas of 0.90. Although the term "dynamic" has not been consistently defined, such accuracies leave little room for further improvement in long-term prediction by dynamic risk factors. We address the mistaken idea that long-term, static risk levels have little relevance for clinical intervention with sex offenders. We conclude that highly accurate prediction of violent criminal recidivism can be achieved by means of highly reliable and thorough scoring of comprehensive multi-item actuarial tools using historical items (at least until potent therapies are identified). The role of current moods, attitudes, insights, and physiological states in causing contemporaneous behavior notwithstanding, accurate prediction about which sex offenders will commit at least one subsequent violent offense can be accomplished using complete information about past conduct.

Sex offenders and actuarial risk assessments: ethical considerations

When assessing the recidivism risk of previously convicted sex offenders, the relevant ethical standards and practice guidelines obligate psychologists to acknowledge numerous limits related to their data and conclusions. For the actuarial instruments used in these assessments, the highest rates of classification accuracy are associated with greater specificity compared with sensitivity. Selecting cut-off scores to maximize sensitivity results in an inordinate frequency of false positive classifications. Attempts at maximizing specificity create an undesirable frequency of false negative classifications.Unfortunately, adjusted actuarial assessment cannot remedy these problems created by the sensitivity-specificity tradeoff. As an unstandardized procedure, the accuracy of adjusted actuarial assessment is severely limited. Consequently, civil proceedings for previously convicted sexual offenders rely on assessments of very limited accuracy. Undertaking these assessments, therefore, may be inconsistent with relevant ethical standards and practice guidelines.

Risk factors for ill health insurance claims

OBJECTIVES

This study examined the information available at application for income protection insurance, to determine if any factors were predictive of a claim. The strength and significance of such factors were assessed and a predictive model was developed.

BACKGROUND

The factors underlying life assurance risks are well known, but this is not the case for income protection insurance. For accurate underwriting of income protection insurance, it is important to know what information available at application has power to predict a claim. Improving the scientific accuracy of underwriting is good business practice, as well as answering the demands of disability legislation.

METHODS

We studied all data available at application for 959 current claimants and 1417 non-claimants, using a case-control study design. Information included applicants' description of their occupation, marital status, build and habits, plus a questionnaire asking about their personal health. For some applicants medical reports were available as well. Information was transcribed onto a database, and univariate and multivariate analyses were performed. A predictive scoring system was established and its performance measured by receiver operating characteristic curves.

RESULTS

Significant associations with claiming were found for many variables, including age (odds-ratio 1.04, p < 0.001), height (0.11, p = 0.03), smoking (2.10, p < 0.001), abstinence from alcohol (1.56, p = 0.01), recent medical advice (1.34, p = 0.06), and having had a lower gastrointestinal disorder (1.51, p = 0.04). Using all the information from the application, a predictive model was constructed. This model had good predictive power with an area under the receiver operating characteristic curve of 72%.

CONCLUSIONS

Classical underwriting factors were generally shown to have predictive power for income protection insurance. The predictive scoring strengthens the scientific basis for underwriting and could be developed to simplify and expedite the underwriting process.