Investigating dependence between frequency and severity via simple generalized linear models

Recently, a body of literature proposed new models relaxing a widely-used but controversial assumption of independence between claim frequency and severity in non-life insurance rate making. This paper critically reviews a generalized linear model approach, where a dependence between claim frequency and severity is introduced by treating frequency as a covariate in a regression model for severity. As an extension of this approach, we propose a dispersion model for severity. For this model, the information loss caused by using average severity rather than individual severity is examined in detail and the parameter estimators suffering from low efficiency are identified. We also provide analytical solutions for the aggregate sum to help rate making. We show that the simple functional form used in current research may not properly reflect the real underlying dependence structure. A real data analysis is given to explain our analytical findings.     

Efficient and flexible model-based clustering of jumps in diffusion processes

Jump–diffusion processes involving diffusion processes with discontinuous movements, called jumps, are widely used to model time-series data that commonly exhibit discontinuity in their sample paths. The existing jump–diffusion models have been recently extended to multivariate time-series data. The models are, however, still limited by a single parametric jump-size distribution that is common across different subjects. Such strong parametric assumptions for the shape and structure of a jump-size distribution may be too restrictive and unrealistic for multiple subjects with different characteristics. This paper thus proposes an efficient Bayesian nonparametric method to flexibly model a jump-size distribution while borrowing information across subjects in a clustering procedure using a nested Dirichlet process. For efficient posterior computation, a partially collapsed Gibbs sampler is devised to fit the proposed model. The proposed methodology is illustrated through a simulation study and an application to daily stock price data for companies in the S&P 100 index from June 2007 to June 2017.     

Affect in Daily Career Decision Self‐Efficacy and Career Choice Anxiety

The authors investigated the impact of emotional intelligence on 2 career decision variables: daily career decision self‐efficacy and daily career choice anxiety. They also examined the mediating effects of daily positive affect on these variables. At baseline, 103 Korean undergraduate and graduate students completed questionnaires about emotional intelligence. Using a daily diary method, the authors also collected data on participants’ daily positive affect, daily career decision self‐efficacy, and daily career choice anxiety for 21 consecutive days. Hierarchical linear model analyses indicated that emotional intelligence predicted daily career decision self‐efficacy and daily career choice anxiety. These findings suggest that fostering emotional intelligence and daily positive affect could help students determine their future career. For individuals experiencing difficulty in the career decision process, counselors may foster career decision self‐efficacy and reduced career choice anxiety via enhancing clients’ emotional intelligence and daily positive affect.     

Self-efficacy and social support for psychological well-being of family caregivers of care recipients with dementia with Lewy bodies,Parkinson’s disease dementia,or Alzheimer’s disease

The study identified factors associated with depressive symptoms in family caregivers of persons with dementia with Lewy bodies, Alzheimer’s disease, or Parkinson’s disease dementia. An Internet-based survey generated 606 response sets. Regression analysis indicated that care recipients’ memory and behavioral problems, caregivers’ self-efficacy, grief, and tangible, emotional, and affectionate support were significantly associated with caregivers’ depressive symptoms. Self-efficacy mediated caregiver burden to improve psychological well-being. Social support mediated the association between caregiver grief and psychological well-being. Social workers can provide psychoeducational interventions to help caregivers to manage emotional distress and improve capacity to manage tasks related to the dementia.     

Same-sex marriage laws and demand for mortgage credit

Marriage for same-sex couples was only permitted in a limited number of states prior to the U.S. Supreme Court’s 2015 decision in Obergefell v. Hodges. We exploit panel variation across states prior to the Supreme Court decision to investigate the effect of marriage laws on demand for mortgage credit. Identification relies on the fact that states permitted same-sex marriage at different points in time, often through court order whereby the outcome and timing of ruling was unknown. We estimate that states permitting same-sex marriage experienced a 6–16% increase in same-sex mortgage applications after the policy was implemented. Federal recognition of marriage is associated with a stronger effect than state same-sex marriage prior to the repeal of the Defense of Marriage Act, but the effect of state-recognized marriage is also stronger than anti-discrimination policies in housing. Our findings provide important insight not only to the housing choices of same-sex households but the impact of marriage on all households.     

Racial/ethnic segregation and health disparities: Future directions and opportunities

Health researchers have investigated the association between racial segregation and racial health disparities with multilevel approaches. This study systematically reviews these multilevel studies and identifies broad trends and potential directions for future research on racial segregation and health disparities in the US. After searching databases including CINAHL and MEDLINE, we systematically reviewed 66 articles published between 2003 and 2019 and found four major gaps in racial/ethnic segregation and health disparities: (a) the concept of segregation was rarely operationalized at the neighborhood level, (b) except for the evenness and exposure dimension, other dimensions of segregation are overlooked, (c) little attention was paid to the segregation between whites and non‐black minorities, particularly Hispanics and Asians, and (d) mental health outcomes were largely absent. Future directions and opportunities include: First, other segregation dimensions should be explored. Second, the spatial scales for segregation measures should be clarified. Third, the theoretical frameworks for black and non‐black minorities should be tested. Fourth, mental health, substance use, and the use of mental health care should be examined. Fifth, the long‐term health effect of segregation has to be investigated, and finally, other competing explanations for why segregation matters at the neighborhood level should be answered.     

Differences in soil chemical properties with distance to roads and age of development in urban areas

The main objective of this study was to characterize variation in soil chemical properties with length of urbanization period and distance to roads. Urban boundaries from 1920’s (old), 1960’s (middle) and 2000’s (new) were identified for three cities in northeast Ohio: Massillon, Wooster and Canton. Within each identified historic boundary, soil samples were collected from two road-side and two interior lawns in one public school site in each city. Thus, there were three urban age and two distance-to-roads classes. Soil particle composition and basic chemical properties including pH, available phosphorus (P), exchangeable potassium (K), calcium (Ca), magnesium (Mg), cation exchange capacity (CEC), nitrate, total carbon (C), total nitrogen (N), and soil organic matter (SOM) were measured. Two notable spatio-temporal patterns appeared repeatedly in the data set. First, total C, total N and SOM were higher in the soils of old (>50 years) urban sites than of newly developed sites. Similar, but not always significant, trends in soil pH, and exchangeable Ca were also observed. Second, road-side soils had higher pH, Ca, total C and N than interior sites regardless of urban age. These data indicate that key soil chemical properties can vary in predictable ways with urban age and distance-to-roads classes. Such variations in key soil chemical properties may influence or reflect soil biota and biogeochemical processes in urban soils.     

From ‘sustainable rural communities’ to ‘social sustainability': giving voice to diversity in Mangakahia Valley, New Zealand

Despite widespread interest in the notion of sustainability, little progress has been made towards an understanding of its social dimensions. Nonetheless, the concept of ‘sustainable rural communities’ is embedded in popular, policy and academic discourses, where the needs of ‘rural communities’ are usually equated with those of farm families. Our ethnographic research in Northland, New Zealand illustrates the diverse interests to be found within ‘rural communities'. Interviews and participant observation were undertaken between August 1995 and July 1996 in the Mangakahia Valley. The increasing divergence in the ethnic, class and occupational makeup of the population has brought with it complexities in terms of what can be said to contribute to ‘sustainable rural communities'. We suggest that ‘sustainable rural communities’ be treated as a folk category, and instead, social science discourse should resort to the broader concept of social sustainability, which will have a locally defined content, not a universal definition, but will include elements of livelihood, social participation, justice and equity.     

Penalized likelihood approach for the four-parameter kappa distribution

The four-parameter kappa distribution (K4D) is a generalized form of some commonly used distributions such as generalized logistic, generalized Pareto, generalized Gumbel, and generalized extreme value (GEV) distributions. Owing to its flexibility, the K4D is widely applied in modeling in several fields such as hydrology and climatic change. For the estimation of the four parameters, the maximum likelihood approach and the method of L-moments are usually employed. The L-moment estimator (LME) method works well for some parameter spaces, with up to a moderate sample size, but it is sometimes not feasible in terms of computing the appropriate estimates. Meanwhile, using the maximum likelihood estimator (MLE) with small sample sizes shows substantially poor performance in terms of a large variance of the estimator. We therefore propose a maximum penalized likelihood estimation (MPLE) of K4D by adjusting the existing penalty functions that restrict the parameter space. Eighteen combinations of penalties for two shape parameters are considered and compared. The MPLE retains modeling flexibility and large sample optimality while also improving on small sample properties. The properties of the proposed estimator are verified through a Monte Carlo simulation, and an application case is demonstrated taking Thailand’s annual maximum temperature data.