Claim Dependence Induced by Common Effects in Hierarchical Credibility Models

In the usual credibility model, observations are made of a risk or group of risks selected from a population, and claims are assumed to be independent among different risks. However, there are some problems in practical applications and this assumption may be violated in some situations. Some credibility models allow for one source of claim dependence only, that is, across time for an individual insured risk or a group of homogeneous insured risks. Some other credibility models have been developed on a two-level common effects model that allows for two possible sources of dependence, namely, across time for the same individual risk and between risks. In this paper, we argue for the notion of modeling claim dependence on a three-level common effects model that allows for three possible sources of dependence, namely, across portfolios, across individuals and simultaneously across time within individuals. We also obtain the corresponding credibility premiums hierarchically using the projection method. Then we derive the general hierarchical structure or multi-level credibility premiums for the models with h-level of common effects.     

Fractionally integrated ARMA for crude palm oil prices prediction: case of potentially overdifference

Dealing with stationarity remains an unsolved problem. Some of the time series data, especially crude palm oil (CPO) prices persist towards nonstationarity in the long-run data. This dilemma forces the researchers to conduct first-order difference. The basic idea is that to obtain the stationary data that is considered as a good strategy to overcome the nonstationary counterparts. An opportune remark as it is, this proxy may lead to overdifference. The CPO prices trend elements have not been attenuated but nearly annihilated. Therefore, this paper presents the usefulness of autoregressive fractionally integrated moving average (ARFIMA) model as the solution towards the nonstationary persistency of CPO prices in the long-run data. In this study, we employed daily historical Free-on-Board CPO prices in Malaysia. A comparison was made between the ARFIMA over the existing autoregressive-integrated moving average (ARIMA) model. Here, we employed three statistical evaluation criteria in order to measure the performance of the applied models. The general conclusion that can be derived from this paper is that the usefulness of the ARFIMA model outperformed the existing ARIMA model.     

Improved CUSUM charts for monitoring process mean

In this paper, we propose new cumulative sum (CUSUM) and Shewhart-CUSUM (SCUSUM) control charts for monitoring the process mean using ranked-set sampling (RSS) and ordered RSS (ORSS) schemes. The proposed CUSUM charts include the Crosier's CUSUM (CCUSUM) and Shewhart-CCUSUM (SCCUSUM) charts using RSS, and the CUSUM, CCUSUM, SCUSUM and SCCUSUM charts using ORSS. Moreover, fast initial response features are also attached with these CUSUM charts to improve their sensitivities for an initial out-of-control situation. Monte Carlo simulations are used to compute the run length characteristics of the proposed CUSUM charts. Upon comparing the run length performances of the CUSUM charts, it turns out that the proposed CUSUM charts are more sensitive than their existing counterparts. A real dataset is used to explain the implementation of the proposed CUSUM charts.     

Mixed probability models for dry and wet spells

When identifying the best model for representing the behavior of rainfall distribution based on a sequence of dry (wet) days, focus is usually given on the fitted model with the least number of estimated parameters. If the model with lesser number of parameters is found not adequate for describing a particular data distribution, the model with a higher number of parameters is recommended. Based on several probability models developed by previous researchers in this field, we propose five types of mixed probability models as the alternative to describe the distribution of dry (wet) spells for daily rainfall events. The mixed probability models comprise of the combination of log series distribution with three other types of models, which are Poisson distribution (MLPD), truncated Poisson distribution (MLTPD), and geometric distribution (MLGD). In addition, the combination of the two log series distributions (MLSD) and the mixed geometric with the truncated Poisson distribution (MGTPD) are also introduced as the alternative models. Daily rainfall data from 14 selected rainfall stations in Peninsular Malaysia for the periods of 1975 to 2004 were used in this present study. When selecting the best probability model to describe the observed distribution of dry (wet) spells, the Akaike’s Information Criterion (AIC) was considered. The results revealed that MLGD was the best probability model to represent the distribution of dry spells over the Peninsular.     

Attachment Relationships and Psychological Adjustment of Married Adults

The present study explored relations among remembered parental (paternal and maternal) acceptance in childhood, spouse acceptance and psychological adjustment of adults. It also explored whether remembered childhood experiences of parental acceptance mediate the relation between perceived spouse acceptance and psychological adjustment. The sample consisted of 354 married adult men (178) and women (176). Results showed that the more accepting both men and women perceived their spouses to be, the better was their psychological adjustment. Similarly, the more accepting both men and women remembered their parents had been to them during childhood, the better was their psychological adjustment. Standard multiple regression analyses revealed that paternal acceptance mediated the relation between perceived spouse acceptance and the psychological adjustment of both men and women. In addition, remembered maternal acceptance mediated the relation between men’s (but not women’s) perceived spouse acceptance and psychological adjustment.     

Self-reported mental health problems and post-traumatic growth among children in Pakistan care homes

ABSTRACT

Children in care experience multiple risk factors, particularly in low-income countries such as Pakistan. The aim was to establish rates of mental health problems and their relationship with posttraumatic growth, as reported by 132 children aged 9–19 years, living in three care homes in Pakistan. Children reported high rates of posttraumatic stress (70.45%) and common mental health symptoms (43.94%) within the clinical range, but also high levels of posttraumatic growth. These findings highlight the high levels of mental health needs among children in residential care, as well as the importance of understanding factors that promote their posttraumatic growth and resilience.     

An empirical analysis of monetary and multidimensional poverty: evidence from a household survey in Pakistan

ABSTRACT

The present study computes multidimensional poverty and compares it with unidimensional estimates of poverty for the district of Mandi Bahuddin in the Punjab province of Pakistan for the years 2010 and 2014. By employing the Foster, Greer and Thorbecke (FGT) and Alkire-Foster Methods, the incidence, severity and depth of unidimensional and multidimensionality poverty was estimated. We found an increase in absolute and relative poverty levels in 2014 as compared to 2010. The multidimensional poverty in terms of household assets has also increased over time. However, the relative proportion of educational and health poverty towards MPI remains higher, thereby calling for a holistic approach to identify multidimensional poverty in the social sector. A comprehensive policy dossier needs to be framed for designing effective poverty alleviation and social welfare programmes in the Punjab, Pakistan.