The quantile-based flattened logistic distribution: Some properties and applications

In this paper, the quantile-based flattened logistic distribution has been studied. Some classical and quantile-based properties of the distribution have been obtained. Closed form expressions of L-moments, L-moment ratios and expectation of order statistics of the distribution have been obtained. A quantile-based analysis concerning the method of matching L-moments estimation is employed to estimate the parameters of the proposed model. We further derive the asymptotic variance–covariance matrix of the matching L-Moments estimators of the proposed model. Finally, we apply the proposed model to simulated as well as two real life datasets and compare the fit with the logistic distribution.     

Applicability of a Neuroprobabilistic Integral Risk Index for the Environmental Management of Polluted Areas: A Case Study

Recently, we developed a GIS-Integrated Integral Risk Index (IRI) to assess human health risks in areas with presence of environmental pollutants. Contaminants were previously ranked by applying a self-organizing map (SOM) to their characteristics of persistence, bioaccumulation, and toxicity in order to obtain the Hazard Index (HI). In the present study, the original IRI was substantially improved by allowing the entrance of probabilistic data. A neuroprobabilistic HI was developed by combining SOM and Monte Carlo analysis. In general terms, the deterministic and probabilistic HIs followed a similar pattern: polychlorinated biphenyls (PCBs) and light polycyclic aromatic hydrocarbons (PAHs) were the pollutants showing the highest and lowest values of HI, respectively. However, the bioaccumulation value of heavy metals notably increased after considering a probability density function to explain the bioaccumulation factor. To check its applicability, a case study was investigated. The probabilistic integral risk was calculated in the chemical/petrochemical industrial area of Tarragona (Catalonia, Spain), where an environmental program has been carried out since 2002. The risk change between 2002 and 2005 was evaluated on the basis of probabilistic data of the levels of various pollutants in soils. The results indicated that the risk of the chemicals under study did not follow a homogeneous tendency. However, the current levels of pollution do not mean a relevant source of health risks for the local population. Moreover, the neuroprobabilistic HI seems to be an adequate tool to be taken into account in risk assessment processes.     

The revolutions of 1989: Socialism,capitalism, and democracy

Many journalists and scholars will look for the correlation of that chain of spectacular transformations that changed, as if at one blow, the fates of tens of millions of individuals and the hitherto firm bipolar picture of the modern world ... Today, many people are talking and writing about the role of the intellectuals, students, and the theatre, or the influence of the Soviets' perestroika, and economic difficulties. They're right. I myself as a playwright would also add the influence of humour and honesty, and perhaps even something beyond us, something maybe even unearthly.Vaclav Havel, Preface to Gwyn Prins (editor),Spring in Winter: The 1989 Revolutions.     

CONFLICT RESOLUTION IN INVESTMENT DECISIONS: IMPLEMENTATION OF GOAL PROGRAMMING METHODOLOGY FOR DUAL-PURPOSE FUNDS*

Goal programming (GP) is designed to resolve allocation problems with conflicting goals. Both goals and constraints are incorporated in the allocational decision, and the objective function is stated in a way that, upon solution, yields a result “as close as possible” to the priority-weighted goals. The present paper applies GP methodology to the investment decision of dual-purpose funds (DPFs), that are required by law to pursue allocational decisions with potentially conflicting objectives. It provides an empirical demonstration that DPF managers could have improved their investment selection and subsequent performance by the use of GP methodology. Finally the paper stresses the importance of sensitivity analysis to improve both the goal-ranking and target-selection aspects of the methodology and provides a limited but illuminating empirical demonstration of post-optimality analysis.     

Decomposition of Changes in Korean Wage Inequality, 1998–2007

South Korea experienced a steep increase in wage inequality between the Asian financial crisis in 1997 and the global financial crisis in 2008. This paper investigates the causes of the sharp change during that time period by looking at the contributions of changes in the distributions of schooling and unionization. The effects are estimated applying two robust distributional function based decomposition methods on Korean Labor and Panel Survey data for the time period 1998–2007. The results suggest changes in the distribution of schooling can explain about 10 % of the changes in the 90/50 percentile wage gap. The declining unionization rate does not have much impact on the upward trend of Korean wage inequality. In addition, aggregate decomposition results suggest that changes in labor force composition can explain a significant proportion of the total wage changes in the upper-tail of the distribution. Based on our findings we provide a list of policy recommendations to address the wage inequality issue in Korea.     

Emotional Climate in Families Experiencing Homelessness: Associations with Child Affect and Socioemotional Adjustment in School

This study examined associations among family‐level risks, emotional climate, and child adjustment in families experiencing homelessness. Emotional climate, an indirect aspect of emotion socialization, was indexed by parents’ expressed emotion while describing their children. Sociodemographic risk and parent internalizing distress were hypothesized to predict more negativity and less warmth in the emotional climate. Emotional climate was expected to predict observer‐rated child affect and teacher‐reported socioemotional adjustment, mediating effects of risk. Participants were 138 homeless parents (64 percent African‐American) and their four‐ to six‐year‐old children (43.5 percent male). During semi‐structured interviews, parents reported demographic risks and internalizing distress and completed a Five Minute Speech Sample about their child, later rated for warmth and negativity. Children's positive and negative affect were coded from videotapes of structured parent‐child interaction tasks. Socioemotional adjustment (externalizing behavior, peer acceptance, and prosocial behavior) was reported by teachers a few months later. Hypotheses were partially supported. Parent internalizing distress was associated with higher parent negativity, which was linked to more negative affect in children, and parent warmth was associated with children's positive affect. Neither emotional climate nor child affect predicted teacher‐reported externalizing behavior or peer acceptance, but parental negativity and male sex predicted lower prosocial behavior in the classroom. Future research directions and clinical implications are discussed.     

Estimating ordered quantiles of two exponential populations with a common minimum guarantee time

The problem of estimating ordered quantiles of two exponential populations is considered, assuming equality of location parameters (minimum guarantee times), using the quadratic loss function. Under order restrictions, we propose new estimators which are the isotonized version of the MLEs, call it, restricted MLE. A sufficient condition for improving equivariant estimators is derived under order restrictions on the quantiles. Consequently, estimators improving upon the old estimators have been derived. A detailed numerical study has been done to evaluate the performance of proposed estimators using the Monte-Carlo simulation method and recommendations have been made for the use of the estimators.     

Protecting the economic health of the poor in India: Are health mutuals the right medicine?

In addition to government‐sponsored health insurance schemes (GSHIS), many microfinance institutions (MFIs) and community‐based organizations (CBOs) in India have started microinsurance health insurance schemes. These include health mutuals for the benefit of their members. This article explores these as an alternative health‐financing model in India. A literature search produced 926 relevant publications. After applying advanced search options and removing duplicates, abstracts of 324 papers were read and then 47 papers reviewed, and finally 29 were included in this review. Five key themes emerged: (1) “Health for all” arguments and opportunities in favour of micro health insurance schemes; (2) micro health insurance products; (3) impact of micro health insurance schemes; (4) systematic irregularities and regulatory framework; and (5) innovation. We also look at the emerging market patterns that will define micro health insurance products. Health mutuals can effectively provide mass health protection to the poor and not so poor through efficient business models, bespoke benefit packages and multiple payment plans. They can reduce financial vulnerability and improve health outcomes. While GSHIS can cover a substantial tranche of expected health‐related costs, the balance can be supplemented through innovative financial products that reduce financial risk.