A Study of Battered Women’s Purpose of Life and Resilience in South Korea

The principal objective of this study is to determine whether battered women’s purpose of life (meaning/value) affects resilience (self‐efficacy/communication efficiency/optimism). This purpose is meaningful in that it may help provide battered women with a new perspective of a changeable life, away from the negative perspectives frequently associated with domestic violence sufferers. The subjects of this study were 110 battered women staying at shelters located in Seoul and Gyeonggi Province, Korea. The survey was conducted between August 15 and September 20, 2010. The data were collected using questionnaires measuring sociodemographic variables, a purpose‐of‐life scale, and a resilience scale. The collected data were evaluated with frequency, correlation, and multiple regression analysis. The results of this study can be summarized as follows. First, the meaning and value of life positively influenced self‐efficacy. Second, only the meaning had a beneficial effect on communication efficiency. Third, only the value variable positively affected optimism. Therefore, this study implied that resilience is an important area in the context of spousal abuse. Based on these results, a program for enhancing the meaning of life is suggested to help domestic violence survivors to build up resilience.     

Impacts of child development accounts on parenting practices: evidence from a randomised statewide experiment

ABSTRACT

This study examines the impact of Child Development Accounts (CDAs) on parenting practices of mothers with young children in a statewide randomised experiment conducted in the United States. The experiment included 2704 primary caregivers of children born in Oklahoma during 2007: 1358 were randomly assigned to the treatment group and 1346 to the control group. Structural equation modelling suggests that the punitive-parenting score among treatment participants was .12 standard deviations smaller than that among control participants (p < . 05). Findings indicate that CDAs reduce punitive parenting, and may serve as an additional tool for positive parent–child interactions.     

Work of Full‐Time Mothers: Putting Voice to the Relational Theory of Working

The purpose of this qualitative research was to explore the work experience of middle‐class, Korean full‐time mothers in their 50s. Interviews, observations, and photographs were collected from 11 Korean full‐time mothers to understand their work and career experiences. The data were analyzed by a case study qualitative method of inquiry. The themes that emerged from the data were paths to becoming full‐time mothers, multiple working roles from relationships, dialectical characteristics of work, meaning of full‐time mothering, and regrets and internalized biases for full‐time motherhood. The findings illustrate how full‐time mothers experience a sense of meaning and mattering from their work; how relationships and work are intertwined in their lives; and how gender, social class, and culture influence the work and relationships of full‐time mothers. Implications for counselors and researchers are discussed.     

RENT-SEEKING FIRMS, CONSUMER GROUPS, AND THE SOCIAL COSTS OF MONOPOLY

Do consumers' consumer-surplus (CS)–defending activities increase the social costs of monopoly compared to when consumers are inactive? Given just one rent-seeking firm, consumers ' CS-defending activities generally increase the social costs of monopoly, but given two or more rent-seeking firms, such activities generally reduce the social costs. (JEL D72, L12)     

Insights on medical tourism: markets as networks and the role of strong ties

Despite a huge amount of speculation and expectation surrounding medical tourism, hard empirical evidence is only now beginning to emerge. This paper widens the focus of discussion by contrasting two country experiences (UK and Korea) which on the surface illustrate the diversity of medical tourism and little else. However, considered more comparatively, the accounts contribute toward wider, albeit tentative, theoretical understandings, and insights. The paper is drawn from two broad programs of empirical study conducted over three years in UK and Korea, respectively. The article is structured in three parts: first, a brief overview of policy, legislative, and accreditation frameworks that exist to govern medical tourist flows. Second, we present evidence around flows, demographics, treatment, and medical tourism for Korea and UK (both for supply and demand). Third, we examine conceptual and theoretical implications of this evidence. We argue that viewing medical tourism as a global market is problematic; some medical tourist markets are best viewed as networks with long-term exchange relationships; some specific areas of activity do function more strongly as price-related; decision making around medical tourism frequently involves a range of information and social networks (economic action as embedded social structure); and medical tourism is a function of globalization.     

Semiparametric methods in nonlinear time series analysis: a selective review

Time series analysis is a tremendous research area in statistics and econometrics. In a previous review, the author was able to break down up 15 key areas of research interest in time series analysis. Nonetheless, the aim of the review in this current paper is not to cover a wide range of somewhat unrelated topics on the subject, but the key strategy of the review in this paper is to begin with a core the ‘curse of dimensionality’ in nonparametric time series analysis, and explore further in a metaphorical domino-effect fashion into other closely related areas in semiparametric methods in nonlinear time series analysis.     

Robust multivariate mixture regression models with incomplete data

Multivariate mixture regression models can be used to investigate the relationships between two or more response variables and a set of predictor variables by taking into consideration unobserved population heterogeneity. It is common to take multivariate normal distributions as mixing components, but this mixing model is sensitive to heavy-tailed errors and outliers. Although normal mixture models can approximate any distribution in principle, the number of components needed to account for heavy-tailed distributions can be very large. Mixture regression models based on the multivariate t distributions can be considered as a robust alternative approach. Missing data are inevitable in many situations and parameter estimates could be biased if the missing values are not handled properly. In this paper, we propose a multivariate t mixture regression model with missing information to model heterogeneity in regression function in the presence of outliers and missing values. Along with the robust parameter estimation, our proposed method can be used for (i) visualization of the partial correlation between response variables across latent classes and heterogeneous regressions, and (ii) outlier detection and robust clustering even under the presence of missing values. We also propose a multivariate t mixture regression model using MM-estimation with missing information that is robust to high-leverage outliers. The proposed methodologies are illustrated through simulation studies and real data analysis.     

Stochastic approximation Monte Carlo EM for change-point analysis

In the expectation–maximization (EM) algorithm for maximum likelihood estimation from incomplete data, Markov chain Monte Carlo (MCMC) methods have been used in change-point inference for a long time when the expectation step is intractable. However, the conventional MCMC algorithms tend to get trapped in local mode in simulating from the posterior distribution of change points. To overcome this problem, in this paper we propose a stochastic approximation Monte Carlo version of EM (SAMCEM), which is a combination of adaptive Markov chain Monte Carlo and EM utilizing a maximum likelihood method. SAMCEM is compared with the stochastic approximation version of EM and reversible jump Markov chain Monte Carlo version of EM on simulated and real datasets. The numerical results indicate that SAMCEM can outperform among the three methods by producing much more accurate parameter estimates and the ability to achieve change-point positions and estimates simultaneously.     

Efficient method for identification of cyclic trends in incidence

Various methods for estimating the parameters of the simple harmonic curve and corresponding statistics for testing the significance of the sinusoidal trend are investigated. The locally reasonable method is almost fully efficient when the size of the trend is very small; however, the maximum likelihood method is preferred generally, especially when the trend is not very small. The log likelihood ratio test is more powerful than the R test which is based on locally reasonable estimates. The efficient method and the log likelihood ratio or equivalent tests are the best statistical techniques for identifying the cyclical trend. Thus they are the methods of choice when adequate computing facilities are available.