Consumption and Saving Behavior of Older and Younger Baby Boomers in Korea

The 1998 Korean Survey of Family Income and Expenditures was used to examine the overall consumption and saving behavior of Korean baby boomers and compared the differences in consumption and saving behavior between older and younger boomers. The t -test results indicated that the younger boomers allocated a significantly higher percentage of their expenditures on food away from home, household appliances, transportation and communication than did the older boomers, whereas the older boomers spent higher amounts and allocated larger budget shares on their children's education than did the younger boomers. The results of Ordinary Least-Squares (OLS) regression analysis showed that, holding other factors constant, older boomers not only spent significantly more in the total consumption expenditures and education expenditures, but older boomers also saved significantly less than did younger boomers.     

Joint tests of non-nested models and general error specifications

This paper is concerned with joint tests of non-nested models and simultaneous departures from homoskedasticity, serial independence and normality of the disturbance terms. Locally equivalent alternative models are used to construct joint tests since they provide a convenient way to incorporate more than one type of departure from the classical conditions. The joint tests represent a simple asymptotic solution to the “pre-testing” problem in the context of non-nested linear regression models. Our simulation results indicate that the proposed tests have good finite sample properties.     

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.     

On nonparametric variogram estimation

A critical step for geostatistical prediction is estimation of variogram from the data. One of the popular methods estimating variogram is a smoothed version of classical nonparametric variogram estimator. In this paper we investigate its theoretical and empirical properties to provide useful information for using it. The main results are based on asymptotic theories (i.e., risk and central limit theorem) under nearly infill domain sampling. Simulation is also employed to make our points.     

Exploring the link between integrated leadership and public sector performance

This study develops the concept of integrated leadership in the public sector. Integrated leadership is conceived as the combination of five leadership roles that are performed collectively by employees and managers at different levels of the hierarchy. The leadership roles are task-, relations-, change-, diversity-, and integrity-oriented leadership. Using data from the Federal Human Capital Survey and Program Assessment Rating Tool, we analyze the relationship between integrated leadership and federal program performance. The findings from the empirical analysis indicate that integrated leadership has a positive and sizeable effect on the performance of federal sub-agencies. The study concludes with a discussion of the implications of the findings and limitations of the study.     

Personality and Subjective Well-Being: Evidence from South Korea

Although the statistically significant relationship between personality traits and subjective well-being (i.e., self-reported happiness and life satisfaction) is well-known in the field of positive psychology, some scholars still cast doubt on the external validity of this finding and the strength of personality dimensions vis-à-vis other individual-level determinants of subjective well-being such as income, employment status, marital status, self-reported health, and so on. Using a nationally representative, face-to-face survey fielded in South Korea in 2009, we find that personality traits (measured by the Five-factor Model)—particularly, Emotional Stability and Extraversion—are positively associated with happiness and life satisfaction, after controlling for other covariates. The effects of personality traits are often on par with, and sometimes even greater than, those of other well-known determinants.     

Comfort with discussions about death,religiosity, and attitudes about end‐of‐life care

In end‐of‐life (EOL) care research, death anxiety and religiosity are often overlooked. Terror management theory (TMT) may provide a useful conceptual model with which to examine how comfort discussing death and religiosity influence attitudes related to EOL care. A telephone‐based survey was conducted among community‐dwelling adults in the Unites States. Via random sampling, with over‐sampling of Hispanics/African Americans, 123 completed survey interviews (response rate = 46%) were analyzed. Respondents were more likely to have better attitudes toward EOL care if they were older or white, religiously active, and comfortable with the subject of death. Religiosity and comfort discussing death were correlated with each other and remained significant predictors of attitudes about EOL care even without demographic covariates. Findings suggest that promoting an open dialogue about mortality may improve attitudes about EOL care and utilization of palliative care services. The study also provides evidence about the utility and applicability of TMT for EOL care.     

Comparison on predictors of mental health service use among Asian older adults

Studies have mostly examined mental health service use of older Asian immigrant combining all Asian Americans into one group whereas immigration backgrounds and socioeconomic status of each Asian minority group are different. Therefore, this study aimed to identify predictors of mental health service use within specific ethnic groups among older Asian adults focusing on Chinese, Japanese, Korean, Filipino, and Vietnamese in California. The Behavioral Model for Vulnerable Populations (BMVP) is used to guide the secondary data analysis of a sample of 3,453 older Asian immigrants from the California Health Interview Survey (CHIS). Logistic and linear regression analyses are performed to examine predictors of mental health service use and the frequency of mental health service use, respectively. As results, mental health‐seeking patterns differ by ethnicity within the older Asian immigrant sample, not being married (Korean), higher levels of acculturation (Filipino), lower levels of neighborhood cohesion (Korean and Vietnamese), higher levels of perceived safety (Korean) and lower levels of perceived safety (Vietnamese), higher levels of mental distress (Korean and Filipino), and having perceived need (all) were related to more visits for mental health services. The study findings highlight the necessity of cultural competency services and programs for each Asian ethnicity.     

A biclustering algorithm for binary matrices based on penalized Bernoulli likelihood

We propose a new biclustering method for binary data matrices using the maximum penalized Bernoulli likelihood estimation. Our method applies a multi-layer model defined on the logits of the success probabilities, where each layer represents a simple bicluster structure and the combination of multiple layers is able to reveal complicated, multiple biclusters. The method allows for non-pure biclusters, and can simultaneously identify the 1-prevalent blocks and 0-prevalent blocks. A computationally efficient algorithm is developed and guidelines are provided for specifying the tuning parameters, including initial values of model parameters, the number of layers, and the penalty parameters. Missing-data imputation can be handled in the EM framework. The method is tested using synthetic and real datasets and shows good performance.