THE RELATIONSHIP BETWEEN PUBLIC OPINION AND SOUTH KOREA’S NUCLEAR DETERRENCE ENHANCEMENT POLICY

Many people are in favor of South Korea enhancing nuclear deterrence options (the redeployment of U.S. tactical nuclear weapons or its indigenous nuclear weapons). Since North Korea’s first nuclear test in 2006, a majority of those surveyed in opinion polls have favored enhancing nuclear deterrence. The results of these polls have attracted the attention of domestic and foreign media as well as those in politics and academia. However, questions remain, such as what this public opinion means both implicitly and explicitly, and what factors have prevented public opinion from influencing the government’s policy-making decisions. This thesis focuses on domestic political factors rather than international factors, such as the feasibility and effectiveness of nuclear deterrence options. This thesis argues that public opinion in favor of enhancing nuclear deterrence options did not influence the government’s policy formation due to 1) characteristics for the public opinion in favor of enacting a new policy, and 2) the existence of alternative policies to the enhancing nuclear deterrence options.Dae-wi, Republic of Korea ArmyApproved for public release. Distribution is unlimited

Growth in Child Executive Function and Maternal Depressive Symptoms: Maternal Sensitivity as a Mediator

Education and Human Ecology: 3rd Place (The Ohio State University Edward F. Hayes Graduate Research Forum)This study examined the mediating role of maternal sensitivity in the links between trajectories of maternal depressive symptoms and developmental trajectories of child executive function (EF). Participants were 1,364 children and their mothers from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development date set. Maternal depressive symptoms (from 6 months through grade 5) and sensitivity (from 36 months grade 5) decreased over time, while child EF (from grade 1 to 5) increased over time. Mediation effects were found: first, low levels of maternal depressive symptoms at 6 months predicted high levels of child EF at grade 1 through increased levels of maternal sensitivity at 36 months; and second, lower levels of maternal depressive symptoms at 6 months were associated with greater growth in child EF through higher levels of maternal sensitivity at 36 months. The results suggest that maternal depressive symptoms in early childhood are important for children’s EF growth in middle childhood, and furthermore, maternal sensitivity is suggested to serve a mechanism linking the associations between early maternal depressive symptoms and child executive function growth.A one-year embargo was granted for this item

Fluctuation of Monthly Birth Number, By Chance or By Intention

There are different number of births per month in South Korea. In general, there are more births in January and fewer births in December comparing to the average monthly births of the year. Does it happen by chance or by intention? This study raises three hypotheses for it – 1) random fluctuation, 2) parents’ seasonal preference, and 3) parents’ educational purpose. From the analysis of vital registration data from 1997 to 2018, the most appealing hypothesis was the parents’ educational purpose. The author argues that the opportunity preference was stronger until early 2000 and the path dependency preference after the mid-2000s. Reflecting the rule change of elementary entrance age, the both theories support why January births are preferred by parents. The number of births from other than hospital also imply that there were intentional fabrications of birth registration. But these intentional changes become weaker recently. Especially after the abolition of guarantee of the neighborhood system at the end of 2016, the monthly birth number become stable and looks changing by chance

Inside the black box: Neural network-based real-time prediction of US recessions

Feedforward neural network (FFN) and two specific types of recurrent neural network, long short-term memory (LSTM) and gated recurrent unit (GRU), are used for modeling US recessions in the period from 1967 to 2021. The estimated models are then employed to conduct real-time predictions of the Great Recession and the Covid-19 recession in US. Their predictive performances are compared to those of the traditional linear models, the logistic regression model both with and without the ridge penalty. The out-of-sample performance suggests the application of LSTM and GRU in the area of recession forecasting, especially for the long-term forecasting tasks. They outperform other types of models across 5 forecasting horizons with respect to different types of statistical performance metrics. Shapley additive explanations (SHAP) method is applied to the fitted GRUs across different forecasting horizons to gain insight into the feature importance. The evaluation of predictor importance differs between the GRU and ridge logistic regression models, as reflected in the variable order determined by SHAP values. When considering the top 5 predictors, key indicators such as the S\&P 500 index, real GDP, and private residential fixed investment consistently appear for short-term forecasts (up to 3 months). In contrast, for longer-term predictions (6 months or more), the term spread and producer price index become more prominent. These findings are supported by both local interpretable model-agnostic explanations (LIME) and marginal effects

Real-time Prediction of the Great Recession and the Covid-19 Recession

A series of standard and penalized logistic regression models is employed to model and forecast the Great Recession and the Covid-19 recession in the US. These two recessions are scrutinized by closely examining the movement of five chosen predictors, their regression coefficients, and the predicted probabilities of recession. The empirical analysis explores the predictive content of numerous macroeconomic and financial indicators with respect to NBER recession indicator. The predictive ability of the underlying models is evaluated using a set of statistical evaluation metrics. The results strongly support the application of penalized logistic regression models in the area of recession prediction. Specifically, the analysis indicates that a mixed usage of different penalized logistic regression models over different forecast horizons largely outperform standard logistic regression models in the prediction of Great recession in the US, as they achieve higher predictive accuracy across 5 different forecast horizons. The Great Recession is largely predictable, whereas the Covid-19 recession remains unpredictable, given that the Covid-19 pandemic is a real exogenous event. The results are validated by constructing via principal component analysis (PCA) on a set of selected variables a recession indicator that suffers less from publication lags and exhibits a very high correlation with the NBER recession indicator

Parenthood Wage Differentials in South Korea

Is there wage differential by parenthood? If then, how is it different by gender and cohort? This study is to study motherhood penalty and fatherhood premium in South Korea using the Korean Labor and Income Panel Study (KLIPS) data. In the essence of the study overall, men have gained the fatherhood premium, while women do not. In addition, the fatherhood premium is getting weaker, but the motherhood penalty is getting stronger in Korean case. It shows that young generation including young men are suffering from wage penalty due to parenthood

Motherhood Wage Discrimination, Evidences from Korean Labor and Income Panel Study (KLIPS) 1998-2017, South Korea

This study uses the KLIPS data between 1998 to 2017 to examine whether wage discrimination between mothers and non-mothers exists in the South Korea labor market. We compare the amount of wage gap from OLS model to a variety of Fixed effect models which have different types of productivity measures. The results show that mothers are discriminated against in the labor market. Interestingly, the amount of discrimination is bigger for highly-educated women than less-educated women. Especially the semi-professional workers who have the educational attainment level at college degree or higher are the most serious victim of the motherhood wage discrimination

Protease Activity: Meeting Its Theranostic Potential

This themed issue provides up-to-date review and research articles covering the theranostic applications in the combined fields of protease research, diagnostics and drug development

Rural/Urban Differences in the Predictors of Opioid Prescribing Rates among Medicare Part D Beneficiaries 65 Years of Age and Older

Purpose: While research has been done comparing rural/urban differences in opioid prescribing to the disabled Medicare Part D population, research on opioid prescribing among the aged Medicare Part D population is lacking. This study aims to fill this gap by exploring the predictors of opioid prescribing to aged Medicare Part D beneficiaries and investigating whether these predictors vary across rural and urban areas. Methods: This is an analysis of ZIP Codes in the continental United States (18,126 ZIP Codes) utilizing 2017 data from Centers for Medicare & Medicaid Services. The analytic approach includes aspatial descriptive analysis, exploratory spatial analysis with geographically weighted regression, and explanatory analysis with spatial error regime modeling. Findings: Both beneficiary and prescriber characteristics play an important role in determining opioid prescribing rates in urban ZIP Codes, but most of them fail to explain the opioid prescribing rates in rural ZIP Codes. Conclusion: We identify potential spatial nonstationarity in opioid prescribing rates, indicating the complex nature of opioid-related issues. This means that the same stimulus may not lead to the same change in opioid prescribing rates because the change may be place specific. By understanding the rural/urban differences in the predictors of opioid prescribing, place-specific policies can be developed that can guide more informed opioid prescribing practices and necessary interventions

Social Isolation, Residential Stability, and Opioid Use Disorder among Older Medicare Beneficiaries: Metropolitan and Non-Metropolitan County Comparison

Research has shown that the prevalence of opioid use disorder (OUD) may rise substantially as society ages, but this issue receives the least attention in the literature. To address this gap, this study utilizes county-level data from multiple data sources (1) to investigate whether social isolation is associated with OUD prevalence among older Medicare beneficiaries, (2) to examine whether and how residential stability moderates the association between social isolation and OUD prevalence in US counties, and (3) to determine if there are any differences in these associations between metropolitan and nonmetropolitan counties. The results show that social isolation is a significant factor for county-level OUD prevalence, regardless of metropolitan status. In addition, counties with high residential stability have low prevalence of OUD among older adults and this association is stronger in metropolitan than in nonmetropolitan counties. Nonetheless, high levels of residential stability reinforce the positive relationship between social isolation and OUD prevalence. As a result, when developing policies and interventions aimed at reducing OUD among older adults, place of residence must be taken into account