The Impact of Covid-19 and its policy response on Korea's export

Thesis(Master) -- KDI School: Master of Public Policy, 2021The lockdown policies, which are composed of various measures like workplace closing, cancel public events, stay-at-home requirements, are adopted to block the transmission of COVID-19. It may succeed in blocking the infections, but it has negative impacts on the global economy in terms of production and consumption. In this research, the author tries to focus on the impacts of COVID-19 and its policy responses on Korea’s exports by using COVID-19 case and death data, policy response data from OxCGRT, immobility data from Google. The importing countries’ COVID-19 and the policy responses have negative impacts on Korea’s exports even though some of the indicators are not statistically significant. Also the country groups such as OECD, EU, ASEAN, and OPEC have shown the mitigation of negative impacts of COVID-19 and its policy responses and immobility. Korea’s COVID-19 situation, its policy responses and immobility in the workplace have positive impacts on Korea''s exports. The author also tries to check the baseline’s results by doing the estimation with product division, adding time-lag variables, and dividing the region by capital and non-capital area and confirms that the direction of coefficients except medical industries. This study contributes to suggest rough ideas about the impact of lockdown measures on Korea’s exports.I. Introduction II. Literature Review III. Model and Data IV. Estimation Results V. Robustness Check VI. Conclusion VII. References VIII. AppendixmasterpublishedSehee KI

A Frailty Approach for Survival Analysis with Error-prone Covariate

This paper discovers an inherent relationship between the survival model with covariate measurement error and the frailty model. The discovery motivates our using a frailty-based estimating equation to draw inference for the proportional hazards model with error-prone covariates. Our established framework accommodates general distributional structures for the error-prone covariates, not restricted to a linear additive measurement error model or Gaussian measurement error. When the conditional distribution of the frailty given the surrogate is unknown, it is estimated through a semiparametric copula function. The proposed copula-based approach enables us to fit flexible measurement error models without the curse of dimensionality as in nonparametric approaches, and to be applicable with an external validation study. Large sample properties are derived and finite sample properties are investigated through extensive simulation studies. The methods are applied to a study of physical activity in relation to breast cancer mortality in the Nurses’ Health Study

Anat as a precursor of Lady Wisdom in Proverbs 8:22–31

This dissertation investigates the identity of Lady Wisdom, the enigmatic figure in Proverbs 8:22–31. The presupposition of this investigation is a widely shared expert interpretation, namely, that Lady Wisdom is a multifaceted female divine figure whose origin and characteristics are interwoven with those of a number of ancient Near Eastern goddesses. The main contribution of this project is to argue that the Ugaritic goddess Anat be considered a possible precursor of Lady Wisdom. According to the author, a fluid and complementary relationship exists between Lady Wisdom’s depiction in the Hebrew Bible and Anat’s depiction in ancient Near Eastern religions, especially since certain aspects of their origin, status, and function are similar. The project also sheds light on the pivotal role of Lady Wisdom as a co-creator and mediator of the heavens and the earth. She should be regarded as a co-creator who is an active and mobile participant in God’s creative work; she is found not only in Proverbs but also in other biblical and deuterocanonical traditions. Moreover, she is a perfect mediator not only between the creation traditions and wisdom literature but also between the divine and human realms. Her mysterious identity is manifested in her own words and in others’ descriptions of her. Humans can either accept or reject Lady Wisdom, but only those who recognize and appreciate her divine knowledge are able to embrace truth in their lives

Improving power for rare‐variant tests by integrating external controls

Due to the drop in sequencing cost, the number of sequenced genomes is increasing rapidly. To improve power of rare‐variant tests, these sequenced samples could be used as external control samples in addition to control samples from the study itself. However, when using external controls, possible batch effects due to the use of different sequencing platforms or genotype calling pipelines can dramatically increase type I error rates. To address this, we propose novel summary statistics based single and gene‐ or region‐based rare‐variant tests that allow the integration of external controls while controlling for type I error. Our approach is based on the insight that batch effects on a given variant can be assessed by comparing odds ratio estimates using internal controls only vs. using combined control samples of internal and external controls. From simulation experiments and the analysis of data from age‐related macular degeneration and type 2 diabetes studies, we demonstrate that our method can substantially improve power while controlling for type I error rate.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138932/1/gepi22057.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138932/2/gepi22057_am.pd

A multilevel analysis of social capital and self-reported health: evidence from Seoul, South Korea

<p>Abstract</p> <p>Background</p> <p>This study aims to resolve two limitations of previous studies. First, as only a few studies examining social capital have been conducted in non-western countries, it is inconclusive that the concept, which has been developed in Western societies, applies similarly to an Asian context. Second, this study considers social capital at the individual-level, area-level and cross-levels of interaction and examines its associations with health while simultaneously controlling for various confounders at both the individual-level and area-level, whereas previous studies only considered one of the two levels. The purpose of this study is therefore to examine the associations between social capital and health by using multilevel analysis after controlling for various confounders both at the individual and area-levels (i.e., concentrated disadvantage) in non-western countries.</p> <p>Methods</p> <p>We conducted a cross-sectional survey from December 2010 to April 2011 in Seoul, South Korea. The target population included respondents aged 25 years and older who have resided in the same administrative area since 2008. The final sample for this study consisted of 4,730 respondents within all 25 of Seoul's administrative areas.</p> <p>Results</p> <p>In our final model, individual-level social capital, including network sources (OR = 1.23; 95% CI = 1.11-1.37) and organizational participation (OR = 2.55; 95% CI = 2.11-3.08) was positively associated with good/very good health. Interestingly, the individual × area organizational participation cross-level interaction was negatively associated with good/very good health (OR = 0.40; 95% CI = 0.32-0.50), indicating that in areas with higher organizational participation, individuals with high organizational participation were less likely to report good/very good health when compared to low organizational participation individuals.</p> <p>Conclusion</p> <p>Our study provides evidence that individual-level social capital is associated with self-reported health, even after controlling for both individual and area-level confounders. Although this study did not find significant relationships between area-level organizational participation and self-reported health, this study found the cross-level interaction for social capital. Hence, in areas with lower organizational participation, the probability of reporting good/very good health is higher for individuals with high organizational participation than individuals with low organizational participation. This study, albeit tentatively, suggests that policy makers should focus upon social capital when making policies which aim to enhance one's health.</p

Joint partially linear model for longitudinal data with informative drop‐outs

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136540/1/biom12566.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136540/2/biom12566_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136540/3/biom12566-sup-0001-SuppData.pd

Estimators for longitudinal latent exposure models: examining measurement model assumptions

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136711/1/sim7268_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136711/2/sim7268.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136711/3/sim7268-sup-0001-Supplementary.pd

A Pairwise Likelihood Augmented Estimator for the Cox Model Under Left-Truncation

Survival data collected from prevalent cohorts are subject to left-truncation and the analysis is challenging. Conditional approaches for left-truncated data under the Cox model are inefficient as they typically ignore the information in the marginal likelihood of the truncation times. Length-biased sampling methods can improve the estimation efficiency but only when the stationarity assumption of the disease incidence holds, i.e., the truncation distribution is uniform; otherwise they may generate biased estimates. In this paper, we propose a semi-parametric method for the Cox model under general left-truncation, where the truncation distribution is unspecified. Our approach is to make inference based on the conditional likelihood augmented with a pairwise likelihood which eliminates the unspecified truncation distribution, yet retains the information about the regression coefficients and the baseline hazard function in the marginal likelihood. An iterative algorithm is provided to solve for the regression coefficients and the baseline hazard simultaneously. The proposed estimator is consistent and asymptotically normal with a closed-form consistent variance estimator. Simulations show a substantial efficiency gain in both the regression coefficients and the cumulative baseline hazard over the conditional approach estimator. Even when the stationarity assumption holds, our estimator results in better efficiency than some length-biased sampling estimators. An application to the analysis of a chronic kidney disease cohort study illustrates the utility of the method

Transforming Dress

In this paper, we produce a fashion show in which a dress is transformed over time, with a storyline of a robot that experiences some emotional changes after falling in love, sheds a symbolic teardrop and at the end becomes a lovely woman. This transformability, which cannot be done in a real fashion show, could open the potential for a new kind of creativity in the fashion industry