• KDI Journal of Economic Policy
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• v.30 no.2
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• pp.225-270
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• 2008

We analyze macroeconomic consequences of pay-as-you-go (PAYGO) public pension system with a simple overlapping generations model. Contrary to large body of existing literatures offering quantitative results based on simulation study, we take another route by adopting a highly simplified framework in search of qualitatively tractable analytical results. The main contribution of our results lies in providing a sound theoretical foundation that can be utilized in interpreting various quantitative results offered by simulation studies of large scale general equilibrium models. We present a simple overlapping generations model with a defined benefit(DB) PAYGO public pension system as a benchmark case and derive an analytical equilibrium solution utilizing graphical illustration. We also discuss the modifications of the benchmark model required to encompass a defined contribution(DC) public pension system into the basic framework. Comparative statics analysis provides three important implications; First, introduction and expansion of the PAYGO public pension, DB or DC, result in lower level of capital accumulation and higher expected rate of return on the risky asset. Second, it is shown that the progress of population aging is accompanied by lower capital stock due to decrease in both demand and supply of risky asset. Moreover, risk premium for risky asset increases(decreases) as the speed of population aging accelerates(decelerates) so that the possibility of so-called "the great meltdown" of asset market cannot be excluded although the odds are not high. Third, it is most likely that the switch from DB PAYGO to DC PAYGO would result in lower capital stock and higher expected return on the risky asset mainly due to the fact that the young generation regards DC PAYGO pension as another risky asset competing against the risky asset traded in the market. This theoretical prediction coincides with one of the firmly established propositions in empirical literature that the currently dominant form of public pension system has the tendency to crowd out private capital accumulation.

• Korean Journal of Social Welfare
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• v.53
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• pp.31-49
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• 2003

Neo-liberalism, the most influential ideology in the current world, argues for the commercialization of social security programs and for the dissolution of the interventionist welfare state. From the neo-liberal viewpoint, social services become more efficient and more advantageous for recipients, when provided by the market, not by the state. It is also argued that the welfare of all social members is best secured when the market freely operates without any interference from the state. From the neo-liberal point of view, an argument was raised to commercialize the state-administered Workers' Compensation program of Korea in the mid-1990s. This argument was faced with strong resistances from labor unions and social welfare circles, and has disappeared since the economic breakdown and the restructuring of Korean society during the late 1990s. Butr, such an argument can emerge anytime as the nee-liberal ideology become more powerful. This article aims to examine the neo-liberal argument that the privatization of social security programs, through an increases in efficiency, improves the interests of the recipients as well as the whole society. For this, this article attempts to analyze the Workers' Compensation programs of the USA, which, from state to state, are administered by the state government or by private insurance companies. This study can serve as an effective critique for the neo-liberal argument, if it finds that state-administered Workers' Compensation programs are more efficient than those managed by insurance companies. This article's another aim is to assess the controversies over the privatization of the Workers' Compensation program of Korea during the mid to late 1990s. The controversies were more about which viewpoint is right and, in most cases, lacked empirical evidence. This study shall empirically criticize the argument for the privatization of the Workers' Compensation program.

• Food Science and Preservation
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• v.23 no.7
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• pp.1065-1073
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• 2016

This study investigated the sensory attributes and quality characteristics of Fuji apples based on market commodity price to provide data for quality index of Fuji apples. Samples were purchased from the Garak market (Seoul Agro-Fisheries & Food Corporation) and divided into four groups depending on the price such as group A, B, C, D. There were no significant differences in their volume and weight among groups. In the soluble solid content and total free sugar, A and B group (high price) showed higher content than those of C and D (low price) group. And also, the A group and B, C, D group showed 386.29 mg% and 320.09~359.28 mg% in the total organic acid content, respectively. As an sensory evaluation results, A group and B group were evaluated higher score than those of C and D group in the uniformity of red color and glossiness of skin and unique apple sensory attributes using quantitative descriptive analysis. Consumer test showed similar to quantitative descriptive analysis results in the various sensory attributes. In the analysis results between quality characteristics and sensory attributes of Fuji apples, total acceptability was correlated positively with titratable acidity (r=0.58), soluble solid (r=0.89), soluble solid content/titratable acidity ratio (r=0.42), total free sugar (r=0.36) and total organic acid (r=0.38). Based on principal component analysis of apple's quality characteristics, apples were primary separated along the first principal component (pH, acidity, soluble solid content, total free sugar, organic acid), which accounted for 66.01% of total variance. In addition, principal component analysis of sensory evaluation revealed a total variance for the quantitative descriptive of 55. 65% and a total variance for the consumer test of 55.84%.

• 한국노년학
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• v.40 no.4
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• pp.801-821
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• 2020

There are a number of prior studies on the poverty experience of Korean women, but little is known about the poverty experience of Korean elderly women in the U.S. The purpose of this study is to examine the poverty experiences of Korean elderly women who immigrated to the U. S. Qualitative case study methods were used to achieve these research objectives. Three Korean elderly women living in Oakland of California who received Supplemental Security Income (SSI) from the U.S. federal government were included in the study. The data were collected by conducting a total of six meetings per participant, and the researcher read the consent form directly to the participants and obtained a hand-written signature. The analysis and interpretation began by repeating the interview transcript several times, and the repeated keywords were to be understood in the context, focusing on time, space, and relationships with other people. The contextual understanding of Korean elderly women's experiences in poverty was interpreted in three dimensions: extending poverty in their mother country, double torture as female immigrants, and limiting labor due to aging and diseases. Before moving to the U.S., they had a difficult livelihood by farming and one of them had to live in poverty due to the bereavement to her husband. But even after moving to the U.S., they have continued to live in poverty. As female immigrants with low education and no special skills, they were incorporated into the periphery of the labor market in the industrialized U.S. and were forced to make a living with low wages. Korean elderly women were unable to return to the labor market in the surrounding areas due to aging and diseases, and were continuing their impoverished lives relying on SSI. From the findings, we discussed the role of the Korean immigrants community as a way to improve the quality of life for Korean elderly women in the U.S.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Journal of Preventive Medicine and Public Health
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• v.3 no.1
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• pp.1-16
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• 1970

The present status of control measures for public health important helminthic infections in Korea was surveyed in 1969 and the following results were obtained. The activities of parasitic examination and Ascaris treatment for the positives which were done during 1966 to 1969 were brought in poor result and could not decrease the infection rate. It is needed to improve or strengthen the activities. The mass treatment activities for paragonimiasis and clonorchiasis in the areas which were designated by the Ministry of Health were carried out during 1965 to 1968 with no good results in decrease of estimated number of the patients. There were too many pharmaceutical companies where many kinds of anthelmintics were produced. It may be better to reduce the number of anthelmintics produced and control the quality. The human feces, the most important source of helminthic infections, was generally not treated in sanitary ways because of the poor sewerage system and no sewage treatment plant in urban areas and insanitary latrines in rural areas. The field soils of 170 specimens were collected from 34 areas out of 55 urban and tourist areas where night soil has been prohibited by a regulation to be used as a fertilizer, and examined for parasites contamination with the result of Ascaris egg detection in 44%. Some kinds of vegetables of 64 specimens each from the supply agents of parasite free vegetables and general markets were collected and examined for parasites contamination with the results of Ascaris egg detection in 25% and 36% respectively. The parasite control activities and the ability of parasitological examination techniques in the health centers of the country were not satisfactory. The budget of the Ministry of Health for the parasite control was very poor. The actual expenditure needed for cellophane thick smear technique was 8 Won per a specimen. As a principle the control of helminthic infections might be led toward breaking the chain of events in the life cycle of the prasites and eliminating environmental and host factors concerned with the infections, and the following methods nay be pointed out. 1) Mass treatment might be done to eliminate human reservoirs of an infection. 2) Animal reservoirs which are related with human infections night be eliminated. 3) The excretes of reservoirs, particularly human feces, should be treated in sanitary ways by the means of sanitary sewerage system and sewage treatment plant in urban areas and sanitary latrines such as waterborne latrine, aqua privy and pit latrine in rural areas. The increase of national economical development and prohibition of the habit of using night soils as a fertilizer might be very important factors to achieve the purpose. 4) The control of vehicles and intermediate hosts might be done by the means of prohibition of soil contamination with parasites, food sanitation, insect control and snail control. 5) The improvement of insanitary attitudes and bad habits which are related with parasitic infections night be done by the means of prohibition of habit of using night soils as a fertilizer, and improving eating habits and personal hygiene. 6) Chemoprophylactic measure and vaccination may be effective to prevent the infections or the development of a parasite to adult in the bodies when the bodies were invaded by parasites. Further studies and development of this kind of measures are needed.

• Reproductive and Developmental Biology
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• v.29 no.3
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• pp.163-168
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• 2005

The aim of this study was to investigate the changes in insulin-like growth factor-I (IGF-I) and growth hormone (GH) in serum, the quantitation of spermato-genesis and the comparable relationships among these measurements during pubertal period in New Zealand White male rabbits. To investigate the age-related testicular changes in DNA contents of spermatogenic cells, the fine-needle testicular biopsies from males aged 10 to 28 wks were evaluated by flow cytometry(FCM). Body weight increased significantly between the ages of 12 and 20 wks (P<0.05) and reached 3.4 kg at 28 wks of age. The highest serum IGF-I level (451.3ng/mL) was observed at 20wks of age (P<0.05) and thereafter remained stable at low levels. Serum GH level at 18 wks of age was 183.3 pg/mL which was significantly higher compared to the other ages (P<0.05), and the rising time in serum GH tend to be somewhat earlier than that of IGF-I. The relative percentage of It-cells in testicular cell compartments was $48.2\%$ at the age of 18 wks which significantly increased than those of 16-wk-old (P<0.05) and thereafter increased with the advance of age to $68\%$. The percentage of 2C-cells in testis was $26.8\%$ at 18 wks of age which was significantly lower than $54.3\%$ at 16 wks old (P<0.05). The percentage of 4C-cells was constantly maintained $2\~6\%$ except the $9.9\%$ at 18 wks of age. In conclusion, the results suggest that the puberty onset occurred at about the 18 wks of age and that the IGF-I and GH in serum during the pubertal period showed the age/growth-specific changes and these changes might be related to the spermatogenesis. The DNA FCM combined with fine-needle testicular biopsy could offer a very sensitive method to monitor the quantitative spermatogenic events related to the puberty onset.

• Journal of Environmental Policy
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• v.13 no.4
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• pp.3-49
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• 2014

Growing interest of stakeholders on corporate responsibilities for environment and tightening environmental regulations are highlighting the importance of environmental management more than ever. However, companies' awareness of the importance of environment is still falling behind, and related academic works have not shown consistent conclusions on the relationship between environmental performance and economic performance. One of the reasons is different ways of measuring these two performances. The evaluation scope of economic performance is relatively narrow and the performance can be measured by a unified unit such as price, while the scope of environmental performance is diverse and a wide range of units are used for measuring environmental performances instead of using a single unified unit. Therefore, the results of works can be different depending on the performance indicators selected. In order to resolve this problem, generalized and standardized performance indicators should be developed. In particular, the performance indicators should be able to cover the concepts of both environmental and economic performances because the recent idea of environmental management has expanded to encompass the concept of sustainability. Another reason is that most of the current researches tend to focus on the motive of environmental investments and environmental performance, and do not offer a guideline for an effective implementation strategy for environmental management. For example, a process improvement strategy or a market discrimination strategy can be deployed through comparing the environment competitiveness among the companies in the same or similar industries, so that a virtuous cyclical relationship between environmental and economic performances can be secured. A novel method for measuring eco-efficiency by utilizing Data Envelopment Analysis (DEA), which is able to combine multiple environmental and economic performances, is proposed in this report. Based on the eco-efficiencies, the environmental competitiveness is analyzed and the optimal combination of inputs and outputs are recommended for improving the eco-efficiencies of inefficient firms. Furthermore, the panel analysis is applied to the causal relationship between eco-efficiency and economic performance, and the pooled regression model is used to investigate the relationship between eco-efficiency and economic performance. The four-year eco-efficiencies between 2010 and 2013 of 23 companies are obtained from the DEA analysis; a comparison of efficiencies among 23 companies is carried out in terms of technical efficiency(TE), pure technical efficiency(PTE) and scale efficiency(SE), and then a set of recommendations for optimal combination of inputs and outputs are suggested for the inefficient companies. Furthermore, the experimental results with the panel analysis have demonstrated the causality from eco-efficiency to economic performance. The results of the pooled regression have shown that eco-efficiency positively affect financial perform ances(ROA and ROS) of the companies, as well as firm values(Tobin Q, stock price, and stock returns). This report proposes a novel approach for generating standardized performance indicators obtained from multiple environmental and economic performances, so that it is able to enhance the generality of relevant researches and provide a deep insight into the sustainability of environmental management. Furthermore, using efficiency indicators obtained from the DEA model, the cause of change in eco-efficiency can be investigated and an effective strategy for environmental management can be suggested. Finally, this report can be a motive for environmental management by providing empirical evidence that environmental investments can improve economic performance.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.52 no.3
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• pp.239-248
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• 2007

Although high nutritional values and continuous identification of important functional substances of soybean [Glycine max (L.) Merrill.] promote consumption of soybean products worldwide, informations on quality of brand soybean is not enough for consumers. Total of 100 brand soybeans [32 for soypaste and source, 45 black testa (lage), and 17 black testa (small) or medicinal soybean and beansprout soybean] were collected at supermarkets and several external quality factors were analyzed. Brand soybeans were marked with the environmental friendly and intimating words along with soybean (white or yellow), black soybean (black-, frost-, late frost-, green or inner-green-), medicinal soybean and beansprout soybean. Among 100 brand soybeans 30% was 1 kg package and 59% was 500 g package, difference between printed and actual weights of 70% brand soybeans was ${\pm}1%$ and weights of 2/3 of brand soybeans were higher than printed weight. Range of 100 seed weights of soypaste and source, black testa (large) and black testa (small) and beansprout soybeans were $23.7{\sim}47.8g$, $21.9{\sim}44.5g$ and $9.5{\sim}15.0g$, respectively. Although ranges of 100 seed weights of soypaste and source and black testa (large) soybeans were similar, 63% of soypaste and source were less than 29 g, while 78% of black testa (large) soybeans were higher than 30 g. Although average and highest percentages of seeds separated with 6.7 mm sieve were similar with 87.4% and 99.9% for soypaste and source soybean and 86.5% and 99.5% for black testa (large) soybean, respectively, the lowest percentages were 70.7% for soypaste and source soybean and 14.4% for black testa (large) soybean. When 100 seed weight was greater than 35 g, 90% of seeds were remained on 6.7 mm sieve. On the other hand 100 g weight and percentage of seeds remained on 6.7 mm sieve showed significantly positive correlations [r=0.7488** for soypaste and source soybean and r=0.7874** for black testa (large) soybean when 100 seed weight was $20{\sim}30g$. Based on hilum color and/or appearance, 76% of brand soybeans collected (more than 90% in yellow testa soybeans) were found to be mixed more than 10% with other cultivars or landraces. Foreign materials such as sand, piece of clothe, wood piece, dead insects, other soybeans were found in 20% of brand soybeans. Average test weight of brand soybeans was 762g $L^{-1}$ with a range of $645{\sim}820g\;L^{-1}$. Soybeans from local markets were as good as brand soybeans in 100 seed weight, uniformity of seeds, weight of foreign materials and test weight.