• Journal of Labour Economics
• /
• v.43 no.4
• /
• pp.117-141
• /
• 2020

The paper focuses on the question of whether and how the labor underutilization indicator supplements the unemployment rate. The research is based on the differences in the labor market behavior among three groups of the not-employed; the unemployed, potential labor force and the rest of outside the labor force. The annual transition rate among the labor market states shows that the potential labor force has the explicit unmet need for employment different from the rest of the outside the labor force. The multinomial logit regression controlling the effects of individual characteristics rejects the hypothesis that the potential labor forces are behaviorally identical to the unemployed. The evidence shows that the two indices should be interpreted distinctively.

• International Commerce and Information Review
• /
• v.14 no.3
• /
• pp.97-112
• /
• 2012

This study aims to analyse determinants of payment balance of Korea, targeting 65 countries which concluded FTA with Korea in 2012 or are pursuing it with Korea( effectuation, agreement, negotiation and joint research). For an analysis model, economic and geographical variables of target countries were included in explanatory variables of the gravity model and divided values which indicate surpluses or deficits in trade with Korea were marked in dependent variables to perform a logistic analysis. If payment balance in trade between Korea and specific countries is a surplus, a value of 1 is given and if it is a deficit, a value of 0 is given. As a result of estimating the logit model, it was discovered that variables of GDP, GDP per person, total trade with trade partners, petroleum, landlocked countries and maritime powers were not statistically significant. However, variables of total trade, export dependency, import dependency, distance and mineral were statistically significant.

• Journal of Labour Economics
• /
• v.27 no.1
• /
• pp.1-25
• /
• 2004

In knowledge-based economy where the human capital has an strong compatibilities, the life cycle of technologies and skills get shorter, and the mobility of labor get greater, the role of the signal system of qualifications have greater importance. This article used the KLIPS(Korean Labor Institute Panel Study) data, and analysed the factors of the acquisition of qualifications and the employment and wage effects of the acquisition of qualifications by fixed effects logit model and random effects model. The lower school stratification acquired the more qualifications, and in the case of men the unemployed one acquired the more qualifications. The employment effects of the acquisition of qualifications are significant at first year and second year in women, but the men's of the employment effects of acquisition of qualifications are not significant. The wage effects of the acquisition of qualifications are not significant. The results of the regression suggest that in Korea the signal system of qualifications do not working, and that the qualifications in Korea need to reform.

• The Korean Journal of Applied Statistics
• /
• v.33 no.1
• /
• pp.47-59
• /
• 2020

In this paper, we present the longitudinal Markov binary regression model with t-link function when its transition order is known or unknown. It is assumed that logit or probit models are considered in binary regression models. Here, t-link function can be used for more flexibility instead of the probit model since the t distribution approaches to normal distribution as the degree of freedom goes to infinity. A Markov regression model is considered because of the longitudinal data of each individual data set. We propose Bayesian method to determine the transition order of Markov regression model. In particular, we use the deviance information criterion (DIC) (Spiegelhalter et al., 2002) of possible models in order to determine the transition order of the Markov binary regression model if the transition order is known; however, we compute and compare their posterior probabilities if unknown. In order to overcome the complicated Bayesian computation, our proposed model is reconstructed by the ideas of Albert and Chib (1993), Kuo and Mallick (1998), and Erkanli et al. (2001). Our proposed method is applied to the simulated data and real data examined by Sommer et al. (1984). Markov chain Monte Carlo methods to determine the optimal model are used assuming that the transition order of the Markov regression model are known or unknown. Gelman and Rubin's method (1992) is also employed to check the convergence of the Metropolis Hastings algorithm.

• Journal of Korea Trade
• /
• v.25 no.2
• /
• pp.111-133
• /
• 2021

Purpose - Although remittance payment in international trade settlements has played a bigger role in recent years, scant research is being done. This study is to zero in on analyzing determinants of international trade payments focused on remittance by constructing a payment prediction model. Design/methodology - This study categorizes the types of trade payments into advance remittance, post remittance, linked remittance, letter of credit, and mixed payment, and analyzes these after constructing a logit model. For empirical analysis, 147 survey data were collected for export manufacturers in Korea, and binominal logistic regression analysis was used to analyze the type of payment method the exporter chooses for trade transactions. Findings - The likelihood of choosing advance remittance increased as the exporters had non-recovery experiences with payments, and decreased as the market power of importers increased. The possibility of post remittance increased when the export amount was large and the character of the buyer was reliable. In the case of linked remittance, it was highly likely to be selected when payment efficiency was important in trade settlement. In addition, when competition among companies in the global market is intense and market uncertainty is high, the possibility of using a letter of credit decreases. It was also found that the greater the export amount, the greater the possibility of choosing advance remittance, and even if the transaction period was longer, exporters using a letter of credit continued to use it. Originality/value - Despite the high proportion of remittances in international trade settlements, it has been hard to find studies that reflect the practical characteristics of remittances. This study classified the types of remittance into advance remittance, post remittance, and linked remittance, and built a trade payment prediction model by adding a letter of credit and mixed payment. In addition, the originality of this study is recognized in that a logistic model was constructed and meaningful results were derived.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.30 no.1
• /
• pp.55-74
• /
• 2005

Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper employs a relatively new machine learning technique, support vector machines (SVMs). to bankruptcy prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use grid search technique using 5-fold cross-validation to find out the optimal values of the parameters of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM. we compare its performance with multiple discriminant analysis (MDA), logistic regression analysis (Logit), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.

• Korean Journal Plant Pathology
• /
• v.14 no.2
• /
• pp.150-156
• /
• 1998

To develop a model for prediction of turnip mosaic virus(TuMV) disease progress of Chinese cabbage based on weather information and number of TuMV vector aphids trapped in Taegwallyeong alpine area, data were statistically processed together. As the variables influenced on TuMV disease progress, cumulative portion(CPT) above 13$^{\circ}C$ in daily average temperature was the most significant, and solar radiation, duration of sunshine, vector aphids and cumulative temperature above $0^{\circ}C$ were significant. When logistic model and Gompertz model were compared by detemining goodness of fit for TuMV disease progress using CPT as independent variable, regression coefficient was higher in the logistic model than in the Gompertz model. Epidemic parameters, apparent infection rate and initial value of logistic model, were estimated by examining the relationship between disease proportion linearized by logit transformation equation, In(Y/Yf-Y) and CPT. Models able to describe the progression of TuMV disease were formulated in Y=100/(1+128.4 exp(-0.013.CPT.(-1(1/(1+66.7.exp(-0.11.day). Calculated disease progress from the model was in good agreement with investigated actual disease progress showing high significance of the coefficient of determination with 0.710.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.41 no.4
• /
• pp.1-8
• /
• 2018

Whole body fatigue detection is an important phenomenon and the factors contributing to whole body fatigue can be controlled if a mathematical model is available for its assessment. This research study aims at developing a model that categorizes whole body exertion into fatigued and non-fatigued states based on physiological and perceived variables. For this purpose, logistic regression was used to categorize the fatigued and non-fatigued subject as dichotomous variable. Normalized mean power frequency of eight muscles from 25 subjects was taken as physiological variable along with the heart rate while Borg scale ratings were taken as perceived variables. The logit function was used to develop the logistic regression model. The coefficients of all the variables were found and significance level was checked. The detection accuracy of the model for fatigued and non-fatigues subjects was 83% and 95% respectively. It was observed that the mean power frequency of anterior deltoid and the Borg scale ratings of upper and lower extremities were significant in predicting the whole body fatigued when evaluated dichotomously (p < 0.05). The findings can help in better understanding of the importance of combined physiological and perceived exertion in designing the rest breaks for workers involved in squat lifting tasks in industrial as well as health sectors.

• Journal of Global Scholars of Marketing Science
• /
• v.13
• /
• pp.135-158
• /
• 2004

On-line consumers have some visit behavior characteristics when they visit internet-shopping mall between visit-stage and purchase-stage. Therefore, information of on-line consumers have influenced on internet-shopping mall's profitabilities at site manager's perspectives. For examples, Are any on-line consumers continuous visiting under any situations? Or are any on-line consumers purchased on any specific internet-shopping mall? Expecially in this paper, researcher tried to understand visit behavioral characteristics of on-line consumers using two-stage mixture regression analysis. Throughout this process, it could be proposed method, which could be reinforced competitiveness of internet-shopping mall by segmental decision-making method. Additionally, it is expected that visit behavioral characteristics' information could be supplied strategic implications between visit-stage and purchase-stage Throughout empirical test it could be proved two-stage decision-making process, which decision-making process of on-line consumers would be processed visit-stage and purchase-stage. In this study, researcher proposed suitable response strategy after understanding visiting behavioral characteristics of on-line consumers. This paper has some academical contributions, which visit behavioral characteristics of on-line consumers could be grasped the meaning by site stickiness and navigation pattern.

• The Journal of the Korea Contents Association
• /
• v.17 no.4
• /
• pp.541-549
• /
• 2017

This research investigates the quantitative screening methods for the Grant Funding system and seeks for the efficient evaluation of a number of proposals. We search foreign cases of Grand Funding, but we found no appropriate model for using in Korea. Thus, we had to develope our own model for better screening. First, we analyse the existing evaluation system and find some problems and challenges. Second, we suggest a quantitative screening system for Grant Funding with a numeric model, and operates a tedious simulation by using the previous data and our suggested model. Third, we test the suggested model and find the optimal model by using simulation method The number of data analysed for simulation is larger than 200 thousands. Last, we suggest some brief policy implications based on the results in the paper.