• Journal of Labour Economics
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• v.33 no.2
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• pp.91-134
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• 2010

This study examines job transition process and its lahor market performance by reasons of job separation, using the Employment Insurance DB(2000~07). The findings show that involuntary job changers lend to suffer greater loss in job spell and real wage than voluntary job changers, which seems to reflect their characteristics such as lower quality of job matching due to unsystematic job search, negative signaling effect in the labor market and decreasing availability of human capital in previous job. In addition, unemployment benefit eligible for involuntary job changers tends to prolong the period of unemployment, while increasing job spell in the following employment.

• Environmental and Resource Economics Review
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• v.19 no.2
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• pp.215-242
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• 2010

This study constructs a bayesian neoclassical DSGE model that applies oil usage. The model includes technology shocks, oil price shocks, and shocks to energy policies as exogenous driving forces. First, this study aims to analyze the roles of these exogenous shocks in the Korean business cycle. Second, this study examines the effects of long-term changes in the energy consumption structure, including the reduction in oil use as a share of energy consumption and improvement in oil efficiency. In the case of oil price shocks, results show that these shocks exert recessionary pressure on the economy in line with those obtained in the previous literature. On the other hand, shocks to energy policies, which reduce oil consumption per capital, result in opposite consequences to oil price shocks, decreasing oil consumption. Also, counterfactual exercises show that long-term changes in the energy consumption structure would mitigate the contractionary effects of oil price shocks.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.121-130
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• 2016

An ansemble of N players arranged in a circle play a spatially dependent Parrondo game B. One player is randomly selected to play game B, which is based on the toss of a biased coin, with the amount of the bias depending on states of the selected player's two nearest neighbors. The player wins one unit with heads and loses one unit with tails. In game A' the randomly chosen player transfers one unit of capital to another player who is randomly chosen among N - 1 players. Game A' is fair with respect to the ensemble's total profit. The games are said to exhibit the Parrondo effect if game B is losing and the random mixture game C is winning and the reverse-Parrondo effect if game B is winning and the random mixture game C is losing. We compute the exact mean profits for games B and C by applying a state space reduction method with lumped Markov chains and we sketch the Parrondo and reverse-Parrondo regions for $3{\leq}N{\leq}6$.

• Journal of the Korean Geotechnical Society
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• v.18 no.2
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• pp.97-105
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• 2002

Random properties of discontinuities were attributed to the limitation of test methods and lack of obtained data. Therefore, the uncertainties are pervasive and inevitable in rock slope engineering as well as other geotechnical engineering fields. The probabilistic analysis has been proposed to deal properly with the uncertainty. However, previous probabilistic approaches do not take account of the condition of kinematic instability but consider only kinetic instability. In this study, in order to overcome the limitation of the previous studies, the geometric characteristics as well as the shear strength characteristics in discontinuities are taken account into the probabilistic analysis. Then, the new approach to evaluate the probability of failure is suggested. The results of the deterministic analysis which was carried out to compare with the result of the probabilistic analysis, are somewhat different from those of the probabilistic approach. This is because the selected and used data in the deterministic approach do not take account of the random properties of discontinuities.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.2
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• pp.169-177
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• 2019

It is very important to understand the intention of a target ship to prevent collisions in multiple-ship situations. However, considering the intentions of a large number of ships at the same time is a great burden for the officer who must establish a collision avoidance plan. With a distributed algorithm, a ship can exchange information with a large number of target ships and search for a safe course. In this paper, I have applied a Distributed Stochastic Search Algorithm (DSSA), a distributed algorithm, for ship collision avoidance. A ship chooses the course that offers the greatest cost reduction or keeps its current course according to probability and constraints. DSSA is divided into five types according to the probability and constraints mentioned. In this paper, the five types of DSSA are applied for ship collision avoidance, and the effects on ship collision avoidance are analyzed. In addition, I have investigated which DSSA type is most suitable for collision avoidance. The experimental results show that the DSSA-A and B schemes offered effective ship collision avoidance. This algorithm is expected to be applicable for ship collision avoidance in a distributed system.

• The Korean Journal of Applied Statistics
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• v.36 no.5
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• pp.381-397
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• 2023

The most representative design used in clinical trials is randomization, which is used to accurately estimate the treatment effect. However, comparison between the treatment group and the control group in an observational study without randomization is biased due to various unadjusted differences, such as characteristics between patients. Propensity score weighting is a widely used method to address these problems and to minimize bias by adjusting those confounding and assess treatment effects. Inverse probability weighting, the most popular method, assigns weights that are proportional to the inverse of the conditional probability of receiving a specific treatment assignment, given observed covariates. However, this method is often suffered by extreme propensity scores, resulting in biased estimates and excessive variance. Several alternative methods including trimming, overlap weights, and matching weights have been proposed to mitigate these issues. In this paper, we conduct a simulation study to compare performance of various propensity score weighting methods under diverse situation, such as limited overlap, misspecified propensity score, and treatment contrary to prediction. From the simulation results overlap weights and matching weights consistently outperform inverse probability weighting and trimming in terms of bias, root mean squared error and coverage probability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.648-654
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• 2010

Request operations and release operations occur repeatedly in resource allocation systems. The process requesting a resource acquires one by any priority-based mechanism, and returns the resource after some periods. In this system, resource failures lead to delay of resource allocation, or to termination of process holding the failed resource. To analyze this process effectively, this paper designs a probabilistic ACSR, a process algebra that extends ACSR with the probabilistic choice operation. The ability to express/analyze both request-release rates and failure-recovery rates is illustrated using probabilistic ACSR.

• Journal of Labour Economics
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• v.24 no.1
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• pp.253-283
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• 2001

This paper attempts to account for the recent decline in the share of 'regular employees' among total employees. It finds, among other things, that the decline which began in 1993 is not associated with the changes in the composition of the worker groups that have differing tendency to work as regular employees. Overall, the decline in the share of regular employment is mainly due to the workers' increased transition probability out of 'regular employment', with the exception of the younger workers for whom the decrease in the rate of entry into 'regular employment' has also been an important reason of such a decline.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.129-138
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• 2010

The purpose of this study was to investigate the most cost-effectiveness screening strategies for cervical cancer in Korea. We calculated the age-specific cervical cancer incidence rate from Korea Central Cancer Registry (2003), and then estimated the schedule sensitivity, detection probability, and screening and confirmative costs of each screening strategy based on the stochastic process (Lee and Zelen, 1998). The efficiency of the screening strategy was evaluated by incremental cost-effectiveness analysis. The most effective strategy was every 3 years pap smear test between the age of 35 and 65 years in the cervical cancer screening. The findings of this study will be helpful to evaluate efficiency of cancer screening strategies, and to provide the theoretical background of development and assessment of early detection of cancer in Korea.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.969-977
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• 2016

Climate change affects the growth of crops which were planted especially in fields, and it becomes more important to use climate data to predict the yields of the major vagetables. The variation of the crop products caused by climate change is one of the significant factors for the discrepancy of the demand and supply, and leads to the price instability. In this paper, using a panel regression model, we predicted the garlic yields with the weather conditions of different regions. More specifically we used the panel data of the several climate variables for 15 main garlic production areas from 2006 to 2015. Seven variables (average temperature, average maximum temperature, average minimum temperature, average surface temperature, cumulative precipitation, average relative humidity, cumulative duration time of sunshine) for each month were considered, and most significant 7 variables were selected from the total 84 variables by the stepwise regression. The random effects model was chosen by the Hausman test. The average maximum temperature (January), the cumulative precipitation (March, October), the cumulative duration time of sunshine (April, October) were chosen among the variables as the significant climate variables of the model