• Journal of Labour Economics
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• v.31 no.3
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• pp.75-105
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• 2008

This paper examines the changes over lime in union relative wage effects during the period of 1988 and 2007. The union wage premium was 3.4 percent in average during the last 20 years. It has fallen in the boom years up to the mid-1990s, but has rapidly risen since the Asian financial crisis of 1997. Time series evidence suggests that the union wage premium is counter-cyclical, which means that it responds to economic conditions with a reverse direction. There has been also a fast increase in the unadjusted wage gap relative to regression-adjusted wage gap during the last 10 years in particular, implying favorable changes in the selection of workers into unionized companies.

• Journal of Forest and Environmental Science
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• v.39 no.4
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• pp.213-224
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• 2023

As abnormal weather events due to climate change continue to rise, landslide damage is also increasing. Given the substantial time and financial resources required for post-landslide recovery, it becomes imperative to formulate a proactive response plan. In this regard, landslide susceptibility analysis has emerged as a valuable tool for establishing preemptive measures against landslides. Accordingly, this study conducted an annual landslide susceptibility analysis using the history of landslides that occurred over many years in the Jeolla region, and analyzed areas with a high potential for landslides in the Jeolla region. The analysis employed an ensemble model that amalgamated 10 data-based models, aiming to mitigate uncertainties associated with a single-model approach. Furthermore, based on the cumulative data regarding landslide susceptible areas, this research identified regions vulnerable to recurring landslide damage in Jeolla region and proposed specific strategies for utilizing this information at various levels, including local government initiatives, adaptation plan development, and development approval processes. In particular, this study outlined approaches for local government utilization, the determination of adaptation plan types, and considerations for development permits. It is anticipated that this research will serve as a valuable opportunity to underscore the significance of information concerning regions vulnerable to recurring landslide damage.

• International Commerce and Information Review
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• v.13 no.3
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• pp.377-401
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• 2011

Under the WTO system, direct export support system that provides financial and tax related support is altogether prohibited. This presented an obstacle in strengthening competitiveness of Korean export business and in increasing exports continuously. One of the methods used to solve this problem was to actively leverage export insurance. In Korea, export insurance services have been conducted by the Korea Trade Insurance Corporation (k-sure) to promote export. Korea has been among the world's active users of the export insurance system. Given this situation, this paper examines the effectiveness of the Korea export insurance system in the promotion of export. In particular, this study analyzed about discriminating effects of the export insurance on the export of big and small-medium business. In order to analyze, We introduce a Export Supply Function model. In this paper, We construct two model. The one is about big business, the other is small-medium business. For empirical analysis, unit-root test was conducted to understand the safety of time series. The results show that all variables are not I(0) time series. Instead, they are I(1) time series. To this, cointegration verification was conducted based on the use of Johansen verification method to define the existence (or non-existence) of long-term balance relationship among variables. The results come out as follows. The export insurance of big business has a stronger effect on export than that of small-medium business. The cause of these results is due to the distinct structure of Korea industries. In view of the fact that the insurance can make the risk decreased. We can say that the export insurance affects the export of a high-risk country.

• Management & Information Systems Review
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• v.36 no.1
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• pp.161-180
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• 2017

This article studies the theory of corporate social responsibility; CSR. By examining the flow of CSR in the Korean market and empirical testing, investigates the relationship between CSR and corporation financial performance (CFP) in Korean enterprises. This paper places emphasis on the change in CSR as a result of globalization and explores the influence of CSR on CFP by using data from 2008 to 2014 of 528 Korean Firms, 1583 time series observations. We found that globalization had a positive influence on Korean CFP and that CSR activities derived from globalization exert a positive influence on CFP. Our findings show that CSR can strengthen the positive influence of globalization on CFP, and the Korean corporations' changing perception of CSR.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.791-799
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• 2015

In random walk hypothesis, we assume that current change of financial time series is independent of past values. It is interpreted as an existency of a unit root in ARMA models and many researches have been focused on whether ${\rho}$ < 1 or not. If some financial data are generated from an explosive autoregressive model, the chance of a bubble economy increases. We have to find the symptoms of it in advance. Since some well-known parameter estimators contain the parameter itself and other statistic is constructed under a specific parameter structure assumption, those are difficut to be adopted. In this paper we investigate a test for explosive autoregressive models using slope signs. We found the properties of the slope sign test statistic under both independent error and correlated error conditions, mainly by simulations.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.169-177
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• 2020

The purpose of this study is to forecast the sales of convenience store flagship products with nonlinear characteristics and time series characteristics. According to the results, the sales of 'Ice Cup' began to increase from March, reached the highest value in summer, especially July and August, and then decreased, revealing a seasonal pattern. Cigarettes showed a seasonal pattern of higher sales in summer and lower sales in winter and was predicted to decrease in sales in the future. This study provides an academic implication in that it focused on the top-selling products that affected an increase in financial performance in a specific convenience store, a method that has been hardly adopted by the existing studies.

• The Korean Journal of Financial Management
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• v.27 no.1
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• pp.209-237
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• 2010

This paper examines the relationship between information risk and equity premium in the Korean stock market. We use accruals quality as a proxy of information risk. Accruals quality (AQ) is estimated by Dechow and Dichev (2002) model, and then AQfactor is constructed based on the estimated AQ. Time-series and cross-sectional regression models are used to examine the relationship between information risk and equity premium, reflecting the critics of Core et al. (2008). The result of the paper shows that information risk proxied by accruals quality is not priced in equity premium in the Korean stock market. This result is consistent with Core et al. (2008) for US firms, but different with Francis et al. (2005) for US firms and Gray et al. (2008) for Australia firms. Also, the result shows that AQfactor is closely correlated with firm characteristic variables such as firm size. This implies that the effect of AQ on equity premium is more likely to arise from the pricing error due to firm characteristics rather than from an unknown risk factor.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.149-169
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• 2023

Purpose - The main purpose of this study is to develop the stress test model for Korean banks by exploring the optimal Monte Carlo simulation and BIS forecasting model. Design/methodology/approach - This study selects 15 Korean banks as sample financial firms and collects relevant 76 quarterly data for the period between year 2000 and 2018 from KRX(Korea Excange), Bank of Korea, and FnGuide. The Regression analysis, Unit-root test, and Monte Carlo simulation are hired to analyze the data. Findings - First, most of the sample banks failed to keep 8% BIS ratio for the adverse and severely Adverse Scenarios, implying that Korean banks must make every effort to realize better BIS ratios under adverse market conditions. Second, we suggest the better Monte Carlo simulation model for the Korean banks by finding that the more appropriate volatility should be different depending on variables rather than simple two-sigma which has been used in the previous studies. Third, we find that the stepwise regression model is better fitted than simple regression model in forecasting macro-economic variables for the BIS variables. Fourth, we find that, for the more robust and significant statistical results in designing stress tests, Korean banks are required to construct more valid time-series and cross-sectional data-base. Research implications or Originality - The above results all together show that the optimal volatility in designing optimal Monte Carlo simulation varies depending on the country, and many Korean banks fail to pass sress test under the adverse and severely adverse scenarios, implying that Korean banks need to make improvement in the BIS ratio.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.73-80
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• 2024

In this paper, we proposes a method to improve the accuracy of predicting the Korea Composite Stock Price Index (KOSPI) by combining topic modeling and Long Short-Term Memory (LSTM) neural networks. In this paper, we use the Latent Dirichlet Allocation (LDA) technique to extract ten major topics related to interest rate increases and decreases from financial news data. The extracted topics, along with historical KOSPI index data, are input into an LSTM model to predict the KOSPI index. The proposed model has the characteristic of predicting the KOSPI index by combining the time series prediction method by inputting the historical KOSPI index into the LSTM model and the topic modeling method by inputting news data. To verify the performance of the proposed model, this paper designs four models (LSTM_K model, LSTM_KNS model, LDA_K model, LDA_KNS model) based on the types of input data for the LSTM and presents the predictive performance of each model. The comparison of prediction performance results shows that the LSTM model (LDA_K model), which uses financial news topic data and historical KOSPI index data as inputs, recorded the lowest RMSE (Root Mean Square Error), demonstrating the best predictive performance.

• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.423-436
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• 2011

Many of the theoretical studies have considered herd behavior as a source of the volatility in financial markets, but there have been few empirical studies on the dynamic herding due to the technical difficulty of detecting herd behavior with time-series data. In this context, this paper proposes a new method for measuring time-varying herd behavior based on QR-GARCH model. Using daily data of KOSPI stocks, this paper provides some empirical evidence for strong and volatile herding among traders of stocks of medium firms, and shows that time-varying herd behavior in traders of some stocks has persistent autocorrelation.