• Journal of the Korean Regional Science Association
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• v.33 no.3
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• pp.3-19
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• 2017

The purpose of this paper is to analyze the impacts of regional industrial diversity on regional business cycle response to national volatility. We employed mean group and pooled mean group estimators of panel vector error-correction models in order to control unobserved heterogeneity of the port cities, such as Pusan, Ulsan and Incheon. The results show that in various industrial regions, short-term fluctuations in the unemployment rate are small compared to other regions. On the contrary, long-term volatility of manufacturing production index is low in those regions.

• Environmental and Resource Economics Review
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• v.28 no.3
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• pp.327-354
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• 2019

In this paper, we conducted panel data analysis considering spatial correlation between regions, which were not considered in previous papers in analyzing the causes of fine dust concentration in Korea. Many existing researchers implicitly assume the independence of the effects of incomes and other explanatory variables of adjoining countries(or regions). Using panel data on fine dust concentration, this paper has established that existing EKC can be established even when considering the spatial correlation of the region, and when these effects are not taken into account, it can be underestimated or overestimated on the effects and causes of fine dust concentration.

• Journal of Labour Economics
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• v.43 no.4
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• pp.179-203
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• 2020

This study aims to compare and analyze the impact of labor unions on job training programs using two different longitudinal data, Workplace Panel Survey (WPS) and Korean Labor and Inocme Panel Study (KLIPS). By applying the Correlated Random Effect (CRE) model to both individual-level and establishment-level data, we observe that labor unions increase the likelihood that establishments provide employees with job training programs and workers participate in the trainings. Our results shed light on the role of labor unions to increase the opportunities of job training programs for workers.

• Korean Journal of Labor Studies
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• v.19 no.1
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• pp.35-64
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• 2013

This paper explores whether or not a minimum wage increase can do much to alleviate working poor. For this purpose, I analyze transitions from working poor to working non-poor and to unemployment or non-economically active states, using KLIPS (Korea Labor and Income Panel Study). This study uses the multilevel multinomial logit model to control unobserved individual heterogenous characteristics. It finds that a minimum wage increase tends to cause a higher probability of transitions from working poor to working non-poor. It is also discovered that a minimum wage increase is not negatively related with the persistence of the working state. It is concluded that minimum wage increases are likely to be effective in improving the living standards of the 'working poor'.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.366-375
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• 2016

This study aims to investigate the impact of total, native-born, and foreign-born employment rates on the increases of GDP and per capita GDP for 24 OECD countries out of 34 countries depending on data availability. The panel data analysis is formed by a fixed-effects model which allows dummy variable in it to permit the intercept term to vary over time-series and cross-sectional units. Empirical evidences obtained by simple and multiple panel regressions reveal that the contribution to increasing of GDP by foreign-born employment is obviously lower than the one by native-born employment. And, native-born labor is substituted by foreign-born labor. It also has to be mentioned that the labor is playing a key role in increasing in national income. And, therefore, labor-related policy should be concerned on decreasing in labor productivity and segmentation of labor market resulted from inflow of foreign labor. It means that labor-related policy has to take care of not only the magnitude, but also the quality of foreign-born labor.

• Management & Information Systems Review
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• v.37 no.2
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• pp.209-233
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• 2018

This study investigates the question of how political and economic factors may affect the export of renewable energy technologies. The relationships are tested using panel data for 19 OECD member countries over the period 1992-2012. Before establishing the empirical model, the current study checks the characteristics of the panel data, which includes various panel framework analyses, such as tests for the presence of normality, structural breaks, first-order autocorrelation, heteroscedasticity, cross-sectional dependence, panel unit-root. From the panel framework analyses, a dynamic panel model is established to test the relationship between the variables examined in this study. In order to reduce the bias of the estimation of the dynamic panel model and obtain efficient parameters, this study uses the bias-corrected least square dummy variable(LSDVC) estimator to estimate the empirical model. The results of this study show that governmental policies expressed as coercive pressure and market size positively affect the export growth of renewable energy technologies. However, public pressure and traditional energy industry have no significant effects on export performance. Policy implications are presented based on the results of this study.

• Information Systems Review
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• v.25 no.3
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• pp.59-81
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• 2023

Elderly suicide problem has become worse in South Korea. With a rapid aging of the population, the trend of suicide among the elderly is expected to accelerate, preventing elderly suicide has been considered an important societal problem. Thus, we aim to investigate various factors that explain suicidal ideation and to develop a predictive model for suicidal ideation in the context of elderly people in South Korea. To this end, this study contributes to addressing the elderly suicide problem. By using seven-year panel data from the Korea Welfare Panel Survey, we extract various potential causal factors for elderly suicidal ideation based on interpersonal theory of suicide and social disorganization theory. Then a panel logit model was employed to assess the impacts of potential factors on suicidal ideation and deep learning and machine learning algorithms were used to develop a predictive model for suicidal ideation of elderly people. The results of our study provide practical implications for preventing elderly suicide by identifying causal factors of suicidal ideation and a high suicidal risk group of the elderly. This study sheds light on synergy of mixed methodology and provides various academic implications.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.436-448
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• 2015

This study examined one of the contemporary financial aspects, the level of corporate cash holdings for the firms belonging to the chaebols in the Korean capital markets. Being accompanied by various alternative econometric methodologies such as static and dynamic panel data model, stepwise OLS, and Fama-Macbeth modelm this research extended the preceding Kim's study (2015) in anticipation of validating the results to identify any financial factors which may significantly affect the chaebol firms' cash reserves. Several financial characteristics such as CASHFLOW, MVBV, REINVEST, and AGENCY, were found to be statistically significant factors on the level corporate liquidity, along with CCC as cash conversion cycle in the models. It may be plausible that any outcomes of this study may be applied to enhance the efficiency of financial strategies of the chaebol firms on cash holdings, thereby expediting the development of the domestic capital markets status quo toward the advanced one in the market classification.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1077-1085
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• 2017

In this study, we have found the major factors which affect Korean women's wage analysing the data provided by 2015 Korea Labor Panel Survey (KLIPS). In general, wage data is difficult to analyze because random sampling is infeasible. Heckman sample selection model is the most widely used method for analysing the data with sample selection. Heckman proposed two kinds of selection models: the one is the model with maximum likelihood method and the other is the Heckman two stage model. Heckman two stage model is known to be robust to the normal assumption of bivariate error terms. Recently, Marchenko and Genton (2012) proposed the Heckman selectiont model which generalizes the Heckman two stage model and concluded that Heckman selection-t model is more robust to the error assumptions. Employing the two models, we carried out the analysis of the data and we compared those results.

• Land and Housing Review
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• v.14 no.1
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• pp.33-46
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• 2023

This study investigated price factors for large apartment complexes in Seoul during the COVID-19 pandemic and compared Gangnam and non-Gangnam areas, which have been recognized as heterogeneous markets. We find that the change in apartment prices in large-scale complexes did not significantly affect the individual characteristics of apartments, unlike previous studies, but was affected by macroeconomic variables such as interest rates and money. On the other hand, considering the units of the interest rate and total monetary volume variables, the effects of two variables on the apartment sales price is significantly high. In addition, the Gangnam area model analysis shows that apartment prices are greatly affected by interest rates and currency volume, and, the non-Gangnam area model analysis shows that apartment prices are greatly affected by interest rates and currency volume, but the degrees are different from the Gangnam area model. Overall, our study shows that interest rates and money supply were the main factors of apartment price changes, but apartment prices in non-Gangnam areas are more sensitive to changes in interest rates and money supply.