• Journal of Labour Economics
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• v.37 no.2
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• pp.79-103
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• 2014

Previous studies show that tall people have better labor market outcomes, but controlling for their abilities reduces the size of height effects. This implies that a failure to properly control for one's ability could overestimate the OLS estimate. This paper contributes to the literature by being the first to control for individual fixed effects (FE) and to examine height effects on the probability of one's attaining a leadership position. The data used are panel data of a cohort obtained during the cohort's middle and high school years. In OLS estimation, this paper finds positive height effects for boys. However, when controlling for individual fixed effects, the estimate is not statistically significant. For girls, the height effects are found on neither OLS nor FE model.

• Korea Trade Review
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• v.44 no.1
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• pp.45-56
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• 2019

The purpose of this study is to investigate the relationship between foreign investment and carbon emissions in the Korean electricity sector, the causal relationship between the foreign investment invested in the electric power sector in the 16 regional regions and the carbon emissions in the region, The purpose of this study is to analyze the effects of foreign investment on these sectors and the carbon footprint of these sectors using Panel Random Effect Analysis, Panel VAR and OLS models. A panel analysis of foreign investment and regional carbon emissions showed that there was a causal relationship. Based on this analysis, OLS analysis showed that 7 out of 16 metropolitan areas were foreign investment And carbon emissions were significant. In the remaining six regions except Gwangju, there was a causal relationship between foreign investment in the local power sector and the reduction of carbon emissions. After categorizing the electric power industry by device, process, purpose and number of employees, causality also appeared in relation to foreign investment in these sectors and their carbon emissions. Through this study, the authors suggest that foreign investment can be a way to solve not only the financial burden of carbon emission problem, but also the development of national economy and industry through the inflow of capital and advanced new technology.

• International Commerce and Information Review
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• v.14 no.3
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• pp.307-322
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• 2012

The purpose of this paper is to examine determinants of export to the East Asia region, using panel unit root, panel cointegration framework, panel VECM (vector error correction model), panel FMOLS (fully modified OLS). Different panel unit root tests confirm that the data series are integrated processes with unit roots. When applying cointegration tests to long-run effect for aggregate panel data, a primary concern is to construct the estimators in a way that does not constrain the transitional dynamics to be similar among different countries of the panel. The regression equations are estimated by various panel cointegration estimators. The panel data causality results reveal that exchange rates has unidirectional effects on export and GDP, and there exists bidirectional causality between export and GDP. Also, the results from the panel FMOLS tests overwhelmingly reject the null hypothesis of zero coefficient. The panel cointegrating vectors show that the export has positive relationship with the GDP and ODI (overseas direct investment).

• Asian Journal of Atmospheric Environment
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• v.11 no.3
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• pp.194-201
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• 2017

This study investigates the factors that affect China's air pollution using city-level panel data and spatial econometric models. We address three air pollutants ($PM_{10}$, $SO_2$, and $NO_2$) present in 30 cities in China between 2004-2012 using global OLS and spatial models. To develop the spatial econometric analysis, we create a spatial weights matrix to define spatial patterns based on two neighborhood criteria - the queen contiguity and k nearest neighbors. The results show that the estimated coefficients are relatively consistent across different spatial weight criteria. The OLS models indicate that the effect of green spaces is statistically significant in decreasing the concentrations of all air pollutants. In the $PM_{10}$ and $SO_2$ analyses, the OLS models find that the number of buses and population density are also positively related to a reduction in the concentration of air pollutants. In addition, an increase in the temperature and the presence of secondary industries increase $SO_2$ and $NO_2$ concentrations, respectively. All spatial models capture a positive and significant effect of green spaces on reducing the concentration of each air pollutant. Our results suggest that green spaces in cities should receive priority consideration in local planning aimed at sustainable development. Furthermore, policymakers need to be able to discern the differences among pollutants when establishing environmental policies.

• Journal of Korea Port Economic Association
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• v.27 no.3
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• pp.135-146
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• 2011

A voluminous research on efficiency employs the DEA(Data Envelope Analysis) models. There are, however, only very few that have an interest in the factors influencing such efficiencies. We, furthermore, do not see any studies which analyze the long-term efficiency of the logistics providers using the panel cointegration techniques. The purpose of this paper, hence, is to evaluate the efficiency, analyse its determinants and show a long-term relationship between turnover and the other variables employing the SBM(Slack Based Measure) model, Tobit model, the panel procedure and the FMOLS(Fully Modified OLS). The panel data are composed of 9 individuals and 6 years. The panel cointegrating vectors show that the group coefficient of asset and employees is not only significant but has expected signs, while some of the individual coefficients are insignificant or/and exhibit wrong signs. The panel cointegrating vectors from fully modified OLS also indicate that the estimated coefficients of the panel analysis tend to be overvalued and the asset influences the turnover far greater than the employee does.

• International Commerce and Information Review
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• v.11 no.2
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• pp.111-126
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• 2009

This study analysed determinants of Foreign Direct Investment to ASEAN+ 3 member nations using panel data for which cross-sectional data are combined with time series data. The data for the analysis included the amount of FDI, GDP, and indexes of economic independence. This study collected data from six nations(Indonesia, Malaysia, Philippines, Singapore, Thailand, Vietnam) whose data were easily available, China and Japan from 2003 to 2007 and analysed them. The results are summarized as follows: Using the pooled OLS method, we found Model 2 had the highest explanatory power whose adjusted R-squared was 89.4%, which accounted for about 89% of foreign investment. Using the fixed effect model, Model 2 had the highest explanatory power whose adjusted R-squared was 96.8%, which accounted for about 97% of foreign investment. Using the probability effect model, Model 5 had the highest explanatory power, but in respect to its statistical significance, only GDP was 1% significant and the rest variables had no significance.

• Journal of Korea Port Economic Association
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• v.29 no.3
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• pp.95-111
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• 2013

The purpose of this study is to draw out the trade effect of the Korea ASEAN FTA by carrying out a panel analysis. For achieving such a purpose, Panel Unit Root, Panel Cointegration Test, Pooled OLS, Hausman Test, Fixed Effect, Random effect are performed. The last 15 years's data over the period of 1997 to 2011 concentrated on the ASEAN countries such as Indonesia, Malaysia, Philippine, Singapore, Thai, Vietnam is used in this study. Major implications are summarized as following. First, our government need to maximize the effect derived from conclusion of FTA(Free Trade Agreement) in order to enhance the competitive edge through obtaining a stable foreign market. Second, it necessary for our government to improve a national system by orienting a FTA conclusion complying with WTO's product and service-related regulation.

• Journal of the Korean Regional Science Association
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• v.33 no.2
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• pp.25-37
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• 2017

The paper is basically designed to investigate how regional consumption affects to regional income in Korea by introducing a model with panel cointegration, rational expectation and FM-OLS cointegration methodology. Empirical evidence reveals that the regional income could be stimulated by manipulating the regional consumption due to the fact that current regional consumption and first-lagged regional income are positively related to the level of regional income. Although there exists a possibility to increase the regional income which is associated with a spending multiplier in the group of regions with highly calculated MPC, but not in the groups of regions with middle and low calculated MPCs. To this end, it could be tentatively concluded that market-oriented system should be implemented elaborately to enable that the spending multipliers are appropriately operated in these two groups.

• Asia-Pacific Journal of Business
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• v.10 no.4
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• pp.87-118
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• 2019

The purpose of this study is to examine the effects of person-job fit, which consists of educational fit and skill fit, on employees' intrinsic job satisfaction. To the end, the 10-year balanced panel data of the Korean Labor and Income Panel Study(KLIPS) by the Korea Labor Institute (KLI) for 2008-2017 are utilized. This study analyzes 12,730 observations by 1,273 employees by using fixed effect model, random effect model, and pooled OLS estimation method. The empirical results are as follows: First, it is founded that educational fit and skill fit seem affect job satisfaction positively. Second, the negative effects of over-education are clear and the negative effects of under-education are unclear, while the effects of over-skilled and under-skilled are insignificant statistically. Third, the results imply that the size of effect of over-education on intrinsic job satisfaction is larger than that of the effect of over-skilled. Forth, it is shown that the use of fixed effect model is more effective and trustworthy than that of random effect model and pooled OLS estimation method, implying that the effect size of coefficients which are estimated by pooled OLS method and random effect model are likely over-estimated. The empirical results above imply that firms and employees should focus on solving over-education issue before all in order to enhance employees' job satisfaction and it is needed to monitor regularly whether systemic job assignment process is done based on the employees' educational attainment and skill level and to provide more chances for job re-allocation and job rotation.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.2
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• pp.20-41
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• 2023

Recently, urban shrinkage due to low birth rate and aging population and the decline of local cities are causing a new urban problem of empty houses. This study examines the distribution of vacant homes using spatial panel data collected from 2015 to 2019 at local administraitve districts and estimates the factors of vacant house occurrence using a spatial panel model considering spatio-temporal dependency. As a result, the spatio-temporal dependence of vacant houses was identified and it was estimated using spatial panel model not OLS model. Based on the spatial panel model, it was found that the most influential factor in the occurrence of vacant houses was the housing-related factor. This result shows that policy considerations for housing supply are necessary for the management of vacant housing as well as population movement and poor infrastructure.