• International Commerce and Information Review
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• v.17 no.1
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• pp.217-240
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• 2015

This paper uses the modified gravity model of international trade to examine the impact of ODA on the export of Korea to 28 aid recipients. In this perspective, the study includes recipient's economic size, trade openness, population, donor's scale of aid and distance between them as key determinants of the export of Korea by using panel data over the period of 2005-2012. To do this task, important econometric methods are fulfilled to test the model adequately, such as panel unit root and panel co-integration test. In addition, the study incorporated the panel OLS, panel GLM and panel EGLS methods. The empirical analysis clearly showed that an increase in Korea's ODA promotes its own exports. The coefficients of recipients's per capita GDP, population and trade openness have a positive impact on Korea's export respectively, while distance between them has a negative impact. Regarding regional dummy variables, aid for the region of Africa and America have a negative impact on Korea's export. Overall, the main implication of this study is that even if it emphasized Korea's economic interests as determinants of ODA disbursements, but it also suggests that an improvement of recipient's economic development, income distribution and educational environment can be an important concern in the future.

• Health Policy and Management
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• v.24 no.1
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• pp.47-55
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• 2014

Background: Korea is considered to have an integrative health system where both western medicine and Korean (traditional) medicine are officially recognized and provided. Although Korean medicine has been covered by National Health Insurance over 20 years, equity in the utilization of Korean medical care has rarely been examined. Methods: We examined medical care utilization and expenditure of outpatient Korean medicine using panel fixed effects model to remove selection bias. Then we compared it with pooled ordinary least square (OLS) model. This study used Korea Health Panel data, which provides accurate information on out-of-pocket health care payment, including non-covered medical services. Results: Principal findings indicate that the frequency of the utilization of Korean medicine is related with unobservable individual choices different from western medicine, so the panel fixed effect model is appropriate. But pooled OLS model is better fitted for the expenditure of Korean medicine, after controlling for western medical care expenditure. After adjusting for the selection bias, socioeconomic status (income, education) was significantly associated with the expenditure of Korean medicine, but not with the frequency of the utilization of Korean medicine. Conclusion: This study shows that expenditure of Korean medicine utilization is inequitable across socioeconomic groups, which implies that health insurance coverage of Korean medicine is not sufficient.

• New & Renewable Energy
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• v.6 no.3
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• pp.13-21
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• 2010

This paper analyzes the factors of renewable energy consumption in Korea, China and Japan. We consider renewable energy consumption per capita as dependent variable, GDP per capita, $CO_2$ emissions per capita and real oil prices as independent variables. To analyze this model, this paper uses three econometric methods such as OLS, fixed effect model and panel GLS, utilizing data from 1990 to 2006 in Korea, China and Japan. According to the results by OLS for each country, an increase in GDP per capita or $CO_2$ emissions per capita or oil prices leads to an increase in renewable energy consumption. According to the results by fixed effect model, an increase in GDP per capita or $CO_2$ emissions per capita leads to an increase in renewable energy consumption. And real oil prices do not have a significant impacts on this model. According to the results by panel GLS, an increase in real GDP per capita as a proxy of income leads to an increase renewable energy consumption. And both $CO_2$ emissions per capita and real oil prices do not correlated closely with renewable energy consumption. Thus oil is not substituted to renewable energy in Northeast asian countries.

• Asian Journal of Business Environment
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• v.10 no.4
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• pp.21-27
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• 2020

Purpose: The present study examines the effects of tourism on carbon dioxide emissions for selected South Asian economies over the time from 1995 to 2016. Research design, data and methodology: The present study is an annual time series analysis of tourism and CO2 emissions. The data is taken from World Development Indicators, an official data bank of World Bank. The study sample covers four South Asian countries, namely Bangladesh, India, Pakistan, Sri Lanka and Nepal. The empirical analysis is conducted by employing Pedroni panel cointegration, Fully Modified OLS, and Dynamic OLS approaches of estimation. Results: Tourism significantly increases environmental degradation in selected South Asian economies. The empirical estimated results indicate, that 1 % increase in tourism related activities leads to 0.16 % increase in CO2 emissions. In addition energy consumption and GDP are also causing an upsurge in CO2 emissions in the selected panel of South Asian economies. As the empirical results indicate that 1% increase in GDP stimulates carbon dioxide emissions by 0.23%. Conclusion: In order to protect the environment, the study emphasizes that sustainable tourism practices need to be promoted in the selected South Asian countries. Policy implication and provided and discussed.

• Proceedings of the KOR-KST Conference
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• 1998.09a
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• pp.160-167
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• 1998

Recent world-wide interest in activity-based travel behavior modeling has generated an entirely new perspective on how the profession views the travel demand process. This paper seeks to further promote the case of activity-based travel behavior models by providing some empirical evidence of relationship between travel time and activity duration decision for worker with transportation panel data. The travel time from home to work and from work to home, without activity involvement, is estimated by the Ordinary Least Squares (OLS) method. And, the travel time to and from the selected activity and the activity duration are modeled simultaneously by the Three Stage Least Squares (3SLS) method due to the endogenous relationship between travel time and activity duration. Two kinds of models, OLS and 3SLS, include selectivity bias corrections in a discrete/continuous framework, because of the inter-relationship between the choice of activity type/travel mode (discrete) and the travel time/activity duration (continuous). Estimation is undertaken using a sample of over 1300 household two-day trip diaries collected from the same travelers in the Seattle area in 1989. The behavioral consequences of these models provide interesting and provocative findings that should be of value to transportation policy formulation and analysis.

• Journal of Korea Technology Innovation Society
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• v.8 no.3
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• pp.1225-1249
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• 2005

This study aims at investigating whether foreign direct investment plays a role as a channel of international technology diffusion. We used the annual panel data from 1980 to 2002. The nonstationary panel techniques, in particular group mean panel FMOLS(fully modified OLS) was exploited as an empirical methodology in order to tackle the heterogeneity between members and low frequency. The empirical results show that inflow direct investments lead to an increase in total factor productivity and economic growth. Also outflow direct investments contribute to an higher total factor productivity and economic growth. These results confirms that both inflow and outflow direct investments are important channels for international technology diffusion or spillover.

• International Area Studies Review
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• v.21 no.1
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• pp.201-219
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• 2017

This paper analyzes the economic effects of the S&T Innovation, R&D, human resources and investment on the economic growth using 18 countries. We have obtained the somewhat mixed results on the existence of unit root roots in variables. While most of Pedroni cointegration tests show that there are no panel cointegration among the variables, Kao cointegration test shows that there is the panel cointegration among the variables such as GDP, human capital, R&D investment and patent. Kao cointegration test result shows that human capital, R&D investment, patent economic growth seem to have the panel cointegration or the long-run relationship among them as a whole. The estimation results of individual OLS and panel estimation show that the human capital, R&D investment and technology innovation or patent had positively significant effects on economic growth or GDP.

• Journal of Korea Port Economic Association
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• v.35 no.1
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• pp.57-76
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• 2019

This study deals with the determinants of employment productivity of transportation labor, who are the main agents of the transportation industry that has made significant contributions to our country's industrial development. The study selected the determinants of employment productivity using the Korea Labor and Income Panel Study data, and analyzed the effects of various factors using panel logistic regression, panel OLS model, and panel robust regression. The results were as follows. First, a more positive effect was shown when employees held a regular job, had a "high level of education", "joining the labor union" and "experiencing vocational training". Second, in the case of job security, having a "high level of education" and "joining the labor union" showed a more positive effect; further, job security was higher for employees who worked in a "big company" or were "married". Third, in the case of higher income productivity, higher values of "age", "academic ability" and "company size" had a more positive effect, whereas larger values of "education" and "health condition except job training" had a negative one. Fourth, in the case of job satisfaction, "female", "joining the labor union" and having a higher "income" or "job security" led to higher satisfaction and a better "health condition compared to an average person". Further, a higher "overall life satisfaction" and "economic level" led to lower job satisfaction. The analysis of the determinants of employment productivity of transportation business and seeking for improvement plan is expected to improve the employment productivity in the transportation business.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3417-3426
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• 2012

This study aims to determine how ownership structure (share-holding ratio of insiders, foreigners) affects agent costs (the portion of asset efficiency or non-operating expenses) through empirical analysis. However, as existing studies on correlations between ownership structure and agent costs adopted Pooled OLS Model, this study focused on additionally formulating Fixed Effect Model and Random Effect Model aimed to reflect the time of data formation and corporate effects as study models based on verification results on the suitability of Pooled-OLS Model before comparative analysis for the purpose of improvement of credibility and statistical validity of the results of empirical analysis based on the premise that the Pooled OLS Model is not reliable enough to verify massive panel data. The data has been accumulated over 10 years from 1998 to 2007 after the IMF crisis hit the nation, from a subject 331 companies except for financial institutions. As a result of the empirical analysis, verification of the suitability of model has determined that the Random Effect Model is appropriate in terms of asset efficiency among agent costs items. On the other hand, the Fixed Effect Model is appropriate in terms of non-operating costs. As a result of the empirical analysis according to the appropriate model, no hypothesis adopted in the Pooled OLS Model has been accepted. This suggests that developing an appropriate model is more important than other factors for the purpose of generating statistically significant empirical results by showing that different empirical results are produced according to the type of empirical analysis.

• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.293-301
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• 2012

Quantile regression proposed by Koenker and Bassett (1978) is a statistical technique that estimates conditional quantiles. The advantage of using quantile regression is the robustness in response to large outliers compared to ordinary least squares(OLS) regression. A regression tree approach has been applied to OLS problems to fit flexible models. Loh (2002) proposed the GUIDE algorithm that has a negligible selection bias and relatively low computational cost. Quantile regression can be regarded as an analogue of OLS, therefore it can also be applied to GUIDE regression tree method. Chaudhuri and Loh (2002) proposed a nonparametric quantile regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning. Lee and Lee (2006) investigated wage determinants in the Korean labor market using the Korean Labor and Income Panel Study(KLIPS). Following Lee and Lee, we fit three kinds of quantile regression tree models to KLIPS data with respect to the quantiles, 0.05, 0.2, 0.5, 0.8, and 0.95. Among the three models, multiple linear piecewise quantile regression model forms the shortest tree structure, while the piecewise constant quantile regression model has a deeper tree structure with more terminal nodes in general. Age, gender, marriage status, and education seem to be the determinants of the wage level throughout the quantiles; in addition, education experience appears as the important determinant of the wage level in the highly paid group.