• Environmental and Resource Economics Review
• /
• v.21 no.3
• /
• pp.519-542
• /
• 2012

In this paper, we empirically analyzed whether carbon leakage really happened in EU by comparing before and after the period of EU ETS. We regarded foreign direct investment outflows as indicator of carbon leakage and analyzed panel regression between production cost including environment cost and this FDI variable. Also we consider foreign market potential to analyze market oriented FDI. According to this analysis, carbon leakage was observed in some models for manufacturing industry. However carbon leakage did not prove consistently in a variety of models and it is hard to speak carbon leakage was happened in EU ETS. Notwithstanding relatively short time series of data, in the view of the fact that carbon leakage was tested in some models, Korea also should keep in mind the possibility of carbon leakage and design emission trading scheme.

• Korea Trade Review
• /
• v.41 no.5
• /
• pp.373-389
• /
• 2016

This study mainly investigates the port SOC's impact on trade volume. In order to investigate the relationships between port SOC and trade volume, we did the empirical analysis using panel data regression and fixed effects model. The total period of 97 years and 1,082 ports' information were applied to panel data and regression model. According to the results, the coefficients of development of container berth, development of bulk berth, maintenance of port, the jetty facilities like breakwater have positive(+) impact on the dependent variable, the trade volume. Especially, the jetty facilities show a strongly positive impact on trade volume. On the other hand, the development of new port and navigation facilities like lighthouse have a negative(-) impact. In examining Hausman test and LR test, the fixed effect model is statistically more appropriate than the random effect model for this study.

• Journal of Intelligence and Information Systems
• /
• v.9 no.1
• /
• pp.71-89
• /
• 2003

Although many studies demonstrate that one technique outperforms the others for a given data set, there is often no way to tell a priori which of these techniques will be most effective in the classification problems. Alternatively, it has been suggested that a better approach to classification problem might be to integrate several different forecasting techniques. This study proposes the linearly combining methodology of different classification techniques. The methodology is developed to find the optimal combining weight and compute the weighted-average of different techniques' outputs. The proposed methodology is represented as the form of mixed integer programming. The objective function of proposed combining methodology is to minimize total misclassification cost which is the weighted-sum of two types of misclassification. To simplify the problem solving process, cutoff value is fixed and threshold function is removed. The form of mixed integer programming is solved with the branch and bound methods. The result showed that proposed methodology classified more accurately than any of techniques individually did. It is confirmed that Proposed methodology Predicts significantly better than individual techniques and the other combining methods.

• Korean Journal of Environment and Ecology
• /
• v.28 no.4
• /
• pp.393-403
• /
• 2014

The aim of this study was to use the information deduced from biotopemap in Boryeong, Chungnam province conducted in 2011 and to select the wildlife survey point. The information used for the study was deduced from the knowledge and experience of wildlife specialists and was realized by 6 environmental variables (Outside distance from food vegetation, Outside distance from farm land, Outside distance from forest, Human density, Outside distance from road, Outside distance from water). 6 environmental variables were modeled by map overlay method and the model could deduce the correlation of 94.72% as a result of comparing with occurrence information. The areas predicted to have many occurrences were rural landscapes, forests, and valleys, and they can be used to deduce the quality wildlife survey results in the limit of survey range (area, schedule, and budget). However, it had the limit points such as the inside of forests was excluded, all species did not prefer the same habitat. The following studies are needed for this part in the future.

• Korean Journal of Environmental Biology
• /
• v.38 no.2
• /
• pp.222-230
• /
• 2020

Temperature-dependent development models for Hydrochara affinis were built to estimate the ecological parameters as fundamental research for monitoring the impact of climate change on rice paddy ecosystems in South Korea. The models predicted the number of lifecycles of H. affinis using the daily mean temperature data collected from four regions (Cheorwon, Dangjin, Buan, Haenam) in different latitudes. The developmental rate of each life stage linearly increased as the temperature rose from 18℃ to 30℃. The goodness-of-fit did not significantly differ between the models of each life stage. Unlike the optimal temperature, the estimated thermal limits of development were considerably different among the models. The number of generations of H. affinis was predicted to be 3.6 in a high-latitude region (Cheorwon), while the models predicted this species to have 4.3 generations in other regions. The results of this study can be useful to provide essential information for estimating climate change effects on lifecycle variations of H. affinis and studies on biodiversity conservation in rice fields.

• The Journal of Korean Association of Computer Education
• /
• v.16 no.3
• /
• pp.61-70
• /
• 2013

In order to increase students' academic achievement effectively and at the same time to draw active participations from students during the computer lab, we applied the reciprocal peer tutoring education model. We focused on a short-term application of the reciprocal peer tutoring to computer operating system lab education with as little preparation as possible. 61 college students majoring in computer engineering participated in this research; half of them studied in the reciprocal peer tutoring setting, and rest of them did in the normal lab setting. Results show that students who participated in the reciprocal peering tutoring lab have higher academic achievement and better satisfaction on overall education and the class's professor. We hope that our method will be easily used in other universities' computer lab education.

• KDI Journal of Economic Policy
• /
• v.29 no.2
• /
• pp.117-133
• /
• 2007

This paper evaluates the efficiency of monetary policy in Korea within the framework of interest rate feedback rules. For this, a small open macroeconomic model is constructed in a similar fashion to Ball (1999). The model is shown to capture key features of the Korean economy well. Using this estimated model, optimal instrument rules are derived for a set of different monetary policy objectives. Empirical results find that the actual monetary policy in the class of instrument rules was not very effective in stabilizing the output gap relative to inflation. However, seemingly successful inflation stabilization observed in the data are not consistent with the policy rules as the reaction of the interest rate to inflation is very low. It also appears that the central bank did not react right to movements in the real exchange rate. This paper offers some suggestions for the conduct of monetary policy in Korea.

• Environmental and Resource Economics Review
• /
• v.12 no.3
• /
• pp.515-529
• /
• 2003

This theoretical model makes three contributions to the study on economic growth and environment. First, emissions are generated during final goods production and technology accumulation. Second, this paper assumes that pollution is directly increasing with increase in final goods output or in consumption. Third, we use reproducible factors associated with labor and capital input in production function and assume constant return to scale in reproducible factors. From growth rate condition we derived, increases in reproducible factors, increases in productivity of either the abatment or technology sector, and decrease in social discount rate would increase the sustainable growth rate. In empirical test, the environmental degradation did not effect the economic growth rate though other factors satisfied the growth rate condition equation. However, through the reinterpretation of this result, we found indirectly the fact of that an inverted U relationship between air pollution and economic growth rate would exist in 20 OECD countries using a panel data for the period of 1986~1995.

• Journal of the Korea Convergence Society
• /
• v.12 no.4
• /
• pp.249-258
• /
• 2021

Bitcoin prices have been soaring recently as investors flock to cryptocurrency exchanges. The purpose of this study is to predict the Bitcoin price using a deep learning model and analyze whether Bitcoin is profitable through investment strategy. LSTM is utilized as Bitcoin prediction model with nonlinearity and long-term memory and the profitability of MA cross-over strategy with predicted prices as input variables is analyzed. Investment performance of Bitcoin strategy using LSTM forecast prices from 2013 to 2021 showed return improvement of 5.5% and 46% more than market price MA cross-over strategy and benchmark Buy & Hold strategy, respectively. The results of this study, which expanded to recent data, supported the inefficiency of the cryptocurrency market, as did previous studies, and showed the feasibility of using the deep learning model for Bitcoin investors. In future research, it is necessary to develop optimal prediction models and improve the profitability of Bitcoin investment strategies through performance comparison of various deep learning models.

• Journal of Korean Society of Forest Science
• /
• v.107 no.4
• /
• pp.402-411
• /
• 2018

This study was conducted to develop ingrowth estimation equations on Pinus densiflora found in Gangwon Province and in the center of Korean Peninsula, based on the National Forest Inventory (NFI)'s permanent sampling plot data. For this study, identical sampling plots in $5^{th}$ and $6^{th}$ NFI data were collected in order to identify ingrowth amounts for the last 5 years. Following two-stage approaches in developing the ingrowth estimation equations, the logistic regression model was used in the first stage to estimate the ingrowth probability. In the second stage, regression analysis on sampling plots with ingrowth occurrence was used to estimate the ingrowth amount. A candidate model was finally selected as an optimal model after a verification based on three evaluation statistics which include mean difference (MD), standard deviation of difference (SDD) and standard error of difference (SED). In results, a logistic regression model based on the number of sampling plot which did not result in ingrowth (model VI), was selected for an ingrowth probability estimation equation and exponential function including the species composition (SC) variable was optimal for an ingrowth estimation equation (model VII). The ingrowth estimation equations developed in this study also evaluated the estimation ability in various forest stand conditions, and no particular issue in fitness or applicability was observed.