• Journal of the Economic Geographical Society of Korea
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• v.14 no.3
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• pp.263-285
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• 2011

Despite the process of neoliberalization has made a decisive influence on our society as a whole, there seems little interests in neoliberal urbanization and entrepreneurial urban projects promoting it. This study is to see relationships between neolibealization process and recent urbanization and urban policies in terms of entrepreneurial city mediating them. In particular, this paper tries to reconceptualize entrepreneurial city as corresponding to privatization and commodification, financialization, state redistribution, and management and manipulation of crises which Harvey(2005) suggests as four main features of neoliberalization process in general and 'accumulation by dispossession' in particular, and to characterize it in terms of 'creative destruction' and of 'entrepreneurial governance'. As examined in the later part of this paper, recent cases of these entrepreneurial urban projects in S. Korea include volatility of land and housing price in the Capital region and urban regeneration and newtown projects, project for free economic zones construction in Incheon and other 5 regions, project for SOC construction heavily relying on private investment, in particular project financing pursued nationwidely including Daegu, and project of urban cultural marketing to promote capital inflow tacitly as well as to enhance urban imagine explicitly.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.168-175
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• 2020

Recently, there has been an increasing need to expand the supply of renewable energy as a solution to greenhouse gas emissions. Therefore, as a measure to promote domestic renewable energy investment and gradual expansion, this study analyzed the investment value of renewable energy projects utilizing the unoccupied spaces of public enterprise's facilities and presented a strategic decision-making framework to support efficient national land development and government measures. The NPV was estimated to be 286 million won if the expansion of the facility was not considered, but it is reasonable to postpone the expansion decision because the value of -130 million won was calculated if the expansion was considered. On the other hand, the real-option value was estimated to be 444 million won, taking SMP uncertainty, expansion, and abandonment options into account, and an additional value of 288 million won was calculated from an analysis of the expansion project using the existing NPV analysis.

• Environmental and Resource Economics Review
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• v.13 no.2
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• pp.271-300
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• 2004

We investigate the two recent simulations of the proto-type domestic carbon emission trading system in Korea and draw some policy implications. The first simulation includes the 5 electric power companies based on baseline and credit. But the second one is with the 7 energy-intensive companies based on cap and trade. The voluntary approaches in this paper revealed the instability of market equilibrium, i.e., price volatility or distortion, excess supply or demand. These phenomena stems from excess incentives to the players, asymmetric information, players' irresponsible strategic behaviors, and non acquaintance of trading system. This paper suggests the basic design for domestic carbon trading system in future and a stepwise introduction strategy for it including the incentive auction scheme, the total quantity of incentive needed, and how to finance it. Meantime, the further simulations on the various sectors based on voluntary participation must be essential for learning experiences and better policy design.

• KDI Journal of Economic Policy
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• v.34 no.4
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• pp.117-156
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• 2012

This paper decomposes and estimates trend/cyclical components of some key macro variables-GDP, inflation, and interest rate, using a simple DSGE model along with flexible trend specification. The extracted cyclical components of output and interest rate are similar to HP-filtered counterparts, despite some differences in persistence and volatility, while inflation resembles that from BK filtering. This implies that the usual practice of applying a single filtering method to the data of interest may be problematic. When the baseline model is extended to incorporate consumption habit and price indexation, habit turns out to be important in explaining the persistence of business cycles. Comparison of several alternative models shows that the usual practice of estimation of DSGE model using filtered data leads to biased results. Finally, various sensitivity analyses illustrate that (1) allowing for correlation between structural cyclical shocks and trend shocks and (2) including irregular components (in inflation rate) may deliver interesting/important implication for gap estimates.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.357-368
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• 2018

For well over 100 years, oil has enabled remote communities to generate electricity and enjoy the benefits of a consistent electrical supply. Relying solely on oil for electricity generation has left island and remote communities exposed to several risks and drawbacks. Oil-based electricity generation is often more expensive and subject to price volatility, which can result in the use of risky fuel hedging strategies. The residents of islands and remote communities express concern over the future impacts of climate change or insist on their opinions for the corresponding action with reduction of carbon emissions. These risks and drawbacks can be overcomed with continuing cost reductions in solar, wind, and energy storage technologies by maker. Reducing costs is not always a straightforward process, relying on more diversely and renewably arranged renewable energy sources led to reduced local construction cost in every situation reviewed in this study. In this paper, a convenient and simple design solution which will facilitate the optimum location and transmission route of renewable energy facility using GIS(Geographic Information System) is proposed. The suggested solutions exercised to the case of geomoon island using GIS and identified by local site survey.

• Management & Information Systems Review
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• v.33 no.1
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• pp.83-97
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• 2014

This study examined the effects institutional block ownership on the stock market liquidity in Korean Stock Market. The two measures of institutional block ownership are used. They are the percentage of a stock owned by institutional blockholder and the number of institutional blockholder that own the stock. This study used the Amihud(2002) illiquidity measure to measure stock market liquidity. The results are as fellows. First, this study showed that the number of institutional blockholder is significantly negatively correlated with the Amihud(2002) illiquidity measure in the analysis which is used the whole data. But we found no a consistent results between the number of institutional blockholder and the Amihud(2002) illiquidity measure in the grouped institutional blockholder's number analysis. This indicates that the effects institutional blockholder on market liquidity is not simple. Second, this study showed that the percentage of a stock owned by institutional blockholder are negatively related with Amihud(2002) illiquidity measure, especially revealed statistically significant in the group 3(11.71%~17.38%) and group 4(7.45%~11.65%). This results suggest that the institutional blockholder have positive effect on the market liquidity in the group 3 and 4. Third, the significance of the percentage of institutional block ownership and the number of institutional block ownership in explaining illiquidity are more showed in the term of the global financial crisis(2008) than the before and the after of the global financial crisis.

• Environmental and Resource Economics Review
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• v.27 no.1
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• pp.67-104
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• 2018

In this paper, we compare the spread effects of the carbon tax imposition method using the real business cycle model considering the productivity and energy price shocks. Scenario 1 sets the carbon tax rate that encourages the representative firm to maintain a constant $CO_2$ reduction ratio in accordance with its green house gas reduction targets for each period. Scenario 2 sets the method of imposing the steady state value of the carbon tax rate of Scenario 1 during the analysis period. The impulse response analysis shows that the responses of $CO_2$ emissions to external shocks are relatively sensitive in scenario 2. And simulation results show that the cost of $CO_2$ abatement is more volatile in scenario 1, and $CO_2$ emissions and $CO_2$ stock are more volatile in scenario 2. In particular, the percentage changes in volatility between the two scenarios of $CO_2$ emissions and $CO_2$ stock increase as the green house gas reduction target is harder. When the green house gas reduction target is 60% and over, the percentage changes(absolute value) between the two scenarios exceed the percentage change(absolute value) of the $CO_2$ reduction cost between them.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.763-776
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• 2020

Onions show severe volatility in production and price because crop conditions highly depend on the weather. The government has designated onions as a sensitive agricultural product, and prepared various measures to stabilize the supply and demand. First of all, preemptive and reliable information on predicting onion production is essential to implement appropriate and effective measures. This study aims to contribute to improving the accuracy of production forecasting by developing a model to estimate the final weight of onions bulb. For the analysis, multi-level model is used to reflect the hierarchical data characteristics consisting of above-ground growth data in individual units and meteorological data in parcel units. The result shows that as the number of leaf, stem diameter, and plant height in early May increase, the bulb weight increases. The amount of precipitation as well as the number of days beyond a certain temperature inhibiting carbon assimilation have negative effects on bulb weight, However, the daily range of temperature and more precipitation near the harvest season are statistically significant as positive effects. Also, it is confirmed that the fitness and explanatory power of the model is improved by considering the interaction terms between level-1 and level-2 variables.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.161-171
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• 2021

According to the equity home bias theory, foreign investors are considered to have less information than native investors. However, as the economy becomes liberalized and overseas economic innovation has a great influence on the local economy, it is possible for foreign investors to invest as informed traders. This study analyzes whether information on trade amount by nationality has specific characteristics. The findings are summarized as follows. First, the increase in trading by foreign investors has negative effects on stock returns. There is no significant difference in these negative effects by nationality. This means that foreign investors show strong herd behavior regardless of nationality. Second, foreigners' investment activities increase stock price volatility, but the impact is not significant. Third, the behavior of foreign investors is still positive feedback. However, there are signs that positive feedback behavior may be changing, especially for funds from the United States and the Cayman Islands. Finally, tax haven zone funds have different investment strategies than other foreign investors. However, Cayman Islands funds, which are estimated to be closely related to Korea, are different from Luxembourg and Ireland funds. These findings undermine the fundamentals of the equity home bias theory.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.17-26
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• 2023

In this paper, we propose a several smoothing techniques are compared and applied to increase the application of the LSTM-based learning model and its effectiveness. The applied smoothing technique is Savitky-Golay, exponential smoothing, and weighted moving average. Through this study, the LSTM algorithm with the Savitky-Golay filter applied in the preprocessing process showed significant best results in prediction performance than the result value shown when applying the LSTM model to Bitcoin data. To confirm the predictive performance results, the learning loss rate and verification loss rate according to the Savitzky-Golay LSTM model were compared with the case of LSTM used to remove complex factors from Bitcoin price prediction, and experimented with an average value of 20 times to increase its reliability. As a result, values of (3.0556, 0.00005) and (1.4659, 0.00002) could be obtained. As a result, since crypto-currencies such as Bitcoin have more volatility than stocks, noise was removed by applying the Savitzky-Golay in the data preprocessing process, and the data after preprocessing were obtained the most-significant to increase the Bitcoin prediction rate through LSTM neural network learning.