• Ocean and Polar Research
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• v.36 no.4
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• pp.505-514
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• 2014

The development of deep seabed manganese nodules has been carried out with the aim of commercial development in 2023. It is important to forecast the price of the four metals (copper, nickel, cobalt, and manganese) extracted from manganese nodules because price change is a criterion for investment decision. The main purpose of the study is to forecast the price of four metals using the ARIMA model and VAR model, and calculate the MAPE to compare a goodness-of-fit between the two models. The estimated results of the two models reveal statistical significance and are in keeping with economic theory. The results of MAPE for goodness-of-fit show that the VAR model is between 0.1 and 0.2, and the ARIMA model is between 0.4 and 0.6. That is, the VAR model is better than the ARIMA model in forecasting changes in the price of metals.

• Korean System Dynamics Review
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• v.9 no.1
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• pp.125-141
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• 2008

It is very difficult to predict future demand/supply, price for resources with acceptable accuracy using regression analysis. We try to use system dynamics to forecast the demand/supply and price for nickel. Nickel is very expensive mineral resource used for stainless production or other industrial production like battery, alloy making. Recent nickel price trend showed non-linear pattern and we anticipated the system dynamic method will catch this non-linear pattern better than the regression analysis. Our model has been calibrated for the past 6 year quarterly data (2002-2007) and tested for next 5 year quarterly data(2008-2012). The results were acceptable and showed higher accuracy than the results obtained from the regression analysis. And we ran the simulations for scenarios made by possible future changes in demand or supply related variables. This simulations implied some meaningful price change patterns.

• ETRI Journal
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• v.6 no.4
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• pp.9-20
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• 1984

Communications is becoming a vital sector to lead Information Society in the nearfuture. In that sense the price system of its services is now being discussed seriously among the people who are directly and indirectly related to communications development. Input-Output analysis model developed by W. Leontief in early 1930's is a very useful tool to measure the price linkage effects in the national economy, which would be induced from the shift of a certain sector's price. 1980's I-0 table with 19 sectors is rear-ranged and applied to price analysis model, in which communications is treated as a exogenous sector, to see the price impacts generated from a change of telephone rate. With the results of this study, the authorities concerned with price policy can make their decisions more reasonable.

• Management & Information Systems Review
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• v.33 no.2
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• pp.119-133
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• 2014

This Research focuses on the effect of the price limits change in KOSDAQ market change on the volatility. The sample period ranges from 22 May 2000 to 24 March 2010 for daily data. We construct two subsample periods for comparing with the effect of the change of the price limit. These limits were relaxed from 12% to 15% on March 25, 2005. The first subsample period is from 25 March 2000 to 24 March 2005. The second subsample period is from 25 March 2005. to 24 March 2010. We employee four different volatility, which are the range-based volatility of Parkinson(1980; PK), Garman and Klass(1980; GK) Rogers and Satchell(1991; RS), Yang and Zhang(2008; YZ). The empirical result as follows. The major findings are summarized as follows; First, the volatility of individual stocks in KOSDAQ market reduces significantly after the price limit change. Second, There is so high volatile especially when the volatility of stock prices is high. Third, There is no meaningful relationship between volatility and market capitalization. Fourth, the more volume stocks reduce the volatility. Our results show the volatility decreased the more large volume, the more trading amount and the high price stock.

• The Journal of Industrial Distribution & Business
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• v.11 no.8
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• pp.31-38
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• 2020

Purpose: This study uses 'Autoregressive Integrated Moving Average Model' to predict the impact of a sharp drop in the base rate due to COVID-19 at the present time when government policies for stabilizing house prices are in progress. The purpose of this study is to predict implications for the direction of the government's house policy by predicting changes in house transaction prices and house rental prices after a sharp cut in the base rate. Research design, data, and methodology: The ARIMA intervention model can build a model without additional information with just one time series. Therefore, it is a time-series analysis method frequently used for short-term prediction. After the subprime mortgage, which had shocked since the global financial crisis in April 2007, the bank's interest rate in 2020 is set at a time point close to zero at 0.75%. After that, the model was estimated using the interest rate fluctuations for the Bank of Korea base interest rate, the house transaction price index, and the house rental price index as event variables. Results: In predicting the change in house transaction price due to interest rate intervention, the house transaction price index due to the fall in interest rates was predicted to change after 3 months. As a result, it was 102.47 in April 2020, 102.87 in May 2020, and 103.21 in June 2020. It was expected to rise in the short term. In forecasting the change in house rental price due to interest rate intervention, the house rental price index due to the drop in interest rate was predicted to change after 3 months. As a result, it was 97.76 in April 2020, 97.85 in May 2020, and 97.97 in June 2020. It was expected to rise in the short term. Conclusions: If low interest rates continue to stimulate the contracted economy caused by COVID-19, it seems that there is ample room for house transaction and rental prices to rise amid low growth. Therefore, In order to stabilize the house price due to the low interest rate situation, it is considered that additional measures are needed to suppress speculative demand.

• Environmental and Resource Economics Review
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• v.19 no.2
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• pp.283-301
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• 2010

This study estimated the paper demand and supply using VAR model. And the variance decomposition and impulse response were analyzed using the model. In the model of paper demand, the own price change accounts for about seventeen percent of variation in the demand, and the gross domestic product change accounts for about twenty eight percent of variation in the demand. And the impacts of a shock to the own price and gross domestic product are significant for about six months on the demand for paper. In the model of paper supply, the own price change accounts for about twenty nine percent of variation in the supply, and the pulp price change accounts for about twelve percent of variation in the supply. And the impacts of a shock to the own price and pulp price are significant for about six months on the supply of paper.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.3
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• pp.264-272
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• 2019

The aim of this study is to analyze the relationship between international oil price as a fuel cost in overseas fisheries and skipjack tuna price as a part of main products in overseas fisheries using monthly time series data from 2008 to 2017. The study also tried to analyze the change of fishing profits by fuel cost. For a time series analysis, this study conducted both the unit-root test for stability of data and the Johansen cointegration test for long-term equilibrium relations among variables. In addition, it used not only the Granger causality test to examine interactions among variables, but also the Vector Auto Regressive (VAR) model to estimate statistical impacts among variables used in the model. Results of this study are as follows. First, each data on variables was not found to be stationary from the ADF unit-root test and long-term equilibrium relations among variables were not found from a Johansen cointegration test. Second, the Granger causality test showed that the international oil prices would directly cause changes in skipjack tuna prices. Third, the VAR model indicated that the posterior t-2 period change of international oil price would have an statistically significant effect on changes of skipjack tuna prices. Finally, fishing profits from skipjack would be decreased by 0.06% if the fuel cost increases by 1%.

• Environmental and Resource Economics Review
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• v.22 no.4
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• pp.759-784
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• 2013

Participants can use the allowances and offsets for implementing the compliance in the Emissions Trading Scheme(ETS). There are alternative commodities which are different prices it gives the opportunities to reduce the compliance costs and get the arbitrage. This study analyzes the price driver of spread which is the difference between EUA and sCER using AR-GARCH model, EUA and CER during the Phase 2 in EU ETS. The results show that there are common elements which impacts the EUA and sCER and also different elements between them. EUA and sCER get the effects from energy price and economic criteria such as coal price and financial crisis as common elements. However them get the effects from electric price, policy criteria such as restricted CERs and difference price between EUA and ERU price as different elements. The results shows that spread will be widen if energy price increase, especially oil and electric price give more impacts the spreads. This study has the means that it explains the reason why the spreads will broaden sharply in 2012. And it also suggests the price driver of spread during the whole period of Phase 2. In addition, this study shows that political aspects maybe become the main criteria of price change with structural elements shch as energy price in Korea ETS which starts in 2015.

• Journal of the Korean housing association
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• v.19 no.3
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• pp.31-38
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• 2008

Recently, Seoul residential real estate market showed a big change, especially in 2007. The residential property price in Seoul had been mainly affected by 5 provideces: Kangnam-gu, Seocho-gu, Songpa-gu, Gangdong-gu and Yangchun-gu, but these providences started to show the decrease in price while the other providences ironically showed the opposite direction. Therefore, this project was derived from this phenomenon recognition and the necessity as the new market trend requires. The pre-research was carried out with the point of social-population academic view, but this project provides the analysis on the new market trend by simplifying the complex valuation indexes, originated from the pre-research. In result, the aspects of the change could be categorized into time-manner classification and territorial-manner classification, in cope with the change in the satisfaction degree on the residential environment and the selection tendency of the residential property. Based on the the moving-preferred area criteria, the territorial classification was categorized into 3 areas: 5 providences, which showed the initial decrease in real estate price (area 1), the other Kangnam area (area 2), and Kangbuk area (area 3). The result illustrated the reasonable change in the satisfaction degree on the residential environment and the selection tendency of the residential property. This project was able to reach the following conclusion : Firstly, the housing development planning should be devised by the residential environment, including the view and the natural environment, not by the area. Secondly, the housing development planning in the other Kangnam area (area 2) and Kangbuk area (area 3) should embrace the business function, not the housing development only. Last, the housing development planning in Kangbuk area (area 3) should be able to enhance education and culture function and be connected by various transportation system. This project analyzes the change in the satisfaction degree on the residential environment and the selection tendency of the residential property. Thereafter, this project has the purpose of providing the aid in understanding of the basis of housing development information.

• Journal of Advanced Technology Convergence
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• v.3 no.2
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• pp.17-23
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• 2024

In this paper, we analyzed the impact of temperature and precipitation on agricultural product prices and predicted the prices of major agricultural products using TensorFlow. As a result of the analysis, the rise in temperature and precipitation had a significant effect on the rise in prices of cabbage, radish, green onion, lettuce, and onion. In particular, prices rose sharply when temperature and precipitation increased simultaneously. The prediction model was useful in predicting agricultural product price changes due to climate change. Through this, agricultural producers and consumers can prepare for climate change and prepare response strategies to price fluctuations. The paper can contribute to understanding the impact of climate change on agricultural product prices and exploring ways to increase the stability and sustainability of agricultural product markets. In addition, it provides important data to increase agricultural sustainability and ensure economic stability in the era of climate change. The research results will also provide useful insights to policy makers and can contribute to establishing effective agricultural policies in response to climate change.