• Korean Journal of Construction Engineering and Management
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• v.16 no.2
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• pp.46-53
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• 2015

Electrical construction cost index is composed of the cost of albor and material. The producer price index is used to the cost of material. The Bank of Korea restructured the formation method and the basic period of the producer price index in 2013. Because fixed-weighted method can't faithfully reflect industrial structure changes. The weighted value and price index of fixed-weighted method is fixed on the basicp eriod. Electrical construction cost index is changed from fixed-weighted method to chain-weighted method in september 2014, because of these on the need. But the change of organization in formation method changes the weighted value. So there is the need of analysis about the statistical continuity of electrical construction cost index. This study is focused on the time series analysis between fixed-weighted and chain-weighted electrical construction cost index. We uses unit root test, cointegration test, regression analysis of long and short term equation, fitness for the estimation of static forecast as time series analysis. We verify that chain-weighted electrical construction cost index can be replaced to fixed-weighted construction cost index accounting analyses result. So users of it recognize that chain-weighted electrical construction cost index has statistical continuity.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.39-44
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• 2018

The application of deep neural networks to finance has received a great deal of attention from researchers because no assumption about a suitable mathematical model has to be made prior to forecasting and they are capable of extracting useful information from large sets of data, which is required to describe nonlinear input-output relations of financial time series. The paper presents a new deep neural network model where single layered autoencoder and 4 layered neural network are serially coupled for stock price forecasting. The autoencoder extracts deep features, which are fed into multi-layer neural networks to predict the next day's stock closing prices. The proposed deep neural network is progressively learned layer by layer ahead of the final learning of the total network. The proposed model to predict daily close prices of KOrea composite Stock Price Index (KOSPI) is built, and its performance is demonstrated.

• The Journal of Fisheries Business Administration
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• v.26 no.2
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• pp.75-92
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• 1995

This paper tried to estimate the pass - through of exchange rate changes to export price of fishery products using export price function. The results are as follows : 1) The variable of fluctuation of exchange rate of Won(equation omitted) to Yen(equation omitted)(variable E2) is more powerful explanatory variable than that of Won to U.S. dollar to explain the fluctiation of export price of fishery products(varible $P_{t}$)- 2) The variable of fish catches(variable K $P_{t}$) is also found to be a statistically significant varible but that of producer price index is not found. 3) The variable E2 have statistically a more influence on variable $P_{t}$ than variable K $P_{t.}$ 4) The estimation shows us that 1% of fluctuation of variable E2 could result in 0.9978% of fluctuation of variable $P_{t.}$

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.163-172
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• 2019

The paper aims to investigate the impact of the gap between domestic and international gold price on money demand in Vietnam, an emerging economy in the Asian region. We use a quarterly database collected from the first quarter of 2004 to the fourth quarter of 2016. The time-series database includes 52 observations. The money demand is represented by M2; Domestic income is the Gross domestic product at the constant prices of 1994; Inflation rate is calculated by the Customer Price Index from the General Statistics Office of Vietnam. The result confirms the existence of a long-term cointegration relationship between the money demand and the gap between domestic and international gold price as well as some variables including domestic income, inflation, and real exchange rate. The regression results also show that the gap between domestic and international gold price has a positive impact on money demand in the Vietnamese economy. Besides, the domestic income and international gold price have positive impacts on money demand while the inflation and real exchange rate are negatively related in the long run. This proves that the gap between the domestic and international gold price really has a positive impact on money demand in Vietnam during the study period.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.1
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• pp.23-48
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• 2022

In this paper, we provide predictive models for the market price of fruits, and analyze the performance of each fruit price predictive model. The data used to create the predictive models are fruit price data, weather data, and Korea composite stock price index (KOSPI) data. We collect these data through Open-API for 10 years period from year 2011 to year 2020. Six types of fruit price predictive models are constructed using the LSTM algorithm, a special form of deep learning RNN algorithm, and the performance is measured using the root mean square error. For each model, the data from year 2011 to year 2018 are trained to predict the fruit price in year 2019, and the data from year 2011 to year 2019 are trained to predict the fruit price in year 2020. By comparing the fruit price predictive models of year 2019 and those models of year 2020, the model with excellent efficiency is identified and the best model to provide the service is selected. The model we made will be available in other countries and regions as well.

• The Journal of Economics, Marketing and Management
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• v.12 no.5
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• pp.63-73
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• 2024

Purpose: Changes in energy prices can be considered as one of the factors of macroeconomic uncertainty. This study examines the impact of coal price shocks on Indonesian macroeconomic variables. Research design, data and methodology: The structural vector autoregressive model is used on monthly data from January 2010 to June 2023. Results: The impulse response functions indicate that coal price shocks have a negative impact on output and a positive impact on CPI (Consumer Price Index) and the effective real exchange rate. Following a shock in coal price growth, output growth takes twelve months, CPI growth takes fifteen months, and the effective real exchange rate takes seventeen months to reach equilibrium. Coal price growth shocks generally do not have a significant contribution to the variation in output, CPI growth and effective real exchange rate. On average over a twelve-month simulation, coal price growth shocks contribute 2.06 percent to output growth variation, 0.0042 percent to CPI growth variation, and 0.0046 percent to effective real exchange rate growth variation. Conclusions: This study finds that the impact of rising coal prices, as an energy source in Indonesia, can be offset by coal export revenues. This is possible considering that 70-80% of Indonesia's coal is exported.

• Environmental and Resource Economics Review
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• v.13 no.1
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• pp.33-47
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• 2004

Even though the price of extracted but unprocessed coal has been available in Korea, the use of it as scarcity index would be inappropriate because of price subsidy. Following Halvorsen and Smith(1984), Kim and Lee(2002) derived estimates of the shadow price of unextracted coal by estimating the restricted cost function and differentiating with respect to the quantity of coal extracted. In Korea, however, due to the limited data the capital prices have been computed inconsistently case by case without relying on the robust formula like the Christensen-Jorgenson methodology used in US, which could result in biased estimators of the restricted cost function. In the paper the shadow prices of the resources in situ are obtained by measuring an input distance function defined by Shephard (1970), which requires only the data on the quantities of inputs and output. Empirical results for the Korean coal mining industry show that these shadow prices as a coal scarcity have increased fast by approximately three times in comparisons with those obtained by Kim and Lee.

• Journal of Korea Port Economic Association
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• v.38 no.2
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• pp.49-67
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• 2022

This study applied the method of Diebold and Yilmaz (2012, 2014, 2016) to analyze the connectedness between the Freight Index (BDI, BDTI, BCTI), energy price(oil, natural gas, coal), and grain price(soybean, corn, wheat) from July 19, 2007 to March 31, 2022. The main analysis results of this paper are as follows. First, according to the network analysis results, the total connectedness was measured to be 20.43% for the entire analysis period, indicating that there was a low correlation between the freight index and the commodity price. In addition, looking at the directional results, the variable with the greatest effects was corn, and conversely, the variable with the lowest effects BDI. When classified by events, BCTI was found to play a major role only during the COVID-19 period. Second, according to the results of the rolling-sample analysis, the total connectedness be found to be highly correlated with changes in economic conditions such as the financial crisis, trade war, and COVID-19 when specific events occurred.

• Journal of Korean Society of Forest Science
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• v.94 no.2 s.159
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• pp.82-89
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• 2005

The purpose of this paper is to investigate index numbers by conducting various comparisons among the widely used index formulas. The comparison is considered in three ways; 1) divergences in the magnitudes of index numbers due to the use of different formulas (Laspeyres, Paasche, Fisher, and Tornqvist); 2) the effect of selection of base year (fixed-year base vs. chain-type); 3) the degree of approximation of indirect to direct quantity index. The empirical application is to sawmills and planing mills industry of U.S. using a national time series data covering years of 1948-2000. The results show that the differences between Laspeyres and Paasche index can be substantial in some cases while the difference between Fisher and Tornqvist index is minimal. We also confirm that the selection of base year can cause significant divergences, especially when the variables undergo rapid price or quantity changes over time. We find that indirect quantity index approximates direct quantity index reasonably well in U.S. sawmill industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.272-277
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• 2010

In respect complication of group, rate of arrearage in domestic bank is composed of various factors. This paper studies focus on estimating the determinants of the rate of arrearage in domestic bank using panel data model. The volume of analysis consist of 3 groups(loaned patterns of enterprise, housekeeping, credit card). Analyzing period be formed over a 54 point(2005. 1~ 2009. 06). In this paper dependent variable setting up rate of arrearage in domestic bank, explanatory(independent) variables composed of the consumer price index, composite stock price index, rate of exchange, the coincident composite index, national housing bonds and employment rate. The result of estimating the rate of arrearage in domestic bank provides empirical evidences of significance positive relationships between the consumer price index However this study provides empirical evidences of significance negative relationships between the coincident composite index and the composite stock price index. The explanatory variables, that is, rate of exchange, national housing bonds and the employment rate are non-significance variables of negative factor. Implication of these findings are discussed for content research and practices.