• The Journal of Fisheries Business Administration
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• v.27 no.1
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• pp.67-90
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• 1996

As an important factor of capitalism economics, price of commodities represents a certain country's economic index. For having correct price policy, there should be an appropriate mechanism to make and use systematic statistical data on price. Price statistics are made by indexes and price indexes are categorized into producer price index(PPI) and consumer price index(CPI). The Bank of Korea is publishing producer price index every year, but the producer price index contains some problems. These include as follows : (a) the impractical selection of fisheries products sample (b) uncorrect measure of aquatic products weights (c) investigating sample places. This study try to substitute producer price index of aquatic products and change construction of fisheries producer price index with experimental research on representative fisheries, weight of each fisheries, and suitability of investigating sample places. It is possible to improve practical fisheries producer price index with the results of this research. The findings are as follow. (a) It will be helpful for the government to make the fisheries price policy. (b) It can be used to understand trends of accurate price and price increase of aquatic products, and it's possible to compare with it other industrial indexes including the mining, agricultural, and manufacturing industry and understand relative price movement. (c) When free sales systems of fisheries products as expected, it will be helpful to analyze price movement of producing fisheries cooperatives, producing fisheries market and consuming fisheries market, analysis of market, and formation and consideration of budget. (d) It can be an important index to determine labor wage.

• Journal of Distribution Science
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• v.15 no.3
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• pp.17-25
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• 2017

Purpose - The study is to examine the impact of the US Purchasing Managers' Index (PMI) on Korea and the US industrial economy including the distribution industry. We analyze its effect on the industrial economy centered on the distribution industry using economy indices in Korea and the US. Research design, data, and methodology - The variables are used to analyze the dynamic relationship which occurs among the US PMI, the industrial production index, producer price index, unemployment rate, and manufacturing Inventories Index in Korea and the US from January 1990 to July 2016 using Vector Error Correction Model. Results - As a main result, the impact of the US PMI on all the economy indices both Korea and the US has the same cyclical movement. The US PMI is positively related to the producer price and the industrial production index of Korea and the US, while it is negatively related to unemployment rate, and the manufacturing inventories index in Korea and the US. Conclusions - The US PMI as an advanced index has a power to predict the economies on Korea and the US. In the end, we find that the US PMI has a great impact on Korea and the US industrial economy.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.16 no.6
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• pp.63-75
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• 2013

The purpose of the study is investigating the price fluctuation of landscaping plants in the Information on Commodity Prices(ICP) and the posted price fluctuation of landscaping plants of Public Procurement Service(PPS) recent 10 years. It also provides the basic information which can be applied to production and sales of landscaping plants, comparing with general price index. The major findings of the study are as follows. First, The price of investigated plants of PPS has increased about 4.56% in average recent 10 years. Among this increase, of evergreen tree was predominant. On the other hand, landscaping trees price of ICP has increased about only 2.34% in average. Secondly, The result shows that average price of investigated plants of PPS is positively related with the price of ICP. For this reason, we found that prices of ICP and of PPS move together in most case. However, we found that there are no relation between Consumer Price Index(CPI), Producer Price Index(PPI) and Agricultural Price Index(API). Therefore, price fluctuation of landscaping trees moves regardless of normal price fluctuation in general. Third, even though result shows that price index of evergreen trees, deciduous trees and shrubs are weakly related with normal price index partly, it was not high enough to be significant. According to the result, we found that price of landscaping plants is not related with market situation. For this reason, we thought that there are some difficulties for the reasonable production and sales of landscaping plants because the price is somewhat decided by rule of thumb. Therefore, understanding the composition of cost and making prediction by price fluctuation available are needed so that it can be practically conducive to reasonable production and sales.

• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.535-542
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• 2012

The consumer price index (CPI) data is one of the important economic measurement of the country. In this article, the Autoregressive Error (ARE) model has been considered for analyzing the monthly CPI data at Seoul, Pusan, Daegu, and Gwangju Cities in Korea, In the ARE model, nine economic variables are used as the explanatory variables for the CPI data set. The nine explanatory variables are CCI (coincident composite index), won-dollar rate, producer price index, oil import price, oil import volume, international current account, import price index, unemployment rate, and amount of currency. The result showed that the monthly ARE models explained about 46-52% for describing the CPI.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.1
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• pp.108-115
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• 1998

The objective of this study was to estimate the quantitative loss of the consumer surplus due to the tariffs on clothing imports during the WTO starting periods. For 1984-1996, the import price elasticity of the clothing was estimated from the regression of pet capita clothing imports on Per capita GNP, import price index and domestic producer price index. Then the quantitative losses of the consumer surplus in clothing were obtained from the simplified formula for 1990-1995. In spite of the decrease in textiles St clothing tariff rates, consumer costs were increasing, which was caused by the tremendous increase in clothing imports during the same period. The loss of the consumer surplus was 7131 billion wonts in 1995, which accounted for 6.4% of the total clothing expenditure.

• Korean Journal of Construction Engineering and Management
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• v.16 no.4
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• pp.21-29
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• 2015

Construction cost index (CCI) has been published for last 10 years, it's contributed to update the historical cost data, analysis cost fluctuation and evaluate the market price for construction works with direct or indirect manner. CCI is a secondary or processed statistics using the basic statistics of input output table (IO table) and producer price index (PPI) from the Bank of Korea (BOK). So once the basic statistics change, it is required to modify the calculating model of CCI. Recently the BOK changed some fundamental principles and the base year (from 2005 to 2010), that can be used in IO table and PPI. This research analyzed the recent revision of basic statistics and their impacts on CCI, and improved the previous CCI model in response to it. Also the validity of new CCI was verified by analyzing the items and weights utilized in CCI and comparing the related index.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.5
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• pp.527-534
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• 2020

A significant factor in construction work is cost. At early- and advanced-stage design, costs should be calculated to derive realistic cost estimates according to unit price calculation. Based on these estimates, the economic feasibility of construction work is assessed, and whether to proceed is determined. Through the Korea Institute of Civil Engineering and Building Technology, the construction cost index has been calculated by indirect methods after both the producer price index and construction market labor have been reprocessed to easily adjust the price changes of construction costs in Korea, and the Institute has announced it since 2004. As of January 2000, however, the construction cost index was released, and this has a time constraint on the correction and use of past construction cost data to the present moment. Variables were calculated to compute a rough construction cost that utilized past construction costs through surveys of the producer price index and the construction market labor force consisting of the construction cost index. After significant independent variables among the many variables were selected through correlation analysis, the construction cost index from 1970 to 1999 was calculated and presented through multiple regression analysis. This study therefore has prominent significance in terms of proposing a method of calculating rough construction costs that utilize construction costs that pre-date the 2000s.

• 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 $P_{t.}$

• Land and Housing Review
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• v.4 no.1
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• pp.43-54
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• 2013

This This paper investigates the variation of the factors to determinate housing price in Seoul metropolitan area after sub-prime financial crisis, in Korea, using a VAR model. The model includes housing price and housing rent (Jeonse) in Seoul metropolitan area from 1999 to 2011, and uses interest rate, real GDP, KOSPI, Producer Price Index and practices to impulse response and variance decomposition analysis to grasp the dynamic relation between a variable of macro economy and and a variable of housing price. Data is classified to 2 groups before and after the 3rd quater of 2008, when sub-prime crisis occurred; one is from the 1st quater of 1999 to the 3rd quater of 2008, and the other is from the 2nd quater of 1999 and the 4th quater of 2011. As a result, comparing before and after sub-prime crisis, housing price is more influenced by its own variation or Jeonse price's variation instead of interest rate and KOSPI. Both before and after sub-prime financial crisis, Jeonse price is also influenced by its own variation and housing price. While after sub-prime financial crisis, influences of Producer Price Index, KOSPI and interest rate were weakened, influence of real GDP is expanded. As housing price and housing rent are more influenced by real economy factors such as GDP, its own variation than before sub-prime financial crisis, the recent trend that the house prices is declined is difficult to be converted, considering domestic economic recession and uncertainty, continued by Europe financial crisis. In the future to activate the housing business, it ia necessary to promote purchasing power rather than relaxation of financial and supply regulation.

• 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.