• Land and Housing Review
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• v.9 no.4
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• pp.1-9
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• 2018

Since year 2000, French housing and rent prices rose at a rapid rate and the housing market has been overheated. Face to this phenomena, the French government enacted a new law Alur which is a legislatif tool to control the private housing rent price for the cities, where the tension of the housing market is very high. This new law has impacted the housing market in two major ways. First, for the 38 cities designated by this law, the rent price's increase rate can not rise above the IRL, which is the rent reference index. Secondly, this law also permits local authorities to control the housing rent's price following the concrete price guidance. Especially in Paris, the city applicated this method for private rental housing since 2015. This city classified its own area by 14 zones. Based on the market surveys of each sector, local authority made a guidance for private housing rent's price. The guideline is consisted of average prices, maxima and minima price by types, which is classified by the construction year, number of rooms and furnished or not. Therefore, this study aims to understand french housing rent's price control system and draw implementation for korean housing rent policies. This research is meaningful for it introduces recent foreign regislations which could be helpful to control the housing market in Korea.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.1
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• pp.81-89
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• 2013

The purpose of this study is to analyze the information effect about the pricing using the ETF price, the benchmark index, and the total tracking error between the ETF price and the benchmark index on the index ETF market and sector ETF markets. Furthermore, the total tracking error is distinguished between the market tracking error and the NAV tracking error. Summary of this study are as follows: First, While KODEX200 don't have impact factors on the price, the most sectors of ETF have the factors affecting the pricing decision. They are the day before the total tracking error or market tracking error. Second, for the ETF price of the most industry, we find that the day before the market tracking error have the price discovery function because it is a negative(-) coefficients. But NAV tracking error could not find such a feature. Finally, the sector ETF price of energy chemical, construction, IT, and semiconductor industries affected of the day before positive(+) impact by the benchmark index price.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.313-320
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• 2017

Price fluctuation contract is imperative and of paramount essence in the construction industry as it provides adequate relief and cushioning for changes in the prices of input resources during construction. As a result, several methods have been devised to better help in arriving at fair recompense in the event of price chang es. However, stakeholders often appear not to be satisfied with the existing methods of fluctuation evaluation, ostensibly because of the challenges associated with them. The aim of this study was to identify the challenges to usage of building construction cost indices in Ghana. Data was gathered from contractors and quantity surveying firms. The study utilized survey questionnaire approach to elicit responses from the contractors and the consultants. Data gathered was analyzed scientifically, using the Relative Importance Index (RII) to rank the problems associated with the existing methods. The findings revealed the following among others; late release of data; inadequate recovery of costs; and work items of interest not included in the published indices as the main challenges of the existing methods. This study will provide useful lessons for policy makers and practitioners in decision making towards the usage and improvement of available indices.

• Survey Research
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• v.9 no.3
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• pp.1-21
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• 2008

The housing market in Korea had mainly consisted of Maemae(purchasing market) and Chonsei(rental market). Since 1997 foreign exchange crisis, the rental housing market has experienced substantial changes in preferred rental contracts between Chonsei and monthly-rent. Even though monthly-rent has taken a substantial portion of housing rental contracts, not yet reliable monthly-rent index has been developed. Furthermore, it isn't obvious to define monthly-rent because there are many types of monthly rent structures from full-monthly-rent to monthly-rent-with-variable-deposit. This study is the basic research of developing a housing price index of monthly-rent in accordance with the existing price index of Maemae and Chonsei in Korea. This research has been carried out with the following contents: (1) Constructing the actually desirable concept of monthly-rent through examining monthly-rental market in Korea. (2) Selecting the reasonable method to investigate monthly-rental market, especially monthly-rent-with-variable -deposit. (3) Designing monthly-rental market samples and calculating the price index of monthly-rent based on 2005 Census.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.44-48
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• 2015

Housing price is a key indicator of housing demand. Actual Transaction Price Index of Apartment (ATPIA) released by Korea Appraisal Board is useful to understand the current level of housing price, but it does not forecast future prices. Big data such as the frequency of internet search queries is more accessible and faster than ever. Forecasting future housing demand through big data will be very helpful in housing market. The objective of this study is to develop a forecasting model of ATPIA as a part of forecasting housing demand. For forecasting, a concept of time shift was applied in the model. As a result, the forecasting model with the time shift of 5 months shows the highest coefficient of determination, thus selected as the optimal model. The mean error rate is 2.95% which is a quite promising result.

• Korean Journal of Construction Engineering and Management
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• v.7 no.2 s.30
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• pp.53-61
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• 2006

Korean Government started to publish Korean CCI(Construction Cost Index) again at February 2004 since CAK(Construction Association of Korea) stopped publishing it 1994. CCI is developed using the verified statistical data, that is, input-output table and producer price index by Korean Bank and labor unit cost by CAK. Though the method is available as it uses the verified statistical data, there is a limitation to reflect the characteristics of construction. For overcoming this limitation, this study suggests CCI development method investigating the input structure of labor and material cost for each type of construction project and applying the cost variations of the items.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.105-113
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• 2006

Construction cost index is generally used to estimate the new project cost based on past construction data and to adjust the contract cost when the price change of various articles and items of expenditure composing the contract occurs. In Korea, it is mostly used for modulation of construction contract cost due to fluctuation of prices. However the method for making cost index had some problems in calculating cost index of each expenditure item that could not properly reflect the change of construction cost. To supplement these problems, the research of developing construction cost index has been executed. Through the precedent research, these problems were partially resolved but still remain. Therefore this research proposes the method for making cost index that utilizes representative items of labor, material, equipment by analyzing bill of quantity of road construction, through analysis and comparison of precedent studies. By using this method, it is expected to solve the problems which were not reflected in preceeding studies.

• Journal of The Korean Digital Architecture Interior Association
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• v.12 no.1
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• pp.89-98
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• 2012

While the housing transaction price of Seoul tends to be stagnant or declining in line with the housing market recession since 2007, the jeonse price keeps continual increase. Such flow of jeonse price change has a serious influence on ordinary person's housing stability seriously. Therefore, it is very meaningful in terms of social policy to analyze the trend of recent jeonse price change. This study aims to have an empirical analysis of structural characteristics of the trend of recent jeonse price change. After the review of various previous studies, this study selected housing jeonse price index, non-sold house quantity, jeonse vs. transaction price rate, and housing construction performance as analytical variables, and employed monthly time series resources from January 2007 to April 2011. As a result, when the housing supply reduced, the potential quantity for jeonse market reduced that occurred unbalance of supply and demand in jeonse market. In turn, it caused the increase of jeonse price. And, in case of jeonse vs. transaction price rate change, the rate increased which means the increase of required rate of return of invested demand. As such, the increase of market risk degenerates the investment sentiment which caused the reduction of quantity for jeonse market as a submarket.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.423-426
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• 2002

The foundation for developing a cost estimation system based on historical data has been being prepared in Korea. Historical data is a priori of developing a cost estimation model. Cost Index, one of the historical data, is used to estimate construction cost and to adjust the amount of contract money in the foreign country, whereas it is not used in domestic except for the road construction project in Korea. Construction cost indices can be used by an estimator in tender analysis, pricing, price adjustment, cost planning, and forecasting. In this regards, this paper identified the problems in developing Cost Index evaluation process by comparing the standard of framing Cost Index used in British to the one used in Korea. Then, the scheme for improving a Cost Index required for Site Developing Construction was proposed. Twenty-two cases of engineering estimate data were used to compare the domestic standard to the foreign one in deriving a Cost Index.

• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.233-260
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• 2022

In this paper, we analyzed how oil price fluctuations affect stock price by industry using the non-parametric quantile causality test method. We used weekly data of WTI spot price, KOSPI index, and 22 industrial stock indices from January 1998 to April 2021. The empirical results show that the effect of changes in oil prices on the KOSPI index was not significant, which can be attributed to mixed responses of diverse stock prices in several industries included in the KOSPI index. Looking at the stock price response to oil price by industry, the 9 of 18 industries, including Cloth, Paper, and Medicine show a causality with oil prices, while 9 industries, including Food, Chemical, and Non-metal do not show a causal relationship. Four industries including Medicine and Communication (0.45~0.85), Cloth (0.15~0.45), and Construction (0.5~0.6) show causality with oil prices more than three quantiles consecutively. However, the quantiles in which causality appeared were different for each industry. From the result, we find that the effects of oil price on the stock prices differ significantly by industry, and even in one industry, and the response to oil price changes is different depending on the market situation. This suggests that the government's macroeconomic policies, such as industrial and employment policies, should be performed in consideration of the differences in the effects of oil price fluctuations by industry and market conditions. It also shows that investors have to rebalance their portfolio by industry when oil prices fluctuate.