• Journal of the Korea Institute of Building Construction
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• v.12 no.6
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• pp.624-635
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• 2012

Construction projects, including housing, are carried out over long periods of time. According to changes to the construction period, the cost of input materials and wages also changes. Therefore appropriate management is important in order to minimize cost risks caused by fluctuations in prices. In Korea, housing units are usually sold in lots prior to construction completion. Therefore, careful management of input elements such as materials and equipment that are sensitive to price fluctuations is very important. This study deals with how the price fluctuation of materials, labor, and equipment influences the change of housing cost and seeks a way for cost management through identifying key resources sensitive to price fluctuation. As a result, a change to the housing cost index multiplies depending on cost changes of materials and labor together. Labor costs are a major factor on the housing cost index. In addition, certain types of materials and labor input to housing construction greatly influence price fluctuations. Thus, it is found that managing those main cost factors is the key for effective cost management.

• Journal of Distribution Science
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• v.13 no.8
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• pp.61-71
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• 2015

Purpose - Before the year 2000, the housing prices in Korea were increasing every decade. After 2000, for the first time, Korea experienced a decrease in housing prices, and the repetitive cycle of price fluctuation started. Such a "boom and bust cycle" is a worldwide phenomenon. The current study proposes a mathematical model to explain price fluctuation cycles based on the theory of consumer psychology. Specifically, the model incorporates the effects of buyer expectations of future prices on actual price changes. Based on the model, this study investigates various independent variables affecting the amplitude of price fluctuations in housing markets. Research design, data, and methodology - The study provides theoretical analyses based on a mathematical model. The proposed model uses the following assumptions of the pricing mechanism in housing markets. First, the price of a house at a certain time is affected not only by its current price but also by its expected future price. Second, house investors or buyers cannot predict the exact future price but make a subjective prediction based on observed price changes up to the present. Third, the price is determined by demand changes made in previous time periods. The current study tries to explain the boom-bust cycle in housing markets with a mathematical model and several numerical examples. The model illustrates the effects of consumer price elasticity, consumer sensitivity to price changes, and the sensitivity of prices to demand changes on price fluctuation. Results - The analytical results imply that even without external effects, the boom-bust cycle can occur endogenously due to buyer psychological factors. The model supports the expectation of future price direction as the most important variable causing price fluctuation in housing market. Consumer tendency for making choices based on both the current and expected future price causes repetitive boom-bust cycles in housing markets. Such consumers who respond more sensitively to price changes are shown to make the market more volatile. Consumer price elasticity is shown to be irrelevant to price fluctuations. Conclusions - The mechanism of price fluctuation in the proposed model can be summarized as follows. If a certain external shock causes an initial price increase, consumers perceive it as an ongoing increasing price trend. If the demand increases due to the higher expected price, the price goes up further. However, too high a price cannot be sustained for long, thus the increasing price trend ceases at some point. Once the market loses the momentum of a price increase, the price starts to drop. A price decrease signals a further decrease in a future price, thus the demand decreases further. When the price is perceived as low enough, the direction of the price change is reversed again. Policy makers should be cognizant that the current increase in housing prices due to increased liquidity can pose a serious threat of a sudden price decrease in housing markets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.518-527
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• 2016

The housing market is changing continuously according to the place and time and these changes have a ripple effect across various fields. On the other hand, the amount of housing that is consumed in the region also acts as a central cause of price movement. Moreover, the cause of variations in the housing market can be separated according to the characteristics of the housing consumer. In addition, the individual characteristics of the consumer varies according to the region. As a result, a study on the regional causal relationship of the housing market is underway. Although significant research has been done on the domestic home sales market, there has been limited research on the housing charter market. Therefore, in this paper, regional causal relationship of the housing market in the Gangnam and Gangbuk area in Seoul and Gyeonggi Province was analyzed using the vector error correction model, and is segmented by housing sale market and housing jeonse market. In addition, housing sale and housing jeonse of Gangam, Ganbuk and Gyeonggi province are defined as analysis variables, and time series data is the monthly material of June 2003 to November 2015. The results of the analysis, in the case of the housing sale market, showed that fluctuations in house prices in Gangnam area have a major influence on the fluctuations in house prices in the surrounding region. Similarly, in the case of the housing jeonse market, it was found that the jeonse price of Gangnam area has a significant impact on the jeonse price of housing in the surrounding area.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.05a
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• pp.319-320
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• 2012

International oil prices is the world's leading macroeconomic indicators. Rising international oil price has been worsening. profitability of construction company including material cost as well stagnation in housing market. Thus, according to fluctuations in international oil prices has cost index need to see any change happening there. in this study, 2000 to 2011 interest rates, exchange rates and oil price fluctuations in construction cost is to compare the impact.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.245-253
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• 2020

If the conversion rate of jeonse price to monthly rent is the market interest rate or the landlord's expected return, then the conversion rate of jeonse price to monthly rent in the country should be the same. However, the conversion rate of jeonse price to monthly rent has always been higher than the market interest rate. This study identifies the supply cost components of rental housing as a risk premium in the presence of current housing prices, market interest rates, depreciation costs, holding taxes, and leases, and identifies the relationship between the current housing prices and each factor. Housing rent is expressed as the current price. This overcomes the shortcomings that implicitly assume fluctuations in housing prices or do not include current housing prices in the conversion rate of jeonse price to monthly rent. This study found that the conversion rate of jeonse price to monthly rent is the required rate of return or required rate of renter, not market interest rate, by expressing the supply cost of rental housing as a combination of components. This not only explained the fact that the conversion rate of jeonse price to monthly rent was always higher than the market interest rate, but also explained the regional differences. It also explained why the conversion rate of jeonse price to monthly rent varies by type of housing.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.43-49
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• 2020

The purpose of this study was to analyze factors affecting the housing market by setting household loans and M2, which are liquidity indicators, and the industrial production index reflecting economic fluctuations, as variables, and to determine the effect of expected housing prices. An empirical analysis was conducted based on the data from January 2005 to May 2020, and the HP filter was applied to the real house price as the expected house price variable. As a result of the analysis, it was found that real household loans, real M2, and so on, had an effect on house prices, and expectations for past house prices and house prices increased the house prices in the present period. These results show that even though the liquidity expansion is aimed at revitalizing the economy, it can affect housing prices as well.

• Journal of the Korean Regional Science Association
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• v.31 no.4
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• pp.91-105
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• 2015

Mortgage-Backed Securities (MBS) was introduced in 1999 in order to stabilize housing market and prevent potential speculation. However, research on MBS is limited, so this paper try to narrow the gap by focusing on the factors relating the pre-payment risk of MBS. We used Granger Causality Validation, Vector Auto Regressive, and HP-filtering with time-series data from 2004 to 2014. This paper shows that the prepayment rate of MBS increases as Mortgage rate decreases because borrowers tend to refinance existing MBS with new lower-rate MBS. In addition, it reveals that the rate increases as housing price increases. This outcome support the hypothesis that introduction of low-rate MBS invites more investment or speculation, and hence the housing price rises. The relationship between the MBS pre-payment rate and housing price is yet a peculiar characteristic of the MBS in Korea.

• Architectural research
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• v.24 no.3
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• pp.85-91
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• 2022

The public rental housing policy aims to provide the housing to the vulnerable class who do not have enough credit to own houses. The Korean government introduced new policies for housing supply to improve the availability of new houses. However, it is difficult to expand the supply because of the accumulated deficit of public rental housing. In this study, the economic feasibility of long-term public rental housing reconstruction projects was examined to ensure the economic and sustainable growth of public rental housing. The research found that the compensation for the accumulated deficit is needed. Also the research analyzed and identified the factors affecting the economic feasibility of reconstruction projects. The significant factors identified in this research are: the supply price of pre-sale/rental housing in the reconstruction project, total cost of the reconstruction project, and total floor area of the reconstruction project. According to the analysis results, it is necessary to increase the rent of existing long-term public rental housing, expand the government subsidy, increase the supply price of pre-sale/rental housing, and reduce the total project cost. However, there are limitations. For example, the fluctuations of construction market, residents' burden of housing costs, and the limit of the budget of the public housing authority. The increasing total Floor Area Ratio(FAR) limitation of the reconstruction project would be the realistic solution to the problem because it gives incentives to the reconstruction project.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.566-576
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• 2016

It is known that the Real Estate Sales Market and Auction Market are closely interrelated with each other in a variety of respects and the media often mention the real estate auction market as a leading indicator of the real estate market. The purpose of this paper is to analyze the relationships between the housing market and auction market before and after macroeconomic fluctuations using VECM. The period from January 2002 to December 2008, which was before the financial crisis, was set as Model 1 and the period from January 2009 to November 2015, which was after the financial crisis, was set as Model 2. The results are as follows. First, the housing auction market is less sensitive to changes in the housing market than it is to fluctuations in the auction market. This means that changes in the auction market precede fluctuations in the housing market, which shows that the auction market as a trading market is activated. In this respect, public institutions need to realize the importance of the housing auction market and check trends in the housing contract price in the auction market. Also, investors need to ensure that they have expertise in the auction market.

• KDI Journal of Economic Policy
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• v.45 no.4
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• pp.57-77
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• 2023

The Chonsei component holds the highest level of weight (5.4%) in the composition of the Korean consumer price index (CPI). The variations in Chonsei prices are directly reflected in the CPI as a representation of cost swings. The Chonsei refers to a deposit that accumulates the costs related to housing services and is mostly affected by variations in rental rates. Nevertheless, it is important to note that Chonsei prices are also susceptible to fluctuations in interest rates, regardless of the rent prices. Therefore, if Chonsei were directly and one-to-one indexed to the CPI, they could include changes other than residential service prices. After analyzing the time series data of the Chonsei index and rent index inside the CPI, it becomes apparent that the Chonsei index displays an average annual growth rate of 2.3%, whilst the rent index reveals a growth rate of 0.9%. The observed disparity in growth rates indicates a divergence in trends between the two indices. It is posited that the Chonsei index, when capitalized, has had a more rapid increase compared to the rental index, owing to the gradual drop in interest rates. To effectively reflect fluctuations in the housing service costs, proxies for the Chonsei index were utilized in the construction of a consumer price index. The findings of our study suggest that, overall, the newly developed CPI demonstrates a comparatively lower rate of inflation when compared to the official CPI. Furthermore, the inclusion of imputed rents for owner-occupied housing in CPI amplifies this effect.