• 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 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 Data and Information Science Society
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• v.28 no.1
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• pp.173-183
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• 2017

We investigate the factors affecting the price of apartments using the spatial and temporal data of private real estate prices. The factors affecting the price of apartment were analyzed using geographical and temporal weighted regression (GTWR) model which incorporates the temporal and spatial variation. In contrast to the OLS, a general approach used in previous studies, and GWR method which is most widely used for analyzing spatial data, GTWR considers both temporal and spatial characteristics of the house price, and leads to better description of the house price determination. Year of construction and floor area are selected as the significant factors from the analysis, and the house price are affected by them temporally and geographically.

• Plant Journal
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• v.14 no.1
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• pp.47-51
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• 2018

This study analyzed the effect of power output reduction in coal fired power generation on the change of system marginal price and green house gas emissions. Analytical method was used for electricity market forecasting system used in korea state owned companies. Operating conditions of the power system was based on the the 7th Basic Plan for Electricity Demand and Supply. This as a reference, I analyzed change of system marginal price and green house gas emission by reduced power output in coal fired power generation. The results, if the maximum output was declined as 29 [%] to overall coal-fired power plant, system marginal price is reduced 12 [%p] compared to before and decreasing greenhouse gas emissions were 9,966 [kton]. And if the low efficiency coal fired power plant that accounted for 30 [%] in overall coal-fired power plant stopped by year, system marginal price is reduced 14 [%p] compared to before and decreasing greenhouse gas emissions were 12,874 [kton].

• Land and Housing Review
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• v.11 no.3
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• pp.1-9
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• 2020

This study fulfills an empirical analysis how the physical factors affect the formation of housing price with the block unit. Block unit houses are a type of housing that pursues comfort and convenience in that the characteristics of individual houses and apartment houses are mixed. Existing studies have focused only on the physical characteristics of various planning elements such as block-type residential complexes. Nevertheless, it is not known whether the physical characteristics of block-type residential complexes reflect the preferences of actual consumers. In addition, there are no sufficient studies on how to evaluate them from the market side. In this study, block-level detached housing sites the target complexes with 10 or more households built between 2002 and 2019. The target areas for analysis are 163 complexes in Paju, Namyangju, Goyang, Suwon, Yongin, Ansan, Gimpo, Incheon, Seongnam, Hwaseong and Gwangju, Gyeonggi-do. The physical elements that make up the unit housing were classified through factor analysis. Finally, regression analysis was conducted to establish the basis determining the price-forming factors. As a result of the analysis, the factors that influenced the price were the site area and the number of community facilities. The variable with negative influence was the distance from Seoul. Based on the results of this study, it can be said that the influence on price formation in various areas was confirmed by presenting the relationship between the facility composition and price of a detached house.

• Journal of the Korean Geographical Society
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• v.43 no.3
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• pp.392-411
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• 2008

The purpose of this paper is to develop a method for exploring hotspot patterns of house price volatility where there is a high fluctuation in price and homogeneity of direction of price volatility. These patterns are formed when the majority of householders in an area show an adaptive tendency in their decision making. This paper suggests a method that consists of two analytical parts. The first part uses spatial scan statistics to detect spatial clusters of houses with a positive range of price volatility. The second part utilizes local Moran's I to evaluate the homogeneity of direction of price volatility within each cluster. The method is applied to the areas of Gangnam-Gu, Seocho-Gu, and Songpa-Gu in Seoul from August to November of 2003; the Participatory Government of Korea designated these areas and this period as the most speculative. The results of the analysis show that the area around Gaepo-Dong was as a hotspot before the Government's anti-speculative 10.29 policy in 2003; the house prices in the same area stabilized in October, 2003 and the area was identified as a coldspot in December, 2003. This case study shows that the suggested method enables exploration of hotspot of house price volatility at micro spatial scales which had not been detected by visual analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1318-1326
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• 2014

The change of concept about real estate marketing and the solution about unsold houses are getting important nowadays. This paper is analyzing the solution of unsold houses as location environment, residential environment, macro environment, and marketing, and research question is which elements are important to real users. In addition, this paper is analyzing on impact relationship in terms of real users' buying intention about unsold houses and satisfaction of price of selling a house (price of selling a house, rise in housing value) by PLS structural equation. To sum up, first, macro environment, residential environment, location environment is statistically valued on the satisfaction of price of selling a house. However, marketing strategic is not impacted on the satisfaction of price of selling. Second, macro environment, marketing strategic, satisfaction of selling a house is statistically valued on buying intention.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5403-5410
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• 2013

This study investigated the effect of symbolic meanings of the artwork objectives on auction price. Based on Buck(1948)'s House-Tree-People(H-T-P) model, we hypothesized that symbolic meanings of these objectives invoke preferences of bidders and increase the price. Using 402 auction price data from June 2010 to May 2011, we found that an artwork including house and people tend to be auctioned off at a higher prices than the artwork without them. This study confirmed that Buck's model can be used to determine artwork price, suggesting that symbolic objectives in the artwork do affect its price.

• Korea Real Estate Review
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• v.24 no.1
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• pp.15-26
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• 2014

Using multivariate GARCH model, we estimate the relationship between the housing sale prices and lease prices in the Korean housing market. In the analysis of relationship between the rate of changes in sale and lease prices, the correlation coefficient of the apartment and detached house is higher than that of the townhouse. By housing type, the correlation coefficient between detached house and townhouse is higher than between apartment and detached house or apartment and townhouse. By housing size, there are no significant different results between the sales price and the rental price. The correlation coefficient between medium and small size is the highest in the apartment housing market, whereas the correlation coefficient between large and medium size is the highest in the detached housing market, resulting from the fact that people may be more interested in medium- and small-sized apartment and large- and medium-sized detached house. In the detached housing market, the correlation coefficient between large-medium size and medium-small size in the rental price is higher than that of sales price. This result implies that the process of the decision making between purchasing and leasing a house might be different.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.555-561
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• 2019

This study analyzed the shipbuilding structure of House Tangerine over a ten day period and according to the month in Jeju. By estimating and analyzing the price flexibility function of House Tangerine, the aim was to determine if the shipment control can stabilize and increase the incomes of House Tangerine farmers and derive policy implications. The greatest decline in the coefficients of the ten-day price flexibility occurred in the equations from early June to late July. Therefore, the shipment control of House Tangerine is required more during early June and late July. The coefficient of DUM_Q, indicating the year in which the quality of House Tangerine is somewhat deteriorated, was statistically significant and had a (-) sign. The coefficients of DUM_SUK, indicating the year in which Chuseok (Korean Thanksgiving Day) was in October, was statistically significant and had a (-) sign in the middle and late October. The greatest decline in the coefficient of monthly price flexibility function occurred in July, June, and September. Therefore, shipment control is required more in July, June, and September. The (-) signs of the coefficients of DUM_Q and DUM_SUK suggest that the need for shipment control is more important when the quality is less than better quality and that the necessity of shipment control is required more when Chuseok is in October, respectively.