• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2004.11a
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• pp.393-397
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• 2004

The purpose of this study was to analyze the needs for managerial service for residents in multi-family housing. For the survey and statistical analysis, the questionnaires from 484 residents and 84 housing managers of multi-family housing within the Seoul metropolitan area were used. The analytical methods adopted in this study were frequency, percentage, t-test, and factor analysis. The results of this study are as follow : (1) Basic services within a multi-family housing included management, minimum residential self governance, basic etiquette, and community program. And additional service were categorized by the health and entertainment program, the consumer service program, the residential life services, the information and financial services program, and the children's program. (2) The favorite needs of residents' additional services were the market news and information, the programs related health, the mail services, the health diagnosis service programs etc. But, housing managers' needs were the market news and information, and the flea market. As to the results analyzing the needs for additional service fir residents, it was found there were differences between residents and housing managers.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.4
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• pp.555-575
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• 2019

Though housing market varies spatially, housing policy is limited in reflecting detailed regional differentiation. This study looked at the differences in Seoul Gu Districts' response to housing policy for the efficient implementation of housing policies in the future. Housing policy index was established by each Gu-districts' according to investigated housing policies from 2003 to 2018, weighted in two categories(financial/urban planning) and the status of designated areas. The VECM model was established to analyze the impact of the housing policy on the housing market. According to the analysis, although housing policies were established in response to market prices change, the impact of policies on prices was lower than the impact of vice versa. The housing policy's impact to the housing market is limited in some areas in northeastern Seoul. These results show that there are differences in the responses to housing policy in Seoul districts', and therefore detailed consideration of the differences in the regional aspects of housing policy is needed.

• Journal of Distribution Science
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• v.11 no.10
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• pp.63-72
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• 2013

Purpose - This study analyzes the relationship and dynamic interactions between stock price index, interest rate, price index, and housing price indices using Korean monthly data from 2000 to 2013, based on a VAR model. This study also examines Granger causal relationships among these variables in order to determine whether the time series of one is useful in forecasting another, or to infer certain types of causal dependency between stochastic variables. Research design, data, and methodology - We used Korean monthly data for all variables from 2000: M1 to 2013: M3. First, we checked the correlations among different variables. Second, we conducted the Augmented Dickey-Fuller (ADF) test and the co-integration test using the VAR model. Third, we employed Granger Causality tests to quantify the causal effect from time series observations. Fourth, we used the impulse response function and variance decomposition based on the VAR model to examine the dynamic relationships among the variables. Results - First, stock price Granger affects interest rate and all housing price indices. Price index Granger, in turn, affects the stock price and six metropolitan housing price indices. However, none of the Granger variables affect the price index. Therefore, it is the stock markets (and not the housing market) that affects the housing prices. Second, the impulse response tests show that maximum influence on stock price is its own, and though it is influenced a little by interest rate, price index affects it negatively. One standard deviation (S.D.) shock to stock price increases the housing price by 0.08 units after two months, whereas an impulse shock to the interest rate negatively impacts the housing price. Third, the variance decomposition results report that the shock to the stock price accounts for 96% of the variation in the stock price, and the shock to the price index accounts for 2.8% after two periods. In contrast, the shock to the interest rate accounts for 80% of the variation in the interest rate after ten periods; the shock to the stock price accounts for 19% of the variation; however, shock to the price index does not affect the interest rate. The housing price index in 10 periods is explained up to 96.7% by itself, 2.62% by stock price, 0.68% by price index, and 0.04% by interest rate. Therefore, the housing market is explained most by its own variation, whereas the interest rate has little impact on housing price. Conclusions - The results of the study elucidate the relationship and dynamic interactions among stock price index, interest rate, price index, and housing price indices using VAR model. This study could help form the basis for more appropriate economic policies in the future. As the housing market is very important in Korean economy, any changes in house price affect the other markets, thereby resulting in a shock to the entire economy. Therefore, the analysis on the dynamic relationships between the housing market and economic variables will help with the decision making regarding the housing market policy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.480-488
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• 2016

As the subprime mortgage crisis spread globally, it depressed not only the financial market, but also the construction business in Korea. In fact, according to CERIK, the BSI of the construction businesses plunged from 80 points in December 2006 to 14.6 points in November 2008, and the extent of the depression in the housing sector was particularly serious. In this respect, this paper analyzes the influence of the financial market fluctuation on the housing market before and after the Global Financial Crisis using VECM. The periods from January 2000 to December 2007 and January 2008 to October 2015, before and after the financial crisis, were set as Models 1 and 2, respectively. The results are as follows. First, when the economy is good, the Gangnam housing market is an attractive one for investment. However, when it is depressed, the Gangnam housing market changes in response to the macroeconomic fluctuations. Second, the Gangbuk and Gangnam housing markets showed different responses to fluctuations in the financial market. Third, when the economy is bad, the effect of low interest rates is limited, due to the housing market risk.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.280-287
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• 2011

The purpose of this study is to analyze that ordinary housing stability policy determines the impact on housing prices. I got a conclusion such as the result next which carried out proof analysis for this. First, as a result of the Granger Causality Test, the house market of all areas appeared by affecting ordinary housing stability policy. Second, the shock reaction shows the reaction of the department (-) in all areas and ordinary housing stability policy appeared to be contributed to some extent house market stability. Third, as a result of having analyzed Logit Regression Analysis, ordinary housing stability policy appeared to considerable effects house market stability except Kangnam area of the Roh Moo-hyun government.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.4
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• pp.592-609
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• 2019

This study attempts to expand the leverage cycle theory using the subprime real estate investors. The leverage cycle theory has demonstrated asset price fluctuations irrelevant to changes in fundamentals through the restructuring of transaction composition centered on optimistic buyers. However, it needs to understand how this theory works in the depressed housing market with low-income residential regions to explain the geographic origins of the financial crisis. In the depressed housing market, the subprime real estate investors focused on low-income residential regions. Through this spatial focus, the low-income residential regions solely have real estate investor-oriented composition of new purchase transactions in the depressed housing market. The discovery of the subprime real estate investors as new actors lays the foundation for applying the leverage cycle theory to the depressed housing market which has been a underserved area for capital investment. This attempt illustrates how the geographical reinterpretation of an economic theory reestablishes spatio-temporal context of economic phenomena.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.39-45
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• 2015

The housing market is transformed by a variety of socio-economic characteristics, also appeared differently according to regional characteristics. This study aims to draw out the change factors influencing on the housing market structure and to analyze the drawn factors' distribution pattern by area. For this purpose, First, targeting 251 areas in the units of city, county and districts nationwide, this study drew out demographic, socio-economic variables influencing on the housing market structure for 5 years ranging 2005 to 2010. For that, the factor analysis was conducted. Second, this study grasped the change factors of the housing market structure's spatial patterns using the kriging method, a spatial statistical method. Third, this study used the Moran I, one of spatial autocorrelation analysis methods in order to grasp whether the factors had statistically significant concentration or dispersion or showed a random distribution pattern.

• Land and Housing Review
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• v.11 no.1
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• pp.59-66
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• 2020

This thesis investigates relationship between Stock-to-Flow price and housing starts in Seoul metropolitan form 2008 year to 2019 year. The paper tests the relationship through two time-series models such as a vector error correction model and Dynamic Panel regression model. The model results show evidence of positive correlation between Stock-to-Flow price and housing starts in the long run. By transforming the regional data into a panel data set and running a fixed effects model, we test the explanatory power of PBR on housing starts. The result of VECM confirms that one unit uprising PBR raises up apartment construction by 7.4%. This result supports that PBR is a major factor in choosing a start of housing construct. Base on the result of empirical model, We also suggest that the market self-regulation function of housing providers is operating in the entire metropolitan area market.

• Journal of the Economic Geographical Society of Korea
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• v.5 no.2
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• pp.293-302
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• 2002

China in the era of economic transition has conducted the housing reform policy over the past 20 years. Housing providing systems have changed from the free distributing housing system under the governmental planning to the monetary housing system for individual customers. The 1998 monetary housing distribution policy, which ended the 20-year Chinese housing reform, departed from the direct distribution system that had blocked housing commodification. The purpose of the housing reform was to provide and reproduce housing without the expenses of the Chinese government and work unit (danwei), which is different from Russia. In order to achieve the housing reform, the Chinese government introduced various policies, which enabled residents to purchase housing by themselves. However, it took long for residents, who had taken government's welfare system granted, to accept housing as goods. In addition, the Chinese government's efforts to reproduce housing by market systems failed because housing was closely linked to land and was expensive consumption goods, which differentiates housing from other goods that can be commodified through market prices and diverse ownerships. Accordingly, despite a political burden, the Chinese government waived the real distribution policy for housing. After the waiver, the housing commodification process excelled through the private housing markets.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.432-439
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• 2013

In this study, we evaluate the volatility of housing prices by using literature review and empirical analysis and furthermore we suggest how to improve. In order to diagnose housing market, the KB Bank's House Price Index, Real estate 114;s materials were compared. In addition, to examine the volatility, GARCH (Generalized Autoregressive Conditional Heteroskedasticity) and EGARCH (Exponential GARCH) model are used. By analysis of this research, we found the volatility of housing price also was reduced in the medium and the large houses since 1998, while the volatility of small housing price relatively was large. We proved that the price change rate of small housing was higher than the medium's. On the order hand, the supply of small apartments fell down sharply. The short-term oriented policy should be avoided, and the efficiency and credibility of policy should be increased. Furthermore, the long-term policy system should be established. and rental market's improvement is necessary for stabilization of housing market.