• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6315-6324
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• 2015

This study analyses the effects of household finances on rental price of apartment in Seoul which play a major role in real estate policy. We estimate VAR models using time series data. Economy variables such as sales price of apartment in Seoul, consumer price index, hiring rate, real GNI and loan amount of housing mortgage, which relate to household finances and influence the rental price of apartment, are used for estimation. The main findings are as follows. In the short term, the rental price of apartment is impacted by economy variables. Specifically, Relative contributions of variation in rental price of apartment through structural shock of economy variables are most influenced by their own. However, in the long term, household variables are more influential to the rental price of apartment. These results are expected to contribute to establish housing price stabilization policies through understanding the relationship between economy variables and rental price of apartment.

• Korean Journal of Construction Engineering and Management
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• v.11 no.5
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• pp.41-52
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• 2010

Even though REITs (Real Estate Investment Trusts) are listed on the stock market, REITs have characteristics that allow them to invest in real estate and financing for real estate development. Therefore REITs is related with stock market and construction business and real estate business. Using time-series analysis, this study analyzed REITs in relation to construction businesses, real estate businesses, and the stock market, and derived influence factor of REITs. We used the VAR (vector auto-regression) and the VECM (vector error correction model) for the time-series analysis. This study classified three steps in the analysis. First, we performed the time-series analysis between REITs and construction KOSPI(The Korea composite stock price index) and the result showed that construction KOSPI influenced REITs. Second, we analyzed the relationship between REITs and construction commencement area of the coincident construction composite index, office index and housing price index in real estate business indexes. REITs and the housing price index influence each other, although there is no causal relationship between them. Third, we analyzed the relationship between REITs and the construction permit area of the leading construction composite index. The construction permit area is influenced by REITs, although there is no causal relationship between these two indexes, REITs influenced the stock market and housing price indexes and the construction permit area of the leading composite index in construction businesses, but exerted a relatively small influence in construction starts coincident with the composite office indexes in this study.

• Korean Journal of Construction Engineering and Management
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• v.20 no.6
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• pp.132-141
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• 2019

1990s, Construction market continued to grow in South Korea exceeding 20% of GDP. In 2015, more than 30 years of old multi-family dwellings amounted to 4.93 million and it continues to increase until 2019. In Particular, the share of Public rental Housing accounts for 90.6% of South Korea's Total aging housing. Before checking the feasibility of Construction Project Management such as Renovation and Reconstruction, Checklists were presented through price impact factor analysis and analysis of housing construction system(Regulation). Based on 32 Price Influencing factors and 20 Indicators based on the housing construction system The Construction project management seems appropriate. As a result, the 22 complexes were found to be suitable for remodeling. This study is meaningful enough to be used for Domestic rental Housing construction and Construction project management and to suggest specificity. Future Research is needed to Quantify the checklist.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.59-70
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• 2013

As people invest most of their asset in real estate, there is high interest in changing in housing and real estate prices in the future for a digital economy. Various variables are affecting the housing and real estate market. Among them, four variables : households, productive population, interest rate and index price are chosen and analyzed representatively. This study is aimed to build decision model of apartment prices in Seoul empirically. From the analysis result the stock index is the only variable which is significant statistically to apartments in Seoul. From this study, the households and productive population show the same direction as shown in the previous studies before but not significant statistically. Among the independent variables, the stock index is chosen as a major variable of determinant of Seoul apartment price. From the result of the research, prediction of stock market should be preceded to forecast the movement of housing and real estate market in the future.

• Korea Real Estate Review
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• v.27 no.3
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• pp.71-86
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• 2017

The purpose of this study was to apply the deep running method to real estate price index predicting and to compare it with the time series analysis method to test the possibility of its application to real estate market forecasting. Various real estate price indices were predicted using the DNN (deep neural networks) and LSTM (long short term memory networks) models, both of which draw on the deep learning method, and the ARIMA (autoregressive integrated moving average) model, which is based on the time seies analysis method. The results of the study showed the following. First, the predictive power of the deep learning method is superior to that of the time series analysis method. Second, among the deep learning models, the predictability of the DNN model is slightly superior to that of the LSTM model. Third, the deep learning method and the ARIMA model are the least reliable tools for predicting the housing sales prices index among the real estate price indices. Drawing on the deep learning method, it is hoped that this study will help enhance the accuracy in predicting the real estate market dynamics.

• 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 the Korean Geographical Society
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• v.38 no.6
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• pp.949-960
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• 2003

The marginal implicit price of air quality can be measured by taking a partial derivative of hedonic price function (HPF) with respect to the level of air quality. It has been pointed out that the size of the marginal implicit price varies with the use of different function forms, different estimation methods, and the different ways of measuring air quality level in estimating HPF. In addition to these factors, this study shows theoretically and empirically the way housing properties are represented on a digital map could differentiate the size of marginal implicit price of air quality when GIS is used to measure location attributes of the housing properties in the Korean apartment market. Furthermore, this study shows that the degree of difference in the marginal implicit price due to the manner in which housing properties are represented on a digital map can be larger than the degree of difference in the marginal implicit price due to using different function forms and estimation methods. The major implication from the results of this study is that one should carefully try diverse ways of representing housing properties in the Korean apartment market on a digital map in the process of estimating HPF, as he or she usually tries diverse function forms and estimation methods, to see if the value of the marginal implicit price of air quality varies substantially.

• Journal of the Korean Home Economics Association
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• v.37 no.4
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• pp.41-58
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• 1999

The purposes of this study were 1) to segment the market based on purchase frequency of products such as apparel, food, home electronics, life commodity in department store and low-price retailing, 2) to identify differences among segments in belief and attitude toward each store, purchase frequency of apparel items in each store and demographic variables. The data were collected via a self-administered questionnaire from 274 married women living in Seoul, Korea and analyzed by factor analysis, cluster analysis, one-way ANOVA and x$^2$-test. The results of this study were as follows: First, using cluster analysis on purchase frequency of products in each store, four groups were identified and labeled as department store patronage/ non-purchasers of apparel in low-price retailing(25.2%), purchasers of apparel in department store and low-price retailing(16.8%), low-price retailing patronage(30.3%) and non-purchasers of products in department store and low-price retailing(27.0%). Second, a series of one-way ANOV As revealed significant differences among four segments on beliefs of low-price retailing(four store attributes: price and variety of apparel product, facilities for convenient shopping, promotion, brand-reputation and fashionability of apparel product) and department store(three store attributes: price and variety of apparel product, facilities for convenient shopping and promotion) and attitude toward low-price retailing and department store. Attitude toward each store was yielded using Fishbein's multiattributes model. There were also significant differences among groups in purchase frequency of seven apparel items in low-price retailing and six apparel items in department store, and six demographic and personal variables(age, educational status, type of husband's occupation, monthly income and housing). Finally, the papers discussed manageral implications for each segments as well as theoretical implications.

• International Area Studies Review
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• v.12 no.3
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• pp.49-67
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• 2008

In this paper, we address the problem of optimal monetary policy rule in the presence of abrupt shifts in the structure of the economy. To do so, we first estimate a Markov switching model for the US housing price inflation, and find evidence supporting the presence of two distinct regimes for the US housing price inflation. One of the two regimes identified appears 'usual', in that housing price inflation negatively responds to higher real interest rate. The other regime is 'unusual', in that the housing price inflation is positively related with real interest rate. We then solve an optimal control problem of the FRB under the presence of the two regimes thus identified. The optimal policy is 'asymmetric' in that the optimal responses in the 'usual' regime require the FRB to lean against the wind to inflationary pressure, while the FRB is recommended to accommodate it in the unusual regime. It is also found that the optimal degree of responses is more conservative when the FRB acknowledges the uncertainty about future regime.