• Architectural research
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• v.9 no.2
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• pp.27-35
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• 2007

Our nation has a problem with discrimination of income distribution and inefficient of resources distribution caused by real estate price rising from a sudden economy growth and industrialization. Specially, in recent years, there is a great disparity of apartment price between the north and south of the Han river. Because the housing price is decided by the immanent value of a house and neighborhood effects of the regional where the house is situated, the housing price is occurred difference. The purpose of study was to analyze the influence of various factors of housing price. Also, this study tried to predict real estate market and to establish previous effective real estate policy. In this study, we analyzed the differences of housing price determinants about apartment developments between the north and south of the Han river, and found the important factors that affect the housing price using Structural Equation Modeling(SEM). As a result of this study, the older the buildings are, the more the housing price and the housing price rising ratio have increased, in Gang Nam area. This reason is that these have large possibility to be reconstructed and many convenient facilities, in this area. In the case of Kang Buk area, the increase rate of housing price are so low that they couldn't take effect on the housing price and they were declined. So to speak, constructing the infrastructure which takes effect on the increase rate of housing price is very urgent.

• Korea Real Estate Review
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• v.27 no.1
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• pp.7-16
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• 2017

In this study, we examine whether there are prospect theory investment patterns for individual investors in the real estate market. We use the maximum potential profit rate and the maximum potential loss rate of individual investors as a research method and additionally analyze it using the Jeong and Park(2015) model. As a result of the analysis, it was found that the investment pattern according to the prospect theory and disposition effect for individual investors. And we find the difference between zoning areas. This difference in investment behavior is believed to be due to the purpose of the real estate and the existence of rent fee, which creates a difference in investment behavior depending on the purpose. The limitations of this study are the analysis measurement of potential profit and potential loss using the land price index like the study of jeong and Park(2015). This implies that a new property price index needs to be developed or a benchmark for real estate assets is needed for deeper study of real estate investment sentiment.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.55-63
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• 2015

The need for estimating the real transaction price of land is increasing in order to build foundation for transparent land transaction and fair taxation. This study looked into the applicability of cokriging combining real transaction price of land, altitude and gradient for effective price estimation on the points where the real transaction does not take place in the course of using the real transaction price of land. The real transaction price of land have been estimated using the real transaction materials of Yeongcheon, Gyeongsangbuk-do from January 2012 to June 2014, and the results have been compared with the estimation results of ordinary kriging. As a result of analyzing the mean error and root mean square error (RMSE) of the estimated price and 2,575 verification points, it was found that compared to ordinary kriging, cokriging results were more effective in terms of the real transaction price estimation and actualization. The reason that cokriging is more effective in the real transaction price estimation is because it takes account of altitude and gradient which are the forces influencing the land value.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.151-157
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• 2013

Since the sub-prime mortgage crisis from the US in 2008, the Korean housing market has plummeted. However, the deposit prices of the Korean local lease contract, Chonsei, had been increasing. This increase of Chonsei prices can be a threat to low-income people, most of whom prefer to live in houses with a Chonsei contract. In the housing and Chonsei market, there are many stakeholders with their own interest, hence, simple thoughts about housing and Chonsei market, such as more house supply, will decrease house price, would not work in a real complex housing market. In this research, we suggests system dynamics conceptual model which consists of causal-loop-diagrams for the Chonsei market as well as the housing market. In conclusion, the Chonsei price has its own homeostasis characteristics and different price behavior with housing price in the short and long term period. We found that unless government does not have a structural causation mind in implementing policies in the real estate market, the government may not attain their intended effectiveness on both markets.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.3
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• pp.499-506
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• 2017

Consideration of influential factors through division of capital market sector and interest rate sector to find and resolve the problems in current housing market and leasing market will become an important index to prepare measures for stabilization of housing sales market and housing lease market. Furthermore, a guideline will be provide you with preliminary data using Big Data to prepare for sudden price fluctuation because expected economic crisis, stock market situation, and uncertain future financial crisis can be predicted which may help anticipate real estate price index such as housing sales price index and housing lease price index.

• The Journal of Industrial Distribution & Business
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• v.7 no.3
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• pp.27-36
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• 2016

Purpose - Considering the importance of housing needs to real estate market, domestic studies on real estate prices from the perspective of demand are basically based on macro-data, but relatively few are associated with micro-data of urban real estate demand. We try to find a reliable relation of elasticity of demand and commercial housing market. Research design, data, and methodology - In this paper, we have derived housing demand theoretic method and have utilized micro-data of residential family housing survey of downtown area in Kunming City in October, 2015 to estimate income elasticity and price elasticity of housing demand respectively and make a comparative analysis. Results - The results indicate that income elasticity and price elasticity of families with owner-occupied housing are both larger than those of families with rental housing. Income elasticity of housing demand of urban residential families in Kunming is far below the foreign average and eastern coastal cities level, however, the corresponding price elasticity is far higher. Conclusions - We suggest that housing affordability of urban families in western China are constrained by the level of economic development, and the current housing price level has exceeded the economic affordability and psychological expectation of ordinary residents. Furthermore, noticing the great rigidity of housing demand, the expansion space of housing market for improvement and for commodity is limited.

• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.271-280
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• 2017

Real-estate values and related economics are often the first read newspaper category. We are concerned about the opinions of experts on the forecast for real estate prices. The Box-Jenkins ARIMA model is a commonly used statistical method to predict housing prices. In this article, we tried to predict housing prices by combining independent component analysis (ICA) in multivariate data analysis and the Box-Jenkins ARIMA model. The two independent components for both the selling price index and the long-term rental price index were extracted and used to predict the future values of both indices. In conclusion, it has been shown that the actual indices and the forecast indices using ICA are more comparable to the forecasts of the ARIMA model alone.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1739-1748
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• 2021

Real estate prices affect countries, businesses, and households, and many studies have been conducted on the real estate bubble in recent soaring real estate prices. However, if the real estate bubble prediction simply compares the real estate price, or if it does not reflect key psychological variables in real estate sales, it can be judged that the accuracy of the bubble prediction model is poor. The purpose of this study is to design a predictive model that can explain the real estate bubble situation by region using the autoencoder technique. Existing real estate bubble analysis studies failed to set various types of variables that affect prices, and most of them were conducted based on linear models. Thus, this study suggests the possibility of introducing techniques and variables that have not been used in existing real estate bubble studies.

• Korean Journal of Construction Engineering and Management
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• v.7 no.2 s.30
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• pp.162-170
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• 2006

Neural network analysis is expected to enhance the forecasting ability for the real estate market. This paper reviews definition, structure, strengths and weaknesses of neural network analysis, and verifies the applicability of neural network analysis for the real estate market. Neural network analysis is compared with regression analysis using the same sample data. The analyses model the macroeconomic parameters that influence the sales price of apartments. The results show that neural network analysis provides better forecasting accuracy than regression analysis does, what confirms the applicability of neural network analysis for the real estate market.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.225-237
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• 2024

Purpose - This study aims to explore the relationship between housing and land prices, with a specific emphasis on the impact of government policies on these factors such as land supply quantity and the ratio of residential land to total land supplied. The goal is to identify the most effective government intervention strategies for controlling both housing and land prices. Design/methodology/approach - Data from 70 primary and medium-sized cities in China spanning from 2003 to 2017 are utilized in this research. The analysis employs a panel vector autoregressive (PVAR) model, with a primary focus on examining the relationships among housing prices, land prices, and government intervention policies. Findings - Housing and land prices are influenced by various factors. Through impulse response analysis and variance decomposition, it is observed that both housing and land prices are predominantly influenced by their internal dynamics, with comparatively weaker effects attributed to policy interventions. Research implications or Originality - By investigating the impact of government policies on housing and land prices, This study establishes a foundation for effective price control measures. Our study advocates for a comprehensive examination of China's land supply mechanism to enhance understanding of the pathways through which government policies influence the markets.