• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.199-205
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• 2020

As many government policies have been announced today regarding real estate, especially housing, interest in prices in the housing market has increased significantly. In this study, I would like to present the direction of government policies by analyzing the relationship among income instability, the psychological condition of real estate price changes and willingness to adjust real estate holding ratio. First, major variables were extracted through the prior study review, and using a survey, data were collected and path analysis was conducted. According to the analysis, the current income instability had a negative impact on the psychological condition of real estate price changes, and a positive influence on the willingness to adjust real estate holding ratio, but the psychological condition of real estate price changes did not have a statistically significant impact on the willingness to adjust real estate holding ratio. Thus, the difference analysis was conducted between groups by dividing the ages and the number of dependents respectively. According to the analysis, the impact of income instability and psychological condition of real estate price changes on willingness to adjust real estate holding ratio differed between groups divided by ages and number of dependents. The results of this analysis will help the government to establish real estate policies and help each household to use the analysis as basic data when they make a decision about real estate. On the other hand, this study has limitations that have only been conducted cross-sectional analysis and analyzing time series changes and differences in perception between regions are going to be conducted in a future study.

• Korean Management Science Review
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• v.31 no.1
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• pp.17-26
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• 2014

This study presents a new real estate value analysis model considering the changes in the population structure. We propose a new model that takes advantage of the binomial option model one of the techniques of real options and considers the changes in the population structure. The real estate market price data of Seoul city from year 2001 to 2012 were extracted and the correlation analysis between real estate prices and changes in the population structure was performed. The result shows that they have positive correlation with one year time lag. The coefficient between the real estate prices and demographic changes was estimated using the OLS analysis and included in the traditional binomial option model to calculate the value of the property. It is assumed for the future price prediction that real estate invested in Seoul in January, 2013 will be sold within five years. Analysis result shows that the values of real estate in September of 2013 were predicted as 583.5 million won in the new model and as 582.4 million won in the traditional model. This reflects that the new model considering the change of population change gives better realistic performance than the traditional one.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.75-87
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• 2023

We designed to employ an Artificial Intelligence learning model to predict real estate prices and determine the reasons behind their changes, with the goal of using the results as a guide for policy. Numerous studies have already been conducted in an effort to develop a real estate price prediction model. The price prediction power of conventional time series analysis techniques (such as the widely-used ARIMA and VAR models for univariate time series analysis) and the more recently-discussed LSTM techniques is compared and analyzed in this study in order to forecast real estate prices. There is currently a period of rising volatility in the real estate market as a result of both internal and external factors. Predicting the movement of real estate values during times of heightened volatility is more challenging than it is during times of persistent general trends. According to the real estate market cycle, this study focuses on the three times of extreme volatility. It was established that the LSTM, VAR, and ARIMA models have strong predictive capacity by successfully forecasting the trading price index during a period of unusually high volatility. We explores potential synergies between the hybrid artificial intelligence learning model and the conventional statistical prediction model.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.62-72
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• 2017

In this study, liner unit root tests and panel unit root tests to the ratio of city to regional house price were applied to examine the ripple effects across 28 cities in the Yangtze River Delta region. Then invert LM unit root tests with two structural breaks for 10 representative cities were conducted. The results showed that there is overwhelming evidence of the existence of ripple effect in the Yangtze River Delta region, while segmentation is restricted to a small group of cities in which there is no long-run relationship with the Yangtze River Delta region average; compared to no- and one-break case, there is overwhelming evidence of a ripple effect with the LM test with two structural breaks. Furthermore, the results of the Granger causality test showed that changes in house prices in Shanghai, Nanjing and Hangzhou have led to changes in house prices in other cities. The findings of this research make certain contributions to the improvements of research system of ripple effect among regional house prices in the Yangtze River Delta Region,and could be referenced by other markets of other cities.

• Journal of Construction Engineering and Project Management
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• v.2 no.4
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• pp.32-41
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• 2012

In recent times, multi-centralization and decentralization as well as large Capital area and suburbanization in the spatial structure of capital area. With rapid growth, urbanization and industrialization are unsystematic, and growth inequality between regions caused negative effects such as discordant centralization and decentralization, fluctuating land value, and gap between living conditions. Accordingly, this study analyzed urban spatial indexes by the self-governed body in the capital area such as Seoul, Incheon, and Gyeonggi province for the analysis of the regional inequality phenomenon. We examined the characteristics of temporal and spatial changes in urban spatial structure in the capital area by utilizing the distribution pattern and density of city indexes such as population, employment, etc, and then drew the commonality of those factors through factor analysis. We evaluated the drawn results through the city standard index by each city, conducted factor score analysis, and identified the interaction between each factor and Housing Purchase Price Composite Indices index, housing rent price index(Housing Jeonse Price Composite Indices), land price fluctuation rate, diffusion ratio of house, and financial independence.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.3
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• pp.393-402
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• 2014

ICT environment to the survey released by the Bureau of Statistics 2012 Household Finance. Korean Welfare survey 24.9% of all households in financial assets, real estate is about three times more than 69.9%, respectively. The problem is that the information is slow and income deciles(deciles 1-4), a relatively high proportion of households with low(78.8 to 69%) of the real estate assets of the expansion of the world economy with low growth and low uncertainty, work from home due to the information changes in the structure of the economy, such as increases in real estate prices remain exposed to the risk of a phenomenon such as Pour House Pour Talent and low-income people is bound to be more serious symptoms. This low correlation is by constructing a composite asset portfolio, the weighted average risk of the individual assets while increasing overall revenue decrease that risk is based on the principle of portfolio by type and different areas in the ICT environment in a portfolio of real estate price index low correlation to financial assets by including the effect of dispersion stable complex asset portfolio and empirical Growth was divided.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.435-440
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• 2022

This study analyzed the impact of changes in real estate prices on the soundness of Korean banks using multiple regression models. As a result of the analysis, changes in real estate prices significantly increase the banks' non-performing loans through the increase in loans. Among macroeconomic variables, short-term interest rates were found to have a significant effect on all soundness indicators such as BIS capital adequacy ratio, non-performing loans ratio, and liquidity coverage ratio. Among the bank characteristics indicators, the loan growth rate had a significant negative effect on BIS capital adequacy ratio, and the real estate mortgage rate had a significant positive effect. In additional, it was found that non-performing loans ratio and liquidity coverage ratio had a negative effect on BIS capital adequacy ratio.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.2_2
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• pp.315-322
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• 2022

Apartments are being established as a universal housing type because of the perception that they are excellent in preservation of asset values and convenience. In this study, through multiple regression analysis, it is a thesis that explores whether it affects the housing market in Gimhae, a small and medium-sized city in the province, and how the price flow in neighboring cities has an effect. It is possible to examine how macroeconomic variables such as the balloon effect and the lowest interest rate caused by the government's tweezers regulation bring about changes in the housing market of small and medium-sized cities in local regions.

• Land and Housing Review
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• v.2 no.4
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• pp.367-377
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• 2011

This paper investigates the determination factors' variation of real estate price after sub-prime financial crisis, in korea, using a VAR model. The model includes land price, housing price, housing rent (Jensei) price, which time period is from 2000:1Q to 2011:2Q and uses interest rate, real GDP, consumer price index, KOSPI, the number of housing construction, the amount of land sales and practices to impulse response and variance decomposition analysis. Data cover two sub-periods and divided by 2008:3Q that occurred the sub-prime crisis; one is a period of 2000:1Q to 2008:3Q, the other is based a period of 2000:1Q to 2011:2Q. As a result, Comparing sub-prime crisis before and after, land price come out that the influence of real GDP is expanding, but current interest rate's variation is weaken due to the stagnation of current economic status and housing construction market. Housing price is few influenced to interest rate and real GDP, but it is influenced its own variation or Jensei price's variation. According to the Jensei price's rapidly increasing in nowadays, housing price might be increasing a rising possibility. Jensei price is also weaken the influence of all economic index, housing price, comparing before sub-prime financial crisis and it is influenced its own variation the same housing price. As you know, real estate price is weakened market basic value factors such as, interest rate, real GDP, because it is influenced exogenous economic factors such as population structural changes. Economic participators, economic officials, consumer, construction supplyers need to access an accurate observation about current real estate market and economic status.

• Journal of the Korean Regional Science Association
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• v.36 no.1
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• pp.37-50
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• 2020

Estimating investment profits of real estate is critical to understand real estate markets and create relevant policy as real estate market and capital market combines closely. Thus, this study applied the concept of Tobin's Q to estimate investment profits for apartments as well as row-houses and multi-family homes in Seoul from 2010 to 2018. Investment profits were estimated by two approaches: subtracting the replacement cost from the transaction price and calculating ratio of the transaction price to the replacement cost, respectively. The spatio-temporal changes in investment profits were apparent in apartments compared with row-houses and multi-family homes. As a result of analyzing the spatial econometrics models, the investment profit was higher in the area with high density and new developments regardless of the housing types. The framework and key findings would be the effective reference to understand residential investment behavior, create relevant housing policy, introduce value capture of windfall, measure regional competitiveness, and estimate housing bubble.