• The Journal of Industrial Distribution & Business
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• v.12 no.2
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• pp.41-52
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• 2021

Purpose: This study aims to provide implications for the government's housing supply policy by analyzing the factors that determine the type of real estate holding and household debt. This study started from the awareness that the determinants of household debt differ depending on the type of real estate holding. Research design, data and methodology: Real estate ownership type was classified and analyzed into 4 models: model 1 (1 household 1 house and self-resident), model 2 (1 household multiple real estate ownership and self-resident), model 3 (1 household 1 house and rent residence), model 4 (1 household holds a large number of real estate and rent residence). The analysis method used multiple regression analysis. The dependent variable was household total debt. As independent variables, household debt, annual gross household income, financial assets, real estate net assets, annual repayment, demographic & residential characteristics were used. Results: 1) Model 4 has the highest household debt and the highest gross income, Model 2 has the most real estate mortgage loans and real estate net asset, and Model 1 has the highest real estate mortgage payments. 2) The positive factor of common household debt determinants is real estate net assets, and the negative factor is financial assets. 3) It was the net assets of real estate that acted as a positive factor in common for the four models. In other words, the more financial assets, the less household debt. It was analyzed that the more net assets of real estate, the more household debt. The annual repayment of financial liabilities had no influence on household debt, while the annual repayment of loan liabilities and household debt had a positive relationship. Conclusions: 1) It is necessary to introduce benefits and systems that can increase the proportion of household financial asset. Specific alternatives include tax benefits and reduced fees for financial asset investment. 2) In the case where a homeless person prepares one house for one household, it is necessary to prepare various support measures according to the income level. The specific alternative is to give additional points for pre-sale or apply an interest rate cut incentive for mortgage loans.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.181-187
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• 2012

This study inquires into what effect the tax burden of investors, for typical taxes related to real estate investment; acquisition tax, comprehensive real estate holding tax, and transfer income tax, might have on the real estate investment behaviors; the purpose of long-term investment. These real estate investment behaviors have been analyzed to see how much they affect investment performance such as realized compound yield. This study model, which considers the fact that the choice of investment behavior for the degree of tax burden of investors may lead to different results in real estate investment, is expected to be an effective decision-making tool for investment.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.243-249
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• 2013

In our country, the real estate information system is operated by public and private institutions to trade real estate effectively from the 1990s. The purposes of this study is as follows: First, this study is aimed to examine how the system quality, information quality and service quality of the real estate IS is related with the system use and user satisfaction. In addition real estate practitioners and real estate non-practitioners is to investigated how different. Regression and t-test analysis was carried out as statistical analysis and survey data was used. The result is as follows: First, in the real estate non-practitioners group, system quality has significant negative impact on the user satisfaction. Second, information quality has significant impact on the user satisfaction in the real estate non- practitioners group. One limitation of this study is that it is limited to the real estate agents among various groups that use the IS. Thus, in the future studies, the target group should be extended to other various groups and more specific IS among various ones should be studied in a more practical way.

• Korea Real Estate Review
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• v.28 no.3
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• pp.53-64
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• 2018

OECD countries have been stimulating private pensions instead of public pensions because the financial stability of public pensions has been threatened by the aging population. Korea, which has the fastest aging population in the world, has been following the recommended policies of major countries. Unlike major economies, however, most of Korea's household assets are composed of real estate assets. Due to the economic and social importance of real estate assets in Korea, the wealth effect of real estate has been used as a major tool in macroeconomic policy. This study analyzed the effect of real estate value changes on the contribution of private pensions (personal pension + retirement pension). Utilizing a two-way, fixed effect model with the balanced panel data of the National Survey of Tax and Benefit, empirical results presented that the private pension contribution increased by 0.171% when the value of real estate increased by 1%. Thus, real estate value changes were analyzed as positive for retirement preparation through private pension. These results suggested that if the real estate market would shrink in the future, consumption would decrease, and the degree of preparation for retirement might be smaller.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.256-263
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• 2021

This paper studies the problems and improvements of government real estate policies. Moon Jae-in government shifted toward regulation and pledge to curb the tax imposed by speculators. It strengthened regulations on reconstruction and bank loans rather than supply, and raised capital gains taxes. As the government implemented measures, emphasizing political logic rather than the economy, the market is unstable and the economy is in a recession. Land has increased the vicious cycle of problems due to population growth, industrialization, urbanization, and wealth growth. Mis-established land policies not only accelerate land prices, but also accelerate the use of disordered land and lead to disruptions in the trading order. In addition, real estate is so difficult to recover from the land problem that it is difficult to contain water that has been spilled once. This is called the irreversible nature of land. Once the land price rises, it is difficult to regain control and reckless development leads to the destruction of the ecosystem, making it difficult to return. This is why such a complex real estate issue should not be implemented as if it were a punishment in a short period of time with government policies. This paper aims to examine the problems of real estate policies and to examine ways to improve them.

• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.221-230
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• 2016

The public mostly get the information regarding real estate policy not from the press release of the government but from news articles. This type of information, though, might be delivered in a different frame depending on inclination of media or press. The media runs the articles within its own frame, so that it often conveys either expectation or concern depending on its inclination. This study analyzed the articles regarding 'Agreement to revise three major real estate regulations to perk up property market' and examined how the real estate policy imprinted in them depending on the disposition of the press. The results showed that the conservative press ran articles within a positive frame expressing favorable expectation. On the other hand, progressive press mostly kept neutral or unfavorable tone on the same regulations within the negative frame. Therefore, it was confirmed that there exist different frames within articles depending on their disposition.

• Journal of the Korean Professional Engineers Association
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• v.38 no.4
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• pp.7-9
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• 2005

The recent speculation fever in Kangnam and its southern vicnity of Seoul resulted in surging apartment prices. The government is determined to employ more effective anti-speculation policy measures to control the property speculative demand. The Government plans to implement support measures to discourage people from owning multiple homes by reinforcing tax measures. To meet the increasing demand for more large-sized apartments in Seoul, the Government may allow to build more large sized units. By the end of August, 'a comprehensive package tool of real estate policy measures' ,as a real estate controlling guidelines, is scheduled to be presented by the Government. We hope that the package tool will stabilize housing market more effectively and enhance the national economy.

• 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.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.47-72
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• 2022

This study aims to understand the trends of subjects related to real estate policies and public's emotional opinion on the policies. Two keywords related to real estate policies such as "real estate policy" and "real estate measure" were used to collect tweets created from February 25, 2008 to August 31, 2021. A total of 91,740 tweets were collected and we applied sentiment analysis and dynamic topic modeling to the final preprocessed and categorized data of 18,925 tweets. Sentiment analysis and dynamic topic model analysis were conducted for a total of 18,925 posts after preprocessing data and categorizing them into supply, real estate tax, interest rate, and population variance. Keywords of each category are as follows: the supply categories (rental housing, greenbelt, newlyweds, homeless, supply, reconstruction, sale), real estate tax categories (comprehensive real estate tax, acquisition tax, holding tax, multiple homeowners, speculation), interest rate categories (interest rate), and population variance categories (Sejong, new city). The results of the sentiment analysis showed that one person posted on average one or two positive tweets whereas in the case of negative and neutral tweets, one person posted two or three. In addition, we found that part of people have both positive as well as negative and neutral opinions towards real estate policies. As the results of dynamic topic modeling analysis, negative reactions to real estate speculative forces and unearned income were identified as major negative topics and as for positive topics, expectation on increasing supply of housing and benefits for homeless people who purchase houses were identified. Unlike previous studies, which focused on changes and evaluations of specific real estate policies, this study has academic significance in that it collected posts from Twitter, one of the social media platforms, used emotional analysis, dynamic topic modeling analysis, and identified potential topics and trends of real estate policy over time. The results of the study can help create new policies that take public opinion on real estate policies into consideration.

• 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.