• Journal of the Korea Institute of Building Construction
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• v.22 no.1
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• pp.81-90
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• 2022

With apartment purchase prices rising, small and medium-sized cities have been highlighted as areas in which real estate speculation is overheated, and thus designated as target districts for adjustment. In addition, tax policy is constantly being adjusted in an attempt to stabilize real estate prices. The purpose of this study is to analyze the basic effect of tax policy on the purchase price of apartments in small and medium-sized cities. This study selected apartments in the Daejeon area that were constructed between 1990 and 2015. In addition, tax policy was divided into regulatory policy and easing policy based on tax increase and tax cut. This study analyzes the short-term difference of one year before and after the change in the purchase price of apartment houses. In addition, this study set the time when real estate policy was implemented and the actual transaction price of apartments in Daejeon as the analysis targets, and analyzed the correlation between tax policy and apartment sales prices through the NPV technique and T-test results. Through the study, it was found that most tax policies changed apartment purchase prices in the short term.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.125-141
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• 2020

This study investigated the time-series relationship between housing consumer sentiment and housing prices in the five major districts in Seoul and also analyzed the effect of the housing consumer sentiment on housing prices using Granger Causality and VEC (Vector Error Correction) models. To describe the key results, first of all, housing consumer sentiment and regional housing market prices were closely related to each other, and the consumer sentiment strongly affected the change of housing prices. Second, the housing consumer sentiment was confirmed to have a discriminatory effect on the housing prices among the districts in Seoul in the short term. Specifically, the housing price of the east southern district (ESD) was the main reason for the change in housing consumer sentiment in Seoul, and that the resulting impact was transferred to other districts. Third, it was analyzed that regions other than the ESD would increase the housing prices in the long term as the housing consumer sentiment turned positive, but that the ESD would see a steady tone. Fourth, in the case of relative influence by district, housing (apartment) price fluctuation in a district was generally found to be most affected by adjacent or competitive districts. Through these findings, this study confirmed that there is a clear causality between housing consumer sentiment and housing prices in each district of Seoul and that there is a discriminatory influence on housing consumer sentiment among the districts.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.228-234
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• 2021

Real estate market participants need to have a sense of predicting real estate prices in decision-making. Commonly used methodologies, such as regression analysis, ARIMA, and VAR, have limitations in predicting the value of an asset, which fluctuates due to unknown variables. Therefore, to mitigate the limitations, an artificial neural was is used to predict the price trend of apartments in Seoul, the hottest real estate market in South Korea. For artificial neural network learning, the learning model is designed with 12 variables, which are divided into macro and micro factors. The study was conducted in three ways: (Ed note: What is the difference between case 1 and 2? Is case 1 micro factors?)CASE1 with macro factors, CASE2 with macro factors, and CASE3 with the combination of both factors. As a result, CASE1 and CASE2 show 87.5% predictive accuracy during the two-year experiment, and CASE3 shows 95.8%. This study defines various factors affecting apartment prices in macro and microscopic terms. The study also proposes an artificial network technique in predicting the price trend of apartments and analyzes its effectiveness. Therefore, it is expected that the recently developed learning technique can be applied to the real estate industry, enabling more efficient decision-making by market participants.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.231-240
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• 2022

This study empirically analyzed the effect of complex commercial facilities on the price of nearby apartments in a Hedonic price model. The spatial range of this study was the walking area of H Department Store located in Pangyo among the second new towns suburb of Seoul, and the time range was 2020. The dependent variable was the real transaction price of the apartment, and independent variable were the characteristics of the housing, the characteristics of the complex, and the characteristics of the region. As a result of the analysis, the area of exclusive use space, the transaction floor, and the highway accessibility had a positive effect on the price of the apartment, and the elapsed year had a negative effect on the price of the apartment. However, the size of the apartment had little effect on apartment prices, and the distance from the complex commercial facilities was shown to be related to apartment prices, indicating that apartment prices declined as it moved away from the complex commercial facilities. Therefore, this is much more influential than the influence of distance from subway stations on apartment price. This confirms that the effect factors of apartment prices and the size of their influence appear differently in the new town area and the existing metropolitan area.

• East Asian Economic Review
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• v.17 no.2
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• pp.161-206
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• 2013

Since the global financial crisis in 2008, the world economy has been suffering from the Great Recession characterized by high and persistent unemployment as well as drastic fall in asset prices. Real business cycle theory or new-Keynesian economics which has been the dominant paradigm in macroeconomics for the last four decades is unable to explain the high and persistent unemployment during the Great Recession. This implies that the economics of Keynes should be taken seriously again as a tool to explain the Great Recession. Farmer (2012) proposes a new way of interpreting the economics of Keynes by providing it with a solid micro-foundation based on labor markets with search. According to Farmer (2012), aggregate economic activity independently depends on the long-term self-fulfilling expectations about the stock prices. As a consequence, the government or the central bank should implement a policy that influences the public's confidence about the stock market. For an open economy like the Korean economy, it is not only stock price but also the price of asset such as house that matters more for the aggregate economic activity. Households in the Korean economy hold more than 70 percent of their wealth in the form of real estate asset, especially housing asset. This makes the public's confidence about the future prices of houses even more important in explaining the business cycles of the Korean economy. Policymakers should implement policies to improve the confidence of households about the housing market to recover from the recession caused by a fall in house prices. Little theoretical work has been done in explaining fluctuations in the aggregate economic activity from the point of house prices. This paper develops a small open economy model with traded and non-traded capital based on Farmer (2012) and shows that the aggregate economic activity also independently depends on the households' self-fulfilling expectations about the future prices of non-traded asset such as houses.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.181-189
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• 2017

The purpose of this research is to set a standard for deciding competitive marketing prices of new supplying apartment houses and to analyze decision factors in sale price of supplying apartment houses with Analytic Hierarchy Process; the resulted model does not use the method that joins the land cost and the cost of construction together, but the method that compares the sales prices of surrounding apartments. This research tries to set a standard for decision of the prices of newly supplying apartment houses by classifying the determinants into the $1^{st}$ step(4 factors), the $2^{nd}$ step(9 factors), and the $3^{rd}$ step(25 factors). According to the process, the relative importance of decision factors in the sale prices is determined and this should be used as the index of sale prices for newly supplying apartment houses when the houses are provided. In addition, through the $2^{nd}$ step including 9 factors, the comparative model for sale prices is defined and the model is presented to be applied in the real business. Subsequent study additionally considering the factors apart from marketing which tries to find a generalized standard needs to be conducted.

• Journal of Venture Innovation
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• v.5 no.3
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• pp.71-80
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• 2022

The real estate market is an important part of a country's economy and plays a major role in economic growth through the growth of many related industries. Changes in interest rates affect asset prices and have a significant impact on housing prices. This study analyzed housing prices by dividing them into nationwide, local, and Seoul housing prices in order to analyze whether the effect of changes in interest rates on housing prices shows regional differences. The analysis was conducted from the first quarter of 2011 to the fourth quarter of 2021, and was analyzed using the DOLS model. The main analysis results are as follows. First, interest rates were found to have a significant negative effect on national housing prices, and a drop in interest rates significantly increased national housing prices and an increase in interest rates significantly lowered national housing prices. The consumer price index and loan growth rate also had a positive effect on housing prices nationwide, but statistical significance was not high. Second, interest rates had a negative effect on local housing prices, unlike national housing prices, but were not statistically significant. On the other hand, it was found that the consumer price index and loan growth rate had a larger and significant positive effect on local housing prices compared to national housing prices. Finally, it was found that the interest rate had the only significant negative effect on housing prices in Seoul. And this effect was greater and more significant than the effect on national and local housing prices. In the end, it was found that the effect of interest rates on Korean housing prices differs locally. Interest rates have a significant negative effect on national housing prices, and local housing prices, but they are not statistically significant. In addition, the interest rate was found to have the largest and most significant negative effect on housing prices in Seoul. In addition, it was found that there was a difference in the effect of macroeconomic variables on housing prices. This means that there are differences between regions with different factors influencing local and Seoul housing prices, and this point should be considered when drafting and implementing real estate policies.

• The Journal of Information Technology
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• v.6 no.3
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• pp.53-64
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• 2003

The purpose of this study is to examine the valuation models and valuation factors for the valuation of real estates. In Korea, the weak market conditions prevented investors from the sound investing the real estates. To develop the real estate investment market, we need the information of sale prices, volume, vacancy rates, and regulatory policies to the various types, and areas of the real estates. In addition, we have to develop the indirect investing methods such as REITs.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.27-33
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• 2021

With increasing interest in key areas of the 4th industrial revolution such as artificial intelligence, deep learning and big data, scientific approaches have developed in order to overcome the limitations of traditional decision-making methodologies. These scientific techniques are mainly used to predict the direction of financial products. In this study, the factors of apartment prices, which are of high social interest, were analyzed through SOM. For this analysis, we extracted the real prices of the apartments and selected a total of 16 input variables that would affect these prices. The data period was set from 1986 to 2021. As a result of examining the characteristics of the variables during the rising and faltering periods of the apartment prices, it was found that the statistical tendencies of the input variables of the rising and the faltering periods were clearly distinguishable. I hope this study will help us analyze the status of the real estate market and study future predictions through image learning.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.2
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• pp.245-256
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• 2024

Since 2020, quantitative easing and easy money policies have been implemented for the purpose of economic stimulus. As a result, real estate prices have skyrocketed. In this study, the relationship between sales and rental prices by housing type during the period of soaring real estate prices in Busan was analyzed spatio-temporally. Based on the actual transaction price data, housing type, transaction type, and monthly data of district units were constructed. Among the spatio-temporal analysis models, the SpVAR, which is used to understand the temporal and spatial effects of variables, and the GSTAR, which is used to understand the effects of each region on those variables, were used. As a result, the sales price of apartment had positive effect on the sale price of apartment, row house, and detached house in the surrounding area, including the target area. On the other hand, it was confirmed that demand was converted to apartment rental due to an increase in apartment sales prices, and the sale price fell again over time. The spatio-temporal spillover effect of apartments was positive, but the positive effect of row house and detached house were concentrated in the original downtown area.