• Journal of Digital Convergence
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• v.19 no.9
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• pp.9-18
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• 2021

Constructing the Metropolitan Railway Express (the GTX) may have an impact on consumer confidence and housing sales price located near the planned route. This study looked at how consumers' psychology and housing prices change as the large-scale transport infrastructure plane was planned. Also, it looked at the relationship between consumer sentiment and housing prices to analyze the impact of new transportation facilities inflows. Using a correlation analysis, the relationship between the consumer sentiment index and the actual transaction price of apartments was identified. The impact of GTX on the consumer sentiment index and the actual transaction price of apartments was looked at using the Difference-in-Differences methodology. Our finding shows that the construction plan of a large-scale transportation infrastructure in the metropolitan area affects the sentiment of housing consumption and actual transactions. In a situation where the government is speeding up the construction of a wide-area transportation network such as GTX with the goal of becoming a city where people can commute to downtown Seoul within 30 minutes, policies that can stabilize the housing market in transportation hubs should be suggested.

• Convergence Security Journal
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• v.8 no.3
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• pp.83-92
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• 2008

In respect complication of group and period, the sales of retail trade is composed of various factors. This paper studies focus on estimating the determinants of the sales of retail trade. The volume of analysis consist of 7 groups. Analyzing period be formed over a 36 point(2005. 1$\sim$2007. 12). In this paper dependent variable setting up sales of retail trade, explanatory(independent) variables composed of composite stock price index, the number of the consumer's online buying behavior company, the coincident composite index, the index of trading price of APT, employment rate, an average of the rate of operation(the manufacturing industry), the consumer price index. The result of estimating the determinants of sales of retail trade provides empirical evidences of significance positive relationships between the coincident composite index, the index of trading price of APT, employment rate, an average of the rate of operation(the manufacturing industry). However this study provides empirical evidences of significance negative relationships between the consumer price index. The explanatory variables, that is, composite stock price and the number of the consumer's online buying behavior company, are non-significance variables. Implication of these findings are discussed for content research and practices.

• Korean Journal of Construction Engineering and Management
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• v.16 no.5
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• pp.77-85
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• 2015

The Hedonic Pricing model is the predominant approach used today to model the effect of relevant factors on real estate prices. These factors include intrinsic elements of a property such as floor areas, number of rooms, and parking spaces. Also, The model also accounts for the impact of amenities or undesirable facilities of a property's value. In the latter case, euclidean distances are typically used as the parameter to represent the proximity and its impact on prices. However, in situations where multiple facilities exist, multi-colinearity may exist between these parameters, which can result in multi-regression models with erroneous coefficients. This research uses Variance Inflation Factors(VIF) and Ridge Regression to identify these errors and thus create more accurate and stable models. The techniques were applied to apartments in Guro-gu of Seoul, whose prices are impacted by subway stations as well as a public prison, a railway terminal and a digital complex. The VIF identified colinearity between variables representing the terminal and the digital complex as well as the latitudinal coordinates. The ridge regression showed the need to remove two of these variables. The case study demonstrated that the application of these techniques were critical in developing accurate and robust Hedonic Pricing models.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.125-139
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• 2021

Continuous subway line expansion over the years in Seoul metropolitan area has contributed to improved accessibility to public transport. Since public transport accessibility has a significant impact on housing decisions, quantitative analysis of correlation between housing prices and public transport accessibility is regarded as one of the most important factors for planning better housing policies. This study defines the reduction of traveling time resulted from the construction of new metro stations despite them not being the closest stations as 'Network Expansion Effect', and seeks to understand how the Network Expansion Effect impacts on housing prices. The study analyzes monthly rent data converted from upfront lump sum deposit, so called Jeonse in Korea, from 2012 to 2018, through 'A Modified Repeat Sales Model.' As a result, the effect of 'Network Expansion' on rental prices in Seoul has stronger during the period of 2017 to 2018 than the base period of 2012 to 2014, which suggests the 'Network Expansion' has a meaningful effect on rent. In addition, in comparison between the most and the least affected group of apartments by 'Network Expansion Effect', the most affected group has more price increase than the least affected group. These findings also indicate that different levels of 'Network Expansion Effect' have various influences on the value of residential real estate properties.

• Journal of the Korea Institute of Building Construction
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• v.10 no.2
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• pp.75-80
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• 2010

With the intensifying of price competition and structural diversifications, the uncertainty of the domestic housing market has been increased. This highlights the importance of the planning stage of construction projects, and the increased need for a higher level of accuracy in approximate estimates. Currently, a number of research and development programs to calculate construction cost at the initial planning stage are being conducted. However, there are few cases in which local characteristics are considered in deriving the results. If local calibration can be conducted during estimates, more accurate cost estimates will be enabled. This could also play a major role in ensuring the success of a project. Therefore, the purpose of this research is to develop a calculation methodology and a model for a local index based on the historical data of public apartment buildings, and to derive a local index that supports accurate construction cost estimates.

• 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 the Economic Geographical Society of Korea
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• v.15 no.4
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• pp.585-600
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• 2012

The purpose of this study related to the liquidity impact of the housing market variables using vector auto-regressive model(VAR) and empirical analysis is to derive some policy implications. October 2003 until May 2012 using monthly data for liquidity variables mortgage rates, mortgage, financial liquidity, as the composite index and nation, Seoul, Gangnam, Gangbuk, the Apartment sales prices were analyzed. Granger Causality Test Results, mortgage rates and mortgage at a bargain price two regions had a strong causal relationship. Since the impulse response analysis, Geothermal difference there, but housing price housing price itself, the most significant ongoing positive (+) reactions were liquidity-related variables are mortgage loans is large and persistent positive (+), financial liquidity weakly positive (+), mortgage interest rates are negative (-), KOSPI, the negative (-) reacted. Liquidity and housing prices that the rise can be and Gangnam in Gangbuk is greater than the factor that housing investment was confirmed empirically. Government to consider the current economic situation, while maintaining low interest rates and liquidity of the market rather than the real estate industry must ensure that activities can be embedded and local enforcement policies should be differentiated according to the policy will be able to reap significant effect.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.432-439
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• 2013

In this study, we evaluate the volatility of housing prices by using literature review and empirical analysis and furthermore we suggest how to improve. In order to diagnose housing market, the KB Bank's House Price Index, Real estate 114;s materials were compared. In addition, to examine the volatility, GARCH (Generalized Autoregressive Conditional Heteroskedasticity) and EGARCH (Exponential GARCH) model are used. By analysis of this research, we found the volatility of housing price also was reduced in the medium and the large houses since 1998, while the volatility of small housing price relatively was large. We proved that the price change rate of small housing was higher than the medium's. On the order hand, the supply of small apartments fell down sharply. The short-term oriented policy should be avoided, and the efficiency and credibility of policy should be increased. Furthermore, the long-term policy system should be established. and rental market's improvement is necessary for stabilization of housing market.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.43-53
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• 2014

This study aims to improve the openness of administrative data and to make extensive use of it in the academic and policy development, analyzing the quality requirements as the users' view of administrative data using statistical purposes. Conducted the exploratory analysis on the case of the Transaction-based Price Index of Housing, applying the administrative data of Realestate Transaction Management System in Korea, based on Denmark's 7 quality indicators for the statistical use of administrative data. According to the results of this study, the administrative data could improve the efficacy of the policy by facilitating the collection of the statistical data which help analyzing the actual market situations. On the other hand, the data have some constraints in adding the required items to producing the statistics, or improving the timeliness problem, due to the characteristics focused on the civil service.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.116-124
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• 2016

In the past, once apartments were built by housing construction companies, their presale went smoothly. Therefore, the developer and construction companies in Korea were extremely competitive in the housing market. However, when the 1997 foreign exchange crisis and 2008 global financial crisis occurred, the quantity of unsold new housing stocks rapidly increased, which caused construction companies to experience a serious liquidity crisis. This paper aims at analyzing the influence of Liquidity on the Housing Market before and after Macroeconomic Fluctuations using VECM. The periods from September 2001 to September 2008 and from October 2008 to October 2015, which were before and after the Subprime financial crisis, were set as Models 1 and 2, respectively. The results are as follows. First, it is important to develop a long-term policy for the housing transaction market to improve household incomes. Second, due to the shortage in the supply of jeonse housing, structural changes in the housing market have appeared. Thus, it is necessary to seek political measures to minimize the impact of transitional changes on the market.