• Journal of Cadastre & Land InformatiX
• /
• v.45 no.2
• /
• pp.203-216
• /
• 2015

This study focuses on the relationship between housing sale prices and Jeonse prices, amid a recent surge of Jeonse price and Jeonse-to-housing sale price ratio. There are many studies about the relationship between house prices and Jeonse, but they couldn't fully explain what makes them spike up. In addition to this relationship, this paper deals with the difference of Jeonse system on regions and price levels. Using Granger causality and Spearman's Correlation Coefficient, the outcome is drawn. As the result, the expected rate for housing sale prices effects on the Jeonse-to-housing sale price ratio. The higher on sale price, the lower the Jeonse-to-housing sale price ratio regarding the region difference.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.3
• /
• pp.281-286
• /
• 2023

This study analyzed the causal relationship between housing sales prices and jeonse prices in Seoul, specifically in the Gangnam and Gangbuk neighborhoods. The time-invariant Granger causality test showed bidirectional causality between the sales price and the jeonse price in Seoul and Gangbuk, but no bidirectional causality was found in Gangnam. However, the time-varying Granger causality test showed a Granger causal relationship between the housing jeonse price and the sales price for the entire period after 1993 in all three areas. Notably, the causal effect of jeonse prices on sales prices has been continuous in Gangnam since 2010. These analysis results suggest that an increase in liquidity supply to the jeonse market could increase volatility throughout the housing market, given the strong influence between the sales and jeonse markets in both directions.

• Korea Real Estate Review
• /
• v.27 no.1
• /
• pp.45-57
• /
• 2017

In this study, the factors influencing logistics warehouse price were analyzed using Hedonic price model. All the actual transaction cases of the logistics centers in Gyeonggi province for 10 years from 2006 to 2015 were investigated. In this hedonic model, statistically significant variables includes building, economic, investment and time characteristics. The analysis permits a better insight of price determinants of warehouse price. First, the purchase price of large size logistics centers is relatively high. Second, the indirect investment shows higher price due to active investment tendency. Third, Foreign investors with various know-how on investment are leading the selling price.

• Journal of Cadastre & Land InformatiX
• /
• v.49 no.2
• /
• pp.39-56
• /
• 2019

In this study, we analyzed the effect of the Eungam Loop Line of Seoul Subway Line 6 on the sale price of adjacent row and multi-family houses on the accessibility and structural characteristics of subway stations. This study empirically analyzed a total of 17,938 cases from 2006 to 2017 based on data on the sale price of row and multi-family houses. In summary, the results of this study using the Hedonic Price Model are as follows. First, this study confirms that the Eungam Loop Line characteristics have a positive effect on the sale price as it is adjacent to the subway station. It is noteworthy that the sale price of 100-200m segment has a positive effect, and the sale price of Bulgwang station, which has excellent mobility and connectivity with CBD, YBD and GBD, has a positive effect. Second, this study shows the locational characteristics such as distance to bus stop, distance to mart, and distance to school have influence on the sale price. Third, this study finds the land characteristics such as land area, land shape, land facing, and road width, have significant effects on the sale price. Fourth, this study discovers the sale price is also is also affected by building and floor characteristics such as the type of housing, building area, the number of households, building age, elevator, and floor level.

• Journal of Digital Convergence
• /
• v.17 no.1
• /
• pp.55-62
• /
• 2019

This study analyzed the relationship between housing price, purchase price, Gini coefficient, interest rate, and the employment, considering that the change in housing price was an important factor influencing macroeconomic variables and income inequality. The panel VAR model was constructed considering the panel data, and the Granger causality, Impulse response and Variance dispersion analysis were performed. As a result, when compared to before and after the global financial crisis, it was shown that the rent price had an effect on income inequality, but in the following period, both the rent price and the selling price affected the income inequality. And that it has a large impact on inequality. In addition, the causality between income inequality and employment rate, interest rate, and tax rate was confirmed. Therefore, it is expected that it will be a desirable policy to mitigate income inequality considering the influence of policy variables for economic activation including government real estate policy.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 2006.04a
• /
• pp.506-512
• /
• 2006

다양한 아파트 특성들을 이용하여 아파트 가격을 추정하고 예측하는 연구 또한 많이 존재하고 있는 실정이다. 그렇지만 이러한 연구들 대부분이 회귀모형에 지나치게 의존하고 있는 실정이다 그러나 회귀모형은 단점보다 장점이 많은 모형이다. 본 연구는 회귀모형을 부정하기보다는 새로운 모형을 도입하여, 회귀모형의 문제점들을 극복하고 회귀모형과 상호보완적인 모형을 도입할 필요성에 의해서 본 연구를 수행한 것이다. 다양한 아파트 특성들에 대하여 신경망모형을 이용하여 아파트 가격을 예측하고, 기존의 회귀모형과 비교하는 것이 본 연구의 주목적이다 또한 회귀모형과 신경망모형의 상호 보완적인 측면을 규명하는 것은 본 연구의 부차적인 목적이 된다 아파트 특성들은 주변에서 쉽게 이용 가능한 데이터를 위주로 하였다. 2004년 6월 기준으로 서울시 송파구와 도봉구의 아파트 매매가격들과 12개의 아파트 특성들을 수집하였다. 아파트 매매가격들 (즉, 매매 하한가, 일반 거래가, 매매 상한가) 을 새로운 측정방법을 이용하여 하나의 매매가격으로 추정하였으며, 대표성을 가지도록 하였다. 신경망모형을 도입하여 아파트 특성들을 이용하여 아파트 가격을 정밀하고 유효하게 예측하고, 기존의 회귀모형들과 비교하는 것은 아파트 가격에 대한 연구 분야에 큰 의미가 있다 하겠다. 그리고 주택에 관한 기존의 연구와 신규 연구에 신경망모형이 활용될 수 있으리라 판단된다.

• Korea Real Estate Review
• /
• v.28 no.2
• /
• pp.7-20
• /
• 2018

This paper has statistically analyzed the determining factors that affect office building sale prices by focusing on strata property sales through the hedonic price function. In this study, 1,171 office building transaction cases were analyzed in Seoul from 2000 to 2017. To determine the influence of various factors on office building sale prices, independent variables included factors that represented macroeconomic characteristics, locational characteristics, physical characteristics, and deal characteristics. The analysis of the strata property sales, which is a major concern in this study, showed that strata property sales enjoyed a discount of about 1.56 million won per pyeong out of the entire sales. In terms of the discount rate, strata property sales were at a 12.6% discount compared to entire property sales, so it was found that strata property sales significantly influenced office building selling price. This is due to the fact that the owner of the strata property encounters more difficulties in distributing cost than the sole proprietor in terms of property rights and the exercise of management rights. The results of this study are expected to contribute in securing transparency in transactions and risk management strategies in the future.

• Journal of the Korea Convergence Society
• /
• v.10 no.3
• /
• pp.193-201
• /
• 2019

The public's interest regarding multi-household houses, one of the small-scale housings used as profit earning property, has been increasing. Previous studies regarding price, such as the rent and sales price of multi-household houses', however, were difficult to find. Thus, this study set forth to find out what characteristics influence the sales price of multi-household houses so as to provide further suggestions to investors' decision makings and developers' strategy establishments. The data was retrieved from multi-household sales transacted in Changwon City. Through empirical analysis, this paper found that prices were high in Euichang-gu and Seongsan-gu, and meaningful variables in terms of locations were distance from major trade areas(-), distance from main streets(-), and Corner site(+). Meaningful variables related to household characteristics were total floor area(+), Studio type(+), Southern exposure(+), Building age(-), and Full-furnished(+).

• The Korean Journal of Applied Statistics
• /
• v.30 no.2
• /
• pp.271-280
• /
• 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 Korean Data and Information Science Society
• /
• v.26 no.3
• /
• pp.561-568
• /
• 2015

In this study we predict apartment prices per unit in Daegu-Gyeongbuk areas by spatial lag and spatial error models, both of which belong to so-called spatial regression model. A spatial weight matrix is constructed by k-nearest neighbours method and then the models for the apartment prices in March, 2012 are fitted using the weight matrix. The apartment prices in March, 2013 are predicted by the fitted spatial regression models and then performances of two spatial regression models are compared by RMSE (root mean squared error), RRMSE (root relative mean squared error), MAE (mean absolute error).