• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.211-231
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• 2022

This study attempted to identify the effects of macroeconomic variables such as the All Industry Production Index, Consumer Price Index, CD Interest Rate, and KOSPI on apartment lease prices divided into nationwide, Seoul, metropolitan, and region, and to present a methodological prediction model of apartment lease prices by region using Long Short Term Memory (LSTM). According to VAR analysis results, the nationwide apartment lease price index and consumer price index in Lag1 and 2 had a significant effect on the nationwide apartment lease price, and likewise, the Seoul apartment lease price index, the consumer price index, and the CD interest rate in Lag1 and 2 affect the apartment lease price in Seoul. In addition, it was confirmed that the wide-area apartment jeonse price index and the consumer price index had a significant effect on Lag1, and the local apartment jeonse price index and the consumer price index had a significant effect on Lag1. As a result of the establishment of the LSTM prediction model, the predictive power was the highest with RMSE 0.008, MAE 0.006, and R-Suared values of 0.999 for the local apartment lease price prediction model. In the future, it is expected that more meaningful results can be obtained by applying an advanced model based on deep learning, including major policy variables

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.457-467
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• 2015

Despite the recent phenomena of Chonsei price increase, low interest rate and low growth, the indexes of financial and insurance industry production showed the results contrary to the common belief that the financial industry is sensitive to such financial crises. This is because the index of financial industry has continuously maintained a certain level of increase as opposed to the index of all industry production. Thus, this study aimed to analyze the dynamic correlation between the index of financial industry production and Chonsei price increase. A vector autoregression (VAR) model, which doesn't have a cointegrating relationship, was used to define the Chonsei price index and the indexes of all industry production and financial and insurance industry, which are macro economic variables, and describe the data. The results of the analysis on the time series data of 183 months from January 2000 to May 2015 showed that Chonsei price increase was not directly derived from the index of financial industry, but the finance industrial index affected Chonsei price increase.

• KDI Journal of Economic Policy
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• v.45 no.4
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• pp.57-77
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• 2023

The Chonsei component holds the highest level of weight (5.4%) in the composition of the Korean consumer price index (CPI). The variations in Chonsei prices are directly reflected in the CPI as a representation of cost swings. The Chonsei refers to a deposit that accumulates the costs related to housing services and is mostly affected by variations in rental rates. Nevertheless, it is important to note that Chonsei prices are also susceptible to fluctuations in interest rates, regardless of the rent prices. Therefore, if Chonsei were directly and one-to-one indexed to the CPI, they could include changes other than residential service prices. After analyzing the time series data of the Chonsei index and rent index inside the CPI, it becomes apparent that the Chonsei index displays an average annual growth rate of 2.3%, whilst the rent index reveals a growth rate of 0.9%. The observed disparity in growth rates indicates a divergence in trends between the two indices. It is posited that the Chonsei index, when capitalized, has had a more rapid increase compared to the rental index, owing to the gradual drop in interest rates. To effectively reflect fluctuations in the housing service costs, proxies for the Chonsei index were utilized in the construction of a consumer price index. The findings of our study suggest that, overall, the newly developed CPI demonstrates a comparatively lower rate of inflation when compared to the official CPI. Furthermore, the inclusion of imputed rents for owner-occupied housing in CPI amplifies this effect.

• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.271-280
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• 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.

• Survey Research
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• v.9 no.3
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• pp.1-21
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• 2008

The housing market in Korea had mainly consisted of Maemae(purchasing market) and Chonsei(rental market). Since 1997 foreign exchange crisis, the rental housing market has experienced substantial changes in preferred rental contracts between Chonsei and monthly-rent. Even though monthly-rent has taken a substantial portion of housing rental contracts, not yet reliable monthly-rent index has been developed. Furthermore, it isn't obvious to define monthly-rent because there are many types of monthly rent structures from full-monthly-rent to monthly-rent-with-variable-deposit. This study is the basic research of developing a housing price index of monthly-rent in accordance with the existing price index of Maemae and Chonsei in Korea. This research has been carried out with the following contents: (1) Constructing the actually desirable concept of monthly-rent through examining monthly-rental market in Korea. (2) Selecting the reasonable method to investigate monthly-rental market, especially monthly-rent-with-variable -deposit. (3) Designing monthly-rental market samples and calculating the price index of monthly-rent based on 2005 Census.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.488-497
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• 2015

The recent increase of chonsei has raised the degree of lease burden of households, and a new residential lease price index needs to be introduced to measure such degree of lease burden. In order to convert the burden into an index, the calculation method of the K-HAI, which is announced by the Korea Housing Financing Corporation, is applied by replacing house purchase with lease. From the calculation, the residential lease prices index of the first quarter of 2014 is estimated to be approximately 114, indicating that the cost of lease exceeds 35% of income. The result of analysis on the trend of the residential lease prices index from the first quarter of 2012 to the present in Seoul indicates that the residential lease prices index in Seoul has continued to increase, compared to that of the entire country. The results of this study will be a foundation to find a solution for the stabilization of chonsei and investigate the degree of lease burden by region when establishing a sustainable housing policy.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.2
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• pp.301-306
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• 2013

The Ratio of APT jeonse to purchase price was still rising. The interaction of APT Purchase and Jeonse price indices by region analysis in order to analyze this phenomenon, and results were summarized as follows. First, because the regional APT purchase and jeonse prices appears the rise and fall differently by region, regional polarization was deepening. Second, the recently real estate market was analyzed the province's booming real estate and the downturn of the metropolitan area. So, the ratio of APT jeonse to purchase price was continued to rise. Finally, the Ratio of APT jeonse to purchase price changing rate is (+) increased if the APT purchase price changing rate is larger then the APT purchase price changing rate and smaller then is (-) decreased.

• Land and Housing Review
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• v.4 no.1
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• pp.43-54
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• 2013

This This paper investigates the variation of the factors to determinate housing price in Seoul metropolitan area after sub-prime financial crisis, in Korea, using a VAR model. The model includes housing price and housing rent (Jeonse) in Seoul metropolitan area from 1999 to 2011, and uses interest rate, real GDP, KOSPI, Producer Price Index and practices to impulse response and variance decomposition analysis to grasp the dynamic relation between a variable of macro economy and and a variable of housing price. Data is classified to 2 groups before and after the 3rd quater of 2008, when sub-prime crisis occurred; one is from the 1st quater of 1999 to the 3rd quater of 2008, and the other is from the 2nd quater of 1999 and the 4th quater of 2011. As a result, comparing before and after sub-prime crisis, housing price is more influenced by its own variation or Jeonse price's variation instead of interest rate and KOSPI. Both before and after sub-prime financial crisis, Jeonse price is also influenced by its own variation and housing price. While after sub-prime financial crisis, influences of Producer Price Index, KOSPI and interest rate were weakened, influence of real GDP is expanded. As housing price and housing rent are more influenced by real economy factors such as GDP, its own variation than before sub-prime financial crisis, the recent trend that the house prices is declined is difficult to be converted, considering domestic economic recession and uncertainty, continued by Europe financial crisis. In the future to activate the housing business, it ia necessary to promote purchasing power rather than relaxation of financial and supply regulation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6315-6324
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• 2015

This study analyses the effects of household finances on rental price of apartment in Seoul which play a major role in real estate policy. We estimate VAR models using time series data. Economy variables such as sales price of apartment in Seoul, consumer price index, hiring rate, real GNI and loan amount of housing mortgage, which relate to household finances and influence the rental price of apartment, are used for estimation. The main findings are as follows. In the short term, the rental price of apartment is impacted by economy variables. Specifically, Relative contributions of variation in rental price of apartment through structural shock of economy variables are most influenced by their own. However, in the long term, household variables are more influential to the rental price of apartment. These results are expected to contribute to establish housing price stabilization policies through understanding the relationship between economy variables and rental price of apartment.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1573-1583
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• 2016

It is necessary to check mutual correlations between related variables because housing prices are influenced by a lot of variables of the economy both internally and externally. In this paper, employing the Granger causality test, we have validated interrelated relationship between the variables. In addition, there is cointegration associations in the results of the cointegration test between the variables. Therefore, an analysis using a vector error correction model including an error correction term has been attempted. As a result of the empirical comparative analysis of the forecasting performance with ARIMA and VAR models, it is confirmed that the forecasting performance by vector error correction model is superior to those of the former two models.