• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.183-190
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• 2011

Loan amount of housing mortgage is composed of various factors. This study paper studies focuses on estimating the determinants of a loan amount of housing mortgage. The region for analysis consist of seven groups, that is, metropolitan city (such as Busan, Daegu, Incheon, Gwangiu, Daejeon, Ulsan.) and Seoul. Analyzing period be formed over a 45 time points(2007. 01.~ 2010. 09). In this paper the dependent variable setting up loan amount of housing mortgage, explanatory(independent) variables are composed of the consumer price index, unemployment rate, average monthly household income per household, expenditure rate of health care, composite stock price index and overdue rate of household loans for commercial bank. In looking at the factors which determine loan amount of housing mortgage, evidence was produced supporting the hypothesis that there is a significant positive relationship between the consumer price index and unemployment rate. The study also produced evidence supporting the view that there is a significant negative relationship between expenditure rate of health care. The study found that average monthly household income per household, expenditure, composite stock price index and overdue rate of household loans for commercial bank were not significant variables. The implications of these findings are discussed for further research.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2011.04a
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• pp.285-289
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• 2011

he purpose of this study is to assess the effects of real estate policy on apartment price index in Seoul. To meet the research goal, this research reviewed real estate policy of the government from January of 1986 to August of 2010, and then it collected monthly apartment price index in 25 local districts of Seoul from January of 2003 to August of 2010. After 25 districts were grouped into 2 areas (14 districts in Gangnam and 11 districts in Gangbuk), the data of two areas were analyzed by using the SAS program, Cluster analysis with Ward method showed 3 clusters on each area, and with 6 clusters in total, the effects of real estate policy in the period were examined by using residual analysis. The analysis indicated two major shocks (one was from May to October of 2003, and the other was from March of 2006 to January of 2007), and the results showed that the intervention of government in the market had the asymmetric effects in bullish and bearish times. It implies that the market volatility is substantially influenced by irrational sentiments. Thus, it's suggested to devise the consumer sentiment index suitable in real estate market.

• Journal of the Korean housing association
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• v.23 no.5
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• pp.103-111
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• 2012

This study empirically investigates the degree of physical exclusiveness of multi-family housing estates and its socioeconomic effects. By combining various physical elements devised to blockade and control the entrance to the estate as well as housing units, it constructs the index to quantify the degree of physical exclusiveness for the multi-family housing estates of more than 300 households in Seoul. The statistics reveal that the degree of physical exclusiveness has increased over time and therefore, as a representative example, two-thirds of the estates are now equipped with barricade at the entrance, which often symbolizes 'gated community'. The estimation result of hedonic price model show that physical exclusiveness has a significant positive effect on housing price. The household survey data for the case study estates also demonstrate that the residents in the estate of higher degree of physical exclusiveness put a higher housing value on socioeconomic 'prestige' as well as 'community', beyond physical 'security', and have closer neighborhood relationship with the residents inside the estate. However, there is no significant difference in neighborhood relationship with the outside residents depending upon the degree of physical exclusiveness.

• Economic Analysis
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• v.17 no.1
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• pp.131-168
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• 2011

We estimate consumer price indexes of eight major cities from 1907 to 1939, and then integrate them into a national level one. The data mainly came from the Statistical Yearbooks of the Government-General of Colonial Korea, and if necessary, we supplement them using wages and unit prices of public utility charges which are used as the price of housing and various services. We apply Laspeyres index method, and the composition ratios of consumption expenditure estimated by the commodity flow method are used as weights. The price indexes of 12 item groups as well as aggregate one are also calculated. In case of Seoul, it is possible to calculate the consumer price index from 1907 to 2009, showing a century-long pattern. This consumer price index is critical for measuring the real income and expenditure before the liberation.

• Proceedings of the Safety Management and Science Conference
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• 2009.04a
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• pp.455-475
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• 2009

According to the returns of Housing and business cycle over the period 1992 to 2007, it is a measure of the total volatility faced by investors in Housing properties. First, it isn't a distinct difference from business cycle contrary to U.S. Second, the rise of purchase price in total apartments moves up the consumer price index. According to the cross-sectional dispersion of returns and growth in net operating income (NOI) of apartments, industrial, retail and office properties using panel data for U.S. metropolitan areas over the period 1986 to 2002, it is a measure of the total volatility faced by investors in commercial real estate. To the extent that most of that volatility is difficult to diversify, cross-sectional dispersion may be an appropriate measure of risk.

• 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.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.43-49
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• 2020

The purpose of this study was to analyze factors affecting the housing market by setting household loans and M2, which are liquidity indicators, and the industrial production index reflecting economic fluctuations, as variables, and to determine the effect of expected housing prices. An empirical analysis was conducted based on the data from January 2005 to May 2020, and the HP filter was applied to the real house price as the expected house price variable. As a result of the analysis, it was found that real household loans, real M2, and so on, had an effect on house prices, and expectations for past house prices and house prices increased the house prices in the present period. These results show that even though the liquidity expansion is aimed at revitalizing the economy, it can affect housing prices as well.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2006.11a
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• pp.231-236
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• 2006

The purpose of this study is to make realistic analysis of qualitative value for apartment view. This study is conducted in two ways. First, 6 apartment complexes in Daegu metropolitan city are selected as research subject. And then the following 4 activities are made in order: picture-data establishment, declared-price research, market-price research, and survey. Second, realistic analysis of qualitative value included in apartment price is made based on the above data. And then the value is compared with apartment's declared price which is a current tax index. The result shows that the view value included in apartment price is realistically different depending on many variables such as story/side, plot planning of apartment complex, view element, unlike the declared price mainly focused on story.

• Korean Journal of Construction Engineering and Management
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• v.6 no.6 s.28
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• pp.98-106
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• 2005

The construction cost index and the forecasting model of apartment house can be efficient for evaluating the validness of the fluctuating price, and for making guidelines for construction firms when calculating their profit. In this study the previous construction cost index of apartment house was improved, and the forecasting model based on X-12 ARIMA was developed. According to the result, during the last five years the construction cost, excluding labor expense, has risen approximately to 22.7%. And during next three years, additional 16.8% rise of construction cost is expected. Those quantitative results can be utilized for evaluating the apartment house's selling price in an indirection, and be helpful to understand the variation pattern of the price.

• Smart Media Journal
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• v.11 no.3
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• pp.62-73
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• 2022

Researches on the prediction of domestic apartment sales price have been continuously conducted, but it is not easy to accurately predict apartment prices because various characteristics are compounded. Prior to predicting apartment sales price, the analysis of major factors, influencing on sale prices, is of paramount importance to improve the accuracy of sales price. Therefore, this study aims to analyze what are the factors that affect the apartment sales price in Gwangju, which is currently showing a steady increase rate. With 6 years of Gwangju apartment transaction price and various social factor data, several maching learning techniques such as multiple regression analysis, random forest, and deep artificial neural network algorithms are applied to identify major factors in each model. The performances of each model are compared with RMSE (Root Mean Squared Error), MAE (Mean Absolute Error) and R² (coefficient of determination). The experiment shows that several factors such as 'contract year', 'applicable area', 'certificate of deposit', 'mortgage rate', 'leading index', 'producer price index', 'coincident composite index' are analyzed as main factors, affecting the sales price.