• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.566-576
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• 2016

It is known that the Real Estate Sales Market and Auction Market are closely interrelated with each other in a variety of respects and the media often mention the real estate auction market as a leading indicator of the real estate market. The purpose of this paper is to analyze the relationships between the housing market and auction market before and after macroeconomic fluctuations using VECM. The period from January 2002 to December 2008, which was before the financial crisis, was set as Model 1 and the period from January 2009 to November 2015, which was after the financial crisis, was set as Model 2. The results are as follows. First, the housing auction market is less sensitive to changes in the housing market than it is to fluctuations in the auction market. This means that changes in the auction market precede fluctuations in the housing market, which shows that the auction market as a trading market is activated. In this respect, public institutions need to realize the importance of the housing auction market and check trends in the housing contract price in the auction market. Also, investors need to ensure that they have expertise in the auction market.

• Korean Journal of Construction Engineering and Management
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• v.17 no.3
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• pp.108-115
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• 2016

The price determinant for land investment depends on the internal information process and subjective decision making by management in general. Accordingly, the systematic frame to determine the feasibility of investment price to the public residential land for multi-housing development by private sector has not been proposed. The purpose of this study is to explore the frame to determine the investment price for public residential land from the perspectives of land attribute and apartment market factor. Multiple regression has been implemented to confirm the eligibility of proposed model. Research findings indicate that the land area, floor area ratio, coverage ratio, location have been identified as the total land cost determinant, and for the determinants for floor area land cost, the ratio of apartment, sale price, rent price, etc, have been identified. This research intends to provide the basis for land providers to predict the land value as a raw material in market and present the indicators for land buyers to review the price adequacy for the investment.

• Land and Housing Review
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• v.5 no.4
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• pp.247-257
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• 2014

This study proposes a new housing need and demand assessment model centering on small-scale housing development projects and happy house development projects that reflected the recent changes in rental and small sized apartment centered public housing policies and development paradigms. The housing need and demand assessment model of public housing development projects consists of quantitative evaluation factors such as potential need indicator and demand pressure indicator and qualitative evaluation factors such as local condition indicator. The potential need indicators of small sized housing development projects are calculated by subtracting the stock of already-supplied constructed rental and purchased rental housings from the potential quantity of need drawn from the small regions such as -eup, -myeon, and -dong. In the potential need indicators of happy house development projects, the potential need is calculated from those who are expected to receive a happy house in the unit of -si, -gun, and -gu. In small-sized housing development projects, demand pressure indictors are the number and the proportion of those who opened a subscription deposit, the number of those who received basic livelihood security and the number of those who were patriots and veterans. The demand pressure indicators of the happy house development projects are stock ratio of small-sized houses, rate of rise in housing rent price, level of housing rent price, and rate of monthly rent house.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.2
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• pp.205-213
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• 2010

This study was to analyze the past regime's real estate policy and the time-series data on real estate price index from 1986 to 2009 in 24 years. Also, the real estate index and macroeconomic variables, the impact on house price index variable conducted to regression analysis and to analyze whether and how much is affected. Analyzed as follows: First, Korea's real estate policy was the post-policy and the past regime's real estate policy was inconsistent with each other. Second, in the normal phase whenever real estate issues, the measures of the strengthening regulation and of the economic recovery were only to repeat periodically. Third, the timing and means of policy enforcement was an inappropriate and Real estate market was getting worse at the time whenever a real estate policies performed. Fourth, The apartments prices index of the housing types rose the highest and were the most popular for 24 years. Increase or decrease the amount of the price index for apartments, Roh Tae-woo(65.0%) - Kim Dae-jung (42.5%) - Roh Moo-hyun (32.8%) were in order. Fifth, the results of the regression analysis carried out: The impact on housing prices among independent variables were followed by Cap Construction- one per capita income - Housing consumer price index - Accompanying Composite Index - Trailing Composite Index - Home subscription Subscriber account - Leading Composite Index.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.3260-3269
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• 2014

The construction industry has strong ties with other industries, and so construction company insolvency also has a strong influence on other industries. Prediction models addressing the insolvency of construction company have been well studied. Although factors contributing to insolvency must precede those of predictions of insolvency, studies on these contributing factors are limited. The purpose of this study is to analyze the influence of changes in the housing market on construction company insolvency by using the Vector Error Correction Model. Construction companies were divided into two groups, and the expected default frequency(EDF), which indicates insolvency of each company was measured through the KMV model. The results verified that 10 largest construction companies were in a better financial condition compared to relatively smaller construction companies. As a result of conducting impulse response analysis, the EDF of large companies was found to be more sensitive to housing market change than that of small- and medium-sized construction companies.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.23-29
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• 2015

In this study, the spatial relevance between the regional housing price data and the spatial distribution of the location-based social media data is explored. The spatial analysis with rasterization was applied to this study, because the both data have a different form to analyze. The geo-tagged Twitter data had been collected for a month and the regional housing price index about sales and lease were used. The spatial range of both data includes Seoul and the some parts of the metropolitan area. 2,000m grid was constructed to consider the different spatial measure between two data, and they were combined into the constructed grids. The Hotspot Analysis was operated using the combined dataset to see the comparison of spatial distribution, and the bivariate spatial correlation coefficients between two data were measured for the quantitative analysis. The result of this study shows that Seocho-gu area is detected as a common hotspot of tweet and housing sales price index data. though the spatial relevance is not detected between tweet and housing lease price index data.

• Korean Journal of Social Welfare
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• v.68 no.3
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• pp.29-50
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• 2016

This study examined the determinants of housing affordability using the 2014 fact-finding survey of housing. This study identified the effects of characters of districts as well as the effects of characters of family and housing, taking advantage of HGLM(Hierarchical General Linear Model). The results of this study showed that male householder, higher education level, the monthly housing, higher satisfaction of environment of housing are the factors that increased the odds of living at unaffordable housing, but higher income, public transfer recipient, living at sub-standard housing, the Jensei housing are the factors that decreased the odds of living at unaffordable housing. And the higher housing price, the higher rent of the districts increased significantly the odds of living at unaffordable housing, but the higher rate of public housing of the districts decreased the odds of living at unaffordable housing. This study provides the basis that the price of housing and rent should be controled and the policy of public housing should be expanded for housing welfare.

• International Area Studies Review
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• v.21 no.4
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• pp.173-194
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• 2017

The research study conducted logistics regression analysis through HLM (Hierarchical Linear Modeling) and presented the value of the outcome in order to investigate characteristic factors of demanders which influence the intention to move into public rental housing. (1) The results of the regression analysis of characteristic factors of household and housing were analyzed as having the significant effect on the intention to move in public rental housing, according to residents moving in monthly rent housing, residents' occupations, rental housing, the number of household, the location of surrounding public rental housing, monthly average income, children's educational level, the number of children, the types of housing and one's own house, in order, out of the types of housing tenure. (2) The results of the regression analysis of characteristic factors of the conditions of location were analyzed that out of the conditions of location of the top five areas in public rental rates, what influences significant effects on the intention to move in public rental housing is the location of surrounding rental housing, income, the number of household and children, children's educational level, job state, housing types, ones' own house, rent housing, monthly rent housing, in order. (3) In case of Seoul, Expanding public rental housing is inevitable in order to stabilize ordinary people's housing stability, owing to the high and rental prices of private housing. Nevertheless, an accurate analysis of the intention to move in public rental housing has not been conducted. Eventually, the research was, thus, conducted, based on the fact that the preference on public housing is low. According to the analytic results of the study, it is required for the government institutions and agencies should consider individual and local characteristics and provide an alternative that meets the real situation, in order to help ordinary citizens with low incomes stabilize housing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.737-744
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• 2016

Seoul Metropolitan Area has been changed by fierce internal migration during the last several decades. To determine the regional structure, we analyzed the in-and-out migration pattern and main factors affecting the intense of mobility. The migration within metropolitan city and province shows that in Seoul, Songpa and Dobong Gu gained a large population, in Incheon, Namdong Gu experienced a huge population influx, and in Gyeonggi Province, Hwasung, Yongin and Paju city gained a great population. In Seongnam, Suwon city lost a lot of population. These population gains and losses came from mainly residential redevelopment projects in the metropolitan city and new land development projects in Gyeonggi Province. The main factors affecting the intense of mobility diverse from city characters. In central type cities, house price gets the more population influx. In job-housing balanced cities, total income growth rate, housing supply rate and roads cause in-migration. In bed-town type cities, the increase of housing supply rate and parks increase the population. In suburban type cities, business density, housing supply rate, housing, subway station number and educational facilities increase population from outside the city. So, we have to prepare more detailed urban and housing policy responses.

• Land and Housing Review
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• v.12 no.2
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• pp.33-45
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• 2021

Due to recent changes in government policy, officetels have received attention as alternative assets, along with the uplift of office and apartment prices in Seoul. However, the current officetel price indexes use small-size samples and, thus, there is a critique on their accuracy. They rely on valuation prices which lag the market trend and do not properly reflect the volatile nature of the property market, resulting in 'smoothing'. Therefore, the purpose of this paper is to create the officetel price index using transaction data. The data, provided by the Ministry of Land, Infrastructure and Transport from 2005 to 2020, includes sales prices and rental prices - Jeonsei and monthly rent (and their combinations). This study employed a repeat sales model for sales, jeonsei, and monthly rent indexes. It also contributes to improving conversion rates (between deposit and monthly rent) as a supplementary indicator. The main findings are as follows. First, the officetel price index and jeonsei index reached 132.5P and 163.9P, respectively, in Q4 2020 (1Q 2011=100.0P). However, the rent index was approximately below 100.0. Sales prices and jeonsei continued to rise due to high demand while monthly rent was largely unchanged due to vacancy risk. Second, the increase in the officetel sales price was lower than other housing types such as apartments and villas. Third, the employed approach has seen a potential to produce more reliable officetel price indexes reflecting high volatility compared to those indexes produced by other institutions, contributing to resolving 'smoothing'. As seen in the application in Seoul, this approach can enhance accuracy and, therefore, better assist market players to understand the market trend, which is much valuable under great uncertainties such as COVID-19 environments.