• Journal of the Korean Geographical Society
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• v.51 no.2
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• pp.219-233
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• 2016

In social science fields, statistical models are used almost exclusively for causal explanation, and explanatory modeling has been a mainstream until now. In contrast, predictive modeling has been rare in the fields. Hence, we focus on constructing the predictive non-parametric model, instead of the explanatory model. Gangnam-gu, Seoul was chosen as a study area and we collected single-family house sales data sold between 2011 and 2014. We applied non-parametric models proposed in machine learning area including generalized additive model(GAM), random forest, multivariate adaptive regression splines(MARS) and support vector machines(SVM). Models developed recently such as MARS and SVM were found to be superior in predictive power for house price estimation. Finally, spatial autocorrelation was accounted for in the non-parametric models additionally, and the result showed that their predictive power was enhanced further. We hope that this study will prompt methodology for property price estimation to be extended from traditional parametric models into non-parametric ones.

• Korean Journal of Construction Engineering and Management
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• v.10 no.3
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• pp.42-52
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• 2009

From the beginning of 2000, Korean housing market has experienced cyclical volatility because of the global economic fluctuation such as steady decline in the interest rate and the house price bubble. In response to these state Korean Government announced policies about housing sales system kinds of Sales Unit Price Restraint and Post-Sales System to stabilize housing market. But such policies has brought unprecedented arguments both for and against, most of whom still seem to stick to self-centered judgement ahead of impact on housing market. In an integrated point of view, applying the system dynamics modeling, the paper aims at proposing basic Korean housing market dynamics models based on basis principles of housing market determined by supply and demand. And then, after research policies about housing sales system, analyze Impact on Korean Housing Market by change of Sales Systems applying policies to basic Korean housing market dynamics models.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.65-77
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• 2018

It is very important to understand the factors affecting the occurrence of vacant houses in research on them. The purpose of this study is to analyze the factors affecting the rural vacancy occurrence. This study set 121 research areas and selected eight independent variables (Aged house rate, housing transaction rate, house diffusion ratio, local extinction index, net migration rate, regional aging index, the ratio of the number of employees to population and financial independence rate) and one dependent variable (vacant house rate). As a result of the study, first, both Model 1 for the entire general agricultural fishing village area and Model 2 for the county (gun) area were statistically significant, there was no problem with the independence of residual. Second, local extinction index and aged house rate had a statistically significant positive (+) relationship in both Model 1 and Model 2. Third, diffusion ratio of house had a statistically significant positive (+) relationship only in Model 1, and housing transactions rate had a statistically significant negative (-) relationship in Model 2. The implications of the study were drawn as follows: First, the increase in the house diffusion ratio without growth in households and population suggests the increase of the probability of the vacancy occurrence in the area, and the higher the aged house rate, the higher the probability of the vacancy occurrence. Second, for the revitalization of housing transactions, it is necessary to have an investment inflow in the area for mid- to long-term development. Third, local extinction index has a significant relationship with vacant house rate, it is necessary to introduce a local revitalization policy from a long-term perspective for the permanence of the area.

• Korean Journal of Construction Engineering and Management
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• v.6 no.2 s.24
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• pp.61-68
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• 2005

The analysis described in this paper indicate the existence of a correlationship for housing demand and water supply ratio. Using subjective statistical data for the trend of population on regional area, water supply ratio and the number of households, the paper examines the correlationship of forecasting factors for apartments in the ways in which the tendency of demands for apartments and water supply ratio have been analyzed within small and mediumsized city. Differences in the correlationship on the several scale of a city are also taken into account in the analysis. The summary table of the tendency for housing supplies, population and water supply ratio on each scale of a city was generated using data from LAIB. This study attempted to address certain factors that are measurable within a specified paradigm, in order to investigate the extent to which the expectation of apartment supplies can be estimated from the correlationship of water supply ratio. Therefore, it can be suggested that the limited scale of a city are set to maintain the correlationship for housing demands and water supply ratio.

• Journal of the Korean association of regional geographers
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• v.9 no.2
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• pp.135-152
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• 2003

The purpose of this study is to suggest the model of supporting decision making and the method of evaluating criteria and alternatives by value judgement and to apply the model and method suggested to the case of the University Student's housing choice. The criteria and alternatives are evaluated in terms of intuitive judgement and the Analytic Hierarchy Process(AHP). The university students of the Daegu Metropolitan area consider the socioeconomic and environmental factors more important than the characteristics of housing to evaluate their future housing types. In terms of the student's intuitive judgement, socio-educational environment, accessibility, economy, natural environment, and the characteristics of housing are considered in order as an important criteria of evaluating housing. The orders of the important criteria done by an intuitive judgement and the AHP are different. In terms of the AHP, apartment, detached dwelling, and row house are preferred in order as the student's future housing types. The orders of preferred housing types are, however, dynamically changed based on specific criteria. In sum, the model of decision making and the method of evaluating criteria and alternatives by value judgement will be applied to the real problems defined by uncertainty and high risk.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.43-51
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• 2012

The OLS(ordinary least squares) method is widely used in hedonic housing models. One of the assumptions of the OLS is an independent and uniform distribution of the disturbance term. This assumption can be violated when the spatial autocorrelation exists, which in turn leads to undesirable estimate results. An alterative to this, spatial econometric models have been introduced in housing price studies. This paper describes the comparisons between OLS and spatial econometric models using housing transaction prices of Busan, Korea. Owing to the approaches reflecting spatial autocorrelation, the spatial econometric models showed some superiority to the traditional OLS in terms of log likelihood and sigma square(${\sigma}^2$). Among the spatial models, the SAR(Spatial Autoregressive Models) seemed more appropriate than the SAC(General Spatial Models) and the SEM(Spatial Errors Models) for Busan housing markets. We can make sure the spatial effects on housing prices, and the reconstruction plans have strong impacts on the transaction prices. Selecting a suitable spatial model will play an important role in the housing policy of the government.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.77-96
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• 2018

A reverse mortgage provides a pension until the death for the insured or last survivor. Long-term risk management is important to estimate the contractual period of a reverse mortgage. It is also necessary to study prediction methods of mortality rates that appropriately reflect the improvement trend of the mortality rate since the extension of the life expectancy, which is the main cause of aging, can have a serious impact on the pension financial soundness. In this study, the Lee-Carter (LC) model reflects the improvement in mortality rates; in addition, multiple life model are also applied to a reverse mortgage. The mortality prediction method by the traditional LC model has shown a dramatic improvement in the mortality rate; therefore, this study suggests mortality projection based on the projection of the skewness for the mortality that has been applied to appropriately reflect the improvement trend of the mortality rate. This paper calculates monthly payments using future mortality rates based on the projection of the skewness of the mortality. As a result, the mortality rates based on this method less reflect the mortality improvement effect than the mortality rates based on a traditional LC model and a larger pension amount is calculated. In conclusion, this method is useful to forecast future mortality trend results in a significant reduction of longevity risk. It can also be used as a risk management method to pay appropriate monthly payments and prevent insufficient payment due to overpayment by the issuing institution and the guarantee institution of the reverse mortgage.

• 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.

• Environmental and Resource Economics Review
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• v.14 no.4
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• pp.923-941
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• 2005

Odor problem of livestock operation is important issue in a local community. I quantified the property price impact of 199 livestock operations for 3,355 housing sales in the U.S (Colorado). Spatial hedonic model was adopted to deal with spatial autocorrelation in housing market. Small beef and dairy operations, which are the traditional agricultural sector, seem to create a positive rural lifestyle amenity effect. However, the impact of livestock operation on rural residential sales turns to negative if the operation is over a certain size and species. Large hog and sheep operation seems to bring fatal economic loss from the local community perspective if it close to residential area. Livestock odor is one of the negative externality, the results provide the potential social cost of the livestock sector in the region. Policy makers may incorporate this social cost in the regional planning to minimize the social and maximize the development effect. Therefore, local officials and private individuals should carefully consider the location and characteristics of new residential properties and livestock operations alike.

• Korean Journal of Construction Engineering and Management
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• v.11 no.1
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• pp.101-112
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• 2010

The Korean real estate market currently is experiencing a slowdown due to the global economic crisis which has resulted from subprime mortgage lending practices. In response, the Korean government has enforced various policies, based on intend to deregulate real estate speculation, such as increasing the Loan to value ratio (LTV) in order to stimulate housing supply, demand and accompanying housing transactions. However, these policies have appeared to result in deep confusion in the Korean housing market. Furthermore, analyses for housing market forecasting particularly those which examine the impact of the international financial crisis on the Korean real estate market have been partial and fragmentary. Therefore, a comprehensive and systematical approach is required to analyze the real estate financial market and the causal nexus between market determining factors. Thus, with an integrated perspective and applying a system dynamics methodology, this paper proposes Korean Real Estate and Mortgage Market dynamics models based on the fundamental principles of housing markets, which are determined by supply and demand. As well, the potential effects of the Korean government's deregulation policies are considered by focusing on the main factor of these policies: the mortgage loan.