2010, Vol.67, No.

The Korea Spatial Planning Review 2023 KCI Impact Factor : 1.2

pISSN : 1229-8638
https://journal.kci.go.kr/krihs

The aim of this paper is to develop indicators for identifying housing demand and to apply ongoing housing development sites. In this analysis, the results implies applicability of housing demand evaluation indicators as policy tool. Twelve housing demand evaluation indicators composed of three aspects with demand triggering factor such as the number of new household, population movement, the ratio of households without homeowner, housing stock conditions factor such as housing supply ratio, unsolded housing units, the number of transaction, affordable housing units, and housing purchasing power factor. The result of empirical analysis on 232 local level administratively showed that 117 local units is not sufficient in housing demand. Specifically, housing demand condition can be divided five grades. First grade is highest housing demand condition. In nationwide, housing demand condition reveals third demand grades among fifth demand grades. For more use as housing policy tool it should be equipped systematical evaluation method, workable operating process, housing statistical data base. Although it is limited in availability, reliability, and accessibility of relevant data, MLTM and KRHIS's biennial Housing Survey can be utilized for building of data.

The purpose of this study is to analyze the characteristics of residential environments according to different patterns of new-town adjacent development. With this purpose, this study finds that ① rent, apartment and complex features, and accessibility apparently distinguish the residential environments related to the types of adjacent developments, ② private development has higher horizontal density, while public development has higher vertical density, ③ each development pattern has different spatial dependency with Boondang and Kangnam areas, respectively, and ④ each development pattern has different accessibilities to public and private transportation, respectively. The results of this study suggest several policy implications as follows. First, it needs to come into force the adjacent development management policy, particularly within the new large development areas. Second, it also needs to charge the development costs for developers to reduce overcrowding. Lastly, it is necessary to perform the public management system for sustainable residential environments.

This article is written from idea that determinants of house prices are different across distribution of house prices. Ordinary least squares method, which estimates conditional mean function, and quantile regression method, estimated for each quantile of conditional distribution of house prices, are used to estimate hedonic price model. The results show that buyers of higher-priced homes value certain housing characteristics differently from customers of lower-priced homes. For Example, the age of house is negative to house prices below 50% quantiles, however positive above 60% quantiles of house price distribution. Hedonic price models are estimated on the data from year 2000 to year 2009 of apartment sales prices in Seoul, Korea, the magnitude and importance of regression coefficients vary with the cycles of general and housing business. Trends of coefficients of two estimation methods show some similarities and differences, especially redevelopment and residential-commercial complex are differ across quantiles of house prices.