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주택시장 경기동향 및 단기전망 연구(Short-term forecasting model for the housing market)

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  • 주택시장 경기동향 및 단기전망 연구(Short-term forecasting model for the housing market)
  • 윤주현; 김혜승
  • 국토연구원


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Title 주택시장 경기동향 및 단기전망 연구(Short-term forecasting model for the housing market)
Similar Titles
Material Type Reports
Author(Korean)

윤주현; 김혜승

Publisher

경기도:국토연구원

Date 2000-12
Series Title; No 국토연 / 2000-53
ISBN 89-8182-140-2
Pages 116
Subject Country South Korea(Asia and Pacific)
Language Korean
File Type Link
Original Format pdf
Subject Territorial Development < General
Holding 국토연구원

Abstract

As the housing market is liberalized the market movement comes to the more important signal of agents’ activities, that can be used in establishing the housing policy. Housing market in Korea has been heavily regulated in order to distribute the scarce new housing units to the excessive buyers with lower price. As the problems of shortage in housing stock and rapid increase in housing price became alleviated, the government bean to gradually deregulate the housing market from the mid-1990s. Thus, the importance of monitoring the market movement has been growing. There are many indices to reveal the market movement. However, we choose the housing price as the target of our analysis since it comprehensively represents the results of agents’ market behavior.
The purpose of this study is to establish the short-term forecasting model for the housing prices which can be used in monitoring the housing market for the present and for the future.
We firstly adopted the time series model named ARIMA since it allowed us to forecast without any further information. ARIMA works well in the monotonic trend of movement. However, it has some limit to reflect the turning trend or extraordinary movement like financial crisis in Korea. Thus, we developed our model to the “intervention model” which added a dummy named intervention variable into the ARIMA model. Intervention model was found to be better in fitting and in forecasting. However, the weakness of the model still remains since it does not use any further information that can be valuable in forecasting. Thus, “transfer function model” was attempted to use more information that raised the forecasting power of the model. Several additional variables such as gross domestic product, money supply, consumer price index, and residential building permits were selected to be inserted into the given model.
Sales price index and Jonsei deposit index reported from the Korea Housing Bank were used as the housing prices. They are classified by the region (whole nation, Seoul, 6 large cities) and by the house type (overall, apartment). Monthly and quarterly data during 1986.1-2006.6 were used in identification, estimation, diagnosis, and prediction of the model. Employing the results of the above work, we finally predict the sales price in 2001 will be increased by 0.6% for the whole nation and by 2.8% for Seoul. And for the Jonsei deposit, it will be increased by 2.9% for the whole nation and 5.4 % for Seoul.

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이 연구보고서의 내용은 국토연구원의 자체 연구물로서 정부의 정책이나 견해와는 상관없습니다.