The Application of the Efficient Housing Price Estimation with and/or without Heteroskedasticity

국문 초록 (Abstract)

이분성의 존재유무의 검증도 없이, 모수의 안정성이 확보되지 않은 행정단위의 지역구분 또는 인위적인 결합은 그 모수 추정에 편기 및 비효율을 초래함으로써 여기에서 유추되는 T-검정 및 F-검정도 그 신뢰성을 믿을 수 없다 하겠다. 또한 그 모수 추정에 대한 편기 및 비효율의 방향도 변수들의 상관관계에 따라 모수의 추정값 및 분산값이 과대평가 되었는지 과소평가 되었는지 구분하기가 실제적으로는 매우 어렵다. 즉, 연구지역에서 최소단위지역의 자료가 동질성을 갖고 있지 않다면 여기서 이루어지는 공간적 병합 및 분할은 잘못된 추론을 가져올 수 있다. 따라서 이러한 지역적 이분성 및 공간적 모수의 불안정성을 모형에 적절하게 통제하지 않으면 여기에서 도출된 어떠한 추론 및 예측도 신뢰의 정도가 약하거나 의심스럽게 되는 것이다. 주택하위시장은 다른 하위시장과는 이질적이면서도 동일 하위시장 내에서는 대체적인 주택시장을 의미하고 있다. 따라서 지역시장에 대한 주택정책 수립 시 상대적으로 동질적인 시장을 파악할수 있다면 주택공급에 따라 각 하위시장별 파급효과를 평가할 수 있어서 주택정책의 실효성을 높이는 중요한 정보가 될 수 있을 것이다. 이는 주택하위시장이 존재한다면 그 가격 추정도 그 주택하위시장의 지역특성에 맞는 가격예측이 필요로 되어지며 이를 기반으로 한 지역정책이 수립되어야 한다는 것을 의미한다고도 볼 수 있다. 따라서 지역적 여건과 특성가격의 추정값이 판이하게 다름에도 불구하고 획일적인 주택가격정책은 반드시 지양되어야 할 것이다. 이는 정확한 또는 논리적 방법적으로 근거한 주택가격 추정을 기본 토대로 하여 지역에 맞는 정책이 수립되어야 함을 함축한다고 하겠다.

다국어 초록 (Multilingual Abstract)

As far as the heteroskedasticity is concerned, it will cause the estimated variance of the coefficient to influence both direction, upward and downward. In other words, the estimated of variance of the coefficient can be overestimated or estimated depends on the nature of causing factors in the model. If we persist in using the usual testing procedures despite heteroskedasticity, whatever conclusions we draw or inferences we make be very misleading. As a result, we can no longer rely on the conventionally computed confidence intervals and the conventionally employed t and F tests. If there is not a homogeneous spatial process underlying the data, any aggregation will tend to be misleading. This aspect of modifiable area unit problem should be considered as a specification issue related to the form of spatial heterogeneity, and not solely as an issue determined by the spatial organization of the data. This paper addresses the question of homogeneity across a housing market. The effect of heteroskedasticity on the test for homogeneity across samples has concentrated on the case of heteroskedasticity between samples but not within samples in the previous research. An assumption of between-sample heteroskedasticity explicitly states that the factor that divides the samples is the only one that generates differences in the spread of the disturbances. Such an assumption may be reasonable in some circumstances after all, the slopes of the equation are presumed to differ as well. The theory usually offers little guidance about the nature of the distribution of the disturbance; however, assuming that heteroskedasticity exists but only as a function of sample-dividing factor is rather specific and too restrictive in many circumstances. Indeed, much of the present-day research on heteroskedasticity is focused on
allowing generality and enhancing flexibility of estimation and testing procedures. Typically, a submarket is defined as a set of dwellings that are reasonable close substitutes for one another, but relatively poor substitutes for dwellings in other submarkets. It is reasonable to set the regional housing policy based on the concrete procedure or statistical method such as housing market segmentation; in addition, the relevant information on the homogeneous housing submarkets will be helpful in order to estimate the spread effect on the regional housing submarkets.

목차 (Table of Contents)

• I. Introduction
• II. The Problem of Heteroskedasticity
• III. The Previous Studies
• IV. Research Method
• V. Data Description and Result of Analysis
• VI. The Comparison of the Chow and Wald models
• VII. Conclusions
• Reference
• Abstract

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