The Comparison of the Efficient Estimators: OLS, WLS, and Spatial Econometric Model

• 발행기관: 한국비교정부학회
• 저자명: Kyoun-Sup Chung
• 간행물 정보: 『한국비교정부학보』제15권 제3호, 127~144쪽, 전체 18쪽
• 주제분류: 사회과학 > 행정학
• 파일형태: PDF
• 발행일자: 2011.12.30

영문 초록

As far as the heteroscedasticity 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 heteroscedasticity, 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. The most important conclusions of this paper in terms of methodological point of view can be summarized as follows: (i) Hedonic models of housing prices must be corrected for heteroscedasticity to ensure greater efficiency in the estimation of hedonic prices wherever the heteroscedasticity does exist, (ii) After careful detection of heteroscedasticity, the method of WLS(Weighted Least Squares) can provide more efficient estimate of the hedonic housing prices in the study area than the traditional OLS(Ordinary Least Squares), (iii) Spatial econometric model, such as SEM(Spatial Errors Model), can be more efficient estimator than the WLS method, and (iv) The spatial econometric model, SEM, is preferable as well as convenient to employ the application.

목차

I. Introduction

II. Data Description and Research Area

III. The Problem of Heteroscedasticity

IV. Detection of Heteroscedasticity and Spatial Autocorrelation

V. The Comparison of the Models

V. Conclusions

References

키워드

효율적 추정량 이분성 검정 가중최소자승법 공간계량모형 Efficient estimator Heteroscedasticity Tests WLS(Weighted Least Squares) Spatial Econometric Models