自從Rosen(1974)根據Lancaster (1966)新效用理論提出隱含價格理論以來，建立特徵價格方程式成為了建構住宅估價模型最常用的方法，過去國內有不少這方面的研究，利用統計工具找出影響住宅價格的變數，建立特徵價格函數。這些研究把誤差項假設為獨立且相等的常態(iid)分佈，但卻沒有考慮到同一地區內之其他鄰近住宅對該住宅價格有著空間相依性的關係。這些鄰近的住宅擁有著相似的社經環境，同時也面對著相同的鄰里環境，例如享用著相同的公共設施、小孩就讀於相同的學校、受相同的警察局和消防局保護等，所以這些同地區住宅的價格並不可能是獨立的，而這種空間相依性的關係也產生了空間自我相關(SA)問題，使模式不符合獨立且相等的常態分佈假設，也使得模式估計能力下降。
　　空間計量經濟學和對於空間自我相關(SA)的研究是自1980年代以後最近被重視的一種研究住宅價格的方法，本研究以台南市東區為研究地區，首先建構住宅資料之空間屬性資料庫，並對住宅價格進行空間自我相關測試，最後比較空間自我迴歸模型與傳統迴歸模型。實證結果發現，住宅價格間有顯著的空間相依性關係，同時空間自我迴歸模型可以解決誤差項的空間自我相關問題。

　　Hedonic price function is the most frequently used to construct models to estimate the housing price since Lancsater(1966) and Rosen (1974). However, when constructing the regression models based on the empirical observation to the housing prices in a same community (or city), the basic assumption of identical and independent distribution (iid) of the housing price variation would very possibly be violated. Not only did the neighborhood share the same environmental and land use control, but also the households might have similar society and economic attributes. For example, they share the same community facilities, and kids go to the same school. In fact, housing prices in the same community would not be independent, and yield less efficiency on the regression models. Since the end if the 1980s, there has been a marked increase in housing studies highlighting concerns about spatial econometrics and spatial autocorrelation. In this study, we collected some housing transaction data in Tainan city, the 4th largest city in Taiwan. The empirical data were limited in the same area, so that all the cases share the same land use control under the city planning regulation. We located all the cases on the GIS map, examined the independence of housing prices by spatial autocorrelation test, and compare the different between traditional hedonic model and spatial autoregressive. We found that housing prices have a signification spatial dependence and SAR model can reduces the spatial dependence among residuals.

一、國內文獻
朱健銘，2000，「土地利用空間型態之研究」，國立台灣大學地理學研究所碩士論文
何志南，2001，「住宅消費意向模式之建構與分析」，國立成功大學都市計劃研究所碩士論 文
周天潁、周學政，1997，「Arc View 透視3.X」，松岡電腦圖書資料股份有限公司
林尚德，2002，「土地估價動態模型之建立」，國立成功大學都市計劃研究所碩士論文
施保旭，1997，「地理資訊系統」，儒林圖書有限公司
洪于婷，1999，「都市發展永續性結構之研究」，國立成功大學都市計畫研究所碩士論文
張秀玲，2001，「整合空間資訊科技與土地大量估價作業之研究」，國立成功大學都市計劃研究所碩士論文
張梅英，1992，「建立土地大量估價方法之研究」，國立政治大學地政研究所碩士論文
梁蘄善，2000，“地理學計量方法”，中國文化大學出版部
許芝芬，1996，「空間資料萃取模式之建立-以土地估價為例」，逢甲大學土地管理研究所 陳彥仲、林國民，1996，「台灣都市住宅屬性隱含需求分析-以高雄市為例」，國立成功大學都市計劃研究所碩士論文
陳郁文，（1997），“地理資訊系統應用於土地估價之研究”， 「人與地」，第一六二期，頁22至28
陳慈仁，2001，「台北市資訊軟體業與網際網路服務業區位分佈之研究」，國立台灣大學建築與城鄉研究所碩士論文
楊文松，1999，「地理資訊系統輔助土地地價區段劃分之研究」，國立政治大學地政研究所碩士論文
楊宗憲，1996，“住宅價格指標之研究-以台北市為例”，「住宅學報」，第四期
鄒克萬，2000，“區域人口分布之時空分析”， 「土地科學學報」，第一期
謝純瑩，2002，“應用空間自相關分析於人口老化時空變遷之研究”， 「人口學刊」，第二 十五期
謝銘智，2000，「公共設施計畫空間公平性之研究」，國立成功大學都市計畫研究所碩士論文

二、國外文獻
Anselin, L. (1988a) “Spatial econometrics: methods and models ”, Kluwer Academic, Dordrecht.
Anselin, L. (1988b) “GIS Research Infrastructure for Spatial Analysis of Real Estate Markets”, Journal of Housing Research , Vol. 9, 113-133.
Anselin, L. (1995) “Local Indicators of Spatial Association: LISA.”, Geographical Analysis, 93–115.
Anselin, L. (1998a) SpaceStat: A Program For the Statistical Analysis of Spatial Data , National Center for Geographic Information and Analysis, University of California.
Anselin, L. (1998b) SpaceStat Version 1.90. http://www.spacestat.com.
Anselin, L. (1998c) “SpaceStat Version 1.90 User’s Guide”, Morgantown, WV:West Virginia University,Regional Research Institute.
Anselin, L. (1999) “Spatial Econometrics ”, Bruton CenterSchool of Social Sciences University of Texas at Dallas Richardson
Anselin, L. (2002) “Under the Hood. Issues in the Specification and Interpretation of Spatial Regression Models”.
Anselin, L. and A.Bera (1998) “Spatial dependence in linear regression models with an introduction to spatial econometrics”, New York, pp. 237-289.
Basu, S. and G. Thomas(1998) “Analysis of Spatial Autocorrelation in House Price”, Journal of Real Estate Finance and Economics, Vol. 17.
Benser ,C. (2002) “A Spatial Autoregressive Specification with a Comparable Sales Weighting”, JRER, Vol. 24, 193-210.
Bivand, R. (1998) “A review of spatial statistical techniques for location studies”，pp.13~16.
Brett, C. and J. Pinkse (1997) “Those taxes are all over the map!: a test for spatial independence of municipal tax rates in British Columbia”, International Regional Science Review, Vol. 20, 131–151.
Burrough, P. (1986) “Principles of Geographical Information Systems for Land Resources Assessment.Oxford”, England: Oxford University Press.
Can, A. (1990) “The Measurement of Neighborhood Dynamics in Urban House Prices.”, Economic Geography
Can, A. (1992) “Specification and Estimation of Hedonic Housing Prices Models”, Regional Science and Urban Economics, Vol. 22, 453-477.
Can ,A. (1998) “GIS and Spatial Analysis of Housing and Mortgage Markets.”, Journal of Housing Research, Vol.9, 61-84.
Cliff,A. and J. Ord (1973) “Spatial Autocorrelation ”, London, Pion.
Cliff, A. and J. Ord.(1981)Spatial Processes: Models and Applications. Pion,London.
Dubin, R.A. (1998) “Predicting House Prices Using Multiple Listings Data. ”, Journal of Real Estate Finance and Economics, Vol. 17, 35–48.
Fotheringham A. S. and C.Brunsdon (1998) “Geographically Weighted Regression :A Natural Evolution of the Expansion Method for Spatial Data Analysis” , Environment and Planning A , Vol. 30, 1905-1927.
Goodchild, M.F. (1987) “A Spatial Analytical Perspective on Geographic Information Systems”, International Journal of Geographical Information Systems ,Vol. 1, 327–34.
Griffith, D.A. (1992) “Simplifying the normalizing factor in spatial autoregressions for irregular lattices.”, Papers in Regional Science , 71–86. Griffith, D. A. (1995) “Some guidelines for specifying the geographic weights matrix contained in spatial statistical models” In S. L. Arlinghaus and D. A. Griffith (eds) Practical handbook of spatial statistics (Boca Raton: CRC Press), 65–82.
Issam ,M., Kara ,M. and Travis ,P.(2002), “Accessibility Indices: A Connection to Residential Land Prices and Location Choices”, Paper Presented at the 81st Annual Meeting of the Transportation Research Board Forthcoming in Transportation Research Record.
LeSage, J.P. (2000) “Bayesian Estimation of Limited Dependent variable Spatial Autoregressive Models”, Geographical Analysis, Vol. 32, 19-35. Li ,B. (1995) “Implementing spatial statistics on parallel computers”, Practical Handbook of Spatial Statistics.,107-148.
Maguire, J. David (1991), “An Overview and Definition of GIS. In Geographical Information Systems,Principles and Applications,” ed. David J. Maguire, Michael F. Goodchild, and David W. Rhind, 9–20.London: Longman. McMillen, D. P. (1992) “Probit with spatial autocorrelation”, Journal of Regional Science, Vol. 32, 335–48.
Pace R.K. and O. Gilley (1997) “Using the Spatial Configuration of the Data to Improve Estimation”, Journal of Real Estate Finance and Economics, Vol. 14, 333-340. Pace,
R. K, and P. LeSage (2000) “Closed-Form Maximum Likelihood Estimates forSpatial Problems”
Pace, R. K, and P. LeSage (2003)”Conditional Autoregressions with Doubly Stochastic Weight Matrices”
Pace, R. K and B. Ronald (1997) “Sparse Spatial Autoregressions”, Statistics and Probability Letters,Vol. 33,291-297.
Paelinck, J. and L. Klaassen (1979)”Spatial Econometrics”, Saxon House, Farnborough.
Smirnov, O. and L. Anselin (2001) “Fast maximum likelihood estimation of very large spatial autoregressive models: a characteristic polynomial approach”,Journal of Computational Statistics & Data Analysis, Vol.35, 301-319 Tiefelsdorf, M. and B. Boots (1995) “The exact distribution of Moran’s I”, Environment and Planning A, Vol. 27, 985–999.
Tiefelsdorf, M. and B. Boots (1997) “A note on the extremities of local Moran’s Iis and their impact on global Moran’s I”, Geographical Analysis, Vol. 29, 248–257.
Torrens ,P.M. (2001) “ New Tools for Simulating Housing Choices” ,Housing & the New Economy
Thrall ,G.I.(1998) “GIS Applications in Real Estate and Related Industries”, Journal of Housing Research, V. 9, 33-59
Upton, G. and B. Fingleton (1985) “Spatial data analysis by example: point pattern and quantitative data”
Wyatt, P. J. (1997) “The Development of a GIS-based Property Information System for Real Estate Valuation”, Geographical Information Science,Vol. 11, 435-450.