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題名：運用地理加權迴歸模型探討都市公園之鄰里效應
作者：陳章瑞 引用關係
作者(外文)：Chen Chang-Jui
校院名稱：中國文化大學
系所名稱：建築及都市計畫研究所
指導教授：陳錦賜
學位類別：博士
出版日期：2009
主題關鍵詞：都市公園；鄰里效應；地理加權迴歸；空間特徵模型；特徵價格法；Urban Park；Neighborhood Effects；Geographically Weighted Regression (GWR)；Spatial Hedonic Models (SHM)；Hedonic Price Method (HPM)
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都市公園具有遊憩、防災、調節氣溫等多重效益，雖然不易對這些個別效益的價值進行評估，但都市公園作為一種地方準公共財，其寧適效益可資本化入周圍不動產的價格上，並在空間面向呈現其正面的鄰里效應（neighborhood effects）、地方外部性（localized externalities）與地方寧適性效益（localized amenities benefits）。都市公園鄰里效應的寧適效益抽象而非具體，不易進行衡量，然而遺漏了將造成環境改善整體效益的偏誤。因此，透過辨認不動產內外部及週邊地方鄰里環境寧適性資源如都市公園等的特徵做為解釋變數，為不動產交易價格建立空間迴歸模型，可得到不動產與都市公園等相關特徵所隱含的特徵價格。本研究主題即在運用地理加權迴歸（GWR）模型探討都市公園空間面向的鄰里效應來衡量與評估都市公園寧適效益及影響。
經濟學家們持續不斷地提出研究文獻證明房地產價格與環境寧適度之間的關係，實際上，在人們認識到它們之間的關係之前，它就已經在新發展起來的特徵價格理論中得到了應用，例如，Ridker（1967）是第一位嘗試以房地產的價值資料為依據來評估環境品質（如空氣污染）變化所產生效益的經濟學家。自從Rosen （1974）根據Lancsater（1966）新效用理論提出特徵價格理論以來，特徵價格函數成為建構估計房地產價格迴歸模型最常用的方法，近30年以特徵價格理論為基礎，人們對非市場性的寧適性資源的貨幣價值問題進行了大量的理論和實證研究，房屋價格的不同，反映了房屋各方面特徵數量的差異，這些差異對於福利分析而言具有非常重要的意義，這一觀點現在已被普遍接受，特徵價格法（Hedonic Price Method）已經在環境經濟學中成為一個既定的方法論（例如，Palmquist 1991）。
自1980年代末，特徵價格法的注意力已轉移至同一地方鄰里內的鄰近房地產與鄰里環境特徵在空間產生互相依賴的關係，留意於鄰近房地產的價格可能有助於特定關注房地產價格解釋的課題（Palmquist 2006），傳統的統計技術以特徵價格法估計房屋特徵價格，視研究樣區為同質區，環境特徵為均質單一關係，而無視於樣區空間之差異，被稱為「全域式」分析（gobal analysis）方法。然而，當在相同的鄰里或社區經驗地觀察房地價格來建構迴歸模型時，常把誤差項假設為獨立且相等的常態分佈，但卻沒有考慮到同一地區內之其他鄰近房地產對該房地產價格有著空間相依性的關係。這些鄰近的房地產擁有著相似的社經環境、相同的鄰里環境、享用著相同的公園與社區公共設施，所以這些相同地區房地產的價格在空間相依性的關係下，使得迴歸模型的誤差項不符合獨立且相等的常態分佈假設，從而產生了空間自相關問題，使得模型估計能力下降（黃紹東 2004）。
近年來的特徵價格理論與實證研究的問題焦點已發現並轉移到如何解決與克服房地產價格在鄰近不同空間效應下的空間互相依賴、空間自相關（Freeman 2003；Palmquist 2006）與空間異質性在估計過程被忽略時可造成的潛在偏差和效力損失結果的問題。空間計量經濟學方法（Anselin 1988）將空間自相關和空間異質性之類的空間效應，帶進解決空間依賴問題的房地產價格模型設定、估計及檢驗的經驗研究與方法應用已日漸普及，進一步改良傳統特徵價格法形成所謂的「空間特徵模型」（Spatial Hedonic Models, SHM）（Anselin and Gallo 2006；Anselin 2008）研究取向的理論與工具，其中地理加權迴歸（Geographically Weighted Regression, GWR）模型，以地方（局域）分析（local analysis）方法，透過地理座標指定頻寬設置及觀察樣本在區位空間的加權，並有利於結合地理資訊系統（GIS）的空間統計與空間分析方法，以及經由圖面探討空間變化的優點，成為當前受重視的一種的空間特徵模型研究方法，此外在環境寧適性評價研究方面，空間特徵取向的方法正方興未艾。
在近十年左右翻新關注於鄰里脈絡與房價研究的重要進展已在都市環境與房價之間形成概念化的關係。在連接環境與房價之間的應用研究仍留在各種空間概念方法，諸如「鄰里」（如鄰里效應、地方化寧適效益等）或「建成環境」（如都市公園系統、公共設施等）的可操作性的限制。本研究探討這些在統計模型的空間概念的表現是植基於鄰里環境的特徵及都市空間結構的差異之上。
探索在多元尺度處理相同分析的實踐以及尋求運用適合於「探索」空間向度的模型是本研究的題旨。在我們所理解的鄰里環境如何影響房價（結果）和空間統計與空間分析方法建模技術之間有一裂縫，因為深入到鄰里（地方）環境寧適效益的衡量和房價（結果）之間關係的空間計量研究這個裂縫必須被整合。本研究主要即在探討兩個課題，一是如何在不同層級都市公園鄰里效應的空間向度下建構適當地描述和估算有關房屋價格和寧適性資源之間關係的地理加權迴歸（GWR）模型；二是如何在不同層級都市公園鄰里效應的空間向度下發展有關福利變化的計量方法。
本研究從理論與實證整合驗證都市公園在空間面向的鄰里效應主要目的有三項：
一、建構地理加權迴歸模型運用體系架構，作為深入到鄰里環境寧適效益和房價之間關係的空間計量研究。探討都市公園空間面向的鄰里效應來衡量與評估都市公園寧適效益及影響。
二、實證地理加權迴歸模型於都市公園之鄰里關係。（運用地理加權迴歸模型看實證關係，即面積和距離的關係）。
三、驗證都市公園之鄰里效應結果。（建構一適用於不同層級都市公園可及性與面積的估計方法，主要在考量影響公園服務之關鍵影響因子，如面積、距離、影響範圍等。）
本研究以台北市大安區都市公園系統為實證範圍，2007年1 月至年底同一區房地產實際交易資料為樣本。
研究結果主要發現有：
一、比對全域的傳統特徵價格迴歸模型與空間特徵模型研究取向之局域的GWR模型，顯示GWR模型可提高迴歸之解釋能力，同時因為GWR模型中融入了地理座標，可在不同樣本點的各種係數估計間進行對比和檢查，易於發現問題，並有利輸出結合於GIS的空間分析，以更具體和直觀的特性來探討都市公園之鄰里效應所帶來的影響與效益。
二、都市公園鄰里效應的影響
（一）都市公園在「面積」方面所呈現的鄰里效應
樣本點300公尺鄰里內因大小層級組合不同之都市公園面積，會產生不同鄰里效應影響，樣本點300公尺半徑內公園面積越大，房地產價格增加率越大，都市公園面積與鄰里效應成正比關係。
（二）都市公園在「距離」方面所呈現的鄰里效應
樣本點因都市公園距離，會產生不同鄰里效應影響，都市公園距離與鄰里效應成反比關係，不同層級都市公園各在不同距離範圍內，離公園越遠，房地產價格遞減。
各章節摘要如下：
第一章、緒論：討論運用地理加權迴歸模型探討都市公園空間面向的鄰里效應來衡量都市公園寧適效益的主題，描述本研究的動機及目的，以界定研究範圍，進而提出研究假設，研擬本研究的內容、步驟、方法及流程。
第二章、相關文獻與理論回顧：基於都市公園之鄰里效應的課題的文獻回顧，發現特徵價格法在空間面向的侷限，探討空間特徵迴歸模型理論與方法的改良，和地理加權迴歸模型理論與實務的發展，以建立理論的研究架構。
第三章、都市公園之鄰里效應實證：提出都市公園之鄰里效應的實證計畫與研究設計，包括傳統線性迴歸與檢驗、空間自相關檢驗方法、GWR模型實證方法等內容。
第四章、實證結果分析與驗證；以台北市大安區都市公園系統為實證範圍探討，2007年1 月至年底的同一區的房地產實際交易資料為樣本。進行空間自相關檢驗結果分析、全域的傳統線性迴歸模型與局域的地理加權迴歸（GWR）模型之比較分析，探討都市公園在空間面向之鄰里效應所帶來的影響與效益。
第五章、結論與建議，提供適切的結論與建議，以供未來學術研究之參考。
An urban park can bring multiple benefits of, such as, recreation, hazard prevention, climate adjustment etc. It is difficult to measure the value for each benefit. However, as a kind of quasi-public goods, its amenity benefit will capitalize into the prices of the surrounding real properties and present the spatial dimensions of positive neighborhood effects, localized externalities and localized amenities benefits. By way of identifying the characteristics of the urban park, and incorporating them with other local neighborhood characteristics of a real property as explanatory variables, we can build a spatial hedonic price model for real properties and find out the hedonic prices of urban park characteristics. The subject of this study are to measure and evaluate the impact and benefit of the urban park amenity by using Geographically Weighted Regression (GWR) Model on the spatial dimensions of neighborhood effects of urban park.
Economists were documenting the relationship between the prices of hous¬ing units and quantities of environmental amenities, even before this rela¬tionship had been recognized as an application of the newly developed the¬ory of hedonic prices, (for example, Ridker(1967)was the first economist to attempt to use residential property value data as the basis for estimating the benefits of changes in measures of environmental quality such as air pollution. Hedonic price function is the most frequently used to construct regression models to estimate the housing price since Lancsater (1966) and Rosen (1974).The past 30 years have seen an explosion of both theoretical and empirical studies of the monetary values of nonmarket amenities and disamenities based on hedonic price theory. Now it is well accepted that housing price differentials reflect differences in the quanti¬ties of various characteristics of housing and that these differentials have sig¬nificance for applied welfare analysis. The hedonic approach（Hedonic Price Method） has become an established methodology in environmental economics (e.g. Palmquist 1991).
Since the end of 1980s, attention has turned to the spatial interdependence of property price. This means that the prices of nearby properties might help to explain the prices of any specific property of interest in the same local neighborhood (Palmquist 2006). Traditional statistics technology using hedonic price method to estimate the hedonic price of the house by way of homogeneity district and environment characteristics, called Global analysis, is not a spatial relation. However, when constructing the regression models based on the empirical observation to the housing prices in a same neighborhood or community, the basic assumption of identical and independent distribution of the housing price variation would very possibly be violated. The neighborhood share the same environmental facilities. In fact, housing prices in the same park and community facilities would not be independent, and yield less efficiency on the regression models.
Recently, empirical econometric work has started to take into account the potential bias and loss of efficiency that can result when spatial effects such as spatial autocorrelation and spatial heterogeneity are ignored in the estimation process. Spatial econometric methods (Anselin 1988), which incorporate the spatial dependence in cross-sectional data into model specification, estimation and testing have become fairly commonplace in empirical studies of housing and real estate, leading to so-called Spatial Hedonic Models(Anselin and Gallo 2006;Anselin 2008 ). GWR model is one of spatial regression models with local analysis method through the coordinate, bandwidth, and observations in proximity weighted using GIS to find out spatial variations by spatial statistic and analysis method and to present the spatial pattern. In the context of the valuation of environmental amenities, a spatial hedonic approach has been less common.
In the decade or so of renewed interest in neighborhood contexts and significant progress has been made conceptualizing the relationships between the urban environment and housing prices (outcome). Applied research on the link between the environment and housing prices remains limited by the way spatial concepts, such as “the neighborhood” (e.g. neighborhood effects, localized amenities benefit) or “the built environment” (e.g. urban park system, public facilities) are operationalized. In this study we argue that representations of these spatial concepts in statistical models should be based upon the neighborhood environment characteristics and urban structure difference.
We explore the practice of conducting the same analysis at multiple scales and find that using model fit to “discover” the spatial dimension is problematic. There is a gap between our understanding of how the neighborhood environment influences housing price (outcome) and statistic and spatial analysis method modeling techniques. For quantitative spatial inquiry into the relationship between measuring the neighborhood environment amenities benefits and housing price (outcome) this gap must be closed. The two issues that have been explored most intensively in this study are how to model the proper specification and estimation of the GWR model relating housing prices to amenities and the development of measures of welfare change under the spatial dimensions of neighborhood effects of deferent level urban park system.
The purposes of this study are as follows:
1. Construct the systematized framework of using Geographically Weighted Regression (GWR) Model as quantitative spatial inquiry into the relationship between measuring the neighborhood environment amenities benefits and housing price, on the spatial dimensions of neighborhood effects of urban park to measure and evaluate the impact and benefit of the urban park amenity.
2. Empirically explore Geographically Weighted Regression (GWR) Model on the relationship between urban park and neighborhood (using Geographically Weighted Regression (GWR) Model to research positive relation – the relationship between area and distance).
3.Verify the outcome of the neighborhood effects of urban park ( Set up a estimation method of accessibility and area for deferent level urban park system , consider the key influence factor of the urban park, for instance area, distance and impact range ,etc.)
We choose the urban park system of Da-An district in Taipei city as the study subject. The sample is the real property transactions in 2007.The empirical data is limited in the same area.
The major findings are as follows:
1.We compare with the different between global analysis of traditional hedonic model and local analysis of GWR model and found out the explanation power of GWR model is higher than traditional hedonic price method, each coefficient estimated value appeared to estimate, propose analyzed according to different positions where each sum of housing price data belong to and different peripheral terms, shown the space distribution figure of the analysis result with GIS according to the parameter of neighborhood effects of urban park impact on hosing price.
2. The impact of neighborhood effects of urban park
(1)Area
There is a positive correlation between urban park area and neighborhood effects. The combination of deferent level urban park area within a 300 meter radius around a property revealed that the size combination of deferent level urban park area had a positive amenity impact, the more area of urban park, the greater the change in housing prices.
(2)Distance
There is a negative correlation between the distance to urban park and neighborhood effects, the distance to urban park decreases housing prices far from urban park. The more distance to urban park, the greater the change in housing prices.
This thesis is divided into five chapters, and each chapter corresponds to an aspect of the research.
Chapter One discussed the subject of measuring the benefit of the urban park amenity by using GWR model on the spatial dimensions of neighborhood effects of urban park, described motives and purposes, and proposed hypotheses for this research. Finally, this chapter explained the research contexts, methods, procedures, and processes.
Chapter Two provided a literature review for the issues of neighborhood effects of urban park, found out the limit of hedonic price method, discussed the improvement of theory and method of spatial hedonic regression model and the development of theory and practice of GWR model, and establish a theoretical research framework.
Chapter Three proposed the experiment proposal and research design of neighborhood effects of urban park include the test and experiment method of traditional hedonic price method, spatial autocorrelation and GWR model.
Chapter Four analyze and verified the experiment outcome of the neighborhood effects of urban park, chosen the urban park system of Da-An district in Taipei city as the study subject, the real property transactions in 2007 as sample. Analyze THE the outcome of spatial autocorrelation, compare with the different between global analysis of traditional hedonic model and local analysis of GWR model ,and discussed the results of the impact and benefit of the urban park amenity on the spatial dimensions of neighborhood effects of urban park.
Chapter Five provide adequate conclusions and recommendations for future scholastic research reference.
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三、網路資料
1.Harris, R. and Orford, S. (2005). There’s Space in Them Lines: The Geography of Multilevel Modelling. http:// www.geodemographics.info，下載日期：2009.03.01。
2.Laissez-faire, http://en.wikipedia.org/wiki/Laissez-faire，下載日期：2009.03.01。
 
 
 
 
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