鑒於過去文獻可知，由於同一地區內的鄰近住宅擁有相同區位及市場特性，因而不動產價值存在高度相依性。空間相依性的產生往往是因為近鄰區域內的住宅有相似的建築結構（往往在同一個時間所興建），以及享有相同社會服務。由於建商在產品策略決策上會參考同一時間內鄰近競爭個案的產品策略，所以鄰近的新推個案會有相似的建築特徵以及相似的產品訂價。因此新推個案的訂價與鄰近的個案產生相關性，而新推個案訂價的相依性程度也會隨著時間距離遞減。 　　本文的目的在於將空間和時間的相依性最適地納入新推個案的訂價模型。採用582個台北市建商推案樣本進行實證。本研究分別以Moran’s I值和LISA值兩項指數來檢測空間自相關，並且比較傳統OLS迴歸模型、空間落遲模型，以及空間誤差模型三個模型的預測能力。此外，我們以不同的空間和時間的加權矩陣納入空間誤差模型中討論。 　　研究結果顯示，考量空間相依性之空間迴歸模型其解釋能力明顯優於一般傳統迴歸模型。而比起空間統計模型，時空迴歸模型更可以提高估計新推個案訂價的準確性。此外，研究結果亦顯示考慮時空交互影響的時空迴歸模型乃為新推個案訂價的最佳推估模式。 / It is well-known from the literature that the values of real estates are highly dependent on their locational and market characteristics of the buildings in adjacent areas. Spatial dependence mainly derives from factors that buildings at nearby properties have similar structural features (which were often developed at the same time) and often share the same social welfare. As developers in making decisions on product strategy will make reference to the strategy of nearby products of competitive cases which developed during the same time, therefore, within a certain period of time, the adjacent new construction will often have similar construction attributes as well as similar products pricing. Not only the pricing of a new construction is likely to be related to the pricing of adjacent new construction, but also the pricing of a new construction would be prone to autocorrelation decays in accordance with time distance. The aim of this paper is to analyze on how to take this temporal and spatial dependence into account in the pricing model of the new construction in the most appropriate way. We use a database of 582 asking prices of real estate developers in Taipei city. Two indices for measuring spatial autocorrelation are considered including (i) Moran’s I Index and (ii) LISA’s Index. We compared the predictive ability of three models including (i) OLS model, (ii) spatial lag model, and (iii) spatial error model. Moreover, we discussed the different temporal and spatial weight matrices in the spatial error model. According to our research results, we concluded that spatial statistical models obviously perform better than the traditional OLS model. Temporal and spatial statistical models would provide more accurate predictions on the pricing of a new construction than spatial statistical models do. The research result reveals that the best pricing model of the new construction is temporal and spatial statistical models which include temporal and spatial correlation.

在社會資源有限分配下，住宅整建已逐漸成為市容景觀改造方法之一，成為都市更新重要的一環，鑑於以往文獻可知，建物整建會增加該不動產的市場價值。僅有Yau et al.（2006）及Yau et al.（2008）藉由視覺的虛擬變數代表受影響範圍，研究建物整建後對鄰近不動產價格的影響，卻無法證實整建之價格外溢效果確實影響範圍。 本研究採用具空間變數的空間迴歸模型，預期能解決一般迴歸模型中空間自相關與估計偏誤的估計問題，並以台北市都市更新整建維護實施辦法通過的補助案例及營造股份有限公司所提供的整建案例，與房地產交易價格簡訊資料為對象進行實證。實證結果發現，台北市住宅整建後確實會產生價格的外溢效果，影響鄰近不動產，且不以視野可及之處為限，距離整建案例半徑200~500公尺內的交易樣本皆會受到影響，顯見加強策略性的地區整建，將能為都市再生帶來更顯著的影響。 / Housing refurbishment has become more important in congested living environment like Taipei. There are some studies focus on refurbishment will enhance the market value of the property. However, there have been a few empirical studies investigating the value enhanced by the refurbishment of neighborhood buildings. As a result, this study aims to empirically estimate the spillover effect of housing refurbishment in Taipei. We find that spatial hedonic model is more accuracy than traditional one, and that the refurbishment brought a significant increase in price of the buildings which located within 200~500 meter radius from the refurbished buildings. Obviously, to enhance house refurbishment is helpful to urban renewal.

都市更新是台北市近年提升老舊地區居住品質的土地開發方法，然過去文獻僅探討都市更新獎勵容積對更新單元的影響，未針對都市更新對鄰近地區房價影響進行實證研究，故引發本研究動機。此外，投入公共資源的都市更新政策，隨外部性提升後，對鄰近地區住宅價格是否產生正向價格外溢效果，進而造成都市房價高漲，本研究將運用空間迴歸分析進一步釐清。 本研究以台北市2004年至2009年之不動產交易案例為樣本，並以2006、2007年核定都更地區或單元時間點為預期房價起漲點，蒐集周圍地區不動產實際成交資料共8996筆，並運用特徵價格理論及空間迴歸分析都更實施前後，及不同規模大小對周圍地區價格影響因素與變化，最後以分量迴歸觀察都市更新對高、低房價的影響。實證結果發現都更實施後會造成周圍地區房價上漲，都更基地規模越大對房價有明顯提升的效果，且對於低價區的房價影響最為顯著。

大眾捷運系統帶來之快捷與便利，使其成為許多都會區民眾依賴之交通工具。捷運系統對鄰近不動產交通可及性提升，所伴隨之便利性將透過資本化效果反映於其價格之上，帶動周邊不動產價格上漲，過去不論國內外關於捷運對周邊房價影響之研究，實證結果亦多支持捷運對於房價有正面影響，且該影響隨著與捷運車站距離增加而遞減。捷運房價效果的區位差異與類型差異過去雖已有研究論及，但對捷運房價效果差異與其變化趨勢未能有明確細緻描述。此外，該等研究均忽略空間相關因素，將影響其估計結果。 　　本文使用國內某金融機構2007、2008年間台北都會區內台北捷運初期路網沿線車站周邊住宅為實證對象，應用空間迴歸模型檢視捷運系統對鄰近住宅價格之影響效果。實證結果顯示，就整體樣本而言捷運對房價確有正向影響但並不如想像之大，且該影響隨區位與類型之不同確有差異。 / Many previous studies have showed that metro system has a positive impact on the property values due to its accessibility benefits and the effect should decline as distance increases. While the pattern of the change and its difference between stations located in different locations has yet not been fully discussed, most of the studies failed to allow for spatial autocorrelation over space. This research uses spatial econometrics to estimate a residential housing model that considers spatial autocorrelation. The empirical results show the difference in the price effect of metro stations between urban and suburban areas does exist. The effect tends to get stronger in certain area, the closer the property lies within to the suburban area the greater the effect is. Also, we find price gaps between different metro station categories. Generally, underground stations and transfer stations have greater positive effect on residential property values.

過去一般認為，土地供給是固定不變，故價格彈性為零。這樣的思考方式背後隱含需求面才是不動產市場的主導力量，因此土地供給面往往被忽略。不動產僵局的議題近年來不斷出現在世界各國，臺灣社會也不例外。由此觀之，都市住宅供給過程中，似乎不完全由市場需求面主導，尤其都市進入成熟發展階段後，土地供給面的重要程度更應該被突顯。故本研究從供給角度出發，並認為土地面積和產權在都市住宅供給過程中，可能扮演關鍵的角色。透過本研究提出之二維向度分析，也確實發現開發難度和住宅區開發量間存在一定的負向關係，為後續迴歸分析的立論基礎。市場力量或政府力量是否能克服基地面積過小和產權複雜問題，亦是本研究關注之重點。 利用臺北市民國94年到103年的使用執照和拆除執照，以里為分析單元，計算臺北市各里住宅區的樓地板面積淨增加率，並觀察其在空間上之高低分布。影響樓地板面積淨增加率的因素除包含土地面積和產權因素，亦應包括總體因素，區位與政策因素。一般迴歸模型和空間迴歸模型之實證結果顯示：各里中住宅供給多寡主要受到總體因素影響。此外，劃定都市更新地區之政策亦具有吸引建築投資之效果。然而土地面積並非是影響住宅供給之關鍵因素。但本研究進一步發現，在相同條件之下，產權單純對於住宅開發供給多寡的差異，因臺北市區位而有不同，住宅開發供給量由多至少依序為早期發展區、郊區和市中心。且在早期發展地區，產權越複雜的里比起產權較單純的里，住宅供給確實有較少的趨勢，顯示土地產權仍然在臺北市部分地區，造成開發上的問題。 / It is understood that land supply is fixed and the price elasticity is zero, which implies that the side of demand is the dominant force in the real estate market. Because of this the supply side of land is often ignored. The issues of gridlock of real estate development are emerging in recent years worldwide, and Taiwan is no exception. In these instances the market does not seem entirely dominated by demand in the process of housing supply. Especially in cities which have entered a mature stage of development, the importance of land supply should be highlighted. This study is taking the perspective of supply and considering that lot size and land property key roles in the process of housing supply. Throughout this study, we proposed a two-dimensional analysis and indeed found that there was a negative relationship between development difficulty and the amount of residential development, which was the theoretical basis for the subsequent regression analysis. Whether market force or government force can overcome the problems of small lot size and complex land property was also a focus of attention in this study. We used Building Use Permit and Demolition Permit from the year2005 to2014 in Taipei and the analysis units were individual neighborhoods. We calculate net increasing rate of floor area in residential sections of Taipei and observe its distribution in space. Factors affecting net increasing rate of floor area in residential sections include lot size and ownership factors, as well as general factors, region and policy factors. According to ordinary least squares (OLS) and spatial regression, the empirical results show that housing supply in each neighborhood in Taipei is dominated by general factors. In addition, the policy of the delineated renewal areas has the effect of attracting construction investment. However, the lot size was not a key factor in the process of housing supply. Furthermore, the study found that under simple land property conditions, housing supply discrepancies over location in Taipei and supplied quantity in order was the old core, periphery and center. And in the old core, compared to the neighborhoods of simple land property, the housing supply in neighborhoods of complex land property has a decreasing trend which reveals that land property is still causing development problems in parts of Taipei.

生育率的降低是影響台灣地區近年來人口老化的顯著因素，因其變化幅度通常高於死亡率，對人口結構的影響較大。過去台灣地區生育率研究多為整體生育(如：總生育率、年齡別生育率)趨勢的模型，較少探討台灣各地區的特色。為能更深入瞭解台灣生育行為變化的特性，本文將生育率的研究層面由整體的資料，延伸至全台灣地區的各鄉鎮市區（不含離島地區有350個鄉鎮市區），希冀能更精確地找出與台灣地區生育率持續下降的相關因素。本文分為兩個部份，以鄉鎮市區的年齡別婦女生育率與年齡別有偶婦女生育率為研究對象，資料時間為1991、1992、2001、2002年：第一部份探討各鄉鎮市區的生育率數值間是否存在空間相關性，並進一步瞭解生育率較高（或較低）的地區是否有聚集的現象。第二部份則套用空間迴歸模型探討與生育率數值有關的因素（例如：人口密度、教育程度等），更精確且客觀地提供生育率未來趨勢的建議。 關鍵字：生育率、人口老化、空間統計、空間群聚、空間迴歸 / Both the fertility rates and mortality rates, especially the fertility rates, have been experiencing dramatic decreases in recent years, and the population aging thus has become one of the major concerns in Taiwan area. In order to identify the factors that are related to the decrease of fertility rates, unlike the previous works that deal with the aggregate national data, we will study the fertility pattern in township level. We will use the data of age-specific fertility rates and total fertility rates in 1991, 1992, 2001, and 2002 in 350 townships of Taiwan area. This study will be separated into two parts. First, we shall explore if there is spatial correlation among 350 townships of Taiwan area and detect if there are spatial clusters for higher fertility townships. The second part of this project will be focused on the spatial regression model. We will use this model to determine the factors that are highly correlated to the dropping of fertility rates. Key Words: Fertility Rates, Aging Population, Spatial Statistics, Spatial Clustering, Spatial Regression

近年臺北市政府試圖藉由興建品質良好的公共住宅，解決住宅價格高漲影響人民居住的問題，然附近居民往往認為公共住宅會造成周圍住宅生活環境品質低落及房價下跌，反對其於住家鄰近興建。過去國內缺乏以實證方式計算公共住宅對周圍住宅價格之影響，亦尚未針對新推出的公營出租住宅個案深入分析；而國外相關研究雖有利用量化實證公共住宅與周圍房價關係，然多針對個別公共住宅社區為研究對象，對不同類型公共住宅及其對不同高低房價住宅之影響與差異，缺乏更全面的探討分析，且亦未釐清住宅價格的空間自相關特性及公共住宅設立的不同階段等，對周圍房價影響效果的差異。 本文應用特徵價格理論傳統迴歸模型、空間迴歸模型及分量迴歸模型，以2012年7月至2015年9月之臺北市不動產實價登錄交易資料為對象，研究整建住宅、出售國宅、出租國宅、公營出租住宅等四類不同時期公共住宅，於100~300公尺不同影響範圍下，分別對周圍住宅價格的影響效果。另外並選取興隆公共住宅作為個案研究對象，以臺北市文山區不動產實價登錄交易資料為對象，應用差異中之差異法結合空間迴歸模型，分析興隆公共住宅的興建完工與住戶入住對於周圍住宅價格之外溢效果。實證結果顯示，附近有早期興建之整建住宅及出租國宅者，其住宅總價皆呈現顯著下跌現象，分別下跌約1.7%至8.9%及1.5%至7.7%；附近有出售國宅之住宅總價漲跌情形不顯著；而近期興建之公營出租住宅則造成周圍住宅價格顯著上漲約1.7%至7.7%；又前述影響程度皆隨影響範圍擴大而隨之減輕。進一步分析不同影響範圍下對周圍高低房價住宅的影響，公營出租住宅對周圍低價住宅正向提升效果為6.2%至7.1%，皆大於高價住宅之無顯著影響至3.2%。而興隆公共住宅的興建完工確實能使周圍住宅價格較外圍地區多提升約6.5%至15.8%，惟住戶入住興隆公共住宅則未具顯著正向的價格外溢效果。由新興辦的公營出租住宅對周圍房價造成正面影響的實證結果，應可釐清公共住宅外部性之正向效果，有助後續公共住宅的興建。 / In recent years, government has tried to build the public housing with high quality to solve the living problems caused by the soaring of the house price. However, residents beside the public housing often regard them as Nimbys that will detrimentally affect property values and oppose public housing to be built nearby. There were short of empirical studies that focus on the effects of public housing on nearby property, as well as the case study of social housing newly built in Taiwan. Besides, the empirical studies in foreign only select a specific public housing as their subject, which few of them analyze different effects caused by different types of public housing, ignore different effects on nearby property with different values, and have not clarify whether the spatial autocorrelation of property values as well as the construction and operation of the social housing leads to different results. This study analyzes the effect of social housing, resettled tenement, public housing for rent and for sale on nearby property values in different ranges separately by using hedonic price theory OLS, spatial and quantile regression as model, and selecting the sale price of real estate in Taipei City from July 2012 to September 2015 as sample. Besides, Xing-Long Social housing and sale prices of real estate in Wenshan district of Taipei City are also selected for case study applying Difference in Difference method with spatial regression, in order to analyze the nearby property values changes after the construction and the move in of the residents of Xing-Long social housing. The result shows that although resettled tenement and public housing for rent detrimentally affect the property values by 1.7% to 8.9% and 1.5% to 7.7% separately, public housing for sale does not affect the property values significantly, and social housing positively affects the property values by 1.7% to 7.7% on the contrary. In addition, these effects decline with distance from public housing. With regard to the impact on high and low priced property in different ranges, social housing has positive effect on low-priced property by 6.2% to 7.1% and no significant effect to 3.2% on high-priced property. The construction of Xing-Long social housing has positive spillover effect by 6.5% to 15.8%, however, the move in of the residents does not. Empirical results show that social housing newly built are able to enhance the property values nearby, which is contributed to the follow-up construction of the public housing.