dc.contributor.advisor | 張金鶚<br>詹士樑 | zh_TW |
dc.contributor.author (Authors) | 紀凱婷 | zh_TW |
dc.contributor.author (Authors) | Chi, Kai Ting | en_US |
dc.creator (作者) | 紀凱婷 | zh_TW |
dc.creator (作者) | Chi, Kai Ting | en_US |
dc.date (日期) | 2007 | en_US |
dc.date.accessioned | 18-Sep-2009 16:20:42 (UTC+8) | - |
dc.date.available | 18-Sep-2009 16:20:42 (UTC+8) | - |
dc.date.issued (上傳時間) | 18-Sep-2009 16:20:42 (UTC+8) | - |
dc.identifier (Other Identifiers) | G0095257012 | en_US |
dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/35902 | - |
dc.description (描述) | 碩士 | zh_TW |
dc.description (描述) | 國立政治大學 | zh_TW |
dc.description (描述) | 地政研究所 | zh_TW |
dc.description (描述) | 95257012 | zh_TW |
dc.description (描述) | 96 | zh_TW |
dc.description.abstract (摘要) | 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。 | zh_TW |
dc.description.abstract (摘要) | 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. | en_US |
dc.description.tableofcontents | 第一章 緒論第一節 研究動機與目的…………………………………………1第二節 研究內容…………………………………………………3第三節 研究方法…………………………………………………5第四節 研究架構與流程…………………………………………7第二章 相關理論與文獻回顧第一節 產品訂價…………………………………………………9第二節 空間相依性文獻回顧……………………………………11第三節 空間分析方法在不動產的相關應用……………………16第三章 研究方法設計第一節 資料蒐集與內容…………….………………………… 18第二節 空間自我相關檢測………………………………………24第三節 空間迴歸模型建構………………………………………28第四節 模型變數選取……………………………………………31第四章 空間統計分析第一節 空間型態分析……………………………………………34第二節 空間自我相關分析………………………………………37第五章 時空相依迴歸模型第一節 模型設定…………………………………………………41第二節 模型校估與驗證…………………………………………46第六章 結論與建議第一節 結論………………………………………………………50第二節 建議………………………………………………………52參考文獻附錄…………………………………………………………………Ι【圖目錄】圖1-1台北市新推個案樣本空間分布圖………………………4圖3-1 台北市新推個案單價空間分布圖……………………20圖3-2 台北市新推個案戶數空間分布圖……………………21圖3-3 台北市新推個案總樓層高度空間分布圖……………22圖3-4 台北市新推個案平均主力坪數空間分布圖…………23圖4-1 新推個案空間分布型態………………………………35圖4-2 空間自我相關圖………………………………………37圖4-3 單價空間相關散佈圖…………………………………38圖4-4 平均主力坪數空間相關散佈圖………………………38圖 4-5 單價LISA 值分布圖……………………………… 39圖 4-6 平均主力坪數LISA 值分布圖…………………… 40圖5-1 實證模型設定示意圖…………………………………41【表目錄】表2-1 空間自我相關測試相關文獻表..........................13表2-2 空間計量經濟學相關文獻表............................15表3-1 變數基本敘述統計...................................19表3-2 LISA 值說明表.....................................27表3-3 變數說明表.........................................33表4-1 最近鄰距離分析結果..................................36表5-1 時空迴歸模型矩陣設定比較表...........................45表5-2 新推個案單價空間迴歸模型估計.........................47表5-3 新推個案單價時間與空間迴歸模型估計....................49 | zh_TW |
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dc.language.iso | en_US | - |
dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0095257012 | en_US |
dc.subject (關鍵詞) | 空間相依性 | zh_TW |
dc.subject (關鍵詞) | 空間迴歸模型 | zh_TW |
dc.subject (關鍵詞) | 產品訂價 | zh_TW |
dc.subject (關鍵詞) | spatial dependence | en_US |
dc.subject (關鍵詞) | spatial autocorrelation | en_US |
dc.subject (關鍵詞) | product pricing | en_US |
dc.title (題名) | 台北市新推個案訂價之時間與空間相依性分析 | zh_TW |
dc.title (題名) | Temporal and spatial dependence of new construction in Taipei city-a study of product pricing | en_US |
dc.type (資料類型) | thesis | en |
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