金融機構為了滿足新版巴塞爾協定必須每年對不動產抵押擔保品進行重新鑑價的規定，採用房價指數來進行資產重新估計。然而，觀察現今發佈的國泰與信義房價指數，發現兩指數走勢及變動幅度上，皆存在相當大的分歧。 因此，本研究採用西元2005年至2007年間台北市十二行政區房屋之實際成交價格為研究範圍，建立特徵價格模型，並結合市場比較法中期日修正概念，利用房價指數進行調整，再依Hit Rate 及MAPE準則評估整體表現。為了避免樣本誤差對於實證結果的干擾，透過隨機抽樣三十次進行重複實驗，測試模型穩定性及估計精確度，最後，採用兩成對樣本T檢定，檢定房價指數是否有助於不動產標的重新估計，並分析兩房價指數何者較能確切的反應當前市價。 實證結果發現:(1)使用房價指數調整之估值正負誤差在10%及20%以內的命中率以及MAPE皆有顯著改善，這說明現今發佈之房價指數具備反映市場實際價值的能力，仍有繼續編制及發佈的必要。(2)經由比較並分析兩房價指數結果可知，以國泰房價指數調整之估值在10%及20%以內的命中率，以及MAPE指標上，皆通過顯著性檢定。而使用信義房價指數調整之估值表現僅在10%及20%以內的命中率通過成對T檢定，故可知國泰房價指數較能充分地扮演著揭露不動產市場訊息的角色。

預售屋價格長久受到台灣產業界與學術界密切關注，然而預售屋價格資訊卻相對成屋缺乏，本研究希望釐清預售屋的特性並建立預售屋大量估價模型，提供預售屋價格資訊。預售屋具期貨交易性質，其價格形成受周遭成屋價格影響，其基差(預售屋與成屋價格差)關係顯得格外重要；另一方面，預售屋為完工前銷售之產品，有品質不易掌握之特性，消費者傾向透過商譽來評斷產品優劣，商譽因而相對凸顯，加上預售屋具有以個案方式為中心之定價模式，相對成屋其個案特徵顯得更加強烈，基差與建商商譽成為預售屋估價上必要考量的兩個重心。 本文以特徵價格方式納入基差與商譽因素進行實證分析與建立模型，研究期間為台北市2012年第3季至2015年第4季，在資料處理上透過座標整合內政部實價登錄資料以及國泰建設市調資料，解決實價登錄資料中缺乏個案屬性的去識別化問題，將預售屋「個案」特徵納入「個戶」估計中，突破過往預售屋研究限縮於個案的限制。實證結果顯示，台北市預售屋單價平均比周圍成屋多出35.5%的水準、而屬於上市上櫃建商的預售產品則相較非上市櫃產品平均高出5.7%的價格；模型估計表現上，本研究實證模型解釋力達到65.1%，模型之絕對平均誤差為10.56%、±10%及±20%的命中率分別為57.86%、88.25%，達到大量估價模型要求水準，值得參考使用。

隨著電腦及統計模型的發展、原本用於稅賦評估工具的大量估價逐漸受到重視。美國更利用完善的國家層級資料，將大量估價改良為自動估價模型（Automated Valuation Model, AVM）。由於估值估算快速、成本低廉及龐大的資料庫等優點，受到美國私部門的歡迎。另一方面，不動產市場仍有存在著個別估價的客觀性的質疑，而估價行為學也證實了個別估價有偏離估價程序的可能。市場上存在著兩者的支持者，但由於兩者特性迥然不同，甚難比較。 本研究以一致的資料庫及衡量標準，將交易價格做為市場價值表徵，以估值的準確性作為衡量兩者的準則，找出兩者的特性及適用範圍。實證結果顯示當勘估標的數量達到一定程度，可忽略不動產的異質性時，個別估價與大量估價準確性並沒有顯著的差異。但個別估價準確性的分配較大量估價集中、且偏誤程度也較低。個別估價較不受不動產特性的影響，適用的範圍較廣；而大量估價較易受到不動產特性影響，適用範圍視資料庫的內容而定。另一方面，個別估價的估價認知具有時間性，表示不動產估價師需更新估價認知，以保持高度的估值準確性。此說明了國內不動產市場的變化快速及國內不動產估價師的專業能力。 / With the development of computer and statistical model, the mass appraisal as assessment tool has been paid attention gradually. Americans utilize the national data to develop Automated Valuation Models (AVMs).For its advantages of faster valuation , less cost and huge database, mass appraisal is used as assessment but also appraisal tool . On the other hand, the real estate market stills have query with objectivity of individual appraisers. The study of appraisers’ behavior suggest that the possibility of deviate from standard procedure of appraising. In a matter of fact, the real state market is filled with supporters of appraisers and mass appraisals. Because of these different characteristic, it’s difficult to compare with. This research will trade selling-prices to seek for the market value form with unanimous database and criterion, regard accuracy of valuation as and weigh the criterion of the two, and find out the characteristic of the two and scope of application .Although the result showed that the accuracy is no difference between appraiser and mass appraisal significantly when the amount of real estates is large enough to neglect heterogeneity. Compare with mass appraisal, the distribution of appraiser’s accuracy is more centralized and the standard deviation is smaller. The accuracy of appraiser is steady, and the scope of application is relatively wide. But the accuracy of mass appraisal is affected by the characteristic of real estate, and the scope of application depends on content of the database.On the other hand, the appraisal cognition has timeliness, it shows appraiser needs to upgrade the appraise cognition and the market condition , in order to keep the valuation accuracy of the height. This has stated the fast-change market and domestic the professional ability of appraisers.

特徵價格模型是傳統常被使用於不動產大量估價的模型，由於模型將造成所有價位的不動產其特徵都具有同樣的邊際價格而無法解釋現實不動產特徵的各種可能狀況，故引發本研究利用分量迴歸建立大量估價模型之動機。研究利用台灣不動產成交行情公報的資料進行台北市大廈的實證分析，針對特徵價格法的延伸與估價準確度做檢視。嘗試應用分量迴歸建立大量估價模型，討論住宅特徵對於價格的邊際影響力於不同價位的住宅是否存在差異，並討論分量迴歸模型的估價精確度。研究採用交互驗證法與重複實驗30次討論模型的估計效果，並利用平均絕對百分比誤差（MAPE）以及命中率（Hit Rate）做為模型預測優劣程度的衡量標準，以討論分量迴歸模型是否可以較最小平方特徵價格模型有更為準確的估計表現。實證首先探討價格分量之下各住宅屬性對於價格的影響狀況，得到大部分住宅特徵對於價格的邊際影響力的確會因住宅價位的不同而有所差異。在估價準確度的部份，經測試得到利用分量迴歸建立大量估價模型的估價效果達研究的預期目標，且其估計表現優於最小平方特徵價格模型。 / 藉由分量迴歸模型，得到隨著住宅價位的增加，坪數與屋齡對於價格的影響力並非呈現一致的趨勢；坪數輪廓與屋齡輪廓出現轉折也為變數增加二次項變數的原因得到實證依據。重複實驗30次的整體表現，分量迴歸模型的MAPE較最小平方迴歸模型低了1.687％；誤差落在正負10％的Hit Rate較最小平方迴歸模型高了3.81％；誤差落在正負20％的Hit Rate較最小平方迴歸模型高了5.14％。30次的實證為分量迴歸模型的估價表現更優於最小平方迴歸模型得到較具說服力的結果。 / Hedonic pricing models are traditionally used for real estate automated valuation models. Because the conditional mean calculated by OLS does not give a complete description of the relationship between dependent variable and independent variables, which leads to the motive of this study. This study inspects the extension of hedonic pricing models and appraisal accuracy, and we attempt to apply quantile regression to real estate automated valuation models and discuss the difference of the marginal contribution in each individual characteristic under different price level. Our study adopts cross validation and repeats empirical process for 30 times, and we use MAPE and hit rate to evaluate accuracy and argue if quantile regression models have better estimation. The empirical results show that the marginal contribution of housing area and age changes with price level; the turning points of area curve and age curve show empirical evidence for including square variables. The entirety performance of repeated experiments points out that the MAPE of quantile regression model is 1.687% lower than OLS model; as error ranged between 10% to -10%, the hit rate of quantile regression model is 3.81% higher than OLS model; as error ranged between 20% to -20%, the hit rate of quantile regression model is 5.14% higher than OLS model. The 30 times experiment of quantile regression models shows a much more persuasive result than OLS models.

現行不動產大量估價主要以特徵價格模型為基礎進行價格之預估，而常以鄰里、轄區或次市場虛擬變數或是與特定公共設施之距離作為控制區位價值之變數。惟僅以次市場變數之係數或是距離特定公共設施距離之係數衡量樣本之區位價值，則因係數之僵化性弱化或低估區位對不動產價格之影響，導致大量估價模型之精度難以突破。 本研究以區位價值波面之概念建立條件式殘差擬合變數，從空間角度評估各樣本之區位價值並以量化數值呈現各樣本區位價值之高低，在細膩處理區位價值下模型之預估能力相對提升。實證結果顯示，整體模型之絕對誤差平均值為10.1%，而10%、20%誤差命中率達62.9%、87.9%，相對優於過去研究之模型預估能力；另外，經過區域侷限性測驗發現，條件式殘差擬合變數修正模型不受次市場之侷限，對於是否劃分模型次市場已不影響模型之預估能力，且經由實證發現，當實價登錄樣本愈趨豐富時，模型之預估能力將更加提升，值得作為後續建立大量估價模型之參考。 / Hedonic model is the most commonly-used tool for real estate mass appraisal, and neighborhoods, districts or sub-market dummies or the distance from the specific public facilities are the common variables used to control the value of location in the model. However, controlling the location value by these ways leads to the coefficient rigidities, making it possible to underestimate the value of the location. This research sets up the conditional-selected residual fitting variable by the concept of location value response surface, and estimates the location value from the spatial perspective. The result shows that the MAPE of the model is 10.1%, and the hit-rate of 10% and 20% come to 62.9% and 87.9%, having significant improvement compared with the past studies. Besides, by the confinement test of sub-market, it has been proved that the CRF modified model successfully gets rid of confinement from the sub-market, and whether dividing sub-markets or not no longer affects the prediction capability of the model. Another test giving us new images that, when the train data gets richer as time goes, the prediction capability of the model gets higher as well.

從1960年代開始，公部門基於稅務處理需求，使得電腦輔助大量估價（Computer Assisted Mass Assessment，CAMA）成為輔助的工具，大幅提升了估價的效率。在1990年代，金融機構因不動產證券化的發展及不良資產估價等業務，而衍生了對大量不動產進行估價的需求，同時在電腦與統計模型的進步之下，自動估價模型（Automated Valuation Models，AVM）應然而生，並被廣泛應用在金融市場。由此可知因為不動產經濟活動的熱絡發展，大量估價的需求日益增加，其具備的客觀與效率等優點更彰顯其重要性。 雖然大量估價的需求日益增加，然而過去對於估價準確性相關研究，主要著重在估價理論與技術層面、估價行為對估價結果的影響、探討個別估價和大量估價的估值比較，而較少單獨探究影響大量估價準確性的因素。由於特徵價格理論隱含不動產高度異質的特性，不動產價格受到總體經濟、政策、住宅屬性、公共設施、區位等因素影響，然而前述因素是否會對估價準確性造成影響?造成影響的因素為何?為本文所欲探討之問題。 本文在實證部分分成兩階段，首先以特徵價格理論為基礎，利用實價登錄資料建立大量估價模型，以MAPE與Hit Rate來衡量估價準確性，結果指出MAPE達到14.19%，而正負誤差10%的命中率為47.18%、正負誤差20%的命中率為74.75%，跟過往研究所建立的大量估價模型相比具有相當的水準，顯示出官方性質的交易資料具有一定的可信度。在建置大量估價模型後，本文以模型價格及成交價格間的比值作為劃分估價準確程度的依據，以多項羅吉特模型進行實證分析，結果指出住宅大樓、捷運站周遭住宅、大坪數住宅估價結果容易呈現低估情形；而新市區中心估價結果容易呈現高估的情形；另外比較特別的是舊市區中心、北郊區估價結果較容易呈現高估及低估，換言之在這兩個區域估價容易得到不準確的結果。 / Since 1960s, public sector began to take advantage of computer assisted mass assessment(CAMA) based on taxation services and greatly improved the efficiency of appraisal. In 1990s, financial institutions due to the development of securitization of real estate and non-performing asset valuation and other services, generating the demand of mass appraisal. Simultaneously, due to the development of computer and statistical models gradually progress, bring in automated valuation models(AVM) in the financial markets. Hence, with the real estate economic activities gradually booming, the increasing demand for mass appraisal, which has the objective of efficiency and other advantages will be more to highlight its importance. While the increasing demand for mass appraisal, but past studies about the accuracy of appraisal, mainly focused on the theoretical and technical aspects, the impact of behavior on the valuation results, and to explore appraisers and mass appraisal of the valuation. However, past studies less focused on a large number of factors affect the accuracy of the appraisal. Since the hedonic price theory implies highly heterogeneous characteristics of real estate, real estate prices affected by factors of macroeconomic, tax policy, housing properties, public facilities, location and so on, but whether the aforementioned factors will affect the valuation accuracy?Is this research seeking to explore the issue. In this paper, the empirical section is divided into two stages, first with the hedonic price theory based on the use actual price registration to establish the mass appraisal models, and base on MAPE and Hit Rate to measure the accuracy of the appraisal, the results indicate MAPE reached 14.19%, while the margin of error of 10% hit rate of 47.18%, 20% hit rate is 74.75%. Compared with the past studies, this model has established a great performance. This research proved that the official data with reliability. After establishing the mass appraisal models, the research use model prices and the transaction price ratio as the basis for division between the accuracy of the appraisal and use multinomial logistic model to conduct empirical analysis. The results indicated that the residential building, housing around MRT stations, the big area housing was prone to result underestimate valuations, the new urban center appraisal results likely to show overvalued valuations. On the other hand, old city center and the northern suburbs results presented overestimate and underestimate valuations simultaneously, in other words, that is usually get inaccurate results in these two regions.

長期以來，不動產估價相關研究皆著重在估價理論與技術的改進，以使最後估值能更為精確。然而實際上，估價人員的行為才是影響價格評定的本質因素；尤其國內、外對於市場比較法的相關研究，皆發現估價人員有偏離理論規範的現象。故本文第一部份是分析估價人員系統行為偏誤問題；第二部分探討特徵價格模型的偏誤，並應用分量迴歸改進不同高低價格的估價模型準確度；第三部分比較估價師個別估價與大量估價模型之偏誤與差異；為提升客觀估價方法，第四部分探討以估價師估值樣本產生最可能價格與機率的方式。本研究藉由估價師估價行為與大量估價模型不同面向的研究，重新檢視市場比較法的各種偏誤現象。 一、市場比較法估價之系統行為偏誤 市場比較法是估價人員最常使用的方法，但在估價過程中主觀判斷部分相對較多也最易引起爭議。過去市場比較法研究著重在估價理論與技術改進，以減少主觀判斷造成的隨機偏誤，然而，研究指出行為偏誤造成的系統偏誤，其持續性的偏誤對於估價偏誤有重要影響。過去探討估價行為的研究，受限於資料樣本取得，幾乎都是以問卷或實驗得到結果，而非實證結果。本文則是以實際估價報告書進行實證分析，以鄒檢定(Chow Test)及似無相關檢定(Seemingly Unrelated Regression)，發現勘估標的估值與比較標的市場成交值兩模型係數有顯著差異，表示估價人員估值模型起始點高於市場成交值模型，估價人員對於使用類型有高估現象，對於面積估計有低估現象，支持估價人員有系統行為偏誤。此外，也發現評估不同市場時，行為偏誤程度亦不同，估價人員於評估拍賣價格時，因估價經驗與比較案例較少，較傾向參考比較案例，行為偏誤亦較小，僅面積係數有差異；但於評估正常市場價格時，估價行為偏誤較大，區位、使用類型及面積係數皆有差異。 二、不同高低價格不動產估價模型之偏誤改進－分量迴歸模型之應用 隨著國內不動產市場M型化推案趨勢，非典型住宅（如：高總價豪宅和低總價小套房）類型逐漸增多，對於此類型產品的估價精準度也需要提升。從過去研究發現，最小平方迴歸估計忽略各特徵屬性對價格條件分配的差異。本研究乃以分量迴歸方法建立住宅大量估價模型，藉以瞭解住宅特徵對於不同價格分量的差異，實證結果發現以最小平方迴歸模型估計相較於分量迴歸，對於一樓、頂樓、車位、區位等變數有高估或低估的情形。比較估值模型預測精確度，本文透過30次重複實驗，發現分量迴歸對於兩側尾端樣本有較佳的預測能力。從實證方法而言，本文改進以最小平方迴歸模型對兩尾端價格高估或低估問題；就實務應用方面，隨著不動產產品差異度增加，以及新版巴塞爾協定（Basel Ⅱ）實施對不動產價值更新的需求，分量迴歸模型可提升兩尾端估計精確度，並提供住宅大量估價系統另一種資產重估方法。 三、大量估價與個別估價之差異分析 不動產估價研究可分為個別估價與大量估價兩類，過去有關個別估價研究多為估價行為或估價方法改進，而大量估價研究則多是運用數量方法建立模型，由於兩者建構方式不同，欲同時進行兩者實證比較並不容易。本文藉由相同勘估標的，取得估價師個別估價資料，與資料庫建立的自動估價系統，進行案例選取、權重調整及最後估值三階段的比較分析。經本文差異比較發現，前二個階段的比較結果，皆是自動估價系統優於個別估價，從估價行為觀點，顯示自動估價系統具有較客觀且符合估價理論程序優點。然而第三階段的估值比較，發現自動估價系統的表現並不如預期，此結果與過去研究結論不同，分析兩者差異值大的案例，發現資料庫樣本較少地區以及非典型住宅類型（面積過大或過小），是造成個別估價估值與自動估價系統估值差異大的原因，顯示自動估價系統有其適用限制，未來若增加資料庫樣本或次市場模型，兩者估值差異將可獲得改善。 四、不動產估值認知與估值機率 本章以估價師估值資料為樣本，藉由蒙地卡羅模擬估值機率模型，其模擬結果可客觀估計最可能價格（the most probable price）與機率。由於資料樣本來自於專業估價師的判斷，估值分配代表的是估價師所估計的可能估值結果；相較於過去僅以單一估值決定資產價值，藉由多位專業估價師所判斷結果而建立的估值區間與最可能價格及機率，應該是更具客觀性且接近市場價值，而且估值機率的呈現將有助於估價報告書使用者評估存在於資產價值的上方（upside risk）及下方風險（downside risk）。 / In the real estate appraisal research, appraisers and mass appraisal are the two methods most often used in the sales comparison approach. Past studies focused on appraisers behavior and mass appraisal model, lack of compared the difference by appraisers for the same objects as well as mass. The first essay reviews the behavior literature regarding real estate appraisers and summarizes the two hypotheses for departure from normative models. The study is based on appraisers’ reports analyzes for the appraisal valuation and the market transaction by hedonic price models. Among the 112 appraisal reports of the transaction data of 230 comparables and the valuations of 224 subjects, the results reveal the effect of the variables on the appraisal valuation are not consistent with those of the market transaction. In addition, comparing the appraisers’ behavior on the general market with the auction market, the result found is the differences between the valuation models and the transaction models are less than the models on the auction market. The empirical evidences support the two hypotheses and can be explained plausibly by the appraisers’ behavioral contention. The second essay analize the current domestic trend of residential types, it is easy to find that high-priced dwelling units and low-priced dwelling units keep gaining popularity. Thus, the estimation of these two types of residences should be more precise. Since ordinary least square regression can not signify the variation caused by different quantile functions of a conditional distribution, this study estimates the housing price by quantile regression. We compare the models by using ordinary least square regression and quantile regression. The empirical results show that the distributions of some variables, such as first floor, top floor, parking lot, location, are different between two models. These are easily to be underestimated or overestimated when ordinary least square regression is applied. Based on thirty repeated experiments using random sampling, the results of hit rate and mean absolute percentage error show that quantile regression estimates more accurately on two-tailed distribution. For mass appraisal application, a quantile regression advances the estimate on two-tailed price and provides a new method on assets reevaluation of banks.

現行公告土地現值的評估，係採用人工的傳統方法，估價結果誤差甚大且過於主觀，無法達到大量估價客觀、快速、精確之目標。本文首先利用土地經濟理論的分析，探討土地市場價值、交易價格、評估價值之間的關係，釐清常見的混淆概念。並藉由估價比率研究，討論公告現值與市價差距的檢定模型，針對台南市的實際資料進行統計檢定，結果發現平均估價比率落於46.74﹪~48.52﹪之區間，並存在輕微的垂直不公平。 為改進現行公告現值不夠準確之缺失，本研究基於都市經濟理論與估價先驗訊息之基礎，利用特徵價格法與可加性模型建立大量估價模式。實證結果發現，影響台南市地價之因素，以區位、臨街關係、路寬、使用分區最為重要。在部份年度中，亦證實存在基地面積規模不經濟（plattage）現象。 傳統特徵價格法必須預設函數型態，若函數設定錯誤則將使參數估計產生偏誤。可加性模型結合無母數迴歸與母數迴歸之優點，不須預設函數型態、估計結果易於解釋且維持母數迴歸之收斂速度。其可經由修勻法配適出更客觀的函數關係，無論在樣本內與樣本外之估計均較特徵價格法為佳。 研究結果發現，本文所提出的二種估價模式確可達到快速精確的目標，使估價比率接近１，比目前評估效率提高一倍；在公平性方面雖無改善，但亦無嚴重之垂直不公平。其中可加性模型又較特徵價格法為佳，在電腦技術快速進步的今天，應用至大量估價的可行性大為提高，值得後續進一步深入研究。 / The present Announced Land Current Value （ALCV）was evaluated by traditional appraisal method that may result in large errors. Comparing to mass assessment approaches, it is hard to be objective, quick and precise. This research begins with the analysis based on land economic theory to discuss the relation among the market value, sale price and assessed value of land in order to clarify some confusing concepts. Through assessment-sale price ratio study, we analyze the difference between ALCV and sale price, and then use the actual data of Tainan City for empirical study. The results show that the average a-s ratio falls between 46.74%~48.52% with slight vertical inequity. To improve the lack of preciseness and objectivity of the present ALCV, this research uses hedonic price theory and Generalized Additive Model（GAM）based on urban economic theory and appraisal priori information. The results show that location, relations with adjacent streets, road width and zoning are the most influencing factors of land price in Tainan City. During some years, the phenomenon of plattage effect also exits. The function form must be set beforehand in the traditional hedonic pricing, meanwhile parameters bias will occur if the pre-determined function form were wrong. GAM has the advantages of nonparametric regression and parametric regression. The function form needs not to be pre-determined, the empirical results are easy to interpret, and the speed of variable convergence can be maintained. More precise functional relations can also be smoothed by GAM. It is superior to the traditional hedonic price in the sample and out of the sample prediction alike. The results of empirical study show that both of two models can reach the goal of rapidity and preciseness and make the a-s ratio toward 1. As to the equity, although they are not improved very much, the models don't bring serious vertical inequity. However, GAM is better than hedonic pricing when compared to each other. Due to the great progress of computer technology, the application of GAM to mass assessment can be increased greatly and is worthy continuing further study.

市場比較法估價過程需要經比較、分析及調整三階段，而估價師於個別估價應用中因缺乏標準化依據，造成估價過程常被質疑過於主觀且偏重經驗法則，導致估價結果產生因人而異現象。基於此本研究乃建立大量估價模型，運用估價師進行市場比較法行為邏輯，在選取比較案例階段採用明科斯基距離概念，並結合特徵價格理論，建立大量樣本的客觀標準化估價模型。藉由此模型分析，估價師不需要主觀預測，可改善過去估價結果不一致情形，並達到大量估價目的。 透過隨機抽樣的重覆實驗，實證結果發現，以模型的平均百分比預測誤差與命中率比較，整體而言未劃分次市場估價模型皆較劃分次市場準確，且其穩定度亦較高，而劃分次市場較不準確的原因，在於舊市區的表現不穩定，與市郊區的估值表現較差所致。經本研究結果，不論劃分次市場與否，標準化大量估價模型大致上均達到研究預設水準，然劃分次市場模型雖有時較準確但未優於未分區模型甚多，顯示適當劃分次市場可提高準確度，但資料太少時，劃分次市場可能產生統計偏誤問題。 / The process of the market comparative approach includes three stages：comparing ,analyzing and adjusting. Real estate appraisers lack the standardized basis in the individual appraisal application, so they are often challenged by subjectivity and stressing experience, which leads to the phenomenon that appraisal results are always different from person to person. Based on this, our research establishes the automated valuation methods. By applying the appraisers’ behavior in market comparative approach, we use minkowski metric in selecting comparative subject, and associate with hedonic price theory to establish objective standardized real estate appraisal model. By using this model, the appraisers can avoid subjective forecasting, reduce inconsistency, and therefore achieve the goal of mass appraisal. Through the repetition experiment of random sampling, we compare MAPE and Hit-rate between models. The result shows that non-delimited markets are more accurate and stable than delimited markets. The reason for this is the instability caused by older district of the city and bad performance in the suburban area. After these findings, no matter delimited market or not, the standardized mass appraisal model achieved the research standard we had set in advance. Sometimes the model of delimited market is more accurate, though not by a significant amount, it shows that higher accuracy can be expected through adequate market segmentation, but will lead to bias when lack of datum.

我國公部門以課徵土地稅、發放土地徵收補償為目的而進行土地大量估價，並以區段價法與路線價法為主要估價方法。由於此二估價方法之評估基礎為平均區段地價，故是否能準確劃分地價區段乃至關重要。然而，地價調查估計規則中有關地價區段之劃分規定，並無具體規範劃分準則與方式，導致地價人員僅能透過參考各項可得之圖表資料，並根據自身認知與前輩經驗，將地價相近、地段相連、情況相同或相似之土地劃為同一區段。因此，地價區段劃分之公平、客觀、準確性往往遭受民眾質疑。 劃分地價區段之目的係為掌握地區特性，故其實屬劃分同質區之概念。惟地區特性乃難以定義或量化之區域因素的空間聚集特性，致使地價人員難以掌握具體劃分準則，並準確劃分地價區段。而過去相關研究指出難以定義或量化之空間因素存於特徵價格模型的殘差之中，遂有分析殘差之空間特性以劃分同質區者。但是，各種劃分方式皆侷限於已知樣本所在位置的空間關係，導致可能出現無法就整體地區劃分同質區，或出現預測樣本不屬於任何同質區的情況。 由於克利金法可依據樣本的空間變異結構特性推估未知空間位置的觀察值，因此本研究以區域化變數理論為基礎，應用克利金法結合地理資訊系統之空間分析功能，進而依殘差之空間特性劃分空間效果同質區。研究結果顯示該同質區可合理呈現空間效果之同質性，應用於大量估價的準確性佳，且不會扭曲地價高低層次。因此，應用克利金法劃分地價區段確實為合理、準確且可行之方式。 / Public assessors evaluate official land value for taxing and compensating by land value district approach and street value approach. Since the basis of these two approaches is land value district, whether public assessors could define it accurately or not is an important issue. However, there are no specific defining criterions in Regulations on Land Value Assessment; public assessors could only refer to concerning information, especially their own subjectivity and experience of senior assessors, to define district in terms of “close land value, connected relation and similar circumstances of lands”. Accordingly, district that defined by public assessors not only the fairness and objectivity, but also the accuracy are quite doubtful. The main purpose of defining land value district is capturing local characteristics; therefore, it’s similar to the task of defining homogeneous area. Nevertheless, local characteristics are agglomerations of spatial effect, which are difficult to define or quantity. Due to the fact that public assessors are unable to get specific defining principles, they cannot define land value district accurately. A few researches indicate that spatial effect is in the residuals of hedonic pricing model, thus, some researches defining homogeneous area according to the spatial distribution of residuals. However, the defining approaches of these researches are all restricted to spatial location of known samples. Hence, it’s possible to fail to segregate different homogeneous area, or fail to take unknown samples into consideration. For the reason that kriging estimation can predict unknown spatial location’s value in basis of spatial variation structure characteristics, this research apply kriging estimation and GIS to define homogeneous area based on Theory of Regionalized Variables. The research concludes that homogeneous area which is defined by kriging can capture homogeneity of spatial effect. Besides, the prediction accuracy is quite well by adding variables of homogeneous area to hedonic pricing model. On the other hand, predicted land values still remain the exact relation between each other. Therefore, applying kriging estimation to define land value district is a reasonable, accurate and feasible method.