Appraisers receive feedback from a variety of sources such as other appraisers, clients and the real estate market. Previous studies find client feedback to introduce an upward bias into commercial and residential appraisal judgments. Hansz and Diaz (2001) find that the provision of transaction price (market) feedback for a previously valued property biases commercial appraisers upwardly in subsequent valuations. The authors provide market optimism, client feedback and a reduced conservatism bias as explanations for their findings. However, previous client and market feedback studies were conducted in upward-trending or booming real estate markets. The identified upward bias in valuation judgments may have been the result of positive real estate market conditions. This study investigates the impact of transaction price feedback on residential appraisal judgment in a changed appraisal task environment, characterized by a depressed housing market, market pessimism, conservative lenders and a changed residential appraisal industry. As Hansz and Diaz (2001) find an upward appraisal bias in an upward-trending market, I expect market feedback to introduce a downward bias into residential appraisal judgments in a depressed market. Compared to a “no feedback” control group, residential appraisers receiving the feedback that their previous value estimates were too high, compared to the realized transaction price, are expected to make significantly lower subsequent value judgments for an unrelated property. The “too low” feedback is not expected to have an impact on subsequent value judgments. I test the hypotheses with a controlled experiment using a pre-posttest design. The experimental design has one factor (transaction price feedback) fixed at three different levels (“too low”, “too high”, “no feedback”). A posttest-only validity control group is added to test for a potential testing bias in the pre-posttest design. This study uses residential expert appraisers, defined as active Oregon State certified residential appraisers, from the Portland metropolitan statistical area (MSA) as subjects. Experimental subjects are randomly selected from a list of all certified residential appraisers in the Portland MSA. Experimental subjects are randomly assigned to the control and treatment groups (10 subjects per group; N=40). Subjects in the treatment groups and pre-posttest “no feedback” control group are asked to value a lot of vacant residential land in the geographically unfamiliar Roswell, Georgia. After they provide their value estimates for this first valuation case, subjects in the treatment groups are given a note from a seller’s broker stating the transaction price for the previously valued property. Subjects in the “too high” feedback group receive a transaction price that is 15% below their estimates and subjects in the “too low” feedback group receive a transaction price that is 15% above their value estimates. The control group receives no feedback. All treatment and control groups are then given a second (unrelated) valuation case of vacant residential land in Newnan, Georgia and asked for their value estimate. The experiment is concluded with an exit questionnaire containing demographic and professional questions as well as manipulation checks. The experimental data are analyzed using the parametric independent samples t-test. The assumptions of normality and equal variances are not violated by the dataset. A one-way ANOVA and the non-parametric Mann-Whitney U test are used as robustness checks. All statistical tests conclude that neither the mean of the “too high” feedback group nor the mean of the “too low” feedback group are statistically different at the 5% level from the mean of the “no feedback” control group. Thus, no evidence is found that transaction price feedback biases residential appraisal judgments in a depressed market. The insignificant results are further analyzed to assess whether they are due to a non-reception of the treatment by subjects, low statistical power or a non-existing relationship: The explanation that subjects did not read the treatment note can be excluded. A power analysis reveals low statistical power and very small effect sizes for both treatments. An alternative explanation for the insignificant results is the absence of the hypothesized relationship. The main client group of experimental subjects is appraisal management companies, which due to legislation passed after 2007, work with appraisers on behalf of lenders. As a consequence, residential appraisers do not receive direct client feedback anymore (compared to Hansz and Diaz, 2001) and may not respond subconsciously to the “too high” feedback.

不動產估價一般需採比較法、收益法及成本法等三種方法查估。不動產估價最終估值決定須進行協調(reconciliation)，協調的目的係為完成關聯(correlation)之步驟，就各種方法資料之質量及優缺點進行分析。為使不動產估價對於比較法三件買賣實例，及三種方法估值採賦予權重之決定方式提供量化解釋，本文分別建立比較法內部及三種方法外部權重模型。內部權重部分，買賣實例（市場）比較法一般需蒐集數個比較標的，經調整後之試算價格決定比較價格。國外以數學計算式計算實例權重雖已相當普遍，但目前尚無應用特徵效用模式，解讀實例權重形成與比較標的內部條件之關聯。本文以2007年及2008年地價基準地6,435筆買賣實例建構特徵權重模型，發現比較法買賣實例權重受價格型態、交易日期接近性、是否屬近鄰地區、實例差異百分率絕對值加總、實例比較項目修正數、其他兩個實例相對值等自變數影響顯著。 欲探討成本法估值是否與成交價存在差異，以作為外部權重設定之基礎，本文以北部地區986筆交易案例，由估價人員逐筆以成本法估計成本價格，俾與成交價格比較。發現成本價格有高估之系統性偏誤現象，分量迴歸(quantile regression)分析實證認為成本法並未因屋齡較新之建物有較高精度。另發現房地交易價格愈高、建物單價愈高、總樓層數愈高、移轉樓層愈低、建物面積愈小、建築工期愈長及利潤率愈小者；估值差異愈小。 外部權重分為三部分，首先將估價過程中之諸項因子，以分析階層程序法(AHP)專家問卷，彙整各種方法權重因子；其次，基於最適加權平均模式在於使三種方法估值總誤差最小之觀點，經由數學計算方程式建構2,150筆基準地三種方法標準差及相關係數模型以計算權重。第三、為了瞭解比較估值、收益估值與土地開發分析估值之關聯，本文將2,150筆三種估價方式權重建立聯立模型，以三階段最小平方法(3SLS)進行估計。實證模型系統加權解釋力甚高，且三種方式權重之自變數多符合預期並顯著，顯見三種方式之關聯性。 最後，不動產估價仍需考慮一般因素，如金融海嘯對全球金融及房地產市場，其影響力無遠弗屆，最終估值之決定即需考慮市場景氣對最終估值之影響。為探討對於(不)景氣時是否(低)高估？影響(低)高估與否之影響因素為何？本文以2002年至2004年國內某金融機構對房屋貸款20,532件之估值，以二項式邏輯特(Binary Logit)模型分析。實證結果發現於不景氣時期抵押貸款低估機率提高，景氣時期則無高估現象。綜上，本文以權重模式、估值差異及市場景氣影響探討不動產估價最終估值之形成，於權重模型建構及預測上，非如以往文獻僅對估值預測，而係就權重預測。於加權平均應用上，外生變數之迴歸係數可作為權重設定之參考。本文直接探討最終估值形成之權重核心，冀使估價之客觀性及科學化程度提高。 / Real estate appraisal comprises the sales comparison, income, and cost approaches to value in general. The purpose of reconciliation is to complete the procedure of correlation and analyze the qualitative and quantitative strengths and weaknesses of different approach data. In order to assist quantifiable explanation when weighted average for three comparables in the Sales comparison approach and indicated values from three approaches are applied, this paper constructs internal and external weight models respectively. For internal weight model, this paper examines the correlation between weight and internal attributes of 6,345 sales comparables from land value benchmark in 2007 and 2008 adopting the hedonic price model. The outcome shows the price type, the proximity of transaction date, inside the neighborhood area or not, total gross adjustment as %, numbers of adjustments and the attributes of other two comparables considered in one appraisal are significant on the weight of comparables. To explore whether the cost approach causes bias or not, and make it reference for establishment of external weight model, this paper compares the cost value, appraised by valuers applying the cost approach individually, from a sample of 986 transactions of properties sold in 2007 and 2008 in northern Taiwan, to sale price and finds the cost value is higher than sale price on average. It proves that the reliability of the cost approach is comparatively questionable due to its systematic bias of overestimation. With quantile regression, the outcome shows that the precision of cost value won’t increase for newer buildings. In addition, this paper finds the more the total property sales amount, the higher the unit construction fee, the higher building, the lower story, the smaller area, the longer construction years of properties, and the smaller profit rate; the smaller the bias. There are three parts for external weights. First, AHP expert questionare is adopted to combine weight factor from each approach. Secondly, based on the logic that the best way to assign weights on three appraisal approaches is to get the minimum total error, this paper calculates the standard error and correlation indicators from three approaches using 2,150 land value benchmarks. Thirdly, in order to realize the weights correlation among the sales comparison value, income capitalization value and land development analysis value, this paper builds a model based on the three-stage least squares method simultaneous equation (3SLS). The empirical result shows system weighted R2 is high and most attributes on the weights of three indication of value are significant and are consistent with expected sign, which means the model fit is good and how the weights of three methods correlate. Finally, general factor also needs to be considered in real estate appraisal. For instance, financial tsunami exerts powerful influence on financial and real estate market globally, which makes it necessary to consider real estate cylce influence when seeking the final value. In order to discuss whether the appraisal value of mortgage is smaller (greater) or not when the market is bearish (bullish) and the corresponding factors, this paper collects 20,532 mortgage appraisal value from one bank from 2002 to 2004. With Binary Logit model, this paper finds the probability of lower appraisal is greater in bear market. The outcome confirms two hypotheses of this paper. However, overestimation is not confirmed in bull market. To sum up, this thesis researches the formation of final value of real estate appraisal by discussing weight model, appraisal bias and influence of real estate cycle. For weight model construction and forecasting, this dissertation forecasts weight directly, instead of value like most literature focus. The regression coefficients estimated from factors during the procedure of each approach could serve for reference if weighted average is applied reconciling the value conclusion by valuers. By delving into the core issue of value formation, it hopes to elevate the degree the objectivity and science of real estate appraisal.