在過去房地產的相關研究文獻中，有著許多指出房屋價格波動與總體經濟情況有 著關聯性和因果關係，以及利用房屋特徵值對房屋物件進行大量估價的研究，本 篇論文的目的，是期望尋找是否可以選取總體經濟變數，對在配對方法下所預估 出來的房屋時間效果，進行建模預測，在模型中，我們假設影響被解釋變數影響 解釋變數的係數，並非恆常不變，而是會隨著時間而有所不同，於是在模型中加 入變數自我迴歸的假設，做為模擬未來期係數的主要方法。此篇論文所採用的研 究資料，是利用 2012 年上線的實價登錄系統之交易資料，研究對象包含：台北 市、新北市、桃園市、新竹市、高雄市，在經過配對方法計算出平均時間效果率 後，將此時間效果視為房屋價格的平均成長率作為被解釋變數和預測目標。

Many thesis point out that the growth rate of housing price have cause effect relationship with the conditions of economics. Following the effort done by Shi et al (2012) figuring out the cause effect relationship between the housing price and economics variables exist in the main cities in Taiwan, in this thesis we try to put several economics variables in model from Hui et al (2010) and add autocorrelation characteristic to simulating the growth rate of housing price. We use the transition data of actual price registration which established since August 2012 as research materials. Taipei City, New Taipei City, Taoyuan City, Hsinchu City and Kaohsiung City are the cities involved in this thesis. By using matching approach, we withdraw the time effect from transition records. We build a forecasting model with the usage multi-external variables as external variables and the assumptions of autocorrelation. Key word: Actual Price Registration, Matching Approach, Multiple Regression, Forecasting Model, Autocorrelation.

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