本研究以投資人對房價的預期效果加入蛛網理論補捉房價的調整，說明住宅需求曲線斜率大小會受到此預期的影響而變動，因而影響房價之均衡。我們並進一步以此理論說明，在實務上觀察到房價有時穩定，有時暴漲或暴跌，可能統是因為投資人預期轉變所引起的，因此在估計長時間房價時，需考量其並脊趨於均衡及不均衡之區間，如此提供了本研究使用存在狀態轉變之誤差修正模型(regime- switching error-correction model)的合理性。本研究之實證結果，確實發現住宅價格趨向均衡的調整速度存在結構性改變的情況，續以狀態轉變之誤差修正模型補捉其於不同狀態之機率，我們觀察到台北住宅價格偏離均衡的時間。最後本研究以估計投資人之預期調整係數，發現此估計而得之係數較高時，住宅價格較易維持均衡的狀態。因此本文理論推論與實證研究可以得到：當預期調整係數較大，需求曲線也會較平緩，所以住宅價格會趨向某一均衡值收斂，住宅市場較穩定。

This study analyzes house price fluctuations by incorporating investor anticipation based on cobweb theory. We theoretically explain that investor anticipation affects housing demand and further affects the house price equilibrium state. The booms and slumps of house prices could be caused by changes of investor anticipation. Therefore it is important to consider changes of these two regimes when estimating house prices and this is the reason we use the regime-switching error-correction model in house price estimation. In the empirical test, structural change indeed exists when the house price is adjusting to an equilibrium level. Our switching error-correction model estimates the probabilities of two regimes for house prices and observes the timings of house price deviation from equilibrium. Finally, we estimate the expected coefficient of adjustment and find that when the coefficient is relatively large, house prices are more stable. From our theory inference and empirical results, we conclude that when the expected coefficient of adjustment is larger, the demand slope will be smoother. Consequently, house prices tend to converge to a steady state level so that the housing market is more stable.