本研究採用平滑移轉模型將人民幣匯率波動率作為門檻變數，消費者物價指數、工業生產指數、利率作為輔助變數，觀察其對上海房地產價格影響的程度。本研究各變數選取時間為2013年7月至2016年12月。實證結果如下：
    當人民幣匯率波動率在門檻值附近時，消費者物價指數與房價呈現同向變動，匯率波動率和利率呈現反向變動。即消費者物價指數上升，匯率波動率與利率下降，會導致房價上升；相反，消費者物價指數下降，匯率波動率與利率上升，會導致房價下降；而工業生產指數對房價的影響是不顯著的。當人民幣匯率波動率在門檻值之上下時，變數工業生產指數依然不顯著，消費者物價指數和利率從顯著轉變為不顯著，只有匯率波動率與房價呈現同向變動，從反向顯著轉變為正向顯著，即匯率波動率越大，房價上升，匯率波動率越小，房價下降。

In this study, the Smooth Transition Regression is used, with the volatility of the RMB exchange rate as the threshold variable, and the consumer price index, the industrial production index and the interest rate as auxiliary variables, to observe the RMB exchange rate changes’ impact on the real estate prices in Shanghai. In this study, the variables were quoted from July 2013 to December 2016. The empirical results are as follows:
When the RMB exchange rate is in the vicinity of the threshold, the consumer price index and house prices tend to move in the same direction, while the exchange rate volatility and interest rates display reverse changes. That is, the rising consumer price index, and the declining exchange rate volatility and interest rates lead to rising house prices; conversely, the declining consumer price index, and the rising exchange rate volatility and interest rates, will lead to lower prices; yet the industrial production index does no significant impact on house prices. When the volatility of the RMB exchange rate is in the vicinity of the threshold, the variable industrial production index is still not significant, the consumer price index and the interest rate change from significant to insignificant, only the exchange rate volatility and house prices tend to move in the same direction, which changes from reverse-significant to positive-significant, that is, the greater the exchange rate volatility, the higher the house prices; the smaller the exchange rate volatility, the lower house prices.

目錄
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 4
第三節 研究流程與架構 5
第二章 文獻探討 7
第一節 人民幣匯率機制 7
第二節 人民幣匯率波動與房地產價格 8
第三節 中國房地產投資市場 10
第三章 研究方法 13
第一節 單根檢定 13
第二節 平滑移轉模型 17
第四章 實證結果分析 23
第一節 資料來源與變數說明 23
第二節 敘述統計 25
第三節 單根檢定 26
第四節 線性檢定 29
第五節 轉換函數檢定 30
第六節 模型參數之估計檢定 31
第五章 結論與建議 35
第一節 研究結論 35
第二節 建議 36
參考文獻 37
中文文獻 37
英文文獻 38
網路資料 41

圖目錄
圖1-3-1 研究流程與架構 6
圖3-2-1 邏輯型函數 20
圖3-2-2 指數型函數 21

表目錄
表4-1-1 變數代號與資料來源 25
表4-2-1 敘述統計 26
表4-3-1 變數之ADF、PP檢定結果 27
表4-3-2 變數之NP、KPSS檢定結果 28
表4-4-1 LM-TYPE線性檢定 29
表4-5-1 轉換函數檢定 30
表4-6-1 ESTAR模型參數預估 33
表4-6-2 解釋變數對上海房地產價格指數之影響 33

中文文獻
1.王運成，劉莉，（2011），「房地產投資風險分析」，現代商貿工業，第18期，頁8-12
2.胡小雲，（2009），人民幣匯率波動對國內房地產價格影響實證研究，武漢科技大學
3.侯長江，（2013），「房地產價格影響因素研究」，工商管理博士論文
4.黃盛，（2006），「人民幣匯率的影響因素及變化趨勢研究」,特區經濟,第11期,頁12-14
5.趙恩博，（2009），上海房地產發展研究-借鑒國際經驗探求上海房地產業發展之路，復旦大學產業經濟博士論文
6.盧麒元，（2012），「爭議聯匯—聯匯之殤年」，環球財金，第7期，頁40—47

英文文獻
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15.Wang.Lulu and Wang.zhaohui, (2017), “An Empirical Study on the Effect of RMB Exchange Rate on Real Estate Price”, Management & Engineering, Brighton East 26, pp. 36-41
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網路資料
1. MBA MBA：wiki.mbalib.com 
2. 維基百科： wikipedia.org
3. 中國家外匯管理局： www.safe.gov.cn 
4. 中國家統計局： www.stats.gov.cn 
5. 中國上海統計局： www.stats-sh.gov.cn 
6. 中國人民銀行 ：www.pbc.gov.cn