本研究目的為觀察國內都會區的房價,包括台北市、新北市、台中市和高雄市,並進一步探討總體經濟的變動對於國內都會區房價之影響。 在回顧國內外相關文獻之後,本研究使用時間序列方法作為實證分析,研究涵蓋之時間將從民國九十年至民國九十九年的季資料,研究變數為以信義房價指數以及四個都會區房價,採用總體經濟四個影響房價之主要變數為實質國民生產毛額年增率、通貨膨脹率、五大行庫房屋貸款利率和台灣加權股價指數。 本研究使用EViews和Gretl統計軟體,透過ADF單根檢定方式,來分析確認時間序列資料之特性。接著以向量自我回歸模型進行Granger 因果關係檢定、衝擊反映分析、預測誤差變易分解和共整合檢定得到以下重要結論:(1)通貨膨脹率影響台北市和新北市的房價是顯著的。(2)房貸利率對於四個都會區房價皆有顯著影響。(3)長期下,都會區房價和總體經濟變數存在穩定均衡。
The study analyzes weather changes in the macro-economic variables affect housing prices of domestic metropolitan areas, including Taipei City, the New Taipei City, Taichung City, and Kaohsiung City. After reviewing the relevant domestic and foreign literature, I decide to use the time series methods as empirical research method. The quarterly data covers research time periods from 2001 to 2010;the variables include lutheran housing price index in terms of four housing prices of domestic metropolitan areas, real GNP annual growth rate, inflation rate, mortgage rates and the weighted stock price index This study applies statistical software Eviews and Gretl to conduct empirical analysis. The study also applies ADF unit root test to analyze the characteristics of time series data. The VAR model is used to proceed the Granger Causality Test, Impulse Response Function Analysis, Forecast Error Variance Decomposition and Co-Integration Tests. Research findings are 1.inflation rates affect the housing prices in Taipei City and New Taipei City which are statistically significant 2.Mortgage rates affect significantly the housing prices of four metropolitan areas. 3.In the long-term period, among the metropolitan housing prices and the macro-economic factors, the variables exist a stable equilibrium relationship.
為了持續優化網站功能與使用者體驗,本網站將Cookies分析技術用於網站營運、分析和個人化服務之目的。
若您繼續瀏覽本網站,即表示您同意本網站使用Cookies。