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  1. NTU Theses and Dissertations Repository
  2. 社會科學院
  3. 經濟學系
Please use this identifier to cite or link to this item: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21729
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dc.contributor.advisor林建甫
dc.contributor.authorShuai-Chi Laien
dc.contributor.author賴帥錡zh_TW
dc.date.accessioned2021-06-08T03:44:17Z-
dc.date.copyright2019-03-26
dc.date.issued2019
dc.date.submitted2019-03-25
dc.identifier.citation中文文獻
林建甫(2006),台灣總體經濟金融模型之建立,《中央銀行季刊》,28(1),5-41。
陳旭昇(2009),時間序列分析-總體經濟與財務金融之應用,修訂版,東華書局。
英文文獻
Beltratti, A., and Morana, C. (2010), International house prices and macroeconomic fluctuations, Journal of Housing Economics, 34, 533-545.
Baffoe-Bonnie, J., The dynamic impact of macroeconomic aggregates on housing price and stock of house:A National and Regional Analysis, Journal of Real Eatate and Economics, 17(2), pp.179-197.
Chen, P. F., Chien, M. S., and Lee, C. C. (2011), Dynamic Modeling of Regional House Price Diffusion in Taiwan, Journal of Housing Economics, 20(4), 315-332.
Gupta, R., and Kabundi, K. (2010), The effect of monetary policy on house price inflation A factor augmented vector autoregression (FAVAR) approach, Journal of Economic Studies, 37(6), 616-626.
Isaac F. M., Allen P. M., and Mary B. S. (2009), The Economic Theory of Housing Demand: A Critical Review, Journal of Real Estate Research, 6(3), 381-393.
John, B. B. (1998), The Dynamic Impact of Macroeconomic Aggregates on Housing Prices and Stock of Houses: A National and Regional Analysis, Journal of Real Estate Finance and Economics, 17(2), pp.179-197.
Jorge, B. F., and Kwaku K. O. (2011), A Time Series Analysis of U.K. Construction and Real Estate Indices, The Journal of Real Estate Finance and Economics, 1-27.
Leung, C. (2004), Macroeconomics and housing: a review of the literature, Journal of Housing Economics, 13(4), 249-267.
Liu, H., and Shen, Y. (2005), Housing Prices and General Economic Conditions: An Analysis of Chinese New Dwelling Market, Journal of Housing Economics, 10(3), 334-343.
Mikhed, V., and Zemcik, P. (2009), Testing for bubbles in housing markets: A panel date approach, Journal of Real Estate Finance and Economics, 38(4), 366-386.
Smith, L.B., Rosen, K.T., and Fallis, G. (1988), Recent developments in Economic Models of Housing Markets, Journal of Economic Literature, 26, pp. 29-64.
Shi, S., Young, M., and Hargreaves, B. (2009), The ripple effect of local house price movements in New Zealand, Journal of Property Research, 26(3), 1-24.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21729-
dc.description.abstract本研究主要探討總體經濟變數對台灣房地產價格之關聯性,其中台灣房地產價格包含台灣、台北市、新北市、桃園市、新竹市、台中市及高雄市,使用的研究變數有台灣及六大都會區信義房價指數、五大行庫房屋貸款利率、國內生產毛額、消費者物價指數及貨幣供給增長率,選用之研究變數均為季資料,共68筆季資料,資料期間為2001年Q1至2017年Q4。
本研究透過單根檢定及共整合檢定分析,發現台灣及六大都會區房價指數、五大行庫房屋貸款利率、國內生產毛額、消費者物價指數及貨幣供給增長率變數間存在長期穩定之均衡關係,接著由向量誤差修正模型顯示,台北市、新北市及台灣房價指數受前一期本身房價有顯著的正向影響,新竹市及高雄市房價指數受前一期本身房價則有顯著的負向影響,表示各都會區之房價指數短期受到外在因素衝擊而偏離長期均衡時,會由本身的均衡誤差修正項與前一期本身的房價調整回長期均衡狀態。房屋貸款利率對台北市房價有顯著負向影響、高雄市為顯著正向影響,另國內生產毛額對新竹市房價有顯著負向影響,則桃園市與台中市房價指數與四項總體經濟變數影響均不顯著。最後使用因果關係檢定,分析研究房價指數與總體經濟變數間之因果關係,發現不同的經濟變數之變動,確實與各都市房地產價格波動呈現領先、落後或雙向回饋等不同對應關係,檢定結果顯示各變數間互動緊密,可作為推測未來趨勢之參考。因此,銀行可針對房地產價格波動做預測,作為控管授信風險之指標,管控銀行對不動產的授信額度,降低承做該產業之授信風險,穩定銀行健全發展。
zh_TW
dc.description.abstractThis study is base in Taiwan house prices index from Sinyi Realty Inc, retrieving 68 samples from 2001Q1 to 2017Q4. The research discusses how macro variables influence the real estate market and the connections and causal relations among them. Chosen variables are the Taiwan house prices index, Taipei City house prices index, New Taipei City house prices index, Taoyuan City house prices index, Hsinchu City house prices index, Taichung City house prices index, Kaohsiung City house prices index, loan rate, gross domestic product growth rate, consumer price index and M2 balance.
This study was analyzed by unit root test and cointegration test, empirical results show that there is a long-term equilibrium relationship among Taiwan house prices index, six metropolitan areas house prices index, loan rate, gross domestic product growth rate, consumer price index and M2 balance.
Then, the vector error correction model shows that the house price index of Taiwan and Taipei City have a significant positive impact on the house price of the previous period. the house price index of New Taipei City, Hsinchu City and Kaohsiung City have a significant negative impact on the price of the previous period. The impact indicates that the house price index of each metropolitan area is affected by external factors in the short-term and deviates from the long-term equilibrium. It will be adjusted back to the long-term equilibrium state by its own equilibrium error correction term and the previous period's own house price. The home loan interest rate has a significant negative impact on housing prices in Taipei, and Kaohsiung City has a significant positive impact. The gross domestic product has a significant negative impact on housing prices in Hsinchu City. The price index of Taoyuan City and Taichung City and the impact of four general economic variables are not significant. Finally, using the Granger causality test check, the causal relationship between house price index and economic variables is analyzed and different populations are found. The changes in economic variables do indeed have different correspondences with the trend of real estate prices in various cities, such as leading, backward or two-way feedback.
The results of the verification show that the variables interact closely and can be used as a reference for speculating future trends. Therefore, the bank can make predictions on real estate price fluctuations, as an indicator to manage the credit risks, manage the bank's credit line for real estate, reduce the credit risk of undertaking the industry, and stabilize the sound development of the bank.
en
dc.description.provenanceMade available in DSpace on 2021-06-08T03:44:17Z (GMT). No. of bitstreams: 1
ntu-108-P05323008-1.pdf: 3667635 bytes, checksum: fc8d199d188e6ccecc197a2573f3ca13 (MD5)
Previous issue date: 2019
en
dc.description.tableofcontents口試委員會審定書 II
誌謝 III
中文摘要 IV
ABSTRACT V
第一章 緒論 1
1.1 研究動機 1
1.2 研究目的 2
1.3 研究架構 3
第二章 文獻回顧 4
2.1 我國都會區房地產分析 4
第三章 實證模型研究方法 6
3.1 實證研究方法 7
3.2 單根檢定(UNIT ROOT TEST) 7
3.3 共整合檢定(COINTEGRATION TEST) 10
3.4 向量誤差修正模型(VECM) 11
3.5 GRANGER因果關係分析模型 12
第四章 實證結果分析 15
4.1 資料來源與定義變數 15
4.2 敘述統計分析 18
4.3 單根檢定結果 22
4.4 共整合檢定結果 27
4.5 向量誤差修正模型檢定結果 32
4.6 GRANGER因果關係檢定結果 46
第五章 結論與建議 48
5.1 研究結論 48
5.2 檢討與建議 50
參考文獻 51
dc.language.isozh-TW
dc.title台灣房價變動與總體經濟變數關係之實證研究zh_TW
dc.titleThe Relationship of Housing Price Index and Macroeconomic Index in Taiwanen
dc.typeThesis
dc.date.schoolyear107-2
dc.description.degree碩士
dc.contributor.oralexamcommittee翁永和,姚睿,張焯然
dc.subject.keyword房地產價格指數,貸款利率,總體經濟變數,單根檢定,共整合檢定,向量誤差修正模型,因果關係檢定,zh_TW
dc.subject.keywordhouse price index,loan rate,economic variable,unit root test,cointegration test,Vertor Error Correction Model,Granger causality test,en
dc.relation.page52
dc.identifier.doi10.6342/NTU201900672
dc.rights.note未授權
dc.date.accepted2019-03-26
dc.contributor.author-college社會科學院zh_TW
dc.contributor.author-dept經濟學研究所zh_TW
Appears in Collections:經濟學系

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