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Please use this identifier to cite or link to this item: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66967
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dc.contributor.advisor陳旭昇(Shiu-Sheng Chen)
dc.contributor.authorChen-Yeh Linen
dc.contributor.author林成燁zh_TW
dc.date.accessioned2021-06-17T01:15:58Z-
dc.date.available2027-08-08
dc.date.copyright2017-08-24
dc.date.issued2017
dc.date.submitted2017-08-14
dc.identifier.citation1.林金龍、吳中書、陳仕偉 (1999),「金融資產與儲蓄-台灣的實證研究」,經濟論文,第27卷第1期,中研院經研所,頁81-102.
2. 張金鶚、賴碧瑩 (1990),房地產景氣指標之建立與分析,《國立政治大學學報》, 61,333-411。
3. 林秋瑾、王健安、張金鶚 (1996),房地產景氣與總體經濟景氣於時間上領先、同時、落後關係之探討,《國科會人文及社會科學彙刊》,7,35-56。
4.Catte, P., N. Girouard, R. Price, and C. Andre (2004), “Housing Markets, Wealth, and the Business Cycle,” OECD Economics Department Working Papers, No. 394 , Paris: OECD, June.
5.Ewing, B. T. and J. E. Payne, (2005), “The Response of Real Estate Investment Trust Returns to Macroeconomic Shocks,” Journal of Business Research, 58, 293-300.
6.Ewing, B. T., (2001), “Monetary Policy and Stock Returns,” Bulletin of Economic Research, 53, 73-79.
7.Grebler, L. and F. G. Mittelbach, (1979), The Inflation of Housing Prices, Its Extent, Causes, and Consequences. Lexington Books. Toronto: D.C. Heath and Company.
8.Harris, J. C., (1989), “The Effect of Real Rates of Interest on Housing Prices,”Journal of Real Estate Finance and Economics, 2, 47-60.
9.Jensen, G. R., J. M. Mercer, and R. T. Johnson, (1996), “Business Conditions, Monetary Policy, and Expected Security Returns,” Journal of Financial Economics, 40, 213-237.
10.Kent, R. J., (1984), “Housing Tenure Choice: Evidence from Time Series,” Journal of Urban Economics, 15, 195-209.
11.Kau, J. B. and D. C. Keenan, (1981), “On the Theory of Interest Rates, Consumer Durables, and the Demand for Housing,” Journal of Urban Economics,10,183-200.
12.Ling, D. C. and A. Naranjo, (1997), “Economic Risk Factors and Commercial Real Estate Returns,” The Journal of Real Estate Finance and Economics, 14, 283-307.
13.Leung, C. (2004), Macroeconomics and housing: a review of the literature, Journal of Housing Economics, 13(4), pp.249-267.
14.McCue, T. E. and J. L. Kling, (1994), “Real Estate Returns and the Macroeconomy: Some Empirical Evidence from Real Estate Investment Trust Data, 1972-1991,” Journal of Real Estate Research, 9, 277-287.
15.Muth, R. F., and A. C. Goodman. (1989). The Economics of Housing Markets. Chur: Hardwood Academic Publishers.
16.Peiser, R. B. and L. B. Smith, (1985), “Home Ownership Returns, Tenure Choice and Inflation,” Journal of the American Real Estate and Urban Economics Association, 13, 343-360.
17.Reichert, A. K., (1990), “The Impact of Interest Rates, Income, and Employment upon Regional Housing Prices,” Journal of Real Estate Finance and Economics, 3, 373-391.
18. Thorbecke, W., (1997), “On Stock Market Returns and Monetary Policy,” Journal of Finance, 52, 635-654.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66967-
dc.description.abstract本研究應用多種時間序列計量方法來探討消費者物價指數、失業率、美國聯邦基金利率及工業生產指數等總體經濟變數與美國標普/席勒10大城市房價指數之間的互動關聯性。研究期間1987年1月 至 2015年 2月,共 323 筆月資料觀察值。
實證結果顯示,房價與工業生產指數有相互Granger的因果關係,房價在1%顯著水準下Granger影響(領先)失業率,顯示房地產市場的景氣對失業率及工業生產指數有影響。另外房價與聯邦基金利率、物價沒有統計上顯著的Granger因果關係,根據文獻上定義,如果房價Granger影響(領先)物價,代表房價具有抗通膨的效果,本研究則顯示房價不具有抗通膨的效果。
房價的衝擊對於工業生產指數有長期正向影響,對於失業率有長期負向的衝擊反應,另外房價如果受自身衝擊影響,將產生正向的影響,且影響時間很長,影響程度為所有變數最大,投資人可考慮參考過去房價走勢來做為投資房地產指標。從預測誤差變異數分解結果來看,美國標普/席勒10大城市房價指數對於工業生產指數及失業率其解釋比例高於其他變數,施政者或許可考量房價對於景氣及失業率的關聯,有利於總體經濟相關政策的執行。
zh_TW
dc.description.abstractAbstract
In this study it attempts to apply multiple time-series econometrics approach to explore the relative correlation of the American Case-Shiller macroeconomics 10-city composite index with macroeconomics in terms of variables such as the American national home price index、the commodity price index、the unemployment rate、the U.S.A. Federal Funds Rate and the Industrial Production Index. The observance data ranging from January 1987 to February 2015,during the study period from January 1987 to February 2015,a total of 323 months of data observation.
The empirical results show that the American Case-Shille 10-city home prices have Granger causality interaction on industrial production index,and at 1% of the significant level Granger impact (leading) unemployment rate,showing the real estate market have effect to unemployment rate. There is no statistically significant Granger causality between house prices and the federal funds rate,which is based on the literature, if the house price Granger affects (leading) prices,the price is anti-inflation,and this study shows that house prices do not have anti-effect.
The impact of house prices has a long-term positive impact on the index of industrial production, there is a long-term negative impact on the unemployment rate,if the housing prices impulse by itself,and impact of their own recession,will have a lasting postitive impact and the degree of impact for all variables the largest, investors can consider the past trend of housing prices as a real estate investment. indicators From the results of the decomposition of the forecast error variance,the price index of the US Standard & Poor's / Case-Schiller 10 cities home prices is higher than the other variables for the industrial production index and the unemployment rate.
Finally the government may consider the relationship between the house price for the economy and unemployment rate,Is conducive to the implementation of the overall economic-related policies.
en
dc.description.provenanceMade available in DSpace on 2021-06-17T01:15:58Z (GMT). No. of bitstreams: 1
ntu-106-P99323012-1.pdf: 2379826 bytes, checksum: 461a3f135c00df04ad3c595adfc14972 (MD5)
Previous issue date: 2017
en
dc.description.tableofcontents第1章(1)
前言(1)
文獻討論回顧(3)
第2章(6)
研究方法(6)
2.1向量自我回歸模型(VAR)(7)
Granger因果關係檢定(9)
衝擊反應函數分析(10)
預測誤差變異數分解(11)
第3章(12)
實證結果(12)
3.1資料敘述(12)
3.2單根檢定(13)
3.3向量自我迴歸模型(14)
3.4Granger因果關係檢定(15)
3.5衝擊反應函數分析(17)
3.6預測誤差變異數分解(18)
3.7穩健性檢視(19)
第4章 結語(21)
參考文獻(22)
圖1.各變數原始樣本繪製走勢圖(24)
圖2.各變數取一階差分後繪製走勢圖(25)
圖3.各變數衝擊反應分析圖 (各變數對於房價衝擊反應結果)(26)
圖4.不同順序變數排列之衝擊反應結果(27)
圖5.各變數衝擊反應分析圖(房價對於各變數衝擊反應結果)(28)
圖6.不同順序變數排列之衝擊反應結果(29)
表1.各變數名稱與各變數代號對照表(30)
表2.各變數單根檢定結果(31)
表3.以 VAR 模型運用各種資訊準則選取最適落後期(32)
表4.Granger因果關係檢定結果(33)
表5.Granger因果關係檢定結果整理(34)
表6.預測誤差變異數分解實證結果(35)
表7.預測誤差變異數分解實證結果(robustness check)(38)
dc.language.isozh-TW
dc.subject預測誤差變異數分解zh_TW
dc.subjectS&P Case-Shiller 10-City Index Composite Home Price Indexzh_TW
dc.subject單根檢定zh_TW
dc.subject向量自我回歸模型zh_TW
dc.subjectGranger因果關係檢定zh_TW
dc.subject衝擊反應函數zh_TW
dc.subjectS&P Case-Shiller 10-City Index Composite Home Price Indexen
dc.subjectUnit Root testen
dc.subjectVARen
dc.subjectGranger Causality Testen
dc.subjectImpluse ResponseForecast error variance decompositionen
dc.title物價、工業產出、失業率、聯邦基金利率與美國10大城市房價之互動關係研究zh_TW
dc.titleA Research of the Interactive Relationship Among the Consumer Price、Industrial Production、Unemployment Rate、Federal Funds Rate And American S&P Case-Shiller 10-City Index Composite Home Price Index.en
dc.typeThesis
dc.date.schoolyear105-2
dc.description.degree碩士
dc.contributor.oralexamcommittee張勝凱(Sheng-Kai Chang),周有熙
dc.subject.keywordS&P Case-Shiller 10-City Index Composite Home Price Index,單根檢定,向量自我回歸模型,Granger因果關係檢定,衝擊反應函數,預測誤差變異數分解,zh_TW
dc.subject.keywordS&P Case-Shiller 10-City Index Composite Home Price Index,Unit Root test,VAR,Granger Causality Test,Impluse ResponseForecast error variance decomposition,en
dc.relation.page40
dc.identifier.doi10.6342/NTU201702754
dc.rights.note有償授權
dc.date.accepted2017-08-14
dc.contributor.author-college社會科學院zh_TW
dc.contributor.author-dept經濟學研究所zh_TW
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