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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/86843

    Title: 2000-2011美國房市泡沫之區域差異化探討 : 以全美50州為例
    Other Titles: Causes and geographic distribution of the 2000-2011 US housing bubble : a state level panel data analysis
    Authors: 許君騰;Hsu, Chung-Teng
    Contributors: 淡江大學美洲研究所碩士班
    柯大衛;Kleykamp, David
    Keywords: 美國房市泡沫;50州;期望價錢;平行數據回歸分析;housing bubble;50 states;expected price;Panel Data Regression
    Date: 2013
    Issue Date: 2013-04-13 10:21:00 (UTC+8)
    Abstract: 美國房市泡沫化的程度在全美50州的差異程度非常大。以房價2000-2007的漲幅為例,漲幅最大的7個州,其房價年成長率高達11%-13%,而漲幅最小的內陸各州,年成長率只有2%-5%;再以房價2007-2011的跌幅為例,房價下跌最嚴重的四個州,其年度跌幅高達9%-11%,而跌幅最小的內陸各州的年度跌幅只有1%-4%,甚至有三個州的房價在此期間上漲,北達科塔州在2007-2011的上漲幅度更是高達11%。相關文獻目前對此現象沒有相關的研究,而作者對房價在各州變動極度不均勻的現象非常有興趣,故將研究問題定為:是什麼原因造成2000-2011房價在全美50州的變動如此地不均勻?

    作者假設此一期間各州的房價變動不均勻是因為以下三項因素在各州的變動程度不同所致:(一)對房價的不理性預期;(二)貸款審核標準;(三)政治傾向。而為了比較以上三項因素在程度上的差異, 我們必須要先將其量化。

    作者融合投資報酬率的概念與Hicks(1946)與Lange(1948)的期望價格彈性理論,以各州的房貸利率、 租金、 房價,將(一)對房價的不理性預期量化;接著以各州的放款人員就業人數,除以各州的貸款審核人員的就業人數, 將(二)貸款審核標準量化; 最後,以1992-2008的四次總統大選結果將全美50州編碼為1、0、或-1,作為政治傾向的量化變項。
    US housing bubble varies in the 50 states in terms of housing price. Between 2000-2007, housing price skyrocketed in 7 states, with annual growth rate between 11-13%, whereas the interior states grew at 2-5% annually. Between 2007-2011, housing price plummeted in 4 states with annual falling rate of 9-11%, whereas the interior states fell only 1-4% annually. Moreover, housing prices in North Dakota rose by 11% in the plummeting years of 2007-2011. Literature on housing bubbles generally ignored the regional disparity which we are interested in and therefore set forth our research question as: what has driven the uneven distribution of the US housing bubble in terms of housing price between 2000-2011?
    We firstly assume that the regional disparity was caused by the variances of the following three variables:(1)irrational expectation on housing prices;(2)mortgage underwriting standards;(3)political preferences. In order to compare and contrast the above three variables, we need to quantify them in the first place.
    We merged the notion of capital gains with the theory of expected price elasticity derived from Hick(1946) and Lange(1949) into a single framework and thus quantified (1)irrational expectation on housing prices; we then divided the employees who issue loans by the employees who check and authorize the loans, and got our quantified(2)mortgage underwriting standards; thirdly, we coded the 50 states political preferences as 1,0, or-1, according to their voting records between the 1992-2008 presidential elections.
    Our panel data regression informs us that the uneven fluctuation of housing prices in the 50 states between 2000-2011 is due to differences in irrational expectation on housing prices among states, as well as differences in recognition of the movements of housing prices in the past three years . Mortgage underwriting standards does explain the movement of housing prices in 2000-2011, however the effect is not so large. Political preferences do not impact housing prices at all; Democratic states do not have more severe bubbles than the Republican states.
    Appears in Collections:[Graduate Institute of the Americas] Thesis

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