香港住宅市場合理價格和泡沫的實證研究外文翻譯

1、<p><b>　　中文2733字</b></p><p>　　本科畢業(yè)論文外文翻譯</p><p>　　外文題目：Detecting rational bubbles in the residential housing markets of Hong</p><p>　　Kong

2、 </p><p>　　出 處： Economic Modelling，2001，1(18)：61-73 </p><p>　　作 者： Hing Lin Chan Shu Kam Lee Kai Yin Woo </p><p

3、><b>　　原 文：</b></p><p><b>　　Abstract</b></p><p>　　This paper attempts to conduct an empirical study for detecting misspecification errors and rational bubbles in the

4、 residential housing markets of Hong Kong. We focus on a fundamental model that defines market fundamental price as a sum of the expected present value of rental income, discounted at a constant rate of return. Testable

5、implications for detecting misspecification errors and/or price bubbles are explored through the flow and stock approaches. In addition, the paper attempts to identi</p><p>　　Keywords: Bubbles; Housing marke

6、t; Modelling</p><p>　　Introduction</p><p>　　The total land area of Hong Kong is approximately 1075 km2. However, 80% of the territory is considered too hilly for property development. Therefore,

7、 only a tiny portion of the total supply could be used for residential purpose. The need to accommodate a total population of 6 800 000 people on a meager 50 km2 of residential land has made Hong Kong one of the most den

8、sely populated cities in the world. Without doubt, land is one of the scarcest resources in Hong Kong. How to use the resource eff</p><p>　　Apart from the above, there are other reasons that motivate us to s

9、tudy this problem. For example, the Hong Kong property markets play an important role in the economy. Several official figures can illustrate this point. First, more than 45% of all bank loans are directly tied to proper

10、ties. More than half of those loans are mortgage loans, which totaled in excess of HK$500 billion as at the end of 1997 (Hong Kong Government, 1998a).In additional, the real estate sector contributes approximately</p&

11、gt;<p>　　Despite the importance of this problem, not many studies have been done on detecting rational bubbles in the residential markets of Hong Kong. Most of the earlier papers, such as Peng and Wheaton (1994) a

12、nd Mok et al. (1995) concentrated on studying the property price without taking the possibility of bubbles into account. In view of this, our paper attempts to fill this gap. To do that, we arrange the discussion in the

13、following manner. Section 2 will discuss the methodology. In particular, we </p><p>　　Methodology</p><p>　　Model specification</p><p>　　We treat property as a good investment, which

14、 produces a stream of rental incomes over its lifetime. The current value of a property is therefore determined by the present value of current rental income and next period’s expected market price. The following equatio

15、n formalizes this relation:</p><p>　　Pt= (1)</p><p>　　where Pt is the real value of property at date t, is the constant ex ante real discount rate, E(．∣) denotes rational expec

16、tations based on , which is a full information set available to the market representatives at time t, and Dt represents the real rental income during the period t.</p><p>　　Eq.(1) can be solved by recursiv

17、ely substituting forward for E(P)and using the law of iterated expectations. The solution is given in Eq. </p><p>　　2.2. Noise detection</p><p>　　In this paper, we follow the signal extraction m

18、ethod of Durlauf and Hall (1989a,b) and Durlauf and Hooker (1994) to investigate the existences of St and Bt by the use of the flow and stock test. To carry out the flow test, let us first consider the perfect foresight

19、fundamental price P.</p><p>　　Because of Eq., r is known as one period excess return on holding property. Once the information of r is available, it is possible to conduct the flow test. To begin with, let L

20、t( x)be the information set available at time t, which is a subset of .Projection of r onto Lt(x) captures the fitted value of St . since t4 and _et4 are, by definition, orthogonal to Lt(x). Therefore, under the null hy

21、pothesis, r is orthogonal to Lt(x). Failing to reject this hypothesis implies that St is zero.</p><p>　　The implementation of the stock test, however, relies on Eq. from which we know that the projection of

22、P onto L(x).can capture the fitted values of Bt and St. Therefore, the null hypothesis assumes that P is orthogonal to Lt( x). Failing to reject the null hypothesis implies that the total model noise,</p><p>

23、;　　Bt + St, is zero.</p><p>　　To sum up, there are three possible outcomes when these two tests are taken together. Firstly, if both flow and stock orthogonal conditions are not rejected, price follows funda

24、mental price solution. That is, the total model noise is zero.Secondly, in the case where the flow projection is zero but the stock projection is non-zero, the model noise contains Bt only. In other words, the price sequ

25、ence is consistent with the general solution Eq. Thirdly, if both orthogonal conditions are rejected, w</p><p>　　Empirical studies</p><p>　　Noise detection</p><p>　　The implementati

26、on of the flow and stock tests requires the construction of r and P. Since we deal with moment (orthogonal) conditions, the generalized method of moments (GMM) is needed to construct r. To do that, we first estimate via

27、 GMM, using the flow projections themselves as given by the following orthogonality conditions,</p><p>　　The role of the GMM estimator is to help select an optimal so that the sample correlations between th

28、e Lt(x) and r are as close to zero as possible. This can be done by varying to minimize the following criterion function (Hansen, 1982):</p><p>　　where m is the sample moment condition, W is a weighting mat

29、rix and N refers to the number of sample observations. A necessary (though not sufficient) condition to obtain an asymptotically efficient estimate of is to set W equal to the inverse of the covariance matrix of the sam

30、ple moments, m. However, since the GMM’s estimates are sensitive to the choice of the bandwidth parameter, we therefore use heteroskedasticity and autocorrelation covariance matrix estimators that make use of automatic d

31、</p><p>　　The data for this study are taken from the Hong Kong Government Property Review. They contain data on monthly averaged rentals and quarterly averaged prices of the private domestic properties withi

32、n the class A, which is defined as those apartments whose sizes are less than 39.9 m2. The rentals are exclusive of rates, management and other charges. Since the urban areas of Hong Kong consist of three main regions: H

33、ong Kong Island, Kowloon and New Kowloon, we will include all of them for analysis.</p><p>　　Estimation of St and Bt</p><p>　　Since we have obtained the estimates of Bt, we can further examine t

34、he time series property of the B?t by using the N 1and N2 test statistics of Bhargava (1986).The purpose of conducting N1 and N2 tests is to examine whether the bubble estimates follow, without and with drift, respective

35、ly, random walk against the alternative of explosive patterns. The results of these tests, summarized in Table 5, accept the null hypothesis for all the three regions in Hong Kong. In other words, the bubble esti</p&g

36、t;<p>　　Conclusion</p><p>　　This paper reports empirical studies for the existence of unobservable misspecification errors and explosive rational bubbles in the property markets of the three urban reg

37、ions in Hong Kong. We assume that the property price is composed of fundamental, rational bubble and misspecification error components. The signal extraction approach of Durlauf and Hall (1989a, b) is employed for uncove

38、ring the unobservable model noise. Since both the nulls of the flow and stock tests are rejected, this means</p><p><b>　　譯 文：</b></p><p>　　香港住宅市場合理價格和泡沫的實證研究</p><p>&l

39、t;b>　　摘要</b></p><p>　　這篇文章傾向于指導揭開香港住房市場的設(shè)定誤差和合理泡沫的實驗研究。我們關(guān)注有關(guān)市場基本價格的重要模型。這種模型把市場的基本價格定義為預計的租賃收入現(xiàn)值和固定盈利率的折扣的總和。通過研究流量和庫存的方法可以驗證設(shè)定誤差和價格泡沫研究的意義。此外，這篇文章還打算在香港房產(chǎn)價格的數(shù)據(jù)中鑒定設(shè)定誤差的數(shù)量和泡沫的組成部分。</p><p&

40、gt;　　關(guān)鍵字：泡沫；住房市場；模型</p><p><b>　　1.介紹</b></p><p>　　香港的總面積大約為1075平方千米。但是，80 %的土地是丘陵不適合房產(chǎn)開發(fā)。因此，在提供可以利用的土地中只有一小部分可以作為住房土地。一片不到50平方千米的住房土地要容納6800000的人口，這使得香港成為世界人口密度最大的國家之一。不用懷疑，土地是香港最稀缺的

41、資源。怎樣有效率的利用這個資源是一個非常重要的問題。在市場經(jīng)濟下，價格是政府制定政策的最重要的信息依據(jù)之一。但是，如果存在價格泡沫，那政府就會被誤導制定錯的政策。這個問題對香港政府來說非常的重要。因為政府已經(jīng)對住房市場進行宏觀調(diào)控好幾年了，盡管香港是世界有名的放任自由的市場經(jīng)濟。近幾年的調(diào)控措施中包括提供公共住房，限制住房土地的供給，房租管理。但結(jié)果卻差強人意，房產(chǎn)價格在政府政策的影響處于白熱化的階段。因此，查明住房市場是否存在泡沫現(xiàn)象

42、是非常重要的。</p><p>　　除上述原因外，還有另一些原因促使我們?nèi)パ芯窟@個問題。例如，香港的房產(chǎn)市場在整個經(jīng)濟中有很重要的地位。一些官方的數(shù)據(jù)可以證明這個觀點。首先，超過45%的銀行貸款和房產(chǎn)有關(guān)，超過一半的貸款是住房貸款。到1997年，住房貸款的總數(shù)超過了5000億港幣。（香港政府，1998a）。另外，1996年香港的不動產(chǎn)拉動GDP10.2%（香港政府，1998b）。最后，1997年和1998年，房產(chǎn)

43、拍賣收入和印花稅收入大約占政府總收益的24%。由于這些復雜的關(guān)系，泡沫的破碎將會帶來沉重的影響，這影響也會持續(xù)很久。無疑的，當局應(yīng)該避免房產(chǎn)市場的價格泡沫的構(gòu)成。另一個研究這個問題的原因是香港在過去十年里的住宅房地產(chǎn)價格波動劇烈。例如，1991年住宅房地產(chǎn)的實際價格上升了40%。1995年房價又急劇下降了16.2%。接著2年內(nèi)又分別明顯的上升了18.9%和20%，1998年又急劇下降50%。根據(jù)這些劇烈的波動現(xiàn)象，去調(diào)查在這非常波動的時

44、期是否已經(jīng)形成了價格泡沫令人關(guān)注。</p><p>　　盡管這個問題非常重要，但探究香港住房市場的合理泡沫的研究還是不多的。最早期的論文有彭粲和惠頓(1994)和莫孫俐 (1995)對資產(chǎn)價格泡沫的可能性考慮的專門研究。鑒于此,本文試圖填補這一差距。要這麼做,我們就安排以下方式的討論。第2部分將討論的是方法論。特別要討論的是這種把市場的基本價格定義為預計的租賃收入現(xiàn)值和固定盈利率的折扣的總和的模型。如何檢測不合理

45、的誤差或投機泡沫的方法也會被討論。在第三節(jié),我們將介紹實證研究的結(jié)果。特別是不合理的誤差的大小和氣泡的組成部分。第4部分將總結(jié)本文的研究發(fā)現(xiàn)。</p><p><b>　　2. 方法論</b></p><p><b>　　2.1模型設(shè)定</b></p><p>　　我們把財產(chǎn)當作是不錯的投資,它一生可以產(chǎn)生一連串租賃收入。

46、物業(yè)的現(xiàn)值因此由現(xiàn)在租賃收入的現(xiàn)值和下個時期的預期市場價格決定的。下列方程說明了這個關(guān)系:</p><p>　　Pt= (1)</p><p>　　Pt是在房地產(chǎn)在日期t的真正價值, 是事前真正的貼現(xiàn)率,E(。∣)是指基于理性預期,這是一個完整的資料集可供市場代表在t時期利用, Dt代表在t時期真正的租金收入。等式。(1)可以解決遞歸的替代了E(P),并利用

47、迭代的律法期望。等式給出了解決的方法。</p><p><b>　　2.2噪音檢測</b></p><p>　　在本文中,我們遵循Durlauf and Hall (1989a,b) and Durlauf and Hooker (1994)的信號提取方法利用組織的流動和股票測試探討St和Bt的存在。進行流量測試前,我們先來考慮一下完美預測的基本價格P。</p&

48、gt;<p>　　根據(jù)公式,r是持有房產(chǎn)的一時期超額回報財產(chǎn)。一旦r的信息是可行的,它可以進行流量測試。首先,讓Lt(x)是在t時期是可以利用的信息,并是 的子集。假設(shè)x在Lt（x）上得St的擬合值。t4和_et4必然正交于Lt(x)。因此在零假設(shè)下，r與Lt(x)相交。這個假設(shè)存在意味著St等于零。</p><p>　　實施股票測試,依靠公式我們知道把P投射到L(x)可以得到擬合值Bt和St.因此

49、,這個零假設(shè)是假設(shè)P正交于Lt(x)。這個假設(shè)的存在意味著總模型的噪音,Bt+St等于零。</p><p>　　綜上所述,當這兩測試放在一起時，存在三種可能的結(jié)果。首先,如果流量和庫存正交存在,價格服從基本的價格方案。也就是說,總模型噪聲為零。其次,在流量預測為零而庫存預測不為零的情況下,模型噪聲只包括Bt。換句話說,價格序列是公式的通解。第三,如果兩個正交條件都不成立,我們能夠確認St的存在,但進一步分析Bt的

50、存在是必要的。</p><p><b>　　3.實證研究</b></p><p><b>　　3.1噪聲探究</b></p><p>　　實施流量和庫存的測試需要構(gòu)建r和p.因為我們處理正交條件,最普遍的方法（GMM）是構(gòu)建r。我們通過GMM初步估計,并在以下正交條件中利用流量預測其本身，</p><p

51、>　　利用高斯混合模型(GMM)去估量是為了選擇一個最佳的,使Lt(x)和r的試樣關(guān)系近乎于零。這可以通過變化的值使準則函數(shù)最小化 (Hansen,1982)。在m是樣本矩條件下,W是稱重矩陣，N指的是試樣的觀察結(jié)果的總和。令W等于樣本矩的協(xié)方差矩陣逆的倒數(shù)m是得到一個漸近有效的估計值的必要 (盡管不是充分)條件。然而,由于高斯混合模型(GMM)的統(tǒng)計對帶寬參數(shù)的選擇非常敏感,因而我們要使用異方差性和自相關(guān)協(xié)方差矩陣函數(shù)并充分利用

52、自動的具有數(shù)據(jù)的圖象的寬帶選擇符（Newey 和West,1994）.</p><p>　　本研究的數(shù)據(jù)來自于香港政府財產(chǎn)審查。它們包含月平均租金和季平均私有家庭財產(chǎn)的價格。我們把這一類人定義為那些公寓面積不到39.9平方米。這里的住房租金不包括差餉，管理費和別的費用。由于香港市區(qū)包括三個主要地區(qū):香港島、九龍和新九龍,我們將對這三個地區(qū)都進行分析。采樣周期從1985年第一季度到1997年第三季度是實證研究時期,

53、并有從1997年第四季度到1998年第三季度的額外數(shù)據(jù)是為構(gòu)建完美的預測價格</p><p>　　3.2 St和Bt的評估</p><p>　　既然我們已經(jīng)得到了Bt的估計值,我們可以利用Bhargava(1986)的N1和N2的校驗統(tǒng)計學更進一步檢查Bt的時間數(shù)列的財產(chǎn)。進行N1及N2測試的目的是為了檢測泡沫是否具無規(guī)律分布并對爆炸的模式有選擇的趨勢。這些測試結(jié)果總結(jié)在表5中,原假設(shè)包括

54、香港的三個區(qū)域。換句話說,泡沫的評估B?t,不具有線性爆炸性的特性,這表明價格泡沫在香港住宅房屋市場是不確定性的。這并不奇怪,因為我們通常觀察泡沫破裂而不是確定性的泡沫。為了說明泡沫是如何爆炸,并隨著時間的推移如何爆炸,我們在表格4-6中把B^t劃分為三個城市地區(qū)。一般來說, B?t從1985年移向1991-1992的頂峰，接著破裂。但是從1995年以來, B?t爆炸點再一次達到1997年的頂峰。</p><p>

55、;<b>　　4.總結(jié)</b></p><p>　　本文的實證研究記錄了香港三個城市地域房產(chǎn)市場的不合理房價和突發(fā)性泡沫。我們假設(shè)房產(chǎn)價格是由基本的、理性的泡沫以及不合理的部件組成。利用了Durlauf的信號提取方法和Hall(1989a,b)的觀察難以發(fā)覺的噪聲模型。并通過假設(shè)流量和庫存測試的不存在,意味著在噪音模型中存在不合理的誤差。為了測量噪音模型中每個組成部分的大小,我們采用Hans