外文翻譯--住房市場的經濟基本原理依據美國大城市的住宅狀況

1、<p><b>　　中文3687字</b></p><p><b>　　畢業(yè)論文外文翻譯</b></p><p>　　外文題目：ECONOMIC FUNDAMENTALS IN LOCAL HOUSING MARKETS: EVIDENCE FROM U.S. METROPOLITAN REGIONS

2、 </p><p>　　出 處： JOURNAL OF REGIONAL SCIENCE，2006，46(8)：425-453 </p><p>　　作 者： Min Hwang John M. Quigley </p><p><b>　　原 文

3、：</b></p><p><b>　　ABSTRACT</b></p><p>　　This paper investigates the effects of national and regional economic conditions on outcomes in the single-family housing market; housin

4、g prices, vacancies, and residential construction activity. Our three-equation model confirms the importance of changes in regional economic conditions, income, and employment on local housing markets. The results also p

5、rovide the first detailed evidence on the importance of vacancies in the owner-occupied housing market on housing prices and supplier activities</p><p>　　INTRODUCTION</p><p>　　Housing markets ar

6、e local, and housing market outcomes reflect local economic conditions. Housing prices are hid up as a result of better employment opportunities and higher incomes enjoyed by residents in an expanding metropolitan market

7、. Changes in the distribution of income are reflected in the distribution of prices and housing amenities. Similarly, housing vacancy rates can be expected to decline when the local economy improves and as the demand for

8、 housing increases. Finally, residential c</p><p>　　This paper considers the inter-relationship among these three forms of economic behavior in the context of local housing markets. We model the relationship

9、 among the prices of owner-occupied housing, vacancy rates, and housing supplier activity in response to the exogenous factors, which affect the fortunes of the regional economy. We also recognize the importance of local

10、 land use and building regulations in affecting the operation of the owner-occupied housing market.</p><p>　　Our analysis uses U. S. metropolitan areas (MSAs) as units of observation, and we follow a panel o

11、f 74 MSAs over the 13-year period, 1987-1999. The panel includes all U.S. metropolitan areas for which annual data are available on the prices of owner—occupied housing, on the vacancy rates in single-family housing, and

12、 on supplier activity (i.e., the number of permits issued for construction of new single-family housing).</p><p>　　In this paper, we develop a model relating exogenous changes in regional employment and inco

13、mes, construction costs and macro economic conditions to these measures of the health of housing markets—prices, vacancies, and new construction. The model is estimated in several variants, and we simulate the responsive

14、ness of the housing market to local economic conditions. The model indicates the strong interdependency between the state of the macro economy, the state of the regional economy, and outco</p><p>　　In Sectio

15、n 2 below, we relate our work to previous attempts to develop regional models of the housing market. Section 3 presents an overview of the data and the methodology we use, as well as the relationships among the various m

16、easures of the housing market. Section 4 presents data. Section 5 presents our statistical results and the simulations based upon them. Section 6 is a brief conclusion.</p><p>　　ANTECEDENTS</p><p&

17、gt;　　A simple model of supply and demand at the regional level motivates the choice of variables to explain outcomes in the housing market over time. Housing demand is a function of prices and incomes and perhaps demogra

18、phic variables as well. Housing supply is a function of profitability, which depends upon housing prices and input prices, including the costs of labor, materials, financing, and regulations inhibiting new construction.

19、Vacancy rates in existing housing reflect the difference between </p><p>　　Several early papers (following Reid, 1962; Muth, 1960, 1968) analyzed variations in housing prices across metropolitan areas, focus

20、ing on the reduced form of relationship between the prices of owner-occupied housing and metropolitan characteristics. Using these models, it is easy to describe the development of house prices, but it is quite difficult

21、 to make inferences about structural parameters or about causation.</p><p>　　In contrast, a few more recent studies have investigated structural relationships among housing market outcomes. Poterba (1984) an

22、alyzed the interaction between movements in prices and housing stocks, modeled as a two-equation system. The growth of housing prices is represented as a function of the difference between current prices and imputed rent

23、als, while the growth of the housing stock is related to real housing prices {as a proxy for profitability) and to the size of the current stock. In t</p><p>　　DiPasquale and Wheaton (1994) specified a model

24、 for housing demand in which the price of owner-occupied housing within a given housing market is a function of the current stock of single-family housing relative to the number of households, their age-expected homeowne

25、rship rate,* the cost of renting relative to owning in the market, and the average household income within the market. In a second equation, the authors modeled housing starts as a function of current prices, costs, and

26、the stock of </p><p>　　OVERVIEW OF THE MODEL</p><p>　　Our model of regional housing markets is based upon a panel of U.S. metropolitan areas, including all markets for which annual data on housi

27、ng prices, vacancies, and construction activity are available for owner-occupied housing. Of the 334 metropolitan housing markets (MSAs) in the United States, consistent measures of house prices are available for 120, be

28、ginning in 1975. Annual measures of the stock of owner-occupied housing, vacancy rates, and supplier activity (i.e., building permits) are a</p><p>　　Our empirical model consists of three equations describin

29、g the movement of housing prices, housing supply, and vacancies in the market for owner-occupied housing. In this section, we describe the key features of the model, deferring issues related to data, measurement, and est

30、imation technique to Section IV.</p><p>　　New Housing Supply</p><p>　　In contrast to the analysis of housing demand and price formation, less is known about the behavior of housing supply. In pa

31、rt, this reflects limitations in available data and in conceptual models (Rosenthal, 1999). DiPasquale (1999) has summarized three empirical difficulties in the housing supply literature. First, estimated housing supply

32、elasticties vary widely. Second, price does not seem to be a sufficient statistic, and other market indicators are quite important in explaining housing sup</p><p>　　We follow Mayer and Somerville, modeling

33、new housing supply as a function of changes in prices and input costs, as well as macroeconomic conditions. Our model is</p><p><b>　　St=</b></p><p>　　where St is new housing supply,

34、Vt represents vacancies, Ct is input costs for labor and materials, ft is financing costs, REGt is the restrictiveness of local regulation, and x represents other supply shifters. We measure new supply as the annual diff

35、erence in the stock of housing; the stock is constructed by adding building permits to the stock in the previous year. Again, lower case letters indicate logarithmic differences. Note that this specification of the suppl

36、y equation includes two endo</p><p>　　Finally, as noted above, there is ample evidence that supply adjustment to changes in price is sluggish and slow. We recognize this by including a variable measuring the

37、 lagged change in housing prices in the empirical model.</p><p>　　Vacancies in Owner-Occupied Housing</p><p>　　The early literature on vacancy in the rental housing market analyzed the empirical

38、 relationship between some "natural" rate of vacancy and housing rents, based on reduced form models (Eubank and Sirmans, 1979; Rosen and Smith, 1983). Theoretical explanations of vacancy focus on the frictions

39、 of search, given the idiosyncratic preferences of households and the heterogeneity of housing units (Arnott, 1989; Wheaton, 1990; Read, 1997). In these models, some level of vacancy facilitates the search p</p>&

40、lt;p>　　If a homeowner chooses to keep a unit vacant rather than selling in response to an offer, this is a decision to hold a real option. That is, when the owner of a vacant unit decides to keep a unit vacant rather

41、than selling it at the current market price, this is because she believes that waiting is worthwhile. Waiting is more worthwhile if prices are expected to increase and if the volatility of housing investment returns is l

42、arger.</p><p>　　DATA AND METHODOLOGY</p><p><b>　　Data</b></p><p>　　The econometric evidence presented in the following section is based on data pieced together from a va

43、riety of sources. With one exception, the data series are publicly available, and most are available online. As noted above, we analyze three dependent variables: prices, vacancies, and supplier activity.</p><

44、p>　　Single-family housing prices are measured using metropolitan housing price indices published by the U.S. Office of Federal Housing Enterprise Oversight (OEHEO). The index is defined by the weighted repeat sales me

45、thod using all single-family houses whose mortgages have been purchased or securitized by Freddie Mac or Fannie Mae since 1975.</p><p>　　Homeowner vacancy rates by MSA are available annually from the U.S. Bu

46、reau of the Census.</p><p>　　We measure supplier activity by the number of building permits issued for single-family housing in each MSA. Most prior research on housing supply is based upon aggregate housing

47、 starts (Topel and Rosen, 1988; DiPasquale and Wheaton, 1994; Mayer and Somervile, 2000). Information on housing starts is simply unavailable at the metropolitan level. However, it is well known that the aggregate series

48、 on permits tracks housing starts very closely (Evenson, 2001; Somervile, 2001).^''' Other studies ana</p><p>　　We also employ several other exogenous variables in the three equations to measure

49、the importance of the local economy. These include per capita income, Yt, employment, EMt, and per capita transfer payments for unemployment, UNt. These data are all available from the REIS database.</p><p>

50、　　A complete listing of variables, definitions and symbols is presented inTable . The subscripts i and t designate variables which vary by MSA and year.</p><p>　　5. CONCLUSION</p><p>　　This pape

51、r estimates the effects of national and regional economic conditions on local housing markets using a panel of U.S. metropolitan areas over a 14-year period. We estimate the effects of exogenous conditions on the prices

52、and vacancy rates for owner-occupied single-family housing, and on building permits issued for new construction of single-family housing. The parameters are estimated by two-stage least squares in an error components fra

53、mework.</p><p>　　The empirical models provide a coherent set of empirical and simulation results. The results confirm the importance of changes in regional economic conditions, income and employment, upon lo

54、cal housing markets, and they confirm the importance of lagged adjustment processes on both the demand and supply sides of the market. The results also provide the first detailed evidence on the importance of vacancies i

55、n the owner-occupied housing market on housing prices and supplier activity. The results a</p><p>　　Simulation exercises, using standard impulse response analyses, document the lags in market responses to en

56、dogenous shocks and the variations in response predicted from a common model depend greatly upon local conditions. Finally, the results suggest the importance of local regulation in affecting the pattern of market respon

57、ses to regional economic conditions. In more regulated markets, levels of housing prices are higher in response to endogenous shocks, and the price increases are far more pe</p><p><b>　　譯 文：</b>

58、;</p><p>　　住房市場的經濟基本原理：依據美國大城市的住宅狀況</p><p><b>　　摘要</b></p><p>　　本文探討了國家和區(qū)域的經濟效應基礎條件對住宅市場;房產價格,空置率和居民住宅建設的影響。我們的3個方程式模型體現了區(qū)域經濟條件，收入，和住宅房屋市場的雇傭關系變化的重要性。結果還首次提供了確鑿的證據證明空置率對

59、業(yè)主房市場的房價和供應商的活動有重要的影響。結果也證明材料,勞動和資本成本變化的重要性,和用標準的脈沖響應模型對新供應模擬模式的影響, 同時也反映了市場對外源沖擊和不同地方的參數差異反應滯后。結果還顯示,地方性法規(guī)對市場反應地區(qū)收入沖擊的模式有重要的影響。</p><p><b>　　簡介</b></p><p>　　當地的住房市場和住宅市場的產出反映本地經濟條件。房

60、價的隱藏是由于在不斷擴大的都市居民有更好的就業(yè)機會和更高的收入。收入分配的改變主要體現在房價的分配和住房待遇的分配。同樣,當地經濟改善和住宅需求的增加時，住宅的空置率就會降。最后,住宅建設和建筑活動對房價,閑置率和當地經濟的健康有重要的影響。高收入增加了住宅的需求,因此房價被抬高;買新建房成了有利可圖的事,誘導著供應商的活動。有些閑置的住宅等待著被重新利用，有些住宅通過整修被重新利用。</p><p>　　本文討

61、論了住宅房屋市場的3種經濟行為的內在關系。我們建立業(yè)主房 ,空置率和住宅供應商活動與外源因數想對應的關系影響了區(qū)域經濟的模型。我們也認識到區(qū)域土地的使用和建筑條例對業(yè)主房市場有重要的影響。</p><p>　　我們把美國大都市(MSAs)作為觀察單位,并遵從美國74了城市在13年內（1987——1999）的變化數據。這個組數據包括所有美國城市業(yè)主房的價格，住宅的閑置率和供應商的活動(例如,允許建設的房屋的數量)。

62、</p><p>　　在本文中,我們提供一種涉及區(qū)域就業(yè)和收入,建設成本和宏觀經濟條件的變化和測量健康住宅市場的模型,這些措施包括房價,閑置,和新的建筑。該模型有幾個變體,我們假設房屋市場和區(qū)域經濟條件是有關聯的。該模型表明國家宏觀經濟，區(qū)域經濟和房地產市場的產出之間有很大的相互依賴性。結果還表明地方性法規(guī)在房產市場的產出方面起著關鍵的作用。</p><p>　　在下面的第2節(jié),我們試圖建

63、立房地產市場的區(qū)域模型。第三節(jié)概述了的數據和方法論的,以及各種測量房地產市場措施的關系。第四節(jié)給出數據。第5條給出重要的統計結果和基于這些數據的模擬。第6部分是總結。</p><p><b>　　前言</b></p><p>　　先是一個簡單的模型。一個地方的供給與需求水平刺激對房地產市場產出的解釋選擇不同的變量。房屋的需求是一個關于物價和收入的函數,也許人口統計學的

64、變量。房屋供應是一個關于利潤的函數,這取決于房價和投入的價格,投入的價格包括勞動力成本、材料、資金、約束新建房的法規(guī)。閑置率的存在反應了在任何時期總供給和總需求之間存在差異。</p><p>　　一些早期報告(following Reid, 1962; Muth, 1960, 1968)分析了在大城市里房價的變量,把業(yè)主房的價格和大城市的特點的關系簡約化。使用這些模型,很容易描述房價的變化,但去推論結構參數或者原

65、因是非常困難的。</p><p>　　相反,更多的最近的研究報告調查了內在結構和房地產市場產出之間的關系。Poterba(1984)分析了住房數量和價格的相互關系，把它們轉化為2個方程式的關系。房屋價格的增長是一個關于現在價格和估算租金之間不同關系的函數,而增長的住宅數與真正的房價{作為盈利的替代)和流通股票的價格是有關系的。在這個簡單的股票和現金的模型中,沒有線索或滯后效應。閑置房的股票忽略不計。</p&

66、gt;<p>　　DiPasquale和惠頓(1994)說明了房屋的需求的一個模型,業(yè)主房的價格在某個特定的房地產市場環(huán)境中是一個關于當前住宅房的股票與家庭的數量,他們預期的住房率,在目前市場上房屋出租的費用,以及該市場平均家庭收入的函數。在第二個方程中,他們定義房產的開工率是一個關于市價、成本和住房股票,以及市場上就業(yè)和時間的函數。在該模型中大多數供應商的行為說明了市場上的利率、就業(yè)水平和時間是外在的變化因素。他們把最后

67、的變量解釋為住房市場緩慢調整的證據。</p><p><b>　　3.模型的概述</b></p><p>　　我們的區(qū)域房地產市場模型是依據美國大城市地區(qū)的數據。這個組數據包括所有美國城市業(yè)主房的價格，住宅的閑置率和業(yè)主房的建設。在美國334個大城市房地產市場（MSAs）中，從1975年開始有120個房地產市場采取房價一致的措施。在1987-1999期間只有75個房地

68、產市場把業(yè)主房的股票，閑置率，供應商的活動（例如，建筑許可證）當做年度措施。我們的分析是基于1987-1999期間74個大城市市場的962組年度觀察值。</p><p>　　我們的實驗模型包括關于房價的波動,住房供給,以及業(yè)主房空缺的三個方程式。在這一節(jié)中,我們主要描述這個模型的延期數據,測量,和估計技術的特點。</p><p><b>　　新建房屋的供應</b>&l

69、t;/p><p>　　與住房需求及價格形成理論相對應的是很少人知道的住房供應行為理論。在某種程度上,這反映了可利用的數據和概念模型的局限(Rosenthal,1999)。DiPasquale(1999)歸納了在房屋供應文獻中三個實證的困難點。首先,假設房屋供應的數據有著很大的不同。第二,在解釋住房供應理論中，價格并不是一個足夠的因素,其他的市場指標卻是非常的重要。第三,建設水平對建設成本和產出的價格反應遲緩。此外還有

70、關于住房供應模型恰當說明的不同意見。在早期的研究中，新房屋供應、房產許可的標準都是根據價格水平和施工成本規(guī)定的(Porterba,1984;Topel和Rosen,1988;DiPasquale 和Wheaton,1994)。最近,Mayer和Somervile(2000)發(fā)明了一種把新住房供應與價格及成本的變化相連接的實驗模型。他們認為住房價格的平均水平與住房空間總需求的住房供應股票相適應,它暗示新房屋的建設以房價的變化,以及其他可變

71、量的變化如施工成本為依據的。</p><p>　　我們依據Mayer和somervill的新住房供給為價格變動和投入的費用以及宏觀經濟條件的函數建模。我們的模型是</p><p><b>　　St=</b></p><p>　　St是新房屋的供應、Vt代表空缺,Ct勞動投入成代表勞動成本和材料的投入,Ft是資金成本、REG是地方性法規(guī),x代表其

72、他供應。我們測量在每年不同的住房股票下的新建房屋的供應;股票由上一年增加的建筑許可證決定。然后,小寫字母表示對數的差異。注意:這個供應方程式說明包括兩個內在的變量,房價的變化和空缺房的變化。我們希望提高住房價格可以增加供應商的活動。增加投入的成本(勞動力、材料或資本)和空缺房會降低供應商活動。</p><p>　　最后,如上所述,我們有充分的證據證明供應調整對價格的變化反應滯后。我們通過一個變量測量房價的滯后變化

73、的模型認識到這一點。</p><p><b>　　業(yè)主房的空置</b></p><p>　　早期關于空置租賃房產市場的文獻基于簡化模型(Eubank和Sirmans,1979年,Rosen和Smith,1983年)分析了“自然”的空缺和房屋租金的實驗關系。有關空缺的理論解釋關注找房過程中的摩擦，要考慮到家庭的特質和房屋單位的不均勻性(Arnott,1989;Wheat

74、on,1990,Read,1997)。在這些模型中,某種程度上的空缺促進了住房需求者尋找的進程,賣方收取更高的價格來抵消閑置房的損失。這些尋找模型表現了獨特的住房市場,和在市場均衡條件下合理的住房閑置。最近,Gabriel和Nothaft(2001)把住房閑置分為2個部分,發(fā)生率和持續(xù)時間。他們認為發(fā)生率與人口的流動有關,持續(xù)時間與找房的費用和住房股票的非均質性有關。他們的研究結果表明,住宅租金更能反映發(fā)生率而非持續(xù)時間。</p&

75、gt;<p>　　如果房主選擇保持房屋的閑置,而不是售出房屋,這個決定才是真正的選擇。那就是說，當一個人決定保持空房屋而不依據當前的市場價格出售,這是因為她認為等待是有價值的。如果房價提高，房屋投入回報波動大，那么等待會得到更多的收入。</p><p><b>　　4．數據和方法論</b></p><p><b>　　數據</b>&

76、lt;/p><p>　　在下一章節(jié)中的經濟依據是基于各種各樣來源的數據的拼湊。但有一個例外,這些數據系列是可以供公共使用的,而且大多數人可以在網上搜索到。如上所述,我們分析三個因變量:價格、空缺和供應商的活動。</p><p>　　獨棟房屋價格可由美國聯邦住房企業(yè)監(jiān)察辦頒布的大城市住房價格指數衡量。這一指數根據加權重復購買理論定義并從1975年開始所有獨棟房的房貸款要被聯邦政府所持有和確認。&

77、lt;/p><p>　　MSA業(yè)主空置率每年由美國統計局公布的人口普查決定的。</p><p>　　我們由在MSA中獨幢房的建筑許可證衡量供應商活動。大多數先前的房屋供應的研究都是基于房產開發(fā)的集合(Topel和ROSEN,1988年,DiPasquale和羅森惠頓,1994,邁耶,和Somervile,2000年)。房產開發(fā)信息在紐約大城市是不可信的。然而,眾所周知,新屋開工許可證的序列卻非

78、常密切,2001;(Evenson,2001)。Somervile ^”其他的研究分析城市數據(例如,Poterba,1991年成立;Drieman和Follain Somervile邁耶,,2004;20(1),2000)也依照建筑許可證。獨幢房的建筑許可證的數據由美國統計局公布并在德州農工大學房產中心的網站上可以利用。</p><p>　　我們也使用在三個公式中若干其他外在變量衡量區(qū)域經濟的重要性。這些變量包

79、括人均收入、Yt、就業(yè)、EMt,人均未就業(yè)轉移支付,UNt。這些數據都可以在REIS數據庫找到。</p><p>　　在表格中有一系列變量，定義和符號。腳注i和t代表了由于MSA和時間的變化而變化的變量。</p><p><b>　　5．總結</b></p><p>　　本文利用一組美國大城市在過去14年里的區(qū)域住房市場的數據評估了國家和區(qū)域的

80、經濟條件。我們估算業(yè)主房的價格和閑置率和新建獨幢房的建筑許可證的外在條件的影響。這些參數的估計在二級最小平方的誤差組成成分的框架內。</p><p>　　實證模型提供一套連貫嚴整的經驗和仿真結果。這些結果證實了區(qū)域經濟的條件,收入和就業(yè)的變化對區(qū)域房屋市場的有重大的影響,同時他們也認為調節(jié)的滯后進程對市場的供給和需求有重要的影響。結果還首次提供了確鑿的證據說明業(yè)主房市場的空缺對房價和供應商的活動有重大的影響。結果