住房市场的经济基本原理：依据美国大城市的住宅状况【外文翻译】.doc

1、1毕业论文外文翻译外文题目ECONOMICFUNDAMENTALSINLOCALHOUSINGMARKETSEVIDENCEFROMUSMETROPOLITANREGIONS出处JOURNALOFREGIONALSCIENCE，2006，468425453作者MINHWANGJOHNMQUIGLEY原文ABSTRACTTHISPAPERINVESTIGATESTHEEFFECTSOFNATIONALANDREGIONALECONOMICCONDITIONSONOUTCOMESINTHESINGLEFAMILYHOUSINGMARKETHOUSINGPRICES,VACANCIES,ANDRES

2、IDENTIALCONSTRUCTIONACTIVITYOURTHREEEQUATIONMODELCONFIRMSTHEIMPORTANCEOFCHANGESINREGIONALECONOMICCONDITIONS,INCOME,ANDEMPLOYMENTONLOCALHOUSINGMARKETSTHERESULTSALSOPROVIDETHEFIRSTDETAILEDEVIDENCEONTHEIMPORTANCEOFVACANCIESINTHEOWNEROCCUPIEDHOUSINGMARKETONHOUSINGPRICESANDSUPPLIERACTIVITIESTHERESULTSALS

3、ODOCUMENTTHEIMPORTANCEOFVARIATIONSINMATERIALS,LABORANDCAPITALCOSTS,ANDREGULATIONINAFFECTINGNEWSUPPLYSIMULATIONEXERCISES,USINGSTANDARDIMPULSERESPONSEMODELS,DOCUMENTTHELAGSINMARKETRESPONSESTOEXOGENOUSSHOCKSANDTHEVARIATIONSARISINGFROMDIFFERENCESINLOCALPARAMETERSTHERESULTSALSOSUGGESTTHEIMPORTANCEOFLOCAL

4、REGULATIONINAFFECTINGTHEPATTERNOFMARKETRESPONSESTOREGIONALINCOMESHOCKS1INTRODUCTIONHOUSINGMARKETSARELOCAL,ANDHOUSINGMARKETOUTCOMESREFLECTLOCALECONOMICCONDITIONSHOUSINGPRICESAREHIDUPASARESULTOFBETTEREMPLOYMENTOPPORTUNITIESANDHIGHERINCOMESENJOYEDBYRESIDENTSINANEXPANDINGMETROPOLITANMARKETCHANGESINTHEDI

5、STRIBUTIONOFINCOMEAREREFLECTEDINTHEDISTRIBUTIONOFPRICESANDHOUSINGAMENITIESSIMILARLY,HOUSINGVACANCYRATESCANBEEXPECTEDTODECLINEWHENTHELOCALECONOMYIMPROVESANDASTHEDEMANDFORHOUSINGINCREASESFINALLY,RESIDENTIALCONSTRUCTIONANDBUILDINGACTIVITYARERESPONSIVETOHOUSINGPRICES,VACANCYRATES,ANDTHEHEALTHOFTHELOCALE

6、CONOMYASHIGHERINCOMESINCREASETHEDEMANDFORHOUSING,PRICESAREBIDUPNEWCONSTRUCTIONBECOMESMOREPROFITABLE,2INDUCINGSUPPLIERACTIVITYDWELLINGSTHATWOULDOTHERWISEBECOMEVACANTREMAINOCCUPIED,ANDSOMEDWELLINGSTHATWOULDOTHERWISELEAVETHEHOUSINGSTOCKARERENOVATEDFORCONTINUEDUSETHISPAPERCONSIDERSTHEINTERRELATIONSHIPAM

7、ONGTHESETHREEFORMSOFECONOMICBEHAVIORINTHECONTEXTOFLOCALHOUSINGMARKETSWEMODELTHERELATIONSHIPAMONGTHEPRICESOFOWNEROCCUPIEDHOUSING,VACANCYRATES,ANDHOUSINGSUPPLIERACTIVITYINRESPONSETOTHEEXOGENOUSFACTORS,WHICHAFFECTTHEFORTUNESOFTHEREGIONALECONOMYWEALSORECOGNIZETHEIMPORTANCEOFLOCALLANDUSEANDBUILDINGREGULA

8、TIONSINAFFECTINGTHEOPERATIONOFTHEOWNEROCCUPIEDHOUSINGMARKETOURANALYSISUSESUSMETROPOLITANAREASMSASASUNITSOFOBSERVATION,ANDWEFOLLOWAPANELOF74MSASOVERTHE13YEARPERIOD,19871999THEPANELINCLUDESALLUSMETROPOLITANAREASFORWHICHANNUALDATAAREAVAILABLEONTHEPRICESOFOWNEROCCUPIEDHOUSING,ONTHEVACANCYRATESINSINGLEFA

9、MILYHOUSING,ANDONSUPPLIERACTIVITYIE,THENUMBEROFPERMITSISSUEDFORCONSTRUCTIONOFNEWSINGLEFAMILYHOUSINGINTHISPAPER,WEDEVELOPAMODELRELATINGEXOGENOUSCHANGESINREGIONALEMPLOYMENTANDINCOMES,CONSTRUCTIONCOSTSANDMACROECONOMICCONDITIONSTOTHESEMEASURESOFTHEHEALTHOFHOUSINGMARKETSPRICES,VACANCIES,ANDNEWCONSTRUCTIO

10、NTHEMODELISESTIMATEDINSEVERALVARIANTS,ANDWESIMULATETHERESPONSIVENESSOFTHEHOUSINGMARKETTOLOCALECONOMICCONDITIONSTHEMODELINDICATESTHESTRONGINTERDEPENDENCYBETWEENTHESTATEOFTHEMACROECONOMY,THESTATEOFTHEREGIONALECONOMY,ANDOUTCOMESINTHEHOUSINGMARKETTHERESULTSALSOSUGGESTTHEKEYROLEOFLOCALREGULATIONINAFFECTI

11、NGHOUSINGOUTCOMESINSECTION2BELOW,WERELATEOURWORKTOPREVIOUSATTEMPTSTODEVELOPREGIONALMODELSOFTHEHOUSINGMARKETSECTION3PRESENTSANOVERVIEWOFTHEDATAANDTHEMETHODOLOGYWEUSE,ASWELLASTHERELATIONSHIPSAMONGTHEVARIOUSMEASURESOFTHEHOUSINGMARKETSECTION4PRESENTSDATASECTION5PRESENTSOURSTATISTICALRESULTSANDTHESIMULAT

12、IONSBASEDUPONTHEMSECTION6ISABRIEFCONCLUSION2ANTECEDENTSASIMPLEMODELOFSUPPLYANDDEMANDATTHEREGIONALLEVELMOTIVATESTHECHOICEOFVARIABLESTOEXPLAINOUTCOMESINTHEHOUSINGMARKETOVERTIMEHOUSINGDEMANDISA3FUNCTIONOFPRICESANDINCOMESANDPERHAPSDEMOGRAPHICVARIABLESASWELLHOUSINGSUPPLYISAFUNCTIONOFPROFITABILITY,WHICHDE

13、PENDSUPONHOUSINGPRICESANDINPUTPRICES,INCLUDINGTHECOSTSOFLABOR,MATERIALS,FINANCING,ANDREGULATIONSINHIBITINGNEWCONSTRUCTIONVACANCYRATESINEXISTINGHOUSINGREFLECTTHEDIFFERENCEBETWEENAGGREGATESUPPLYANDDEMANDINTHEMARKETINANYPERIODSEVERALEARLYPAPERSFOLLOWINGREID,1962MUTH,1960,1968ANALYZEDVARIATIONSINHOUSING

14、PRICESACROSSMETROPOLITANAREAS,FOCUSINGONTHEREDUCEDFORMOFRELATIONSHIPBETWEENTHEPRICESOFOWNEROCCUPIEDHOUSINGANDMETROPOLITANCHARACTERISTICSUSINGTHESEMODELS,ITISEASYTODESCRIBETHEDEVELOPMENTOFHOUSEPRICES,BUTITISQUITEDIFFICULTTOMAKEINFERENCESABOUTSTRUCTURALPARAMETERSORABOUTCAUSATIONINCONTRAST,AFEWMORERECE

15、NTSTUDIESHAVEINVESTIGATEDSTRUCTURALRELATIONSHIPSAMONGHOUSINGMARKETOUTCOMESPOTERBA1984ANALYZEDTHEINTERACTIONBETWEENMOVEMENTSINPRICESANDHOUSINGSTOCKS,MODELEDASATWOEQUATIONSYSTEMTHEGROWTHOFHOUSINGPRICESISREPRESENTEDASAFUNCTIONOFTHEDIFFERENCEBETWEENCURRENTPRICESANDIMPUTEDRENTALS,WHILETHEGROWTHOFTHEHOUSI

16、NGSTOCKISRELATEDTOREALHOUSINGPRICESASAPROXYFORPROFITABILITYANDTOTHESIZEOFTHECURRENTSTOCKINTHISSIMPLESTOCKFLOWMODEL,THEREARENOLEADSORLAGSVACANCIESINTHEHOUSINGSTOCKAREIGNOREDDIPASQUALEANDWHEATON1994SPECIFIEDAMODELFORHOUSINGDEMANDINWHICHTHEPRICEOFOWNEROCCUPIEDHOUSINGWITHINAGIVENHOUSINGMARKETISAFUNCTION

17、OFTHECURRENTSTOCKOFSINGLEFAMILYHOUSINGRELATIVETOTHENUMBEROFHOUSEHOLDS,THEIRAGEEXPECTEDHOMEOWNERSHIPRATE,THECOSTOFRENTINGRELATIVETOOWNINGINTHEMARKET,ANDTHEAVERAGEHOUSEHOLDINCOMEWITHINTHEMARKETINASECONDEQUATION,THEAUTHORSMODELEDHOUSINGSTARTSASAFUNCTIONOFCURRENTPRICES,COSTS,ANDTHESTOCKOFHOUSING,ASWELLA

18、SEMPLOYMENTANDTIMEONTHEMARKETFORNEWUNITSMOSTOFSUPPLIERBEHAVIORINTHISMODELISEXPLAINEDBYEXOGENOUSCHANGESININTERESTRATES,EMPLOYMENTLEVELS,ANDTIMEONTHEMARKETTHEAUTHORSINTERPRETTHISLATTERVARIABLEASEVIDENCEOFSLOWADJUSTMENTINHOUSINGMARKETS3OVERVIEWOFTHEMODELOURMODELOFREGIONALHOUSINGMARKETSISBASEDUPONAPANEL

19、OFUSMETROPOLITAN4AREAS,INCLUDINGALLMARKETSFORWHICHANNUALDATAONHOUSINGPRICES,VACANCIES,ANDCONSTRUCTIONACTIVITYAREAVAILABLEFOROWNEROCCUPIEDHOUSINGOFTHE334METROPOLITANHOUSINGMARKETSMSASINTHEUNITEDSTATES,CONSISTENTMEASURESOFHOUSEPRICESAREAVAILABLEFOR120,BEGINNINGIN1975ANNUALMEASURESOFTHESTOCKOFOWNEROCCU

20、PIEDHOUSING,VACANCYRATES,ANDSUPPLIERACTIVITYIE,BUILDINGPERMITSAREAVAILABLEFORONLY75MSASANDONLYFORTHEPERIOD19871999OURANALYSISISBASEDUPON962OBSERVATIONSREPORTINGAPANELOF74MSASOBSERVEDANNUALLYDURINGTHEPERIOD19871999OUREMPIRICALMODELCONSISTSOFTHREEEQUATIONSDESCRIBINGTHEMOVEMENTOFHOUSINGPRICES,HOUSINGSU

21、PPLY,ANDVACANCIESINTHEMARKETFOROWNEROCCUPIEDHOUSINGINTHISSECTION,WEDESCRIBETHEKEYFEATURESOFTHEMODEL,DEFERRINGISSUESRELATEDTODATA,MEASUREMENT,ANDESTIMATIONTECHNIQUETOSECTIONIVNEWHOUSINGSUPPLYINCONTRASTTOTHEANALYSISOFHOUSINGDEMANDANDPRICEFORMATION,LESSISKNOWNABOUTTHEBEHAVIOROFHOUSINGSUPPLYINPART,THISR

22、EFLECTSLIMITATIONSINAVAILABLEDATAANDINCONCEPTUALMODELSROSENTHAL,1999DIPASQUALE1999HASSUMMARIZEDTHREEEMPIRICALDIFFICULTIESINTHEHOUSINGSUPPLYLITERATUREFIRST,ESTIMATEDHOUSINGSUPPLYELASTICTIESVARYWIDELYSECOND,PRICEDOESNOTSEEMTOBEASUFFICIENTSTATISTIC,ANDOTHERMARKETINDICATORSAREQUITEIMPORTANTINEXPLAININGH

23、OUSINGSUPPLYTHIRD,CONSTRUCTIONLEVELSSEEMTORESPONDQUITESLUGGISHLYTOCONSTRUCTIONCOSTSANDOUTPUTPRICESFURTHERMORE,THEREAREDISAGREEMENTSABOUTTHEAPPROPRIATESPECIFICATIONOFMODELSOFHOUSINGSUPPLYINEARLYRESEARCH,NEWHOUSINGSUPPLY,MEASUREDBYEITHERHOUSINGSTARTSORBYPERMITS,ISSPECIFIEDASAFUNCTIONOFTHELEVELOFPRICEA

24、NDTHELEVELOFCONSTRUCTIONCOSTPORTERBA,1984TOPELANDROSEN,1988DIPASQUALEANDWHEATON,1994MORERECENTLY,HOWEVER,MAYERANDSOMERVILE2000DEVELOPEDANEMPIRICALMODELLINKINGNEWHOUSINGSUPPLYTOCHANGESINPRICESANDCOSTSTHEYARGUETHATTHEEQUILIBRIUMLEVELOFHOUSINGPRICEMATCHESTHESTOCKOFHOUSINGSUPPLIEDWITHTHETOTALDEMANDFORHO

25、USINGSPACE,WHICHIMPLIESTHATNEWCONSTRUCTIONWILLHEAFUNCTIONOFCHANGESINHOUSINGPRICE,ASWELLASCHANGESINOTHERVARIABLES,SUCHASCONSTRUCTIONCOSTSWEFOLLOWMAYERANDSOMERVILLE,MODELINGNEWHOUSINGSUPPLYASAFUNCTIONOF5CHANGESINPRICESANDINPUTCOSTS,ASWELLASMACROECONOMICCONDITIONSOURMODELISSTTTTCVP321WHERESTISNEWHOUSIN

26、GSUPPLY,VTREPRESENTSVACANCIES,CTISINPUTCOSTSFORLABORANDMATERIALS,FTISFINANCINGCOSTS,REGTISTHERESTRICTIVENESSOFLOCALREGULATION,ANDXREPRESENTSOTHERSUPPLYSHIFTERSWEMEASURENEWSUPPLYASTHEANNUALDIFFERENCEINTHESTOCKOFHOUSINGTHESTOCKISCONSTRUCTEDBYADDINGBUILDINGPERMITSTOTHESTOCKINTHEPREVIOUSYEARAGAIN,LOWERC

27、ASELETTERSINDICATELOGARITHMICDIFFERENCESNOTETHATTHISSPECIFICATIONOFTHESUPPLYEQUATIONINCLUDESTWOENDOGENOUSVARIABLES,CHANGESINHOUSINGPRICESANDCHANGESINVACANCIESWEEXPECTTHATINCREASESINHOUSINGPRICESWILLLEADTOANINCREASEINSUPPLIERACTIVITYINCREASESININPUTCOSTSLABOR,MATERIALSORFINANCIALCOSTSWILLREDUCESUPPLI

28、ERACTIVITY,ANDINCREASESINVACANCIESWILLALSOREDUCESUPPLIERACTIVITYFINALLY,ASNOTEDABOVE,THEREISAMPLEEVIDENCETHATSUPPLYADJUSTMENTTOCHANGESINPRICEISSLUGGISHANDSLOWWERECOGNIZETHISBYINCLUDINGAVARIABLEMEASURINGTHELAGGEDCHANGEINHOUSINGPRICESINTHEEMPIRICALMODELVACANCIESINOWNEROCCUPIEDHOUSINGTHEEARLYLITERATURE

29、ONVACANCYINTHERENTALHOUSINGMARKETANALYZEDTHEEMPIRICALRELATIONSHIPBETWEENSOME“NATURAL“RATEOFVACANCYANDHOUSINGRENTS,BASEDONREDUCEDFORMMODELSEUBANKANDSIRMANS,1979ROSENANDSMITH,1983THEORETICALEXPLANATIONSOFVACANCYFOCUSONTHEFRICTIONSOFSEARCH,GIVENTHEIDIOSYNCRATICPREFERENCESOFHOUSEHOLDSANDTHEHETEROGENEITY

30、OFHOUSINGUNITSARNOTT,1989WHEATON,1990READ,1997INTHESEMODELS,SOMELEVELOFVACANCYFACILITATESTHESEARCHPROCESSBYHOUSINGDEMANDERSSELLERSCHARGEHIGHERPRICESTOCOVERTHECOSTOFMAINTAININGVACANCIESTHESESEARCHMODELSPROVIDEINSIGHTSONTHEUNIQUEASPECTSOFHOUSINGMARKETS,ANDTHEYPROVIDEARATIONALEFORHOUSINGVACANCIESINMARK

31、ETEQUILIBRIUMMORERECENTLY,GABRIELANDNOTHAFT2001DISTINGUISHEDTWOCOMPONENTSOFVACANCY,INCIDENCE,ANDDURATION,ARGUINGTHATTHEINCIDENCECOMPONENTISAFFECTEDBYPOPULATIONMOBILITYANDTHEDURATIONCOMPONENTBYSEARCHCOSTSANDTHEHETEROGENEITYOFTHEHOUSINGSTOCKTHEIREMPIRICALRESULTSSUGGESTTHATRESIDENTIALRENTSAREMORERESPON

32、SIVETOTHEINCIDENCECOMPONENTTHANTHEDURATIONCOMPONENT6IFAHOMEOWNERCHOOSESTOKEEPAUNITVACANTRATHERTHANSELLINGINRESPONSETOANOFFER,THISISADECISIONTOHOLDAREALOPTIONTHATIS,WHENTHEOWNEROFAVACANTUNITDECIDESTOKEEPAUNITVACANTRATHERTHANSELLINGITATTHECURRENTMARKETPRICE,THISISBECAUSESHEBELIEVESTHATWAITINGISWORTHWH

33、ILEWAITINGISMOREWORTHWHILEIFPRICESAREEXPECTEDTOINCREASEANDIFTHEVOLATILITYOFHOUSINGINVESTMENTRETURNSISLARGER4DATAANDMETHODOLOGYDATATHEECONOMETRICEVIDENCEPRESENTEDINTHEFOLLOWINGSECTIONISBASEDONDATAPIECEDTOGETHERFROMAVARIETYOFSOURCESWITHONEEXCEPTION,THEDATASERIESAREPUBLICLYAVAILABLE,ANDMOSTAREAVAILABLE

34、ONLINEASNOTEDABOVE,WEANALYZETHREEDEPENDENTVARIABLESPRICES,VACANCIES,ANDSUPPLIERACTIVITYSINGLEFAMILYHOUSINGPRICESAREMEASUREDUSINGMETROPOLITANHOUSINGPRICEINDICESPUBLISHEDBYTHEUSOFFICEOFFEDERALHOUSINGENTERPRISEOVERSIGHTOEHEOTHEINDEXISDEFINEDBYTHEWEIGHTEDREPEATSALESMETHODUSINGALLSINGLEFAMILYHOUSESWHOSEM

35、ORTGAGESHAVEBEENPURCHASEDORSECURITIZEDBYFREDDIEMACORFANNIEMAESINCE1975HOMEOWNERVACANCYRATESBYMSAAREAVAILABLEANNUALLYFROMTHEUSBUREAUOFTHECENSUSWEMEASURESUPPLIERACTIVITYBYTHENUMBEROFBUILDINGPERMITSISSUEDFORSINGLEFAMILYHOUSINGINEACHMSAMOSTPRIORRESEARCHONHOUSINGSUPPLYISBASEDUPONAGGREGATEHOUSINGSTARTSTOP

36、ELANDROSEN,1988DIPASQUALEANDWHEATON,1994MAYERANDSOMERVILE,2000INFORMATIONONHOUSINGSTARTSISSIMPLYUNAVAILABLEATTHEMETROPOLITANLEVELHOWEVER,ITISWELLKNOWNTHATTHEAGGREGATESERIESONPERMITSTRACKSHOUSINGSTARTSVERYCLOSELYEVENSON,2001SOMERVILE,2001OTHERSTUDIESANALYZINGMETROPOLITANDATAEG,POTERBA,1991DRIEMANANDF

37、OLLAIN,2003MAYERANDSOMERVILE,2000ALSORELYUPONBUILDINGPERMITSDATAONBUILDINGPERMITSFORSINGLEFAMILYHOUSESBYMSAARERECORDEDBYTHEUSBUREAUOFTHECENSUSANDAREAVAILABLEONLINEFROMTHEREALESTATECENTERATTEXASA房产价格,空置率和居民住宅建设的影响。我们的3个方程式模型体现了区域经济条件，收入，和住宅房屋市场的雇佣关系变化的重要性。结果还首次提供了确凿的证据证明空置率对业主房市场的房价和供应商的活动有重要的影响。结果也证

38、明材料,劳动和资本成本变化的重要性,和用标准的脉冲响应模型对新供应模拟模式的影响,同时也反映了市场对外源冲击和不同地方的参数差异反应滞后。结果还显示,地方性法规对市场反应地区收入冲击的模式有重要的影响。1简介当地的住房市场和住宅市场的产出反映本地经济条件。房价的隐藏是由于在不断扩大的都市居民有更好的就业机会和更高的收入。收入分配的改变主要体现在房价的分配和住房待遇的分配。同样,当地经济改善和住宅需求的增加时，住宅的空置率就会降。最后,住宅建设和建筑活动对房价,闲置率和当地经济的健康有重要的影响。高收入增加了住宅的需求,因此房价被抬高买新建房成了有利可图的事,诱导着供应商的活动。有些闲置的住宅等

39、待着被重新利用，有些住宅通过整修被重新利用。本文讨论了住宅房屋市场的3种经济行为的内在关系。我们建立业主房,空置率和住宅供应商活动与外源因数想对应的关系影响了区域经济的模型。我们也认识到区域土地的使用和建筑条例对业主房市场有重要的影响。我们把美国大都市MSAS作为观察单位,并遵从美国74了城市在13年内（19871999）的变化数据。这个组数据包括所有美国城市业主房的价格，住宅的闲置率和供应商的活动例如,允许建设的房屋的数量。在本文中,我们提供一种涉及区域就业和收入,建设成本和宏观经济条件的变化和测量健康住宅市场的模型,这些措施包括房价,闲置,和新的建筑。该模型有几个变体,我们假设房屋市场和区

40、域经济条件是有关联的。该模型表明国家宏观经济，区域经济和房地产市场的产出之间有很大的相互依赖性。结果还表明地方性法规在房产市场的产出方面起着关键的作用。9在下面的第2节,我们试图建立房地产市场的区域模型。第三节概述了的数据和方法论的,以及各种测量房地产市场措施的关系。第四节给出数据。第5条给出重要的统计结果和基于这些数据的模拟。第6部分是总结。2前言先是一个简单的模型。一个地方的供给与需求水平刺激对房地产市场产出的解释选择不同的变量。房屋的需求是一个关于物价和收入的函数,也许人口统计学的变量。房屋供应是一个关于利润的函数,这取决于房价和投入的价格,投入的价格包括劳动力成本、材料、资金、约束新建

41、房的法规。闲置率的存在反应了在任何时期总供给和总需求之间存在差异。一些早期报告FOLLOWINGREID,1962MUTH,1960,1968分析了在大城市里房价的变量,把业主房的价格和大城市的特点的关系简约化。使用这些模型,很容易描述房价的变化,但去推论结构参数或者原因是非常困难的。相反,更多的最近的研究报告调查了内在结构和房地产市场产出之间的关系。POTERBA1984分析了住房数量和价格的相互关系，把它们转化为2个方程式的关系。房屋价格的增长是一个关于现在价格和估算租金之间不同关系的函数,而增长的住宅数与真正的房价作为盈利的替代和流通股票的价格是有关系的。在这个简单的股票和现金的模型中,

42、没有线索或滞后效应。闲置房的股票忽略不计。DIPASQUALE和惠顿1994说明了房屋的需求的一个模型,业主房的价格在某个特定的房地产市场环境中是一个关于当前住宅房的股票与家庭的数量,他们预期的住房率,在目前市场上房屋出租的费用,以及该市场平均家庭收入的函数。在第二个方程中,他们定义房产的开工率是一个关于市价、成本和住房股票,以及市场上就业和时间的函数。在该模型中大多数供应商的行为说明了市场上的利率、就业水平和时间是外在的变化因素。他们把最后的变量解释为住房市场缓慢调整的证据。3模型的概述我们的区域房地产市场模型是依据美国大城市地区的数据。这个组数据包括所有美国城市业主房的价格，住宅的闲置率和

43、业主房的建设。在美国334个大城市房地产市场（MSAS）中，从1975年开始有120个房地产市场采取房价一致的措施。在19871999期间只有75个房地产市场把业主房的股票，闲置率，供应商的活动（例如，建筑许可证）当做年度措施。我们的分析是基于19871999期间74个大城市市场的962组年度观察值。我们的实验模型包括关于房价的波动,住房供给,以及业主房空缺的三个方10程式。在这一节中,我们主要描述这个模型的延期数据,测量,和估计技术的特点。新建房屋的供应与住房需求及价格形成理论相对应的是很少人知道的住房供应行为理论。在某种程度上,这反映了可利用的数据和概念模型的局限ROSENTHAL,199

44、9。DIPASQUALE1999归纳了在房屋供应文献中三个实证的困难点。首先,假设房屋供应的数据有着很大的不同。第二,在解释住房供应理论中，价格并不是一个足够的因素,其他的市场指标却是非常的重要。第三,建设水平对建设成本和产出的价格反应迟缓。此外还有关于住房供应模型恰当说明的不同意见。在早期的研究中，新房屋供应、房产许可的标准都是根据价格水平和施工成本规定的PORTERBA,1984TOPEL和ROSEN,1988DIPASQUALE和WHEATON,1994。最近,MAYER和SOMERVILE2000发明了一种把新住房供应与价格及成本的变化相连接的实验模型。他们认为住房价格的平均水平与住房

45、空间总需求的住房供应股票相适应,它暗示新房屋的建设以房价的变化,以及其他可变量的变化如施工成本为依据的。我们依据MAYER和SOMERVILL的新住房供给为价格变动和投入的费用以及宏观经济条件的函数建模。我们的模型是STTTTCVP321ST是新房屋的供应、VT代表空缺,CT劳动投入成代表劳动成本和材料的投入,FT是资金成本、REG是地方性法规,X代表其他供应。我们测量在每年不同的住房股票下的新建房屋的供应股票由上一年增加的建筑许可证决定。然后,小写字母表示对数的差异。注意这个供应方程式说明包括两个内在的变量,房价的变化和空缺房的变化。我们希望提高住房价格可以增加供应商的活动。增加投入的成本劳

46、动力、材料或资本和空缺房会降低供应商活动。最后,如上所述,我们有充分的证据证明供应调整对价格的变化反应滞后。我们通过一个变量测量房价的滞后变化的模型认识到这一点。业主房的空置早期关于空置租赁房产市场的文献基于简化模型EUBANK和SIRMANS,1979年,ROSEN和SMITH,1983年分析了“自然”的空缺和房屋租金的实验关系。有关空缺的理论解释关注找房过程中的摩擦，要考虑到家庭的特质和房屋单位的不均匀性ARNOTT,1989WHEATON,1990,READ,1997。在这些模型中,某种程度上的空缺促进了住房需求者寻找的进程,卖方收取更高的价格来抵消闲置房的损失。11这些寻找模型表现了独

47、特的住房市场,和在市场均衡条件下合理的住房闲置。最近,GABRIEL和NOTHAFT2001把住房闲置分为2个部分,发生率和持续时间。他们认为发生率与人口的流动有关,持续时间与找房的费用和住房股票的非均质性有关。他们的研究结果表明,住宅租金更能反映发生率而非持续时间。如果房主选择保持房屋的闲置,而不是售出房屋,这个决定才是真正的选择。那就是说，当一个人决定保持空房屋而不依据当前的市场价格出售,这是因为她认为等待是有价值的。如果房价提高，房屋投入回报波动大，那么等待会得到更多的收入。4数据和方法论数据在下一章节中的经济依据是基于各种各样来源的数据的拼凑。但有一个例外,这些数据系列是可以供公共使用

48、的,而且大多数人可以在网上搜索到。如上所述,我们分析三个因变量价格、空缺和供应商的活动。独栋房屋价格可由美国联邦住房企业监察办颁布的大城市住房价格指数衡量。这一指数根据加权重复购买理论定义并从1975年开始所有独栋房的房贷款要被联邦政府所持有和确认。MSA业主空置率每年由美国统计局公布的人口普查决定的。我们由在MSA中独幢房的建筑许可证衡量供应商活动。大多数先前的房屋供应的研究都是基于房产开发的集合TOPEL和ROSEN,1988年,DIPASQUALE和罗森惠顿,1994,迈耶,和SOMERVILE,2000年。房产开发信息在纽约大城市是不可信的。然而,众所周知,新屋开工许可证的序列却非常密

49、切,2001EVENSON,2001。SOMERVILE”其他的研究分析城市数据例如,POTERBA,1991年成立DRIEMAN和FOLLAINSOMERVILE迈耶,2004201,2000也依照建筑许可证。独幢房的建筑许可证的数据由美国统计局公布并在德州农工大学房产中心的网站上可以利用。我们也使用在三个公式中若干其他外在变量衡量区域经济的重要性。这些变量包括人均收入、YT、就业、EMT,人均未就业转移支付,UNT。这些数据都可以在REIS数据库找到。在表格中有一系列变量，定义和符号。脚注I和T代表了由于MSA和时间的变化而变化的变量。5总结12本文利用一组美国大城市在过去14年里的区域住房市场的数据评估了国家和区域的经济条件。我们估算业主房的价格和闲置率和新建独幢房的建筑许可证的外在条件的影响。这些参数的估计在二级最小平方的误差组成成分的框架内。实证模型提供一套连贯严整的经验和仿真结果。这些结果证实了区域经济的条件,收入和就业的变化对区域房屋市场的有重大的影响,同时他们也认为调节的滞后进程对市场的供给和需求有重要的影响。结果还首次提供了确凿的证据说明业主房市场的空缺对房价和供应商的活动有重大的影响。结果也证明了新的供应和材料，劳动力，资本这些变量对增加独幢房的供应有重大的影响。模拟训练利用标准的脉冲响应分析证明在市场在区域条件下对内在的冲击