The Microfoundations of Housing Market Dynamics

房价动态的微观基础(0721136)帕特里克·拜尔和克里斯托弗·蒂明斯住宅建筑业的波动在经济商业周期中发挥着核心作用。在低利率的推动下，1997-2006年间美国房价的飙升，以及随后的建设热潮，通常被认为是这段时期经济扩张的推动力。而且，对房地产市场大幅回调的担忧，在美联储随后决定货币政策的过程中发挥了核心作用。然而，尽管研究人员已经记录了房地产市场动态的许多重要的宏观经济方面，但人们对个人购房者和卖家在房地产繁荣-萧条周期中不同时间点的行为知之甚少。特别是，关于当地房地产繁荣-萧条周期的性质和持续时间的根本决定因素的一些问题仍然悬而未决。该项目的智力价值来自于其设计的两个新特征，这使得分析能够提供关于住房市场动态的新见解。首先是建立一个新的数据集，该数据集使用15年期间数百万住房交易的详细信息。第二是开发一种易于处理的社区选择模型，允许在动态的背景下研究个人的购房和售房决策。该项目的实证应用遵循两条主要调查路线，试图改善我们对(I)住房价格波动的根本原因和(Ii)推动城市种族隔离动态的根本因素的理解。第一线研究的主要目标是提供住房市场的微观基本经济要素(即，支配个人买卖决定的因素)与总体市场动态(例如，价格的积极持续性、当地住房泡沫等)之间的明确联系。尤其重要的问题是，在当地房地产周期的不同时间点，个人购房者和卖家是否对房地产市场动态有理性的预期。换句话说，个人是否在当地房地产繁荣时期变得非理性乐观，而在低迷时期变得过度悲观？第二条研究路线包括三篇论文，旨在提高我们对推动种族隔离动态的微观经济力量的理解。前两篇论文分别对住房交易中的种族歧视和种族小费进行了新的实证检验。每一篇论文都使用交易数据的详细性质来设计测试，与迄今文献中出现的测试相比，这些测试受到的混淆问题要少得多。这一系列研究的第三篇论文使用社区选择的估计动态模型来更好地理解价格偏好与预期以及社区动态在种族隔离的演变和持续中的作用。该项目具有许多更广泛的影响。作为该项目的一部分开发的新数据集和方法可能适用于研究住房市场和城市中更广泛的动态现象。此外，加深对住房市场波动的性质和原因的了解，对联邦和地方两级的政策制定都有直接的好处。

AbstractThe Microfoundations of Housing Price Dynamics (0721136)Patrick Bayer and Christopher TimminsFluctuations in home building play a central role in economic business cycles. Fueled by low interest rates, the upsurge in housing prices in the US between 1997-2006, and the subsequent building boom, is generally considered to have been a driving force in the expansion of the economy over that period. And, worries about a major housing market correction have played a central role in the determination of monetary policy by the Fed in the subsequent period. Yet while researchers have documented many of important macroeconomic aspects of housing market dynamics, little is understood about the behavior of individual home-buyers and sellers at various points in a real estate boom-bust cycle. In particular, a number of questions about the fundamental determinants of the nature and length of local real estate boom-bust cycles remain open. The intellectual merit of the project derives from two novel features of its design, which permit the analysis to deliver new insights concerning housing market dynamics. The first is the construction of a new dataset that uses detailed information on millions of housing transactions over a 15-year period. The second is the development of a tractable model of neighborhood choice that permits the study of individual home-buying and selling decisions in a dynamic context. The empirical applications in the project follow two main lines of inquiry, seeking to improve our understanding of (i) the underlying causes of housing price fluctuations and (ii) the underlying factors driving the dynamics of racial segregation in cities. The principal goal of the first line of research is to provide a clear linkage between the microeconomic primitives of the housing market (i.e., the factors governing individual buying and selling decisions) and the aggregate market dynamics (e.g., the positive persistence of prices, local housing bubbles, etc). Of particular importance is the question of whether individual home buyers and sellers have rational expectations about housing market dynamics at different points in a local real estate cycle. In other words, do individuals become irrationally exuberant during local real estate booms and unduly pessimistic during downturns? The second line of research includes three papers that aim to improve our understanding of the microeconomic forces driving the dynamics of racial segregation. The first two papers develop new empirical tests for racial discrimination in housing transactions and racial tipping, respectively. Each paper uses the detailed nature of the transaction data to devise tests that are subject to far fewer confounding issues than those that have appeared in the literature to date. The third paper in this line of research uses the estimated dynamic model of neighborhood choice to better understand the roles of preferences versus expectations about price and neighborhood dynamics in the evolution and persistence of racial segregation.This project has a number of broader impacts. The new dataset and methodologies developed as part of the project are potentially applicable to the study of a much wider set of dynamic phenomena in housing markets and cities. Moreover, an increased understanding of the nature and causes of housing market fluctuations has direct benefits for the setting of policy at both the federal and local levels.