The Microfoundations of Housing Market Dynamics

住房价格动态的微观基础（0721136）帕特里克拜尔和克里斯托弗蒂明斯住房建设的波动在经济商业周期中起着核心作用。在低利率的推动下，1997-2006年美国房价飙升，以及随后的建筑热潮，通常被认为是这一时期经济扩张的推动力。 而且，对房地产市场大幅调整的担忧在美联储随后的货币政策决策中发挥了核心作用。 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宏观经济方面，但对于真实的房地产繁荣-萧条周期中各个点上的个人购房者和卖家的行为却知之甚少。 特别是，关于当地真实的房地产繁荣-萧条周期的性质和长度的基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其设计的两个新颖特征，这使得分析能够提供有关住房市场动态的新见解。 首先是构建一个新的数据集，该数据集使用了15年期间数百万房屋交易的详细信息。第二个是开发一个易于处理的邻里选择模型，允许在动态环境中研究个人的房屋买卖决策。 该项目中的实证应用遵循两条主要调查路线，旨在提高我们对（i）房价波动的根本原因和（ii）推动城市种族隔离动态的根本因素的理解。第一条研究路线的主要目标是在住房市场的微观经济原语（即，支配个人购买和销售决定的因素）和总的市场动态（例如，价格的积极持续性、当地房地产泡沫等）。 特别重要的是，在当地真实的房地产周期的不同阶段，个人购房者和卖房者是否对房地产市场动态有理性预期。 换句话说，在当地真实的房地产繁荣时期，个人是否会变得非理性地繁荣，而在低迷时期，个人是否会变得过度悲观？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。前两篇论文分别为住房交易中的种族歧视和种族小费开发了新的实证检验。每一篇论文都利用交易数据的详细性质来设计测试，这些测试受到的混淆问题远远少于迄今为止文献中出现的问题。第三篇论文在这条线的研究使用的邻居选择的估计动态模型，以更好地理解的角色的偏好与预期的价格和邻里动态的演变和种族隔离的持久性。 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，对联邦和地方各级的政策制定有直接好处。

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.