Collaborative Research on Models of Bargaining and Price Determination of Residential Real Estate, with and without Real Estate Agents

提案编号：0635806机构：马里兰州，学院公园NSF计划：经济学首席研究员：锈，约翰标题：合作研究模式的讨价还价和价格确定的住宅房地产，有和没有真实的房地产经纪人。住宅真实的房地产在现代经济体的财富和GDP中占很大份额。 此外，大多数家庭拥有自己的住房，住房的销售和/或购买往往是家庭进行的最大的金融交易。令人惊讶的是，几乎没有模型可以用来分析住房交易过程。本研究将研究住宅市场的交易过程。 它将开发房屋市场中买家，卖家和中介行为的计算模型，并使用个人房屋交易的高频微观数据来估计模型，其中包括如何随着时间的推移修改标价，买家每次访问的信息，以及PI将在美国和英国收集的大量房屋样本在很长一段时间内讨价还价的结果。该模型有3个代理-卖方，买方，和真实的房地产代理谁互动在几个讨价还价轮。真实的房地产经纪人被建模为具有访问的技术和数据（MLS），可以增加买家的到来率，以及匹配潜在的买家seller.This研究扩展，应用，并实证实施不完全信息下的动态决策和讨价还价理论的住房市场，以描述这些大市场的运作和效率。这是首次尝试将动态决策应用于住房市场，对现有文献做出了重大贡献。 了解住房市场的交易过程本身就很重要。 此外，更好的住宅真实的房地产市场分析模型还可能带来公共政策方面的好处。例如，美国司法部目前正在调查美国全国房地产经纪人协会，以确定该协会是否制造了不公平的准入壁垒，特别是在限制进入MLS方面，以维持庞大的真实的房地产佣金。 这项研究的结果可能是非常有用的，在这样的诉讼。分析将扩展到包括其他真实的房地产中介和一个内生的选择是否出售通过一个真实的房地产代理，或出售的业主。这将使研究人员与真实的房地产经纪人，包括内生决定的真实的房地产合同和佣金的产业组织问题。使用来自美国和英国的数据，使PI能够揭示制度，法律和习俗对住房市场不同组织形式的相对效率的影响。这项研究的结果也应该帮助家庭和真实的房地产经纪人了解在制定房屋销售或购买策略时的权衡。

Proposal No: 0635806Institution: University of Maryland, College ParkNSF Program: ECONOMICSPrincipal Investigator: Rust, JohnTitle: Collaborative Research on Models of Bargaining and Price Determination of Residential RealEstate, with and without Real Estate Agents. Residential real estate accounts for a large share of wealth and GDP in modern economies. In addition, the majority of households own their homes and the sale and/or the purchase of a home is often the largest financial transaction a household engages in. Surprisingly, there are few models available to analyze the housing transaction process. This research will study the transaction process in the housing market. It will develop computationally tractable models of the behavior of buyers, sellers, and intermediaries in the housing market, and estimate the models using a high frequency micro data on individual housing transactions, which include how list prices are revised over time, information on each visit by buyers, and outcomes of bargaining for a large sample of homes over a long period of time the PIs will collect in both the US and the UK. The model has 3 agents---seller, buyers, and real estate agents who interact in several bargaining rounds. Real estate agents are modeled as having access to a technology and data (the MLS) that can increase the arrival rate of buyers as well as match potential buyers to sellers.This research extends, applies, and empirically implements theories of dynamic decision making and bargaining under incomplete information to the housing market, in order to describe the operation and efficiency of these large markets. This is the first attempt to apply dynamic decision making to the housing market, a significant contribution to the existing literature. Understanding the transaction process in the housing market is important in itself. In addition, there are potential public policy benefits resulting from better analytical models of the residential real estate market. For example, the U.S. Department of Justice is currently investigating the U.S. National Association of Realtors to determine whether it has created unfair barriers to entry, particularly in restricting access to the MLS, in order to maintain large real estate commissions. The result of this research could be very useful in such litigation.The analysis will be extended to include other real estate intermediaries and an endogenous choice of whether to sell via a real estate agency, or to sell by owner. This will allow researchers industrial organizational issues connected with real estate agents, including endogenous determination of real estate contracts and commissions. Using data from both the US and the UK allows the PIs to shed light on institutions, laws, and customs affect the relative efficiency of different forms of organization of the housing market. The results from this research should also help households and real estate agents understand the trade-offs at play when formulating home selling or buying strategies.