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

有或没有房地产经纪人的住宅房地产讨价还价和价格确定模型的协作研究

• 批准号: 0635806
• 负责人: John Rust
• 金额: $ 15.04万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0635806&HistoricalAwards=false
• 关键词: Collaborative; Research; Models; Bargaining; Price

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.

提案编号：0635806 机构：马里兰大学帕克分校 NSF 项目：经济学 首席研究员：Rust, John 标题：有或没有房地产经纪人的住宅房地产讨价还价和价格确定模型的合作研究。在现代经济中，住宅房地产在财富和国内生产总值中占据很大份额。 此外，大多数家庭拥有自己的房屋，房屋的出售和/或购买往往是家庭从事的最大的金融交易。令人惊讶的是，很少有模型可用于分析住房交易过程。本研究将研究住房市场的交易过程。 它将开发住房市场中买家、卖家和中介机构行为的计算可处理模型，并使用个人住房交易的高频微观数据来估计模型，其中包括标价如何随时间修改、每次访问的信息PI 将在美国和英国收集，并在很长一段时间内收集大量房屋样本的讨价还价结果。该模型有 3 个代理人——卖方、买方和房地产经纪人，他们在几轮讨价还价中进行互动。房地产经纪人被建模为能够获得技术和数据（MLS），可以提高买家的到达率，并将潜在买家与卖家进行匹配。这项研究扩展、应用并实证实施了动态决策和讨价还价的理论在不完全信息下对住房市场进行描述，以描述这些大市场的运行和效率。这是将动态决策应用于房地产市场的首次尝试，是对现有文献的重大贡献。 了解房地产市场的交易过程本身就很重要。 此外，更好的住宅房地产市场分析模型还可以带来潜在的公共政策好处。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，以确定其是否设置了不公平的准入壁垒，特别是限制进入 MLS，以维持巨额房地产佣金。 这项研究的结果在此类诉讼中可能非常有用。分析将扩展到包括其他房地产中介机构以及是通过房地产中介出售还是由业主出售的内生选择。这将使研究人员能够研究与房地产经纪人相关的行业组织问题，包括房地产合同和佣金的内生决定。使用美国和英国的数据，PI 可以揭示影响不同形式的住房市场组织相对效率的机构、法律和习俗。这项研究的结果还应该帮助家庭和房地产经纪人了解在制定房屋销售或购买策略时所发挥的权衡。