Collaborative Research on Models of Bargaining and Price Determination of Residential Real Estate, 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.
