Price formation and the appraisal function in real estate markets

Abstract

A real estate market model characterized by incomplete information, costly search, and varying expectations is presented. The model describes a self-selection process for market participants and a distribution of transaction prices. These transaction prices, which arise from a Nash equilibrium, can be expressed as a noisy signal, reflecting incomplete information as well as the conditions of sale. The appraiser's role is formalized as the task of signal extraction. The model emphasizes the differences in information available to individual buyers and sellers, who make transactions only infrequently, and the appraiser, whose expertise comes from observing many transactions. Based on the model, it is shown that contrary to popular perceptions, appraisal smoothing is consistent with an optimal updating strategy.Even in light of the development of general models of market imperfections, the simple competitive market model remains the dominant tool in real estate analysis. However, despite its popularity, the competitive market model provides an inadequate portrayal of the trading environment in real estate markets. Specifically, three important features of real estate markets distinguish the price formation process from that implied by the standard model:(1) Participants in real estate markets often have incomplete information about the attributes of the purchase, and decisions to buy and sell must often be made based on this partial knowledge.(2) Given the heterogeneity and fixity of real estate, some period of costly search must be incurred by potential buyers. (3) Trades are decentralized, and market prices are the outcome of pairwise negotiations. This price determination process represents a significant departure from Walrasian auction.This article introduces a model of real estate transactions which incorporates these three features, all of which play a crucial role in determining the eventual transaction price. The model is also useful in understanding the role of property appraisal in real estate markets and the techniques for making appraisals. This application to the appraisal function can be quite important. In real estate markets, purchases and sales of individual properties occur only infrequently. Thus the current market value of the stock of real capital, or the worth of any investor's holdings of real estate, must be inferred from limited information about recent transactions.

Commercial Real Estate Prices and Stock Market Returns: An International Analysis

“…1 To the best of our knowledge, the only other multi-country study is Goetzmann and Watcher (1995) Quan and Quigley (1991) for further discussion of this). To understand why the buildings that drop in price the most are less likely to be sold during the initial downturn consider the situation facing someone who bought a building for $50 million with a $40 million loan.…”

Optimal two-stage pricing strategies from the seller’s perspective under the uncertainty of buyer’s decisions

“…For instance, Quan and Quigley (1991), and Biswas and McHardy (2007) adopt the seller's viewpoint in their research. Furthermore, Stigler (1962); Rothschild (1974); Gastwirth (1976); Quan and Quigley (1991); Bruss (2003) and Egozcue et al (2013) explore the problem from the buyer's perspective. Pricing under different seller's risk attitudes has been studied in the real estate literature as well.…”

“…Although our general model is not limited to any specific price distribution, in our numerical illustrative considerations, we assume that the prices follow the gamma distribution, which is a very reasonable assumption, extensively used in the literature (see, e.g., Pratt et al 1979;Quan and Quigley 1991;Hong and Shum 2006). In particular, Quan and Quigley (1991) characterize the density function of the reservation price of a group of self-selected buyers using this distribution.…”

“…In particular, Quan and Quigley (1991) characterize the density function of the reservation price of a group of self-selected buyers using this distribution. Hong and Shum (2006) apply the gamma distribution to model search costs, including time, energy and money spent on researching products, or services, for purchasing.…”

Finding a Good Price in Opaque Over-the-Counter Markets

“…First, rejected offers in real estate markets can often be recalled, as modeled by Quan and Quigley (1991) and Cheng, Lin, and Liu (2008), whereas rejected offers in markets for OTC financial securities lapse quickly. Second, buyers and sellers in real estate markets trade with each other directly, sometimes hiring brokers as agents to speed up the search process (Yinger (1981) and Yavas (1992)).…”