Scandinavian Working Papers in Economics
Working Paper Series,
Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance
No 19/2: The relationship between property transaction prices, turnover rates and buyers' and sellers' reservation price distributions
Åke Gunnelin () and Olof Netzell
Additional contact information
Åke Gunnelin: Department of Real Estate and Construction Management, Royal Institute of Technology, Postal: Department of Real Estate and Construction Management, Royal Institute of Technology, Teknikringen 10B, 100 44 Stockholm, Sweden
Olof Netzell: National Board of Housing, Building and Planning, Postal: Department of Real Estate and Construction Management, Royal Institute of Technology, Teknikringen 10B, 100 44 Stockholm, Sweden
Abstract: This paper analyzes the relationship between movements in property transaction prices and movements in the underlying reservation price distributions of buyers and sellers and how these movements are linked to time varying turnover rate. A main conclusion in previous research is that transaction prices lag changes in buyers’ reservation price distribution and that an index tracking transaction prices is less volatile than an index tracking buyer reserves. We show that our less restrictive model of search and price formation reverses the volatility result in previous papers in realistic scenarios, i.e., transaction prices may be more volatile than underlying buyer reserves. We model transaction prices and turnover rates as functions of the moments of buyers’ and sellers’ reservation price distributions, the search intensity and the average bargaining power among buyers and sellers respectively. We derive the probability density function of transaction prices as a function of these parameters and hence a Maximum-likelihood estimator of the parameters, which serves as a new method of estimating indexes tracking movements in reservation price distributions from transaction data. We perform simulations where we show that the Maximum-likelihood estimator works as intended.
Keywords: Price formation; Transaction price index; Index tracking; Reservation price distributions; Turnover rates; House price volatility
23 pages, April 5, 2019
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