Using Revisions as a Measure of Price Index Quality in Repeat-Sales Models

Abstract

Repeat-sales indexes are the most widely used type of transaction based property price indexes. However, such indexes are particularly prone to revision. When a new period of transaction data becomes available and is used to update the repeat-sales model, all past index values can potentially be revised. These revisions are especially problematical for commercial real estate (as compared to housing), due to the relative scarcity of transaction data and the heterogeneity of the underlying properties. From a methodological perspective, the magnitude of the revisions is a particularly useful measure of the index quality, as it directly reflects both the precision of the index and its practical usefulness in economic and business applications. This paper focuses on index revisions in thin, commercial property markets, the type of market that is most challenging. We present multiple specifications of the repeat-sales model (both existing and new), seeking to reduce revisions. We are able to reduce overall index revisions by more than 50%, compared to more traditional repeat-sales models.

Preferences of Institutional Investors in Commercial Real Estate

“…As a result, we would have to omit a lot of data if we would use property and investor fixed effects. It is well known from indexing literature that only including properties that sold multiple times in the data introduces a bias toward "winners", or "better" properties, see Abraham and Schauman (1991), Shiller (1993), Clapp and Giaccotto (1999), Clapham et al (2006), and Van de Minne et al (2019) for more details on this bias. These random effects "capture" all (non time-varying) unobserved heterogeneity of properties and investors.…”

“…We use two datasets (RCA, and RCA CPPIs) to construct this value. The RCA CPPIs (or Real Capital Analytics Commercial Property Price Indexes in full) are asset price indexes based on a structural time series repeat sales model given in Van de Minne et al (2019). The RCA CPPIs are location and sector (i.e.…”

The Dynamics of Liquidity in Commercial Property Markets: Revisiting Supply and Demand Indexes in Real Estate

“…13 In order to apply the method in thin markets, the time trend in the repeat sales equation is modeled as a random walk with an additional autoregressive (AR) parameter on the returns. As discussed in more depth in Van de Minne et al (2019) an AR representation (inertia) is inherent to the price formation process in the real estate market. We therefore specify the returns in the state equation as an AR process with parameter (ρ):…”

“…We then plug in the difference between the IMRs in the repeat sales model as given by Equation (16). We estimate the repeat sales model in a Bayesian framework similar to the Commercial Property Price Indexes published by RCA (Van de Minne et al, 2019). The difference is that we use normally distributed errors instead of t-distributed errors in order to use the multivariate…”

Daily appraisal of commercial real estate a new mixed frequency approach

“…This paper relates to multiple strands in the literature. First, it fits in the growing field of structural time-series repeat sales models, where time fixed effects (dummy variables) are replaced by a stochastic trend specification (Francke, 2010;Francke & Van de Minne, 2017;Van de Minne et al, 2020). Bollerslev et al (2016) provide an example of daily house pricing in the United States using such a stochastic trend specification.…”