Asset productivity, local information diffusion, and commercial real estate returns

Abstract

An extensive literature finds that indices of returns on equity real estate investment trusts (REITs) predict return indices in the private commercial real estate (CRE) market. Using a novel geographically weighted proxy for the quarterly performance of the property types within the local markets in which an REIT is invested, or property portfolio return (PPR), we find a “private predicts public” result in a cross‐sectional, firm‐level context. This finding suggests that geographically dispersed information and investors’ limited attention can delay timely stock price adjustments. Our findings also suggest that it is the diffusion of information about “local” price changes, rather than local supply elasticities, regulatory constraints, the degree of local information risk, current rental income, or local liquidity that predicts REIT returns. The PPRs associated with REIT allocations to major “gateway” markets are more predictive of REIT returns than the PPRs produced by allocations to secondary and tertiary markets. This study improves our understanding of the speed at which “local” information about the perceived productivity of a firm's assets is capitalized into stock prices.

Location density, systematic risk, and cap rates: Evidence from REITs

“…In contrast, we suggest a simple rationale for why properties in different locations may have different betas, and provide evidence consistent with that conjecture. Thus, our work contributes to the growing literature on property location characteristics and associated real estate investment performance (see Feng & Wu, 2021;Ling et al, 2021;Ling et al, 2021aLing et al, , 2021bWang & Zhou, 2020). However, to our knowledge, we are the first to focus on the relationships between zip code-level location density and commercial real estate investment outcomes.…”

Local Beta: Has Local Real Estate Market Risk Been Priced in REIT Returns?

“…More recently, Fisher et al (2020) study the locational characteristics, particularly the density, and show that REITs with property holdings in high-density locations experience higher NOI growth, earn higher risk-adjusted returns, and carry higher systematic risk than their otherwise comparable peers in low-density locations. Ling et al (2020a) propose a novel measurement to calculate a "property portfolio return" for individual REITs based on the geographic distribution of properties and private real estate returns (using MSA level NCREIF data). They then adjust these returns for REIT systematic risk factors (national sensitivity to real estate and financial market variables) and find that the risk-adjusted property portfolio returns (characterised as alpha) have predictive power in explaining future REIT returns.…”

“…They argue this shows a slow information diffusion process from private to public markets (in contrast to previous research that finds price discovery effects from public to private markets). Unlike Ling et al (2020a), our study focuses on the beta risk of the local real estate markets. Our work has a stronger focus on risk and, specifically, the impact of local real estate market volatility on the required returns of REIT investors.…”

“… Indeed, Fisher et al (2020) do not find significant impact of the local real estate market risk measured by the local economic conditions on the REIT returns. Instead, zip-code level employment density influences REIT performance Ling et al (2020a). show that the private information of the local property market, which is measured by the risk-adjusted property portfolio returns, can predict the cross-sectional return of REITs, indicating the diffusion of asset information to the stock price.…”

“…Various measures have been employed. Some literature focuses on the 'quality' of the location, including exposure to the so-called 'Gateway' markets (Ling et al, 2018a), the risk-adjusted property market portfolio returns (Ling et al, 2020a), and locational characteristics such as density and locational economic risks (Fisher et al, 2020). Other literature investigates the distance of properties from firm headquarters (Ling et al, 2018b;Milcheva et al, 2021).…”