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Commercial Real Estate: Valuation

Paper Session

Friday, Jan. 5, 2018 8:00 AM - 10:00 AM

Loews Philadelphia, Washington B
Hosted By: American Real Estate and Urban Economics Association
  • Chair: Erasmo Giambona, Syracuse University

Riskiness of Real Estate Development: A Perspective from Urban Economics & Option Value Theory

Anil Kumar
,
Aarhus University
David Geltner
,
Massachusetts Institute of Technology
Alex Minne
,
Massachusetts Institute of Technology

Abstract

Conventionally, investment in real estate development is viewed as being riskier than investment in stabilized property assets. In this paper we define a new construct for urban economic analysis which puts this conventional wisdom in a new light. We call the new construct, the “Development Asset Value Index” (DAVI). The DAVI is a value index for newly-developed properties (only in a geographical property market. It tracks longitudinal changes in the Highest & Best Use (HBU) value of locations as reflected in gross physical capital formation, and it reveals developer and landowner behavior taking advantage of the optionality inherent in land ownership. In particular, the DAVI reflects developers' use of the timing flexibility in the exercise of the call option represented by the right (without obligation) to (re)develop the property. We empirically estimate the DAVI for commercial property (i.e., central locations) and compare it with the corresponding traditional transaction price based hedonic Property Asset Price Index corrected for depreciation (PAPI), in the same geographical market. We believe that the difference primarily reflects the realized value of timing flexibility in land development. For our test cities of New York and Los Angeles, we find that the DAVIs display greater value growth and are smoother and less cyclical than their corresponding PAPIs. This suggests that development may be riskier than stabilized property investment only due to leverage effects. We also find that development density (Floor/Area Ratio) is an increasing function of the location value.

Dissecting the Value Premium in Publicly Traded Real Estate Markets

Mariya Letdin
,
Florida State University
Stace Sirmans
,
University of Arkansas

Abstract

Do highly discounted, low price-to-NAV REITs outperform because they are riskier or because they are underpriced? This paper contributes to this debate and studies the nature of the value premium in the REIT market. A simple discounted cash flow model shows that a REIT's Price-to-NAV ratio is theoretically driven by expectations regarding asset productivity, safety, and growth opportunities collectively referred to "quality". While low Price-to-NAV REITs do indeed tend to be low quality, we find that it is not their low quality that explains their outperformance. In fact, only the component of Price-to-NAV unexplained by quality that drives the value premium in REITs. We further show that a strategy that buys high quality, low price-to-NAV REITs and sells short low quality, high price-to-NAV REITs generates more than 13 per year, outperforming a simple price-to-NAV value strategy by 6% per year. This strategy's temporal performance is mostly unrelated to economic and stock market conditions and strongly negatively related to sentiment in the real estate market. Overall, the evidence supports a mispricing explanation for the price-to-NAV value premium in the REIT market.

Benchmarking Local Commercial Real Estate Returns: Statistics Meets Economics

Liang Peng
,
Pennsylvania State University

Abstract

This paper proposes a new approach to overcome extreme data scarcity in estimating local real estate return indices. This approach reduces the number of parameters by imposing testable structural assumptions on return dynamics, and extracts and uses information on common return dynamics from properties in the whole national market in estimating local indices. This paper further proposes three tests to evaluate economic merits of indices. Applying both the index estimation approach and the three tests to an unique dataset of commercial real estate returns in the U.S. market, this paper estimates metro level return indices and finds that the indices successfully capture unique local return dynamics and help explain local property returns both in- and out-of sample.

Do REITs Use Dividends to Signal Large Future Earnings Increases?

James Shilling
,
DePaul University
William Cheung
,
Waseda University
Scott Fung
,
California State University-East Bay

Abstract

Finance theory suggests that an increase in dividend payout serves as an unambiguous signal to market that the firm anticipates higher future earnings. Yet, because it is often unclear just what an increase in dividend payout signals and how it does so, testing the theory using a sample of ordinary firms proves difficult in general. In this paper, we focus on the application of dividend signaling theory to the case of Real Estate Investment Trusts (REITs). REIT managers have valuable information about the firm’s re-leasing spread profit, and will, in the presence of asymmetric information, choose to convey this insider’s information to outside investors in periods of when the market lease rate is high or is expected to increase through dividend changes. Consistent with our theoretical predictions, we find substantial evidence of a positive relation between dividend changes and future earnings changes for REITs with high investment spending in periods when current lease rates are expected to increase in the future. Further, we find very little evidence of dividend signaling in all other cases, even when we do a detailed analysis of REITs with low investment spending in periods when current lease rates are expected to increase in the future. The evidence clearly supports the dividend signaling hypothesis, thus contributing to our understanding of whether changes in dividends have information content.
Discussant(s)
Albert Zevelev
,
Baruch College
Gianluca Marcato
,
University of Reading
Steven Bourassa
,
Florida Atlantic University
Eva Steiner
,
Cornell University
JEL Classifications
  • G3 - Corporate Finance and Governance
  • G1 - General Financial Markets