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REITs

Paper Session

Friday, Jan. 5, 2018 2:30 PM - 4:30 PM

Loews Philadelphia, Washington A
Hosted By: American Real Estate and Urban Economics Association
  • Chair: Walter Boudry, Cornell University

REIT Executive Compensation and Firm Risks

William Hardin III
,
Florida International University
Zhonghua Wu
,
Florida International University
Zifeng Feng
,
Florida International University

Abstract

This paper examines REIT executive compensation in the REIT S&P index era with a focus on the relationship between compensation and firm risks. Using a sample of U.S. equity REITs from 2001 to 2015, we find that total compensation of REIT executives rose significantly in the new era and a large portion of the increase came from the rise in stock grants. Moreover, consistent with principal-agent theory, total executive compensation of REITs is positively correlated with the lagged stock price risk and credit risk measures, indicating that REIT executives working at riskier firms are compensated with higher pay. Furthermore, compared with financial firms, REIT executives seem to be compensated for higher risks largely through cash-based compensation, not through equity-based compensation. These results imply that a subtle difference may exist among firms in terms of how executives are compensated for risks. Finally, stock grants awarded to REIT executives are strongly
correlated with the lagged firm performance. Taken together, this paper provides new evidence to the debate about the pay and risk relationship in the cross-section, suggesting that risks play an important role in the optimal compensation contract design. Also, the findings in the paper suggest that REITs have improved their compensation plans by closely linking executive pay to the firms’ long-term financial performance.

Dividend Regulations and Investment

Manish Gupta
,
University of Nottingham

Abstract

When external funds are costly, the joint effect of a simultaneous increase in internal funds and agency costs on investment is theoretically indeterminate. The REITs Modernization Act (2001) by lowering REITs' dividend distribution requirement from 95% to 90% resulted in an increase in internal funds, which, in turn, aggravated agency costs. Internal funds, if invested in positive net present value (NPV) projects, can result in value creation for investors, but, instead, if invested in negative NPV projects, can also result not only in lower returns for investors but also in a reduction of capital stock in the economy. Thus, there is a tradeoff between value creation for investors due to an increase in investment in positive NPV projects owing to an increase in internal funds and value destruction due to escalated agency costs triggered by the same increment in internal funds. The Act therefore provides a rare opportunity to empirically evaluate the unanswered question. To gauge agency costs, this paper uses the presence of a blockholder as a proxy for monitoring. Employing differences-in-differences methodology we find that less-monitored REITs indulge in overinvestment. Furthermore, we find that less-monitored REITs, compared with monitored firms, increase cash holdings but do not accordingly reduce their reliance on external funds. The findings suggest the existence of principal-agent conflicts (free cash flow hypothesis).

Spatial Dependence and Real Estate Returns

Bing Zhu
,
University of Reading
Stanimira Milcheva
,
University College London

Abstract

When analyzing asset prices in isolation, the classical asset pricing models only account for the time-series variation of the asset with the factors. However, we show that valuable information can be extracted if we account for spatial dependence across the assets when pricing real estate companies. We extend the factor model in Fama and French (2012) to include a spatial term and estimate a spatial factor model. We model the spatial linkages across real estate company returns using the physical distance between their properties. We find that the spatial factor model is not rejected and the spatial parameter is significant. The spatial factor model performs better than the factor model, substantially improving the model explaining real estate returns. Proximity across the property holdings of real estate companies can be used to model prices for listed real estate companies in addition to size, style and momentum factors. The spatial factor model is then used to disentangle direct and indirect spillover effects through idiosyncratic and market shocks respectively. We find that the spillover effect increases during the global financial crisis and can explain up to 30% of total return variation in the US. UK. and EU markets.

Economic Depreciation in the Property Value: Cross-sectional Variations and Their Implications on Investments

Jiro Yoshida
,
Pennsylvania State University and the University of Tokyo

Abstract

This study compares the rate of property value depreciation between different property types, locations, and countries by using commercial and residential data for the U.S. and Japan. The property-level depreciation rate is larger if a property is commercial, newer, denser, located in a smaller city, more distant from the central business district, and in Japan. A larger depreciation rate directly decreases appreciation returns and increases the equilibrium income returns (i.e., cap rates). The depreciation rate for the structure component also varies significantly by property type and country; approximately 7% for residential properties and 10% for commercial properties in Japan in contrast with 1% for residential structures in the U.S. This study also demonstrates the difference in the estimation methods and the importance of correcting survivorship biases. These results serve as important inputs for the analysis of real estate investment, consumer choice of housing, sustainability, and macro economy.
Discussant(s)
Alan D. Crane
,
Rice University
S. McKay Price
,
Lehigh University
Jamie Alcock
,
University of Sydney
David Geltner
,
Massachusetts Institute of Technology
JEL Classifications
  • G3 - Corporate Finance and Governance
  • R3 - Real Estate Markets, Spatial Production Analysis, and Firm Location