Findings from the 2015 Institutional Real Estate Capital Allocations Monitor

Since 2013, the Baker Program in Real Estate and Hodes Weill & Associates have co-sponsored the Institutional Real Estate Capital Allocations Monitor (the “Allocations Monitor”). The Allocations Monitor was created to conduct a comprehensive annual assessment of institutional allocations to real estate investments through analyzing trends and collecting survey responses of institutional portfolios and allocations by region, type, and size of institution. The Allocations Monitor reports on the role of real estate investments in institutional portfolios, and the impact of institutional allocation trends on the investment management industry.

Living with Terminal Capitalization Rates: A Look at Real Estate Valuation Model Parameter Setting

This paper examines assumptions about future prices used in real estate applications of DCF models. We confirm both the widespread reliance on an ad hoc rule of increasing period-zero capitalization rates by 50 to 100 basis points to obtain terminal capitalization rates and the inability of the rule to project future real estate pricing. To understand how investors form expectations about future prices, we model the spread between the contemporaneously period-zero going-in and terminal capitalization rates and the spread between terminal rates assigned in period zero and going-in rates assigned in period N. Our regression results confirm statistical relationships between the terminal and next holding period going-in capitalization rate spread and the period-zero discount rate, although other economically significant variables are statistically insignificant. Linking terminal capitalization rates by assumption to going-in capitalization rates implies investors view future real estate pricing with myopic expectations. We discuss alternative specifications devoid of such linkage that align more with a rational expectations view of future real estate pricing.

2016 Real Estate Industry Leader Profile: MaryAnne Gilmartin

[Excerpt] Cornell University and the Baker Program in Real Estate are pleased to announce the 2016 Real Estate Industry Leader Award recipient: MaryAnne Gilmartin, President & CEO of Forest City Ratner Companies. MaryAnne’s leadership in the real estate industry has made a powerful and positive impact on society as a driving force behind several of the highest-profile, largest-scale additions to the urban landscape of New York City.

Real Estate Case Competitions

Real Estate is by nature a hands-on business in which real-world experience and new challenges are the best teacher. With this in mind, graduate real estate education has embraced case competitions as a way to apply education-based learning to real world project simulation. In recent years, teams from Cornell have consistently stood out in these competitions, making impressions and forming relationships that they will carry with them over their careers. In this issue of the Review, we recognize a composite of previous winners of the four major real estate-focused case competitions, and look back on what was a very successful year for case competition teams at Cornell. The case competitions draw students from all the constituent programs of Real Estate at Cornell, including the Baker Program, Johnson Graduate School of Management, City and Regional Planning, Architecture, and Landscape Architecture.

Autonomous Vehicles and Commercial Real Estate

Hardly a day goes by without the release of a handful of news stories about autonomous vehicles (or AVs for short). The proverbial “tipping point” of awareness has been reached in the public consciousness as AV technology is quickly becoming the new focus of firms from Silicon Valley to Detroit and beyond. Automation has, and will continue to have far-reaching implications for many human activities, but for driving, the technology is here. Google has been in talks with automaker Ford (1), Elon Musk has declared that Tesla will have the appropriate technology in two years (2), GM is paired-up with Lyft (3), Uber is in development-mode (4), Microsoft and Volvo have announced a partnership (5), Apple has been piloting its top-secret project “Titan” (6), Toyota is working on its own technology (7), as is BMW (8). Audi (9) made a splash by sending a driverless A7 concept car 550 miles from San Francisco to Las Vegas just in time to roll-into the 2016 Consumer Electronics Show. Clearly, the race is on.

Joint Leverage and Maturity Choices in Real Estate Firms: The Role of the REIT Status

We explore the interdependence of leverage and debt maturity choices in Real Estate Investment Trusts (REITs) and unregulated listed real estate investment companies in the U.S. for the period 1973-2011. We find that the leverage and maturity choices of all listed real estate firms are interdependent, but in contrast to industrial firms, they are not made simultaneously. Across the different types of real estate firms considered, we find substantial differences in the nature of the relationship between leverage and maturity. Leverage determines maturity in non-REITs, whereas maturity is a determinant of leverage in REITs. We suggest that the observed differences reflect the effects of the REIT regulation, rather than solely being a function of real estate as the underlying asset class. We also present novel evidence that the relationship between leverage and maturity in both firm types can be used to moderate the effects of other exogenous financing policies.

Macroeconomic Risk Factors and the Role of Mispriced Credit in the Returns from International Real Estate Securities

The benefits of diversification from international real estate securities are generally well established. However, the drivers of international real estate securities returns are insufficiently understood. We jointly examine the empirical implications of three major international asset pricing models that account for broad macroeconomic risk factors. In addition, we develop the hypothesis that an indicator of mispriced credit is significant in explaining the time series variation in international real estate securities returns. We employ the returns generated by a large sample of firms from 20 countries over the period 1999 to 2011 to test our hypothesis. We find support for the predictions of the major international asset pricing models. We also find evidence in favour of our hypothesised link between local credit conditions and the performance of international real estate securities.

On the Capital Structure of Real Estate Firms

The leverage and debt maturity choices of real estate companies are interdependent, and are not made separately as is often assumed in the literature. We use three-stage least squares (3SLS) regression analysis to explore this interdependence for a sample of listed U.S. real estate companies and Real Estate Investment Trusts (REITs) traded between 1973 and 2006.We find substantial differences in the nature of the relationship between leverage and maturity for the two firm types. Leverage is a determinant of maturity for non-REITs, whereas maturity is a determinant of leverage for REITs. We also find that the drivers of capital structure choices in real estate companies and REITs clearly reflect the effects of the REIT regulation.

Limited Partnerships and Reputation Formation

This paper analyzes the optimal quality decision of a producer in a multi-period setting with reputation effects. Using a unique database of returns on real estate limited partnerships (RELPs), we empirically examine alternative theoretical predictions of optimal producer strategy. In particular, we test whether the producers in our market invest in reputation building by initially selling high quality goods and then lowering quality. Using a variety of statistical tests, we find evidence consistent with reputation building, both in the aggregate and for individual developers.

HOTVal Toolkit

**************************************************************************** Scroll down to "Additional Files" to access the HOTVal Toolkit. **************************************************************************** HOTVal is a hotel valuation spreadsheet based on a regression model discussed in the Center for Real Estate and Finance at Cornell called Cornell Hotel Indices: Second Quarter 2012: The Trend is Our Friend by Crocker H. Liu, Adam D. Nowak, and Robert M. White, Jr. The model which will be continually updated, provides a rough estimation of the value of a hotel property once the user inputs information on whether the hotel is a large or small hotel, the year and quarter of the valuation, the state where the property is located, the number of rooms, the number of floors, the land area of the hotel property, the actual age of the hotel and whether the hotel is located in a Gateway city. For the first three inputs as well as the last input, if the user clicks on a cell highlighted in yellow, a pull down menu will appear to expedite inputting. The model is provided as a free public service by The Center for Real Estate and Finance at the School of Hotel Administration at Cornell University to academics and practitioners on an as-is, best-effort basis with no warranties or claims regarding its usefulness or implications. The estimates should be considered preliminary and subject to revision. *This October 2016 version updates the previous Hotel Valuation model, published in 2012 , provides valuation estimates up to and including the third quarter of 2016.