Options, Depreciation, and Performance in Commercial Real Estate

Paper Session

Sunday, Jan. 8, 2017 1:00 PM – 3:00 PM

Sheraton Grand Chicago, Ontario
Hosted By: American Real Estate and Urban Economics Association
  • Chair: Robert Connolly, University of North Carolina-Chapel Hill

Simultaneous Implication of Credit Risk and Embedded Options in Lease Contracts

Henry Huang
,
National Central University
Chuang-Chang Chang
,
National Central University
Hsiao-Wei Ho
,
Shih-Chien University
Yildiray Yildirim
,
Baruch College

Abstract

We propose an integrated reduced-form model to calculate the values of adjustable-rate leases with an embedded cancellation option, a purchase option, and default risk. Most previous researches use a structural-form model to value lease contracts. With this method, however, it is difficult to identify the critical region of exercising embedded options in empirical study. As an alternative, the reduced form model developed in this paper is able to value lease contracts without setting boundary conditions, and it thereby provide an implementable framework to handle several state variables in empirical study. To show the value of embedded options and comparative statics, we conduct a numerical analysis. In our numerical example we show that for a 30-year lease contract, the lessor will offer a 15% discount in the initial rent for the rate adjustment, but charge an additional 12.16% for the purchase option, 33.14% for the cancellation option, and 20.73% for default risk compared with the non-defaultable one without embedded options. This result suggests that ignoring embedded options in valuing a lease contract leads to significant pricing errors. Thus, our model provides a flexible and implementable framework to value complex lease contracts.

Optimal Compensation and Value Added in Commercial Real Estate Brokerage

Walter Dlima
,
Pennsylvania State University

Abstract

This paper presents a model characterizing a Pareto optimal brokerage agreement between a seller of a property and a real estate broker who has private information about the market valuation of the property. Under the assumption that the broker faces increasing costs of securing higher offers for the property, the model predicts that an optimal brokerage commission should be a convex function of the size of the offer that the broker secures for the property. In addition, we present a novel sample of actual contracts from a major commercial real estate broker that is consistent with the predictions of the model.

Commercial Buildings Capital Consumption and the United States National Accounts

Sheharyar Bokhari
,
Massachusetts Institute of Technology
David Geltner
,
Massachusetts Institute of Technology

Abstract

Commercial buildings are a major asset class, over $16 trillion of nonresidential structure value on a net current cost basis, 30 percent of the value of the stock of all produced assets according to the BEA. Yet, commercial buildings depreciation has not been comprehensively and rigorously studied since the highly influential work of Hulten and Wykoff almost 40 years ago. This study updates and extends that earlier work, and applies the findings to the national accounts, including demonstration of price indices for commercial structures and land. The paper is based on a combined database of over 112,000 transactions of commercial buildings and development sites, and over 17,000 property records of capital improvement expenditures, spanning 2001-14. The paper’s major contributions to the previous published literature include: (i) More flexible and precise estimation of the net depreciation value/age profile, allowing much finer characterization of the building life cycle; (ii) Explicit quantification of the land value component of commercial property value, enabling net depreciation to be quantified as a fraction of remaining structure value; (iii) Inclusion of capital improvement expenditures, allowing estimates of “gross depreciation” (total capital consumption), which includes the cost of capital improvements as well as “net depreciation” (which is the loss in real value as a function of structure age even after and including capital improvements); and (iv) Application and implications of the paper’s net and gross depreciation findings to and for the national accounts, including BEA quantification of capital consumption and commercial structure fixed asset value in the National Balance Sheets, as well as demonstration of how to use the paper’s findings to construct pure price and quantity indices for commercial structure and land values as necessary for the national accounts.

Real Estate Returns by Strategy: Have Value-Added and Opportunistic Funds Pulled Their Weight?

Joseph Pagliari
,
University of Chicago

Abstract

Private-market (commercial) real estate strategies broadly fall into three categories: core, value added and opportunistic. They are thought to align themselves along a risk/return continuum, with core representing the low-risk/low-return option and opportunistic representing the high-risk/high return option (with value-added falling in between). However, an empirical examination, based on the 17-year period examined here, indicates that the net investment returns from indices of value-add and opportunistic funds have – on a risk-adjusted basis – underperformed the net returns available from an index of core funds. In concluding that value-added and opportunistic funds have failed to pull their weight, this article departs from standard capital asset pricing models in two important respects: the total risk – rather than the systematic risk – of the returns from such indices is used and the cost of borrowing increases – rather than an assumed constant cost of borrowing (at the risk-free rate) – with the degree of leverage. While the first departure has no substantive effect (but it is consistent with how lenders price risky debt), the second departure lowers the estimate of the underperformance of non-core funds (which would have otherwise resulted were debt cost costs assumed to be constant).
Discussant(s)
Richard Buttimer
,
University of North Carolina-Charlotte
Maisy Wong
,
University of Pennsylvania
Jiro Yoshida
,
Pennsylvania State University
Lynn Fisher
,
Mortgage Bankers Association
JEL Classifications
  • G1 - Asset Markets and Pricing
  • R3 - Real Estate Markets, Spatial Production Analysis, and Firm Location