Improving US real estate returns with cost segregation
| DOI | https://doi.org/10.1108/JPIF-02-2019-0021 |
| Pages | 334-344 |
| Date | 05 April 2019 |
| Published date | 05 April 2019 |
| Author | Ivan C. Roten,Jarrod G. Johnston |
| Subject Matter | Real estate & property,Property management & built environment |
Improving US real estate returns
with cost segregation
Ivan C. Roten and Jarrod G. Johnston
Department of Finance, Banking and Insurance,
Appalachian State University, Boone, North Carolina, USA
Abstract
Purpose –US taxing authorities allow property investment to be separated into components. The purpose of
this paper is to demonstrate how the classification of property affects the amount and timing of depreciation.
Increased and accelerated depreciation increases after-tax cash flows and investor returns.
Design/methodology/approach –This paper explains traditional methods to analyze real estate
investments and introduces modified methods that include the effect of taxes to improve the estimate of the
potential return to the investor. Commonly used property classification methods are evaluated and
projections are used to demonstrate the impact on investor returns.
Findings –Modified methods may improve return estimates and appropriately classifying property
improves investor returns.
Practical implications –After-tax cash flows should be used to analyze potential real estate investments
and properties should be accurately classified to maximize returns.
Originality/value –This paper demonstrates how to analyze real estate investments and maximize returns.
Keywords Taxation, Asset valuation, Real estate, Property valuation, Cost segregation, Investor returns
Paper type Conceptual paper
1. Introduction
Real estate generates positive or negative returns for investors through annual cash flow,
adjusted net worth and price change. Investors should strive to optimize the benefits while
reducing the risk of investing in an illiquid asset. Real estate also increases the
diversification of typical portfolios. Patrick and Conway (1988) found that real estate
investments have a low correlation to stocks and bonds, concluding that real estate provides
a positive risk/return trade-off. MacKinnon and Al Zaman (2009) determined the optimal
investment portfolio should include a 17 percent or higher allocation to real estate. They also
found the benefits of real estate increase with investment horizon and direct real estate
investment is preferable to real estate investment trusts.
Many investors require the expected rental income of a potential real estate investment to
exceed the operatingexpenses and debt service if the investment is leveraged. When making
this calculation, it is essential to have a reasonable estimate of the vacancy rate. The annual
debt serviceincludes both interest and principalpayments on borrowed funds. The amountof
borrowing has a substantial impact on the estimated return calculations. Positive cash flows
are more likely when debt is avoided. However, a higher level of debt increases returns by
reducing the amount invested. Storms (2001) showed the importance of low interest rates on
real estate returnsregardless of the amount of leverage used. Shillingand Wurtzebach (2012)
found that high real estate returns depend on leverage and market conditions.
Separating the value of property into its components is difficult and subjective. Hendriks
(2005) found the commonly used apportionment methods are unreliable and argues that
property should not be separated into its components. Ozdilek (2016) defended the
separability thesis for residential properties and suggested methods to improve reliability.
Boyd and Boyd (2012) supported the market comparison approach for land valuation and
recommended improvements. Given that classifying property into its components is
common in the USA and allowed for tax purposes, investors should examine how property
classification, or cost segregation, can increase returns.
Journal of Property Investment &
Finance
Vol. 37 No. 4, 2019
pp. 334-344
© Emerald PublishingLimited
1463-578X
DOI 10.1108/JPIF-02-2019-0021
Received 8 February 2019
Revised 9 March 2019
Accepted 11 March 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1463-578X.htm
334
JPIF
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