Are All Crises the Same? - Cornell Hotel Indices: Second Quarter 2020
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CORNELL CENTER FOR HOSPITALITY RESEARCH
CORNELL CENTER FOR REAL ESTATE AND FINANCE
Cornell Hotel Indices: Second Quarter 2020:
Are All Crises the Same?
by Crocker H. Liu, Adam D. Nowak, and Robert M. White, Jr.
A
lthough the Great Recession is useful in offering insights into how hotel performance might fare
during a crisis, we show that the current crisis is much worse in terms of risk and the loss of relative
wealth. Not surprisingly while the price of hotels in all regions continue to exhibit negative price
momentum, hotels in the Middle Atlantic and New England regions were particularly hard hit. Hotels in
gateway cities experienced less price decline relative to those in non-gateway cities. Both our moving aver-
age trendlines and standardized unexpected price performance metrics indicate a hemorrhaging in the price
of both large and small hotels. The cost of debt financing spiked in this quarter with financing available only
on refi deals in general. The relative risk premium that lenders require for hotels over and above other com-
mercial real estate has also increased on these refi deals. Our tea leaves suggest that both large and small
hotels should continue to decline in price. This is report number 35 of the index series.
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 1
ABOUT ABOUT
THE AUTHORS
THE AUTHORS
ABOUT THE AUTHORS
Crocker H. Liu is a professor of real estate at the School of Hotel Administration at Cornell where he holds the Robert A. Beck Pro-
fessor of Crocker H. Liu
Hospitality is a professor
Financial of real estate
Management. He at the Schooltaught
previously of Hotel atAdministration at Cornell where
New York University’s Sternhe holds the
School Robert A. Beck
of Business Professorand
(1988-2006) of
at Arizona Hospitality
State Financial
University’s Management.
W.P. Carey He previously
School of taught
Business at New York
(2006-2009) University’s
where Stern
he held School
the of Business
McCord
Crocker H. Liu is a professor of real estate at the School of Hotel Administration at Cornell where he holds the Robert A. Beck Professor of (1988-2006)
Chair. His researchand at Arizona
interests State
are focused
Hospitality on issues
Financial Management. HeUniversity’s
in real estate W.P.
finance,taught
previously Carey
particularly
at New School
York of
topics Business
related
University’s to(2006-2009)
agency,
Stern where
corporate
School hegovernance,
of Business held(1988-2006)
the McCord Chair. His research
organizational
and at Arizona State interests
forms, mar- are
ket focused
efficiency and on issues
valuation. in real
Liu’s estate finance,
research hasparticularly
been topics
published related
in theto agency,
Review
University’s W.P. Carey School of Business (2006-2009) where he held the McCord Chair. His research interests are corporate
of Financialgovernance,
Studies, organizational
Journal
of
focused onforms,
Financial issues market
in realefficiency
Economics, Journal
estate andofvaluation.
finance, Business,
particularlyLiu’s research
Journal
topics hastobeen
of Financial
related agency, published
andcorporate in the
Quantitative Review of organizational
Analysis,
governance, Financial
JournalStudies,
of Law
and Journal
Economics, of Financial
Journal of Economics,
Financial Journal
Markets, of Business,
Journal ofJournal
Corporateof Financial
Finance,
forms, market efficiency and valuation. Liu’s research has been published in the Review of Financial Studies, and Quantitative
Review of Analysis,
Finance, Journal
Real of Law
Estate
Economics, and Economics,
Journal of Journal
Urban of Financial
Economics, Markets,
Regional Journal
Scienceof Corporate
and Urban Finance,
Economics,
Journal of Financial Economics, Journal of Business, Journal of Financial and Quantitative Analysis, Journal of Law Review of Finance,
Journal of Real
Real Estate
Estate
Research,
and Economics,
Economics, andJournal Regional
the Journal ofScience
of Financial Real and Urban
Estate
Markets, Economics,
Finance
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and Economics.
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in realWisconsin
estate fromunder of Texas
Wisconsin under
under Dr.
Dr. James A.Vijay
Dr. James Bawa.
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Graaskamp, andanda Ph.D.
a Ph.D.in finance
in financeand andrealreal estate fromthe
estate from the University of
Texas under Dr. Vijay S. Bawa.
University of Texas under Dr. Vijay Bawa.
Adam D. Nowak is an assistant professor of economics at West Virginia University. He earned degrees in
Adam
Adam D. mathematics
D.Nowak
Nowak is an andassociate
is an economics
assistant at Indiana
professor
professor ofUniversity–Bloomington
economics
of economics at West at in 2006 and
WestUniversity.
Virginia Virginia Heaearned
degreedegrees
University. in near-east
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in degrees
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University–Bloomington Statein University.
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a taught
degree
mathematics and economics at Indiana University–Bloomington in 2006 and a degree in near-east languages and in an introduction
near-east to
languages
and macroeconomics
cultures that same course
year. He and a survey
received a of international
Ph.D. from economics
Arizona State at Arizona State.
University. He
cultures that same year. He received a Ph.D. from Arizona State University. Nowak taught an introduction to Hewaswas the
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research analyst
analystinin
charge ofcharge of constructing
constructing residential
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Urban Economics, Journal of Applied Econometrics, Real
Journal of Applied Econometrics, and the Journal of Real Estate Research. Estate Economics, and the Journal of Real Estate
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Acknowledgments
Acknowledgments
Acknowledgments
We wish to thank Glenn Withiam for copy editing this paper.
We wishtotothank
We wish thank Glenn
Glenn Withiam
Withiam for copy
for copy editingediting this paper.
this paper.
Disclaimer
Disclaimer
Disclaimer
The Cornell hotel indices produced by The Center for Real Estate and Finance at the School of Hotel Administration at Cornell University are
The
The Cornellprovided
Cornell hotel
hotel as a free
indices
indices servicebytoThe
produced
produced academics
by Center andReal
The Center
for practitioners
forEstate
Realand onFinance
an as-is,
Estate best-effort
andatFinance atbasis
the School the with Administration
no warranties
School
of Hotel or
at claims
Cornellregarding
of Hotel Administration itsare
usefulness
at Cornell
University Univer-or
provided as a free service to academics and practitioners on an as-is, best-effort basis with no warranties or claims regarding its usefulness or to
sity are implications.
provided as aThe indices
free are
service not
to audited,
academics and they
and are not necessarily
practitioners on an free of
as-is, errors or omissions
best-effort basis although
with no every
warrantieseffort has
or been
claims made
regarding
its minimize
usefulness
implications. these.are
Theorindices Thenot
implications. reported
audited, indices
The indices for any
are
and they quarter
notnot
are audited,of any
andyear
necessarily theyshould
free ofare beornecessarily
not
errors considered
omissionspreliminary and subject
free of errors
although every to been
or omissions
effort has revision.
although
made to every effort
has been made to minimize these. The reported indices for any quarter of any year should be considered
minimize these. The reported indices for any quarter of any year should be considered preliminary and subject to revision. preliminary and subject to
revision.
2 The Center for Real Estate and Finance • Cornell University
2 The Center for Real Estate and Finance • Cornell University
2 The Center for Real Estate and Finance • Cornell University
CORNELL CENTER FOR REAL ESTATE AND FINANCE Cornell Hotel Indices: Second Quarter 2020 Are All Crises the Same? by Crocker H. Liu, Adam D. Nowak, and Robert M. White, Jr. Using the Great Recession as a Comparison Benchmark I t isn’t necessarily déjà vu. As the point of departure for this quarter’s analysis, we first consider the extent to which the Great Recession is useful in offering insights into hotel performance during this pan- demic. In the process, we look at several salient metrics. Exhibit 1 compares the relative wealth effect from investing $100 in a portfolio of hotel REITs during the Great Recession versus holding the same hotel REIT portfolio during the pandemic. exhibit 1 Relative wealth from investing in hotel REITs CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 3
exhibit 2
Volatility associated with a portfolio of hotel REITs
Sources: NAREIT, Cornell Center for Real Estate and Finance
While it isn’t surprising that an investor suffers a loss lower loss of $18 (decline from $100 to $81.94) if this same
in wealth over either time period, holding the portfolio portfolio is held for the first 23 weeks of the Great Reces-
during the current period results in a wealth decline of sion. Exhibit 2 shows the corresponding volatility associat-
$42.75 ($100-$57.25). In contrast, the investor experiences a ed with holding this hotel REIT portfolio over the first 23
About the Cornell Hotel Indices
In our inaugural issue of the Cornell Hotel Index series, we introduced three new quarterly metrics to monitor real
estate activity in the hotel market. These are a large hotel index (hotel transactions of $10 million or more), a small
hotel index (hotels under $10 million), and a repeat sales index (RSI) that tracks actual hotel transactions. These
indices are constructed using the CoStar and RCA commercial real estate databases. The large and small hotel
indices are similar in nature and construction to the consumer price index (CPI), while the repeat sale hotel index is
analogous to the retail concept of same store sales. Using a similar logic process for hotels, we compare the sales
and resales of the same hotel over time for that index. All three measures provide a more accurate representation of
the current hotel real estate market conditions than does reporting the average transaction prices, because the av-
erage-price index doesn’t account for differences in the quality of the hotels, which also is averaged. A more detailed
description of these indices is found in the first edition of this series, “Cornell Real Estate Market Indices,” which is
available at no charge from the Cornell Center for Real Estate and Finance. Starting with our 2018Q1 issue, we in-
troduced the Gateway Cities Index as a new metric in our hotel analytics arsenal.1 Starting in 2019, we included 30+
days delinquent data for hotel loans that have been securitized into CMBS from Trepp to offer further insights to our
readers on hotel trends. We now have introduced our new Regional Indices to add further granularity to hotel perfor-
mance. We also present updates and revisions to our hotel indices along with commentary and supporting evidence
from the real estate market, together with an examination of the effects of the corona virus epidemic.
1
Cities that we define as gateway cities include Boston, Chicago, Honolulu, Los Angeles, Miami, New York, San Francisco, and Washington DC. For a
general discussion on what constitutes a gateway city, please see Corgel, J.B. (2012), What is a Gateway City?: A Hotel Market Perspective, Center for Real Estate
and Finance Reports, Cornell University School of Hotel Administration (https://scholarship.sha.cornell.edu/cgi/viewcontent.cgi?article=1007&context=crefpubs).
The study of Corgel, J. B., Liu, C., & White, R. M. (2015). Determinants of hotel property prices. Journal of Real Estate Finance and Economics, 51, 415-439 finds
that a significant driver of hotel property prices is whether a hotel is located in a gateway city. The presumption is that hotels (and other real estate) in gateway cities
exceed other cities as IRR generators in part due to a generally stronger economic climate as a result of higher barriers to entry, tighter supply, and/or relatively
stronger performance in terms of revenue per available room than other top cities that are not gateways.
4 The Center for Real Estate and Finance • Cornell University
exhibit 3
CMBS delinquency rate (30+ days) for lodging
Sources: Trepp, Cornell Center for Real Estate and Finance
weeks of the two crises. This exhibit shows that the hotel rate (30+ days) for lodging properties from Trepp, shown
REIT portfolio is more volatile during the current period in Exhibit 3. For the first three months of the financial
(i.e., riskier relative to holding the same portfolio during crisis and pandemic, the delinquency rates were relatively
the recession over the same 23-week window). On average, low. However, in the fourth month of the pandemic the
the weekly volatility is 3.2 percent for the recession versus delinquency rate for hotels rose from 2.7 percent to 19.1
12.1 percent for the pandemic period. percent, compared to a decline in hotel delinquencies
The higher relative risk for hotel properties during from .66 percent to .47 percent during the recession. This
the pandemic is also reflected in the CMBS delinquency delinquency rate rose further, from 19.1 percent to 24.3
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 5
exhibit 4
Corporate credit spread: Baa–Aaa
Sources: St Louis Fed, Cornell Center for Real Estate Finance
percent, in June 2020, while it remained constant during credit spread for the Covid-19 crisis (1.15%) was greater
the fifth month of the recession. The Baa–Aaa corporate than during the recession (.88%). By the eleventh week of
credit spread provides further evidence that the market the pandemic, the credit spread stood at 1.91 percent, com-
perceives the pandemic as a relatively riskier event (Exhib- pared to a .83 percent during the recession. Since then, the
it 4). In good economic times, the credit spread between credit spread has narrowed. Currently, the corporate credit
Baa and Aaa firms is small. As the likelihood of poorer spread is 1.2 percent (compared to 1.01 percent during the
economic conditions increases, however, the probability recession). With respect to the behavior of the default pre-
of default rises more for Baa firms compared to Aaa firms. mium in the real estate market, since new originations on
This in turn results in a wider corporate credit spread. For commercial mortgages have ceased except for refinancing,
the first six weeks of the pandemic, the corporate credit we look at loan originations in the single-family housing
spread was similar to that for the recession over the same market. Subtracting the interest rate on fixed-rate 30-year
time window. Starting in the seventh week, the corporate mortgages from the constant maturity yield on the 10-year
6 The Center for Real Estate and Finance • Cornell University
exhibit 5
Default premium on single family home loans
Sources: St Louis Fed, Cornell Center for Real Estate Finance
exhibit 6
Comparison of RevPAR for the U.S.: financial crisis versus pandemic
Sources: STR, Cornell Center for Real Estate Finance
Treasury bond (default premium), Exhibit 5 reveals that the In terms of the relative performance of hotels over
default premium during the pandemic is 50 basis points these two crisis periods, Exhibit 6 shows that hotel per-
higher on average than the default premium over the same formance was initially similar until about the sixth week,
time period during the financial crisis. using RevPAR data from STR. Subsequent to this, hotels on
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 7
exhibit 7
Comparison of RevPAR for the various regions: financial crisis versus the pandemic
Sources: STR, Cornell Center for Real Estate Finance
average took a deep hit during the pandemic, although RevPAR has continued approximately similar during both periods of crisis. Hotel RevPAR performance
to rise since week 11 (April 11, 2020). As of June 27, 2020 (22nd week), RevPAR is is also similar for various census regions, as displayed in Exhibits 7a and 7b.
8 The Center for Real Estate and Finance • Cornell University
exhibit 7b Comparison of RevPAR for the various regions: financial crisis versus the pandemic (concluded) CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 9
exhibit 8a
Time series hotel performance for seven regions (post-recession)
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
Analysis of Indices through Q2, 2020 Atlantic region (i.e., New Jersey, New York, and Pennsylvania) had the worst
price performance, with the New England region (hotels in Connecticut, Maine,
Hotels in all regions continue to exhibit negative price momentum. For the
Massachusetts, New Hampshire, Rhode Island, and Vermont) following close
most recent quarter (2020Q2), Exhibits 8a and 8b show that hotels in the Middle
behind. Mid-Atlantic hotels declined 19.2 percent quarter over quarter, with a
10 The Center for Real Estate and Finance • Cornell Universityexhibit 8b
Cross-section hotel performance for seven regions (post-recession)
-9.6% QoQ
-27.2% YoY
-5.3% QoQ
-11.3% YoY
-19.2% QoQ
-3.8% QoQ
-25.3% YoY
-18.3% YoY
+3.8% QoQ
-3.9% YoY
-3.8% QoQ
-9.7% YoY
-3.8% QoQ
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics -9.7% YoY
25.3 percent fall year over year, while the price of New England hotels decreased performance (3.8%) for the quarter, all hotels experienced price declines year
9.6 percent quarter over quarter and 27.2 percent year over year. Although hotels over year, continuing the downward trend from the previous period.
in the Mountain states were the only region that experienced a positive price
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 11exhibit 9
Hotel performance for gateway cities versus non-gateway cities
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
Performance of hotels in gateway cities declined less is primarily the result of a rise in the return on invest-
those in than non-gateway cities. Exhibit 9 shows that ed capital (ROIC, aka cap rate) from 5.11 percent in the
the price performance of hotels in gateway cities fell 2.6 previous quarter (2019Q4) to 8.14 percent in 2020Q1. This
percent, compared to the 3.4-percent decline of hotels in increase was relatively greater than the rise in the weight-
non-gateway cities quarter over quarter. Year over year, ed average cost of capital (WACC), which rose 100 basis
the price of hotels in gateway cities fell 4 percent, and it points, from 6.2 percent to 7.2 percent. Taken from a slight-
dropped 12 percent in non-gateway cities, continuing the ly different perspective (no equity financing considered),
negative momentum in the prior year-over-year period the cost of debt financing as measured by the mortgage
(-8.3% for gateways, and -11.4% for non-gateway cities, in constant rose from 5 percent to 6.8 percent over the same
2020Q1). period. Thus, Exhibit 11 shows that leverage is positive in
Hotel investment based on operating performance 2020Q1, the latest quarter for which ACLI data are avail-
was positive for the first quarter of 2020. Our economic able. This means that the return that an investor received
value added (EVA) indicator in Exhibit 10 turned positive from operations exceeded his or her borrowing cost (cost of
at .9 percent in the first quarter of 2020, the latest quarter debt financing).
for which data for the calculation of EVA are available. This
12 The Center for Real Estate and Finance • Cornell Universityexhibit 10
Economic value added (EVA) for hotels
Sources: ACLI, Cornell Center for Real Estate and Finance, NAREIT, Federal Reserve
exhibit 11
Return on investment capital versus cost of debt financing
Sources: ACLI, Cornell Center for Real Estate and Finance
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 13exhibit 12a
Transaction volume (observed) and median sale price
14 The Center for Real Estate and Finance • Cornell Universityexhibit 12b Transaction volume (observed) and median sale price (continued) CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 15
exhibit 12c
Transaction volume (observed) and median sale price (concluded)
Source: Cornell Center for Real Estate and Finance
16 The Center for Real Estate and Finance • Cornell Universityexhibit 13
Median sale price and number of sales (hotels with sale prices of $10 million or more)
Sources: CoStar, Real Capital Analytics
The median price of hotels declined on both a large hotels relative to small hotels on a year-over-year
quarter-over-quarter and a year-over-year basis, continu- basis reveals that the median price of large hotels declined
ing the negative momentum from the prior period. The 15.4 percent compared to a drop of 5.1 percent in the prior
median price based on all hotel transactions (both large period on weaker volume (-84%), while the median price
hotels and small hotels combined) fell 17 percent from the of smaller hotels experienced a steeper decline (-21.7%) on
previous quarter ($3.4M versus $4.1M) on weaker volume weaker volume (-74%). Quarter over quarter, large hotels
(81 transactions for 2020Q2 versus 307 transactions for declined less than 1 percent on weaker transaction volume
2020Q1), as reported in Exhibit 12a, 12b, and 12c. Year over (-79%). The median sale price of small hotels fell more
year (2020Q1 versus 2020Q2), the median price of hotels sharply (-25%), also on weaker volume (-73%). Exhibit 13
fell 15.3 percent compared to a reduction of 23.2 percent in and Exhibit 14 show these year-over-year trends in the
the prior year-over-year period on weaker volume (-75.7% number of transactions for large hotels and small hotels.
compared to +5.9% in the prior period). A comparison of
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 17exhibit 14
Median sale price and number of sales (hotels with sale prices less than $10 million)
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
Our moving average trendlines and our standardized in Exhibit 15, shows that the price of large hotels fell 3
unexpected price (SUP) performance metrics both indi- percent this quarter compared to remaining relatively flat
cate a hemorrhaging in the price of both large hotels and at .13 percent last quarter. Small hotels fell 2.4 percent this
small hotels. Exhibit 16, which graphs the prices reported quarter, compared to a gentler decline of .83 percent last
18 The Center for Real Estate and Finance • Cornell Universityexhibit 15 Hotel indices through 2020, quarter 2 Source: Cornell Center for Real Estate and Finance CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 19
exhibit 16
Hedonic hotel indices for large and small hotel transactions
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
exhibit 17
Year over year change in large-hotel index with a moving average trendline
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
20 The Center for Real Estate and Finance • Cornell Universityexhibit 18
Year over year change in small-hotel index with a moving average trendline
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
quarter. Year over year, Exhibit 17 shows that large hotels Consistent with our analysis, our moving average
fell 3.75 percent (2019Q2-2020Q2) compared to a drop of trend lines for large hotels (in Exhibit 19) shows that the
2.8 percent in the prior year-over-year period (2019Q1- price for large hotels has dropped further below both its
2020Q1). Exhibit 18 shows that smaller hotels declined 4.5 short-term and long-term moving average. Large hotels
percent year over year (2019Q2-2020Q2), compared to a continue to exhibit negative price momentum, indicating
4.1-percent fall in the prior period (2019Q1-2020Q1). a further softening in prices. The price for small hotels (in
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 21exhibit 19
Moving average trendline for large hotel index
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
exhibit 20
Moving average trend line for small hotel index
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
22 The Center for Real Estate and Finance • Cornell Universityexhibit 21
Standardized Unexpected Price (SUP) for large hotel index
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
Exhibit 20) also falls below both its short-term and long- new low. While this is not yet the case for small hotels,
term moving average. Exhibit 22 reveals that this scenario might occur in the next
Our Standardized Unexpected Price (SUP) metric (in quarter if the price of small hotels continues its negative
Exhibit 21) shows that the standardized price for large price trajectory.
hotels has reached a statistically significant trough—a
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 23exhibit 22
Standardized Unexpected Price (SUP) for small hotel index
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
exhibit 23
Moving average trend line for repeat-sale index
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
24 The Center for Real Estate and Finance • Cornell Universityexhibit 24
Standardized Unexpected Price (SUP) for hotel repeat-sale index (full sample)
This graph depicts the interest rate spread between
Class A interest rates (as well as B&C rates) on full
service hotels over the ten-year Treasury bond which is
a leading indicator of hotel loan delinquencies. As this
spread widens, lenders demand a higher (lower) com-
pensation for making hotel loans. Likewise, a narrower
spread means lower compensation.
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
Repeat-sales metrics: prices continue to revert toward 1.03 to .95) this quarter. Exhibit 25 shows that the repeat
their mean. Our repeat-sale indicator, which reflects the sale price index fell 1 percent year over year (2019Q2 to
price of hotels that have sold more than once, continues 2020Q2), dropping further from its .8-percent decline
to revert towards its short-term and long-term moving in the prior period (2019Q1 to 2020Q1). From a quar-
average, although it is still higher than both averages, as ter-over-quarter perspective, the index experienced a slight
displayed in Exhibit 23. Our SUP performance metric (in decrease (a drop of .2%) in the current period (2020Q1-
Exhibit 24) indicates that standardized prices continue to 2020Q2), compared to a steeper decline of 1.7 percent in the
revert to the standardized mean of zero with the three-year prior quarter (2019Q4-2020Q1).
SUP declining from .70 to .51 (and the 5-year SUP, from
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 25exhibit 25
Year-over-year change in repeat-sale hotel index, with a moving average trendline
Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics
exhibit 26
Mortgage origination volume versus the loan-to-value ratio for hotels
Sources: Mortgage Bankers Association, Cornell Center for Real Estate and Finance, Cushman Wakefield Sonnenblick Goldman
26 The Center for Real Estate and Finance • Cornell Universityexhibit 27
Interest rates on Class A versus Class B and C Hotels
Source: Cushman Wakefield Sonnenblick Goldman
Mortgage financing volume for hotels fell year over that the interest rate that CWSG reported for this quarter
year as well as quarter over quarter. Exhibit 26 shows that is based only on loan refinancings, not loan originations,
the mortgage origination volume for hotels, as reported so the interest rate this period isn’t necessarily comparable
for the first quarter of 2020, fell 42% year over year, con- to the interest rate in the prior quarter. Exhibit 27 shows
tinuing the declining trend from the prior period (-25%). that interest rates on Class A and Class B and C hotel deals
Loan origination volume for hotels also declined 57 percent increased 40 percent year over year. Quarter over quarter,
quarter over quarter. The maximum loan to value (LTV) interest rates rose 66 percent for Class A Hotels and 63
ratio for hotels continues to remain at 70 percent. percent for Class B and C Hotels.
The cost of hotel debt financing spiked this quarter The relative risk premium that lenders require for
and has also risen sharply on a year-over-year basis. The hotels over other commercial real estate has widened.
cost of obtaining hotel debt financing, as reported by Cush- Exhibit 28 shows the spread between the interest rate on
man Wakefield Sonnenblick Goldman, rose this quarter Class A full-service hotels (as well as B and C properties),
for both Class A and Class B and C hotels. We should note compared to the (equally weighted) interest rate on other
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 27exhibit 28
Interest rate spreads of hotels versus non-hotel commercial real estate
Source: Cushman Wakefield Sonnenblick Goldman
exhibit 29
30-plus-day delinquency rate for hotels
Source: Trepp
28 The Center for Real Estate and Finance • Cornell Universityexhibit 30
Standardized 30-plus-day delinquency rate for hotels
Source: Trepp
(non-hotel) commercial real estate. A positive spread percent in June, exceeding the previous high of 19.3 percent
associated with this hotel real-estate premium indicates set in September 2010. This also exceeds the 19.1-percent
that lenders demand more compensation to make hotel hotel delinquency rate in May. For comparison purposes,
loans than on loans for other major property types, because the delinquency rate for retail real estate in June was 18.1
hotels are perceived to be relatively riskier. The monthly percent. The June delinquency rate for other property types
hotel real estate premiums for both higher and lower quali- reported by Trepp is as follows: Industrial, 1.57 percent;
ty properties. Class A premiums widened from .34 percent Multifamily, 3.29 percent; and Office, 2.66 percent. Exhibit
(34 bps) in the prior quarter to over 1.69 percent (169 bps). 29 displays the historical 30-plus-day delinquency rate for
For Class B and C hotels, the spread widened from 39 basis hotels, while Exhibit 30 shows the standardized version of
points to 174 basis points. This signals that lenders perceive the 30-plus-day delinquency rate for hotels. Both exhib-
the default risk for hotel properties to be relatively high at its reveal that the delinquency rate for hotels with loans
the moment. securitized as part of CMBS deals are above their long-term
The delinquency rate on hotel loans has reached a average. If the indicator is above or below 1.645 (Z-score)
new high. Along that line, the CMBS delinquency rate (30+ then this indicates that the indicator has hit a statistically
days) for lodging properties reached a new high of 24.3 significant new high or low. In this case, we see a new low.
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 29exhibit 31
Cost of equity financing using the capital asset pricing model and hotel REITs
Sources: NAREIT, Cornell Center for Real Estate and Finance
Although the cost of equity financing is now lower, though it increased 258.5 percent on a year-over-year basis.
the riskiness of hotels has risen relative to other types of This indicates that the perceived default risk for hotels has
commercial real estate. The cost of using equity financing widened relative to other types of commercial real estate
for hotels as measured using the capital asset pricing model consistent with our other hotel risk premium indicators.
(CAPM) on hotel REIT returns declined in June, as shown Our reading of the tea leaves suggests that the price
in Exhibit 31, making it theoretically cheaper to borrow of large hotels and small hotels should to continue to fall
from equity markets. The cost of using equity is currently year over year. Exhibit 33 compares the performance of the
7.1 percent for 2020Q2 compared to 7.75 percent in the repeat sales index relative to the NAREIT Lodging/Resort
prior quarter, a drop of 65 bps. In terms of total risk (sys- Price Index. Looking ahead, although the NAREIT lodging
tematic risk + risk that is unique to hotel REITs), Exhibit 32 index rose 5.5 percent this quarter, it declined 50 percent
shows that the total risk of hotel REITs relative to the total year-over-year.
risk of equity REITs dipped slightly this quarter (-3.6%), al-
30 The Center for Real Estate and Finance • Cornell Universityexhibit 32
Risk differential between hotel REITs and equity REITs
Sources: Cornell Center for Real Estate and Finance, NAREIT
exhibit 33
Repeat sales index versus NAREIT lodging/resort price index
Sources: Cornell Center for Real Estate and Finance, NAREIT
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 31exhibit 34
Repeat sales index versus architectural billings index
Sources: American Institute of Architects, Cornell Center for Real Estate and Finance
The architecture billings index (ABI) for commercial metric is one of the few that offers some hope for a quicker
and industrial property, shown in Exhibit 34, fell 41 percent recovery, although it is still too early to call it a trend.
this quarter (24.8 versus 41.9). Year over year, the ABI de- The Conference Board’s Consumer Confidence Index,
clined 53 percent. graphed in Exhibit 36, which we use as a proxy for antic-
The National Association of Purchasing Managers ipated consumer demand for leisure travel and a leading
(NAPM) index shown in Exhibit 35, which is an indicator indicator of the hedonic index for low-price hotels, fell 18
of anticipated business confidence, rose 7.1 percent this percent this quarter and also fell 19 percent year over year.
quarter and increased 1.7 percent year over year. This
32 The Center for Real Estate and Finance • Cornell Universityexhibit 35
Business confidence and high-price hotels
: Cornell Center for Real Estate and Finance, Institute for Supply Management (ISM)
exhibit 36
Consumer confidence and low-price hotels
Sources: Cornell Center for Real Estate and Finance, Conference Board
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 33exhibit 37
Analysts forecast of hotel REIT earnings
Source: Cornell Center for Real Estate and Finance
Wall Street’s view. Starting with this issue, we also
look at Wall Street analysts’ earnings estimates for hotel
REITs, both in terms on next-quarter earnings per share
(EPS) and also annual EPS. Exhibit 37 indicates that ana-
Hotel Valuation Model (HOTVAL)
lysts are expecting quarterly EPS to decline between 158
Has Been Updated
percent (median) and 162 percent (mean) on average, with
annual EPS falling 80 percent to 112 percent on average. We have updated our hotel valuation regres-
Since analysts’ estimates reflect the earnings guidance from
sion model to include the transaction data
management, this suggests that we should expect further
price declines for the rest of 2020. n used to generate this report. We provide this
user friendly hotel valuation model in an Ex-
cel spreadsheet entitled HOTVAL Toolkit as a
complement to this report which is available
for download from our CREF website.
34 The Center for Real Estate and Finance • Cornell UniversityAppendix
SUP: The Standardized Unexpected Price Metric
The standardized unexpected price metric (SUP) is similar to the standardized unexpected earnings (SUE) indicator used to determine whether
earnings surprises are statistically significant. An earnings surprise occurs when the firm’s reported earnings per share deviates from the street
estimate or the analysts’ consensus forecast. To determine whether an earnings surprise is statistically significant, analysts use the following
formula:
SUEQ = (AQ – mQ)/sQ SUP data and σ calculation for high-price hotels
(12 quarters/3 years)
Price
where SUEQ = quarter Q standardized unexpected earnings, surprise
High-price Moving indicator
AQ = quarter Q actual earnings per share reported by the firm, Quarter hotels m average σ (SUP)
mQ = quarter Q consensus earnings per share forecasted by analysts in quarter Q-1, and
sQ = quarter Q standard deviation of earnings estimates.
From statistics, the SUEQ is normally distributed with a mean of zero and
a standard deviation of one (~N(0,1)). This calculation shows an
earnings surprise when earnings are statistically significant, when SUEQ
exceeds either ±1.645 (90% significant) or ±1.96 (95% significant). The
earnings surprise is positive when SUEQ > 1.645, which is statistically
significant at the 90% level assuming a two-tailed distribution. Similarly, if
SUEQ < -1.645 then earnings are negative, which is statistically
significant at the 90% level. Intuitively, SUE measures the earnings
surprise in terms of the number of standard deviations above or below
the consensus earnings estimate.
From our perspective, using this measure complements our visual analysis of the movement of hotel prices relative to their three-year and five-
year moving average (µ). What is missing in the visual analysis is whether prices diverge significantly from the moving average in statistical
terms. In other words, we wish to determine whether the current price diverges at least one standard deviation from µ, the historical average
price. The question we wish to answer is whether price is reverting to (or diverging from) the historical mean. More specifically, the question is
whether this is price mean reverting.
To implement this model in our current context, we use the three- or five-year moving average as our measure of µ and the rolling three- or five-
year standard deviation as our measure of σ. Following is an example of how to calculate the SUP metric using high price hotels with regard to
their three-year moving average. To calculate the three-year moving average from quarterly data we sum 12 quarters of data then divide by 12:
Average (µ) = (70.6+63.11+58.11+90.54+95.24+99.70 +108.38+99.66+101.62+105.34+109.53+115.78)
= 93.13
12
Standard Deviation (σ) = 18.99
Standardized Unexp Price (SUP) = (115.78-93.13)
= 1.19
18.99
CREF Hotel Indices • CHR Report • July 2020 • www.cref.cornell.edu • Vol. 20 No. 4 35CREF Advisory Board
Arthur Adler ’78, P’16 David Israel ’09 Cornell Hotel Indices
Chairman, Americas Senior Vice President, CHA Center for Hospitality Research
Jones Lang LaSalle hotelAVE Reports
Bob Alter ’73 David Jubitz ’04 Vol. 20 No. 4 (July 2020)
President Co-Chief Investment Officer
Seaview Investors Clearview Hotel Capital
© 2020 Cornell University. This report
Steven M. Angel Alan Kanders ’87 may not be reproduced or distributed
Principal Principal without the express permission of the
Fulcrum Hospitality LLC Three Wall Capital publisher.
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Governor and Chief Executive Officer CEO & Co-Founder The CREF Report series is produced for
HBC The Chartres Lodging Group the benefit of the hospitality real estate
Michael Barnello A&S ’87 Neil Luthra and finance industries by The Center
Former President & CEO Principal for Real Estate and Finance at Cornell
LaSalle Hotel Properties Highgate University.
Robert Buccini A&S ’90 Jay Mantz P ’21
Co-president President, New York Steven Carvell, Arthur Adler ’78 and
The Buccini/Pollin Group Rialto Karen Newman Adler ’78 Academic
Marty Burger P’17, P’20 Alfonso Munk ’96 Director
Chief Executive Officer Americas Chief Investment Officer and
Silverstein Properties, Inc. Head of Latin America Glenn Withiam, Contributing Editor
Adam Burinescu CALS ’03 Prudential Real Estate Investors
Managing Director Chip Ohlsson Kate Walsh, Dean, E.M. Statler
Centerbridge Partners, LP Executive Vice President and Chief Professor, School of Hotel Administration
Rodney Clough ’94 Development Officer, North America
Managing Partner Wyndham Hotel Group
HVS Mark Owens ’00 Center for Real Estate and Finance
Howard Cohen ’89 EVP and Head of Hospitality Capital Cornell University
Chief Executive Officer Markets
Cornell SC Johnson College of Business
Atlantic | Pacific Companies CBRE
School of Hotel Administration
Navin Dimond P’14, P’19 Daniel Peek ’92
Statler Hall
President & Chief Executive Officer President, Hotel Group
HWE Ithaca, NY 14853
Stonebridge Companies
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Chief Development Officer, The Americas Chief Executive Officer www.cref.cornell.edu
InterContinental Hotels Group (IHG) Access Point Financial
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SVP for Real Estate and Asset Co-founder and President
Management The Buccini/Pollin Group
Hilton Worldwide Ray Potter CALS ’87, MBA ’92
Russell Galbut ’74 Founder and Managing Partner Robert Springer ’99
Managing Principal R3 Funding Executive Vice President,
Crescent Heights Michael Profenius, P’15, P’17 Chief Investment Officer
Chief Operating Officer Sunstone Hotel Investors
Nolan Hecht ’97
Senior Managing Director Northwood Investors Alan Tantleff ’87
Square Mile Capital David Rosenberg P ’11, P’13, P’19 Senior Managing Director–Corporate
Chief Executive Officer Finance/Restructuring Practice Leader,
Kate Henrikson ’96 Hospitality Gaming and Leisure
SVP Investment and Portfolio Analysis Sawyer Realty Holdings
FTI Consulting
RLJ Lodging Trust Chuck Rosenzweig ILR ’85, JD ’88
Founder and Managing Partner Dan Unger ’97
Kenneth Himmel ’70 Chief Development Officer
President and CEO Criterion Real Estate Capital
Tishman
Related Urban Ben Rowe ’96
Co-Managing Partner Founder and Managing Partner Robert White
Gulf Related KHP Capital Partners President
Real Capital Analytics
Jeff Horwitz Seth Singerman ’99
Partner, M&A Private Equity Real Estate Managing Partner Lanhee Yung ’97
(Head), Lodging and Gaming (Head) Singerman Real Estate (SRE) Managing Director of Global Fundraising
Private Equity Corporate Governance and Investor Relations
Jackie Soffer P’20 Starwood Capital Group
International Practice Group Chairman & CEO
Proskauer Turnberry
36 The Center for Real Estate and Finance • Cornell UniversityCenter for Hospitality Research Advisory Board
Cornell Hospitality Report
Vol. 20, No. 4 (July 2020)
Pablo Alonso
Chief Executive Officer ©2020 Cornell University. This report may not be reproduced
HotStats or distributed without the express permission of the publisher.
Scott Berman ’84 Cornell Hospitality Report is produced for the
Principal, Real Estate Business Advisory Services, benefit of the hospitality and service industries by
Industry Leader, Hospitality & Leisure The Center for Hospitality Research
PwC
at Cornell University.
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GM, Lodging Revenue Performance Solutions Linda Canina, Academic Director
Expedia Group
Nicole McQuiddy-Davis, Assistant Program Manager
Patrick Bosworth Glenn Withiam, Contributing Editor
Co-Founder and Chief Executive Officer
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Ian-Michael Farkas Kate Walsh, Dean, E.M. Statler Professor,
Vice President, Strategic Accounts School of Hotel Administration
Local Measure The Center for Hospitality Research
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Global President of Operations Cornell SC Johnson College of Business
Hyatt Cornell University
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Founder and CEO Ithaca, NY 14853
ReviewPro
607-254-4505
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Senior Vice President, Loyalty & Partnerships chr.cornell.edu
Wyndham Hotels & Resorts
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HotelPlanner.com Vice President, Analytics
Hilton
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Senior Vice President of Research Michele Sarkisian
STR Partner
Avenger Capital
Taimur Khan, MENG ’93
Vice President, GM Travel, Transportation, Stacy Silver
Hospitality Solutions Team President
Salesforce Silver Hospitality Group
Balaji Krishnamurthy Dan Skodol MMH ’04
Chief Executive Officer Vice President of Data Science and Analytics
Pure Wellness Cendyn
Christopher Kronenthal Cecil Staton
President and Chief Technology Officer President and Chief Executive Officer
FreedomPay AAHOA
Mark Lomanno P ’08 Scott Taber ’85
CHR Advisory Board Chair, Senior Vice President, Rooms
Partner & Senior Advisor for Kalibri Labs Four Seasons Hotels and Resorts
Kalibri Labs Adam Weissenberg ’85
Kelly McGuire, MMH ’01; PhD ’07 Global Travel, Hospitality and Leisure Leader and
Managing Principal Hospitality National Managing Partner, Clients & Industries
ZS Deloitte & Touche USA
Dan O’Sullivan Rick Werber RPA, FMA ’82
Vice President of Sales, EMEA Senior Vice President, Engineering and Sustainability
Translations.com Host Hotels & Resorts
Michael Partridge ’92 Michelle Woodley ’89
Vice President of Sales and Revenue Analysis President
Marriott International Preferred Hotels & Resorts
Dilip Petigara Mark Woodworth ’77; MPS ’78
Chief Executive Officer Senior Managing Director
Access Point Financial CBRE Hotels Research
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