CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 1 Cornell Hotel Indices First Quarter 2024: CORNELL PETER AND STEPHANIE NOLAN SCHOOL OF HOTEL ADMINISTRATION CENTER FOR HOSPITALITY RESEARCH CENTER FOR REAL ESTATE AND FINANCE Large Hotels Reach a New Statistical Low EXECUTIVE SUMMARY Only the Midwest, South Atlantic, and West South-Central regions posted moderate single- digit hotel-price gains in the first quarter 2024 (Midwest, 3.2%; South Atlantic, 3.8%; and West South-Central, 1.6%). Hotels in gateway cities experienced a reversal, exhibiting better performance than hotels in non-gateway cities this quarter. Transaction volume fell year over year and quarter over quarter for both large and small hotels in gateway and non-gateway cities. Standardized prices of large hotels continue to soften while those of smaller hotels remain relatively stationary. The cost of hotel debt financing and the delinquency rate for hotels rose in the recent quarter, even though credit spreads continued to tighten and relative risk narrowed. As in prior periods, borrowing costs still exceed the return on hotels. Expect to see a rise in the price of large hotels and a decline in prices for small hotels next quarter based on our leading indicators of hotel price performance. by Crocker H. Liu, Adam D. Nowak, and Robert M. White, Jr. 2 The Center for Real Estate and Finance • Cornell University 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 Hospitality Financial Management. He previously taught at New York University’s Stern School of Business (1988-2006) and at Arizona State University’s W.P. Carey School of Business (2006-2009) where he held the McCord Chair. His research interests are focused on issues in real estate finance, particularly topics related to agency, corporate governance, organi- zational forms, market efficiency and valuation. Liu’s research has been published in the Review of Financial Studies, Journal of Financial Economics, Journal of Business, Journal of Financial and Quantitative Analy- sis, Journal of Law and Economics, Journal of Financial Markets, Journal of Corporate Finance, Review of Finance, Real Estate Economics, Journal of Urban Economics, Regional Science and Urban Economics, Jour- nal of Real Estate Research and the Journal of Real Estate Finance and Economics. He is the former co-editor of Real Estate Economics, the leading real estate academic journal. He currently serves on the editorial boards of Real Estate Economics and Journal of Real Estate Research. He previously served on the editorial board of Financial Review, Journal of Real Estate Finance and Economics, Journal of Property Research, and the Journal of Real Estate Finance. He is a past president of AREUEA (2019), the leading real estate academic organization. Professor Liu earned his BBA in real estate and finance from the University of Hawaii, an M.S. in real estate from Wisconsin under Dr. James A. Graaskamp, and a Ph.D. in finance and real estate from the University of Texas under Dr. Vijay S. Bawa. Adam D. Nowak is an associate professor of economics at West Virginia University. He earned degrees in mathematics and economics at Indiana University – Bloomington in 2006 and a degree in near-east languages and cultures that same year. He received a Ph.D. from Arizona State University. He was the research analyst in charge of constructing residential and commercial real estate indices for the Center for Real Estate Theory and Practice at Arizona State University. Nowak’s research has been published in the Review of Financial Studies, American Economic Review: Insights, Economic Inquiry, Journal of Urban Economics, Regional Science and Urban Economics, Journal of Applied Econometrics, Applied Economics Letters, Contemporary Economic Poli- cy, Journal of Economics and Finance, Real Estate Economics, and the Journal of Real Estate Research. Robert M. White, Jr., CRE, is the founder and former president of Real Capital Analytics Inc., an international research firm that publishes the Capital Trends Monthly. On August 2, 2021, he sold Real Capital Analytics to MSCI. MSCI-Real Capital Analytics provides real time data concerning the capital markets for commercial real estate and the values of commercial properties. He is the 2014 recipient of the James D. Landauer/John R. White Award given by The Counselors of Real Estate. In addition, he was named one of National Real Estate Investor Magazine’s “Ten to Watch” in 2005, Institutional Investor’s “20 Rising Stars of Real Estate” in 2006, and Real Estate Forum’s “10 CEOs to Watch” in 2007. Previously, Mr. White spent 14 years in the real estate investment banking and bro- kerage industry and has orchestrated billions of commercial sales, acquisitions and recapitalizations. He was formerly a managing director and principal of Granite Partners LLC and spent nine years with Eastdil Realty in New York and London. Mr. White is a Counselor of Real Estate, a Fellow of the Royal Institution of Chartered Surveyors and a Fellow of the Homer Hoyt Institute. He serves on the board of directors for the Pension Real Estate Association and the advisory board for the Real Estate Research Institution. He is also a member of numerous industry organizations and a supporter of academic studies. Mr. White is a graduate of the McIntire School of Commerce at the University of Virginia. White’s research has been published in the Journal of Real Estate Finance and Eco- nomics. Mr. White is a noted authority on the real estate capital markets with credits in The Wall Street Journal, Barron’s, The Econo- mist, Forbes, The New York Times, and the Financial Times, among others. Acknowledgments We wish to thank Glenn Withiam for copy editing this paper. Disclaimer The Cornell hotel indices produced by The Center for Real Estate and Finance at the School of Hotel Administration at Cornell Univer- sity are 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 implications. The indices are not audited, and they are not necessarily free of errors or omissions although every effort has been made to minimize these. The reported indices for any quarter of any year should be considered preliminary and subject to revision. ABOUT THE AUTHORS CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 3 exhibit 1a Time series hotel performance for seven regions CORNELL CENTER FOR REAL ESTATE AND FINANCE Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics Analysis of Indices through Q1, 2024 Only three regions exhibited positive hotel-price performance. Exhibits 1a through 1c show that only the Midwest (5.6%), Mid-Atlantic (4.4%), and West South-Central (3.1%) regions experienced year-over-year gains in the first quarter that exceeded gains in the prior period. The remaining regions all posted year-over-year price declines. A similar situation exists quarter over quarter; only the Midwest (3.2%), South Atlantic (3.8%), and West South-Central (1.6%) regions posted moderate single-digit quarter-over-quarter gains. Losses occurred in all other regions. Cornell Hotel Indices First Quarter 2024: Large Hotels Reach a New Statistical Low by Crocker H. Liu, Adam D. Nowak, and Robert M. White, Jr. 4 The Center for Real Estate and Finance • Cornell University exhibit 1b Cross-section hotel performance for seven regions Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics -7.3% QoQ -7.9% YoY 3.2% QoQ 5.6% YoY 1.6% QoQ 3.1% YoY 3.8% QoQ -0.5% YoY -2.5% QoQ 4.4% YoY -3.7% QoQ -11.9% YoY -5.3% QoQ -2.2% QoQ% YoY exhibit 1c Changes in regional price indices, year over year and quarter over quarter In terms of standardized un- expected prices (Z-Scores), which are useful in detecting turning points (peaks and troughs),1 hotel prices trended downwards in all regions, moving towards their historical averages. The one exception is the Midwest region, which reached a new statistical high this quarter. Hotels in gateway cities out- performed non-gateway cities, reversing a prior trend. Reversing the trend in the prior five periods, hotels in gateway cities finally exceeded hotels in non-gateway cities, increasing 5.4 percent compared to a decline of 1 percent 1 A new statistical high is achieved at z = 1.645, while a new statistical low occurs at z = -1.645. Standardized Unexpected Prices (Z-Scores) CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 5 exhibit 1d Regional comparison of standardized unexpected prices (SUP), with confidence boundaries Midwest Middle Atlantic New England South AtlanticPacific West South Central Note: Regions are as follows: Middle Atlantic region: New Jersey, New York, and Pennsylvania; New England region: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont; South Atlantic region: Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, and West Virginia; East South Central region: Alabama, Kentucky, Mississippi, Tennes- see; East North Central region: Illinois, Indiana, Michigan, Ohio, and Wisconsin; West South Central region: Arkansas, Louisiana, Oklaho- ma, and Texas; West North Central region: Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota; Mountain region: Arizona, Colorado, Idaho, Montana, New Mexico, Nevada, Utah, and Wyoming; Pacific: Alaska, California, Hawaii, Oregon, and Washington. Mountain 6 The Center for Real Estate and Finance • Cornell University exhibit 2 Hotel performance for gateway cities versus non-gateway cities Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics for non-gateway cities on a quarter-over-quarter basis, as shown in Exhibit 2. Year over year, hotel prices in both gateway and non-gateway cities declined approximately 2 percent. Transaction volume fell year over year and quarter over quarter for both large and small hotels in gateway and non-gateway cities. Weakness in transaction volume Gateway cities are Boston, Chicago, Honolulu, Los Angeles, Miami, New York, San Francisco, and Washington, DC. on all hotel transactions (both large hotels and small hotels combined) continued year over year. Transaction volume was also weaker quarter over quarter for all categories, including large hotels, small hotels, and hotels in gateway and non-gateway markets (see Exhibits 3a, 3b, and 3c). Ex- hibit 4 and Exhibit 5 show this year-over-year trend in the number of transactions for large hotels and small hotels. Quarter over Quarter Gateway Cities Non-Gateway Cities Current Period (2024Q1) 5.4% -1.0% Prior Period (2023Q4) -3.4% -1.0% Year over Year Current Period (2024Q1/2023Q1) -2.1% -1.9% Prior Period (2023Q4/2022Q4) -9.0% 0.2% CREF Hotel Indices • CHR Report • January 2022 • www.cref.cornell.edu • Vol. 22 No. 1 7 exhibit 3a Transaction volume (observed) and median sale price (1995–2003) 8 The Center for Real Estate and Finance • Cornell University exhibit 3b Transaction volume (observed) and median sale price (continued, 2004–2012) exhibit 3c Transaction volume (observed) and median sale price (concluded, 2013–2024) Source: Cornell Center for Real Estate and Finance CREF Hotel Indices • CHR Report • January 2022 • www.cref.cornell.edu • Vol. 22 No. 1 9 10 The Center for Real Estate and Finance • Cornell University exhibit 4 Median sale price and number of sales, large hotels (sale prices of $10 million or more) Sources: CoStar, Real Capital Analytics Full Sample Large Hotels Small Hotels Median Price No. of Sales Median Price No. of Sales Median Price No. of Sales 2024Q1 $5,269,000 325 $13,575,000 72 $3,750,000 253 Quarter over Quarter -12.2% -14.7% -24.6% -33.9% -9.9% -7.0% Year over Year 5.4% -6.6% -22.2% -14.3% 4.6% -4.2% Full Sample Gateway Hotels Non-Gateway Hotels Median Price No. of Sales Median Price No. of Sales Median Price No. of Sales 2024Q1 $5,269,000 325 $9,550,000 20 $5,200,000 305 Quarter over Quarter -12.2% -14.7% -0.52% -51.2% -10.3% -10.3% CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 11 exhibit 5 Median sale price and number of sales, small hotels (sale prices less than $10 million) Sources: CoStar, Real Capital Analytics 12 The Center for Real Estate and Finance • Cornell University exhibit 6 Hotel indices through 2024, quarter 1 Source: Cornell Center for Real Estate and Finance CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 13 exhibit 7 Hedonic hotel indices for large and small hotel transactions Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics Moving averages indicate a “sell” signal for large hotels and a “buy” signal for small hotels. Standardized prices of large hotels continue to soften, while small hotel prices remain relatively stationary. Exhibit 7 graphs the prices reported in Exhibit 6. The price of large hotels fell almost 6 percent, while the price of small hotels remained relatively flat at .9 percent this quarter. 14 The Center for Real Estate and Finance • Cornell University exhibit 8 Year-over-year change in large-hotel index with a moving average trendline Exhibit 8 and Exhibit 9 show the historical year-over-year change in large and small hotel indices. Year over year, large hotels fell 12 percent, compared to an imperceptible increase of .6 percent in the price of small hotels. To gauge whether the prices of large and small hotels signal a buy or sell, we compare the hedonic price relative to the 3-year and 5-year moving averages in Exhibit 10 and Exhibit 11. Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 15 exhibit 9 Year-over-year change in small-hotel index with a moving average trendline Sources: Cornell Center for Real Estate and Finance, CoStar, MSCI-Real Capital Analytics 16 The Center for Real Estate and Finance • Cornell University exhibit 10 Moving average trendlines for large hotel index Sources: Cornell Center for Real Estate and Finance, CoStar, MSCI-Real Capital Analytics Hedonic Price Moving Average Standardized Unexpected Price (Z-Score) Large Hotels Price 3 Year 5 Year 3 Year 5 Year 2023Q1 169.93 2023Q4 158.01 -1.36 -1.05 2024Q1 149.12 166.36 163.66 -2.23 -2.05 Quarter over Quarter -5.6% Year over Year -12.2% Small Hotels Price 3 Year 5 Year 3 Year 5 Year 2023Q1 177.73 2023Q4 177.30 0.93 1.31 2024Q1 178.82 166.71 160.86 0.91 1.31 Quarter over Quarter 0.9% Year over Year 0.6% CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 17 exhibit 11 Moving average trendlines for small hotel index Sources: Cornell Center for Real Estate and Finance, CoStar, MSCI-Real Capital Analytics If the price is above a moving average, the trend is up, whereas a price below the moving average is depicted as a downtrend. Since the hedonic price for large hotels is be- low both its associated 3-year and 5-year moving averages, this indicates a sell signal. In contrast, the hedonic price that is above the moving averages for small hotels indicates a buy signal. To assess whether the price of a large or small hotel has reached a new statistical high or low, we again use the Z-scores statistical technique (see appendix) to standardize prices so that the average price is at zero. As a reminder, if prices rise above 1.645, then this indicates a new statistical high, whereas if prices fall below -1.645, this 18 The Center for Real Estate and Finance • Cornell University exhibit 12 Standardized unexpected price (SUP) for large hotel index exhibit 13 Standardized unexpected price (SUP) for small hotel index Sources: Cornell Center for Real Estate and Finance, CoStar, MSCI-Real Capital Analytics Sources: Cornell Center for Real Estate and Finance, CoStar, MSCI-Real Capital Analytics CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 19 exhibit 14 Moving average trendline for repeat-sale hotel index is a new statistical low. Exhibit 12 and Exhibit 13 show that the standardized price for large hotels and small hotels has continued to lose momentum. In that regard, the standard- ized price of large hotels reached a statistically significant new low, while the standardized price of small hotels slid imperceptibly but again remained above its standardized average price of zero. Sources: Cornell Center for Real Estate and Finance, CoStar, MSCI-Real Capital Analytics Repeat Sale Price Moving Average Standardized Unexpected Price (Z-Score) Repeat Sale Hotels Price 3 Year 5 Year 3 Year 5 Year 2023Q1 231.94 2023Q4 222.97 0.63 1.14 2024Q1 219.07 214.16 200.59 0.29 0.87 Quarter over Quarter -1.8% Year over Year -5.6% 20 The Center for Real Estate and Finance • Cornell University Sources: Cornell Center for Real Estate and Finance; CoStar, Real Capital Analytics Sources: Cornell Center for Real Estate and Finance, CoStar, Real Capital Analytics Prices of frequently sold hotels remain above their moving averages, signaling a buy-hold. Standardized prices of repeat-sale hotels continue to revert toward their standardized average. Hotels that tend to sell frequently fell almost 2 percent this quarter and lost 6 percent year over year (see also Exhibit 16). Like small hotels, our repeat sale indicator continues to remain above both its short-term (219.07 > 214.16) and long-term (219.07 > 200.59) moving averages (see Exhibit 14). Thus, these hotels continue to remain a buy opportunity. Our SUP performance metric in Exhibit 15 indicates that both the 3-year and 5-year SUP continue to revert toward their standardized mean (of zero). exhibit 15 Standardized unexpected price (SUP) for hotel repeat-sale index (full sample) CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 21 exhibit 16 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 22 The Center for Real Estate and Finance • Cornell University exhibit 17 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 Mortgage financing volume rose 132 percent for the most recent quarter reported, and rose 80 percent year over year. Exhibit 17 shows that the mortgage origination volume for hotels, as reported for the fourth quarter of 2024, rose 132 percent this quarter compared to a 2-percent increase in the previous quarter. Hotel loan volume also rose 81 percent year over year, reversing what had been a 52-percent decline in the prior year-over-year period. The maximum loan to value (LTV) ratio for hotels remains at 60 percent this quarter. The cost of hotel debt financing rose in the recent quarter even though credit spreads continued to tighten and relative risk narrowed. The cost of obtaining hotel debt financing as reported by Cushman Wakefield Sonnen- blick Goldman rose 2 percent quarterly, from 7.62 percent (7.87 percent) in December 2023 to 7.78 percent (8.03%) in March 2024 for Full-service Class A hotels (Class B&C hotels). However, interest rates have declined 8.5 percent year over year. In March 2023, interest rates for Class A and Class B&C hotel were at 8.52 percent and 8.77 percent respectively. The rise in interest rates hinders the feasibility of hotel deals near term. Exhibit 18 displays the historical time series graph of hotel interest rates. MBAA Hotel Origination Volume Index (2001 Avg Qtr = 100) 2022Q4 145 2023Q3 113 2023Q4 262 Quarter over Quarter 131.9% Year over Year 80.7% CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 23 exhibit 18 Interest rates on Class A versus Class B & C hotels Sources: Cornell Center for Real Estate and Finance, Cushman Wakefield Sonnenblick Goldman To evaluate how risky hotel interest rates are, we compare the interest rate on hotels to other types of commercial real estate (CRE). The interest rate spread for both higher quality (Class A) and lower quality (Class B&C) hotels continues to tighten from the previous two quarters and the previous two year-over-year periods. This indicates that lenders have lowered the additional compensation they require to make hotel loans compared to loans on other major property types given the relative riskiness for hotels. To obtain further insights, we also compare the interest rate on hotels to the yield on a 10-year Treasury bond. The interest-rate spread on this metric has also continued to narrow for both Class A and Class B&C hotels. 24 The Center for Real Estate and Finance • Cornell University exhibit 19 Interest rate spreads of hotels versus non-hotel commercial real estate Sources: Cornell Center for Real Estate and Finance, Cushman Wakefield Sonnenblick Goldman Interest Rates Full-Service Hotels Interest Rate Spread (Hotel – CRE) Interest Rate Spread (Ho- tel – 10 Yr TBond) Class A Class B&C Class A Class B&C Class A Class B&C March 2023 8.52% 8.77% 2.14% 2.18% 4.55% 4.80% December 2023 7.62% 7.87% 1.28% 1.32% 3.75% 4.00% March 2024 7.78% 8.03% 1.04% 1.08% 3.45% 3.70% Quarter over Quarter 2.1% 2.0% -18.3% -17.7% -8.0% -7.5% Year over Year -8.7% -8.4% -51.4% -50.4% -24.2% -22.9% CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 25 Sources: NAREIT, Cornell Center for Real Estate and Finance exhibit 20 Risk differential between hotel REITs and non-hotel commercial-property REITs Another way to view default risk is to look at the equi- ty market. Exhibit 20 shows that the total risk of hotel REITs relative to the total risk of an equally weighted port- folio of commercial real estate equity REITs (office, indus- trial, retail, and multifamily). The risk differential, which should reflect the risk that is unique to hotel properties, is currently at -.73 percent (σHotel - σCRE = 6.22% - 6.94%), down from .54 percent (σHotel - σCRE = 8.33% - 7.78%) in the prior quarter. This indicates that the expected default risk for hotels has decreased relative to other major types of commercial real estate. This suggests that the cost of financing for hotels should become less expensive relative to other major property types in the short run. The delinquency rate on hotel loans rose slightly this quarter. The CMBS delinquency rate (30+ days) of 5.45 percent for lodging properties in March is only slightly above the previous quarter’s hotel delinquency rate of 5.4 percent (December 2023). It is also higher than the 4.41-percent hotel delinquency rate in same period for the prior year (March 2023). The hotel delinquency rate is lower than the retail delinquency rate of 5.56 percent and the office delinquency rate of 6.58 percent. Exhibit 21 displays the historical 30+ day delinquency rate for hotels, while Exhibit 22 shows the standardized version of the 30+ day delinquency rate for hotels. 26 The Center for Real Estate and Finance • Cornell University exhibit 21 30-plus-day delinquency rate for hotels Source: Trepp The cost of borrowing continues to exceed the return for hotels. Our economic value added (EVA) or economic profit is -1.52 percent, while the shareholder value add- ed (SVA) stands at -3.8 percent. Both the EVA and SVA continue to be negative, as they have since April 2022. This indicates that economic profit for hotels is negative (i.e., the return on hotels is less than their total borrowing cost (EVA), and the return on equity for hotels is less than their cost of equity (SVA). Consequently, the return on hotels is driven mainly from anticipated future price gains. Exhibit 23 depicts the historical EVA and SVA hotel performance. Trepp 30+ days CMBS Lodging Delinquency Rate Lodging Industrial Multifamily Office Retail March 2023 4.41 0.37 1.91 2.61 6.23 Decem- ber 2023 5.40 0.57 2.62 5.82 6.47 March 2024 5.45 0.47 1.84 6.58 5.56 Quarter over Quarter 0.9% -17.5% -29.8% 13.1% -14.1% Year over Year 23.6% 27.0% -3.7% 152.1% -10.8% CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 27 exhibit 23 Economic value added (EVA) and equity (shareholder) value added (SVA) for hotels Sources: Cornell Center for Real Estate and Finance, Cushman Wakefield, NAREIT, MSCI-Real Capital Analytics, St Louis Fed Source: Trepp exhibit 22 Standardized 30-plus-day delinquency rate for hotels 28 The Center for Real Estate and Finance • Cornell University exhibit 24 Standardized unexpected RevPAR (36-month moving average) vs. NAREIT lodging-price index Note: ROIC is the return on invested capital (cap rate), WACC is the weighted average cost of capital, and ROE is the return on equity or cash on cash. Sources: Cornell Center for Real Estate and Finance, CoStar (STR), NAREIT ROIC WACC EVA ROE Cost of Eq- uity SVA June 2023 8.45% 9.4% -1.04% 8.05% 10.64% -2.59% September 2023 8.62% 9.81% -1.19% 8.10% 11.07% -2.97% December 2023 8.56% 9.50% -0.95% 8.51% 10.87% -2.36% February 2024 8.21% 9.73% -1.52% 7.43% 11.23% -3.80% Our reading of the tea leaves suggests that we should see a rise in price for large hotels, but negative price momentum for small hotels near term. Standardized unexpected RevPAR continued its decline, falling from 1.16 in September 2023 to 1.02 in December 2023 and further to .91 in March 2024, as shown in Exhibit 24. In contrast, the NAREIT Lodging Price Index rose from 85.34 last quarter to 89.28 this quarter. The standardized unexpected price of the NAREIT Lodging Index is currently .64, as Exhibit 25 depicts. Based on the standardized unexpected price and the 12-month moving average of the NAREIT Lodging Price Index, we expect hotel prices based on repeat sales to rise in the near term. The architecture billings index (ABI) for commercial and industrial property shown in Exhibit 26 remained rela- tively flat, declining imperceptibly 0.6 percent this quarter from 46.40 to 46.10 (based on the February 2024 value). Year-over-year, the index was also down 7.2 percent, de- creasing from 49.7 to 46.10. Based on the moving average of the ABI index, we should expect downward price momen- tum in the next period. CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 29 exhibit 26 Repeat sales index versus the architecture billings index Sources: Cornell Center for Real Estate and Finance, NAREIT exhibit 25 Standardized unexpected NAREIT lodging/resort price index Sources: American Institute of Architects, Cornell Center for Real Estate and Finance Center for Real Estate and Finance 30 The Center for Real Estate and Finance • Cornell University exhibit 27 Business confidence and high-price hotels index Sources: Cornell Center for Real Estate and Finance, Institute for Supply Management (ISM) The National Association of Purchasing Managers (NAPM) index shown in Exhibit 27, an indicator of antici- pated business confidence, currently stands at 51.4. It rose 8.4 percent (47.4 to 51.4) this quarter, compared to a decline of 3.3 percent last quarter (49 to 47.4). Year over year, the NAPM index increased 11 percent (from 46.3 to 51.4). This contrasts with a fall of 2.1 percent in the prior period (48.4 to 47.4). Expect high-price hotels to rise further in price in the near term. Finally, the Conference Board’s Consumer Confidence Index, graphed in Exhibit 28, our proxy for anticipated consumer demand for leisure travel and a leading indicator of the hedonic index for low-price hotels (<$10 million), fell 5.4 percent this quarter. However, it was relatively station- ary (0.5%) year over year. Expect low-price hotels to decline in the near term based on a four-quarter moving average of the Consumer Confidence Index. n CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 31 exhibit 28 Consumer confidence and low-price hotels Sources: Conference Board, Cornell Center for Real Estate and Finance Hotel Valuation Model (HOTVAL) Has Been Updated We have updated our hotel valuation regres- sion model to include the transaction data used to generate this report. We provide this user-friendly hotel valuation model in an Excel spreadsheet entitled HOTVAL Toolkit as a comple- ment to this report, which is available for download from our CREF website (cref.cornell.edu). http://www.hotelschool.cornell.edu/industry/centers/cref/ 32 The Center for Real Estate and Finance • Cornell University Appendix 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 where SUEQ = quarter Q standardized unexpected earnings, AQ = quarter Q actual earnings per share reported by the firm, 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) Standard Deviation (σ) = 18.99 Standardized Unexp Price (SUP) = (115.78-93.13) SUP data and σ calculation for high-price hotels (12 quarters/3 years) Quarter High-price hotels m Moving average σ Price surprise indicator (SUP) 12 = 93.13 18.99 = 1.19 CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 33 Pablo Alonso Chief Executive Officer HotStats Matt Carrier ’11 Vice President of Innovation Policy and Research AHLA Carolyn Corda MPS ’89 Managing Director Deloitte Jeff Garber ’92 Vice President, Revenue System Transformation IHG Hotels & Resorts Steve Hood Senior Vice President of Research STR Klaus Kohlmayr Chief Evangelist and Head of Strategy IDeaS Jamie Lane Vice President, Research AirDNA Mark Lomanno Partner & Senior Advisor Kalibri Labs Robert Mandelbaum ’81 Director, Research Information Services CBRE Hotels Research Kelly McGuire MMH ’01, PhD ’07 Manging Principal Hospitality ZS Katie Moro Vice President, Data Partnerships Amadeus Neal Patel Past Chair (2022-2023) AAHOA Stephanie Perrone Goldstein ’01 Principal Deloitte Jess Petitt ’05 Senior Vice President, Commercial Strategy, Insights & Analytics Hilton Cornell Hospitality Reports April 2024 Vol. 24, No. 9 ©2024 Cornell University. This report may not be reproduced or distributed without the express permission of the publisher. The authors were granted permission to use the photos, names, and stories of the people referenced in this article. The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Center for Hospitality Research, its advisory board, the Cornell Nolan School of Hotel Administration, Cornell SC Johnson College of Business, or Cornell University. Cornell Hospitality Reports are produced for the benefit of the hospitality and service industries by the Center for Hospitality Research at Cornell University. Center for Hospitality Research Cornell Nolan School of Hotel Administration Cornell SC Johnson College of Business Cornell University Statler Hall Ithaca, NY 14853 Kate Walsh, Dean, E.M. Statler Professor Linda Canina, Academic Director Robert Gregor, Interim Executive Director Nicole McQuiddy-Davis, Interim Director Shana Claar, Interim Assistant Program Manager Glenn Withiam, Contributing Editor chr.cornell.edu Prashanth Radhakrishnan Vice President, Global Topline Analytics Marriott International Stacy Silver President Silver Hospitality Group Liesl Smith Senior Vice President, Marketing, Communications, and Sales Enablement FreedomPay Randell Smith Founder (Retired) STR Emily Weiss Senior Managing Director, Global Industry Sector Lead Travel Accenture Center for Hospitality Research Advisory Board 34 The Center for Real Estate and Finance • Cornell University Adam Docks Partner and Firmwide Co-chair, Hotels and Leisure Industry Group Perkins Coie LLP Habib Enayetullah SVP for Real Estate and Asset Management Hilton Worldwide Paul Fine ’07 Managing Director, Real Estate KKR Russell Galbut ’74 Managing Principal Crescent Heights Andrew Gindy ’11 Senior Principal Walton Street Capital Nolan Hecht ’97 Senior Managing Director and Head of Real Estate Certares Management LLC Kate Henrikson ’96 SVP, Investment and Portfolio Analysis RLJ Lodging Trust Faron A. Hill, MBA ’20 Founder and President Peregrine Oak Kenneth Himmel ’70 President and CEO Related Urban Co-managing Partner Gulf Related David Hirschberg Managing Director H.I.G. Realty Partners Jeffrey Horwitz Senior Partner, Co-head of Private Equity Real Estate Proskauer LLP David Israel ’09 Senior Vice President, CHA hotelAVE Dana Jacobsohn ’92 Senior Vice President, Global Mixed-use Development Marriott International, Inc. Arthur Adler ’78 Chairman, CREF President Adler Hotel Advisors LLC Jun Ahn MPSRE ’00 CEO, Core Value, and Managing Director of Real Estate Division YIDO Bob Alter ’73 President Seaview Investors LLC Richard Baker ’88 Governor and Executive Chairman Hudson’s Bay Company (HBC) Kenneth M. Blatt ’81 Principal CPG Real Estate Robert Buccini A&S ’90 Co-president The Buccini/Pollin Group Marty Burger P ’17, P ’20 Chief Executive Officer Silverstein Properties Adam Burinescu CALS ’03 Managing Director Centerbridge Partners Rodney Clough ’94 Managing Partner HVS Howard Cohen ’89 Chief Executive Officer Atlantic | Pacific Companies Kevin Davis Senior Managing Director—Hotels and Hospitality Group JLL Greg Dickhens ’91 Principal and Managing Partner Trinity Investments Navin Dimond P ’14, P ’19 Chairman and CEO Stonebridge Companies Cornell Center for Real Estate and Finance Advisory Board David Jubitz ’04 Co-chief Investment Officer Clearview Hotel Capital Alan Kanders ’87 Principal Three Wall Capital Brian Kaufman ’08 Managing Director The Blackstone Group Rob Kline ’84 CEO and Co-founder The Chartres Lodging Group Jeffrey Kruse ’16 Managing Director Kolter Group Jason Lee ’95 Managing Director, Chief Investment Officer– Asia and Senior Portfolio Manager AEW Terence Loh ’97 Senior Vice President CDIB Capital William Lovejoy President and CEO Masterworks Development Co. LLC Neil Luthra Founding Partner Newbond Holdings Jay Mantz P ’21 President, New York Rialto Justin McAuliffe ’10 Equity Research Analyst GAMCO Investors, Inc. David Mei ’94 Vice President, Global Capital Investments and Transactions IHG Hotels and Resorts Daniel Moritz ’03 (CALS) Principal The Arker Companies Alfonso Munk ’96 Chief Investment Officer–Americas Hines Steven Carvell, Arthur Adler ’78 and Karen Newman Adler ’78 Director Elizabeth Cunningham, Program Manager Shanna Claar, Interim Assistant Program Manager Cornell Center for Real Estate and Finance Kate Walsh, Dean, E.M. Statler Professor Cornell Peter and Stephanie Nolan School of Hotel Administration Statler Hall Cornell SC Johnson College of Business Ithaca, NY 14853 607-254-3383 • www.cref.cornell.edu http://cref.cornell.edu CREF Hotel Indices • CHR Report • April 2024 • www.cref.cornell.edu • Vol. 24 No. 9 35 Chip Ohlsson Executive Vice President and Chief Development Officer, North America Wyndham Hotel Group Mark Owens ’00 Executive Vice President and Head of Hospitality Capital Markets CBRE Daniel Peek ’92 Chief Operating Officer HWE David Pollin ’90 Co-founder and President The Buccini/Pollin Group Ray Potter CALS ’87, MBA ’92, P ’22 Founder and Managing Partner R3 Funding Michael Profenius, P ’15, P ’17 Chief Operating Officer Northwood Investors David Rosenberg P ’11, P ’13, P ’19 Chief Executive Officer Sawyer Realty Holdings Chuck Rosenzweig ILR ’85, JD ’88 Founder and Managing Partner Criterion Real Estate Capital Ben Rowe ’96 Founder and Managing Partner KHP Capital Partners Paul Rubacha, CALS ’72, MBA ’73 Co-Founder and Principal Ashley Capital Richard Russo ’02 Principal Highgate John Ryan Founder and CEO Metro Development Group C. Patrick Scholes ’94 Managing Director, Lodging and Leisure Equity Research Truist Securities Nirav Shah MMH ’05 Regional Vice President, Development Hyatt Matthew Shore ’00 Cheif Investment Officer DRA Advisor Seth Singerman ’99 Managing Partner Singerman Real Estate (SRE) Justin D. Smith ’00 President Prestige Hospitality Group Jackie Soffer P ’20 Chairman & CEO Turnberry Stephen Sotoloff ’03 Senior Principal Walton Street Capital Richard Stockton ’92 Founder and Chief Executive Officer Braemar Hotels & Resorts Richard Stockton ’92 Founder and CEO Braemar Hotels & Resorts Andrew Taffet A&S ’05 Chief Investment Officer and Head of Asset Management The Carrington Companies, LLC Alan Tantleff ’87 Senior Managing Director–Corporate Finance/ Restructuring, Practice Leader, Hospitality Gaming and Leisure FTI Consulting Dan Unger ’97 Chief Development Officer Tishman Brad Walker ’10 Managing Director, Investments Mavik Capital Management Eva Wasserman Managing Director GEM Realty Capital Jacob Wright MBA ’22 Founder and Chief Executive Officer Guide Hospitality Shai Zelering ’01 Managing Partner Brookfield Real Estate Group 36 The Center for Real Estate and Finance • Cornell University 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-sale index (RSI) that tracks actual hotel transactions. These indices are construct- ed 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 average-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 introduced the Gateway Cities Index as a new metric in our hotel analytics arsenal.*1 In our 2019Q2 issue, we introduced our new regional indices to add further granularity to hotel performance. More recently, we have included information on hotel delinquencies, as well as short-term and long-term hotel earnings expectations to aid hotel decisionmakers. We also present updates and revisions to our hotel indices along with commentary and support- ing evidence from the real estate market. Starting in 2021Q2, we included standardized unexpected price for our regional price indices as well as standardized unexpected RevPAR for the U.S. as a whole. We also introduced shareholder value added (SVA) as a complementary metric to EVA so that readers can now compare the profitability of hotel real estate to investors’ equity return. * Cities that we define as gateway cities are Boston, Chicago, Honolulu, Los Angeles, Miami, New York, San Francisco, and Washington, DC. For a general discus- sion 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 prop- erty 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.