Buying high and selling low in the lodging-property market: the prices of lodging properties are influenced by the motivations and knowledge level of the parties on both sides of transactions.

Originally published in 1994, this is an analysis of more than 1,300 hotel transactions recorded between 1985 and 1992. The study revealed a pattern of consistent overpayment by some types of buyers and underselling by certain classes of sellers. Further comparisons of specific hotel-property types with various combinations of buyers and sellers showed that sale prices are frequently affected by certain combinations of property characteristics with the attributes of buyers and sellers. Individual buyers, for example, regularly overpaid for the properties they bought and were particularly influenced by average daily rate. On the other hand, the Resolution Trust Corporation created considerable market distortion by regularly discounting hotels it sold, because it undervalued its properties' proximity to city centers and their ADRs.

**********

Each year ownership of hundreds of U.S. lodging properties is transferred in the real-estate market. In theory, the mutually agreed upon sale price for a property is based on the buyer's and the seller's financial goals, their investment outlook, and their knowledge of the property's characteristics. That price is strongly influenced by the physical characteristics of the property (e.g., number of rooms, restaurants, pools, etc.), its location relative to other land uses, and the economic conditions of the market in which it is located. Physical, locational, and economic factors cumulatively generate income or loss and cause value changes over time.

Property prices relate directly to property fundamentals. The analysis of those fundamentals underlies both traditional and currently applied approaches to property valuation in the real-estate-appraisal profession. (1) Because the physical, locational, and economic aspects of a mid-market hotel, for example, are observable and the cash flows from operations and future sales may be estimated by the buyer and seller using standard financial-analysis techniques, the buyer should be able to avoid overpaying for a hotel and the seller should be able to avoid selling a hotel too cheaply. Extending this theoretical argument to the general case of all lodging-property sales, neither a buyer's nor a seller's wealth should be abnormally enhanced or reduced as the result of any transaction.

But not all buyers and sellers are equal. Some buyers are better informed than others about the local economic conditions that affect property prices. Some sellers are not as adept at negotiation as others. Some parties in transactions are more motivated than others to complete transactions in a timely manner and may pay more or accept less for expediency. Japanese hotel buyers during the late 1980s, for example, are thought to have overpaid for properties, perhaps because of their strong motivation to place money in the U.S. real-estate market when it was booming, perhaps because they wished to obtain trophy properties, or perhaps because they made purchase decisions without good information about key property and market fundamentals. (2) The Resolution Trust Corporation (RTC) is another example. Some believe that political pressure from Congress pushed the RTC into selling property from its portfolio quickly and cheaply instead of waiting until the real-estate market recovered.

To show that a particular type of buyer overpaid or that a seller undersold in the lodging-property market, however, is far too general a finding to be useful to market participants. If some buyers pay premiums and some sellers offer discounts, do these outcomes persist in all transactions in which a specific type of participant is involved? Suppose buyer premiums and seller discounts are the result of mistakes. The root causes of such "errors" should be of interest to market participants who want to fill information gaps and exploit inefficiencies. Some foreign buyers, for example, are known for their careful examination of the physical characteristics of properties, but because of their foreign residency, they may not astutely evaluate how local market economics affect real-estate prices or they may unduly weight such factors as residual property value much more heavily than do sellers based in the United States. Armed with the knowledge of how mistakes are made, brokers and consultants may be of better service to these buyers by providing detailed local marker information.

In this article we explore the idea that the transaction price may be different for a given lodging property in the case of one buyer and seller pair relative to another. The findings reported here are from a statistical exploration that is made possible by a large database of lodging-property transactions that occurred throughout the United States during the late 1980s and early 1990s. We begin with a discussion of previous research on the influence of buyers and sellers on property prices, then we present the findings from our study and their implications.

What We Already Know

Property-rights theory suggests that private contracts do not influence real-estate prices in competitive markets unless the contracts affect the underlying property rights. Private contracts including leases, management agreements, franchise agreements, and contracts for sale are outside the realm of rent and price formation unless they restrict the use of the property. For example, a contract for sale accompanied by a deed that restricts owners' rights to use a property only as a hotel would diminish value because of the options it destroys.

Only recently has serious testing begun on the effect of private contracts on value. Sirmans and Sirmans present some evidence that professional management has a positive effect on monthly apartment rent. (3) Shilling, Sirmans, Turnbull, and Benjamin provide somewhat stronger evidence that contingency clauses in contracts for sale lead to significant increases in the prices of houses (such clauses often involve the ability to obtain financing and the sale of the currently owned property). (4) However, Hanson was unable to find differences between the ratios of operating income to replacement costs for hotels affiliating with a chain and engaging a management company versus independent hotels. (5) Corgel also could not establish that the franchise affiliations of hotels had a statistically significant effect on hotel-sale prices. (6)

Each contract for sale represents the agreement on price and terms reached by a specific buyer and seller combination. The idea that the price of a lodging property may be different in the case of one buyer and seller combination compared to another is rooted in the belief that buyer and seller characteristics influence price formation even though property rights have not been disturbed. In theory, a given buyer behaves differently from other buyers and a given seller behaves differently from other sellers for three reasons. (7) First, each buyer and seller is capable of pricing errors because neither buyer nor seller has all the information about every property in the market that is necessary to set a perfect price for any single property. Second, buyers and sellers are not equally patient. Some sellers, for example, are overly eager to sell and thus sell at low prices while other sellers are willing to wait for their price. Finally, there are strategic reasons why market participants may be willing to transact for the same property at different prices. A hotel company, for instance, may value a property higher than an individual because of the competitive edge the property provides to the brand.

The corporate-finance literature is rich with evidence that the values of securities are affected by the presence of investors driven by tax and leverage clienteles. Maris and Elayan review this literature and find in their study a tax-induced clientele that is willing to pay more for equity REITs. (8) We know of only one study that addresses these issues in the market for real estate that does not involve securities. During the 1980s some real-estate-market observers believed that limited-partnership syndications overpaid for properties to gain maximum tax subsidies for limited partners. Holding other factors constant, Beaton and Sirmans accept the null hypothesis that the prices paid for apartments by different types of buyer organizations are equal. (9) In other words, their data indicate that the form of the buyer's organization is unrelated to the price paid.

Lodging-property-transaction data

Our statistical study of the effects of buyers and sellers on lodging-property sale prices relies on a large database of hotel and motel transactions. For this purpose, a property is defined as a hotel if it includes at least 150 rooms, meeting and banquet space, and restaurant facilities. The data are national in scope and include a large proportion of the lodging-property transactions that occurred during the period beginning in the first quarter of 1985 and ending in the last quarter of 1992. The data are detailed with respect to property characteristics, location, and local economic information. Buyers and sellers in the transactions are identified so that they may be classified (see Exhibit 1).

The primary source of transaction information is the database of the Hospitality Market Data Exchange (HMDE) maintained by Hospitality Valuation Services (HVS). The HMDE contains the sale price, number of rooms, date of sale, and general-location information for several thousand properties. Some information about the characteristics of the properties, such as average room rate, age, amenities, and the conditions of the sales (e.g., financing terms and the organization forms of buyers and sellers) were obtained during visits to the HVS office. Other data were gathered from the following sources:

* Hotel & Travel Index, the AH&MA Hotel and Motel Redbook, and Mobil Travel Guides;

* Members of the Hotel and Motel Brokers Association;

* Telephone interviews with hotel and motel managers;

* Bureau of Labor Statistics and U.S. Bureau of the Census; and

* Sales and Marketing Management magazine.

The database comprises more than 1,300 transactions. Although the sample was not randomly chosen, efforts were made to avoid concentrations of property sales by quarter, geographic region, chain affiliation, and other property characteristics.

About 40 percent of the sales in the database are omitted from consideration for parts of this study because average daily rate and occupancy statistics are unavailable or the property has extraordinary characteristics, such as casino gambling.

Perspective

A broad perspective on behavioral differences among participants in lodging-property markets is gained from the descriptive statistics presented in Exhibit 2. Although the exhibit presents only averages for selected characteristics of transactions across buyer classifications, it reveals quite clearly that different buyers favor different types of properties. Not surprisingly, individuals generally purchase lower-price properties, primarily older motels that are at a greater distance from commercial centers and airports than the average. At the other end of the buyer spectrum are institutions and foreigners who favor high-price hotels. Institutions seem to be especially interested in newer hotels. Partnerships, hotel corporations, real-estate corporations, and other corporations represent a large and rather homogeneous middle class of buyers. During the period 1990 through 1992, however, there was greater diversity in the buying behavior of those entities.

Insight on the behavior of lodging-property-market participants is gained from an examination of the prices they paid and received. Holding all other factors constant, we investigated the effects of unique buyer and seller factors on aggregate prices. More specifically, we determined which effects on pricing of particular property characteristics, such as room rate or age of property, caused the different classes of buyers to overvalue or undervalue a property. By effects we mean overpayment by buyers and underselling by sellers (i.e., selling too cheaply).

We use multivariate-regression procedures to determine the effects of buyers and sellers on prices while holding other factors constant. The model has the following general form:

[S.sub.i]= s ([P.sub.i], [L.sub.i], [E.sub.i], [Q.sub.i], [T.sub.i], [X.sub.i], [Y.sub.i]; [beta], e),

where:

* [S.sub.i] is the cash equivalent sale price of the ith property;

* [P.sub.i] is a vector of property characteristics of the ith property at the time of sale;

* [L.sub.i] is a vector of locational characteristics of the ith property at the time of sale;

* [E.sub.i] is a vector of economic characteristics of the local area in which the ith property is located at time of sale;

* [Q.sub.i] is an unobserved quality measure of the ith property at the time of sale; (10)

* [T.sub.i] is the year of sale of the ith property;

* X is a vector of buyer classifications, one buyer class for the ith property;

* Y is a vector of seller classifications, one seller class for the ith property; and

* [beta], e are estimated parameters and the error terms of the model, respectively.

Exhibit 3 shows which buyer classes paid premiums or gained discounts and which sellers received premiums or gave discounts in the lodging-property market during the study period. The determination as to whether premiums or discounts occurred comes from the regression coefficients for the X and Y variables. Although the procedure is somewhat complicated, essentially it involves identifying buyer and seller classes that either pay or receive 10 percent more and identifying buyer and seller classes that either pay or receive 10 percent less than the theoretically correct prices predicted by the regression model.

As indicated in Exhibit 3, some buyers consistently bought lodging properties at premiums, particularly individuals and foreign buyers, and some sellers consistently sold at discounts, particularly financial institutions and the RTC. These are not shocking results. Theory tells us that the less-informed buyers will err by overpaying and the less-patient sellers will let properties go at discounts. (11)

Fortunately the data allow for a more penetrating analysis than that just described. The results presented in Exhibit 4 are interesting because they yield information about the characteristics that encouraged buyers to pay premiums and sellers to accept discounts. Partnerships, for instance, paid more per dollar of room rate than other buyers. Likewise, individuals paid more per room, foreign buyers paid more for proximity to an airport, and banks paid a premium for proximity to commercial centers. A proper interpretation of the results is that some buyers were willing to pay significantly more on average than others for additional units of the particular characteristics they sought.

Where did financial institutions and the RTC go wrong as sellers in the lodging-property markets? The analysis of property characteristics suggests that these sellers accepted less than the market was willing to pay for proximity to commercial centers and airports and for property located in areas with greater effective buying income. Discounts, however, were partially offset by premiums received for room rate and local-area employment strength.

The Right Price

Prices of lodging properties are influenced by the behavior of parties on both sides of transactions. Price discounts and premiums seem to result from buyers' and sellers' information-gathering capabilities, bargaining skills, and patience. As we expected, individuals consistently paid premiums for properties. These premiums are positively related to the number of rooms in a given property. Also as we expected, some foreign buyers paid premiums based on the weight they gave to the effective buying income of the local area and a property's proximity to an airport. Finally, financial institutions and the RTC discounted the properties they sold as compared to the price they might have commanded in consideration of the location and local economic conditions. The implications of our findings are as follows:

(1) When appraisers apply the sales-comparison approach to value, they are justified in adjusting comparable sales to account for buyer and seller influences.

(2) Brokers are better able to demonstrate the value of their services, particularly in pricing properties for buyers and finding high-paying buyers for sellers. Agents or brokers with access to up-to-date data can recommend certain courses of action based on the most recent transactions available for comparable deals.

(3) Lenders should be more careful when issuing loans to certain classes of buyers for particular types of properties. For example, if an individual (or group of individuals) seeks to purchase a large hotel, the lender may wish to offer a loan at a slightly lower loan-to-value ratio than the lender would offer to other borrowers.

This study does not answer two important questions. First, do all buyers and sellers in a class behave in the same way? Aggregation of market participants into classes is a limitation of the study. Foreign buyers, for example, are not a homogeneous group and the results in Exhibits 3 and 4 tend to confirm that foreign buyers behave differently from one another (e.g., foreign buyers did not overpay during 1985-86). Disaggregation of this and other classes of buyers and sellers was not possible due to sample-size problems.

Second, do the premiums and discounts associated with classes of buyers and sellers persist through time? Another limitation of the study is that the results tend to be time specific. Some market participants are only in the market for a brief period (e.g., RTC) and other market participants will learn from their previous behavior.

The data are constantly improving and future studies using more-complete data sets should not be burdened with the same limitations as this study. EXHIBIT 1 Classification of buyers and sellers

CLASSIFICATION CODE * I. Individual or husband and wife Individual II. Partnerships

a. Limited partnership--public Ltd. Partner

b. Limited partnership--private Ltd. Partner

c. General and other partnerships Gen. Partner III. Domestic hotel corporations Hotel Co. IV. Domestic real-estate corporations Real Estate Co. V. Domestic non-real-estate corporations Corporation VI. Domestic institutions

a. Life-insurance companies Life Co.

b. Banks Bank

c. Savings and loan companies S&L

d. Resolution Trust Corporation RTC

e. Other institutions (pension, government) Pension VII. Foreign individuals, partnerships, banks, Foreign

hotel companies, and real-estate companies * These codes are used in subsequent exhibits to identify specific buyer and seller classes. Note that some subclassifications were combined. EXHIBIT 2 Mean values of selected characteristics from lodging-property transactions 1985-1992, by buyer classification

BUYER CLASSIFICATIONS SELECTED PROPERTY CHARACTERISTICS All Buyers Individual Partnership All periods (1985-1992) Number of transactions 1,314 273 406 Cash equivalent price $11,010,126 5,646,353 9,893,522 Percent hotel (versus motel) 44.5% 17.5 48 Age of property 15.8 Yr. 19.3 14.2 Distance to airport 15.7 Mi. 19.8 14.7 Distance to commercial center 4.9 Mi. 5.3 4.9 Early period (1985-1986) Number of transactions 350 59 142 Cash equivalent price $11,742,123 6,667,962 12,058,662 Percent hotel (versus motel) 50% 27 52 Age of property 14.6 Yr. 16.3 14.6 Distance to airport 12.9 Mi. 16.7 10.9 Distance to commercial center 4.9 Mi. 5.5 4.9 Middle period (1987-1989) Number of transactions 534 109 156 Cash equivalent price $12,495,720 8,657,491 11,329,130 Percent hotel (versus motel) 44.5% 13 52 Age of property 16.3 Yr. 21.4 13.3 Distance to airport 15.9 Mi. 18.5 16.2 Distaru:e to commercial center 5.6 Mi. 6.4 5.5 Late period (1990-1992) Number of transactions 430 105 108 Cash equivalent price $8,569,414 1,946,459 4,973,109 Percent hotel (versus motel) 39.9% 16 35.2 Age of property 16 Yr. 18.7 14.8 Distance to airport 17.6 Mi. 22.9 17.7 Distance to commercial center 4.9 Mi. 3.9 4.2

BUYER CLASSIFICATIONS SELECTED PROPERTY Hotel Real-Estate Other CHARACTERISTICS Corporation Corporation Corporation All periods (1985-1992) Number of transactions 221 211 78 Cash equivalent price 10,014,587 8,603,001 7,976,053 Percent hotel (versus motel) 55.6 46.9 44.8 Age of property 16.7 14.5 14.3 Distance to airport 13.9 14.9 14.6 Distance to commercial center 4.6 4.9 5.7 Early period (1985-1986) Number of transactions 50 65 16 Cash equivalent price 8,372,469 12,401,650 12,023,753 Percent hotel (versus motel) 58 61 43 Age of property 14.5 12.6 16.4 Distance to airport 16.8 11.2 12.4 Distance to commercial center 4.9 5.4 2.6 Middle period (1987-1989) Number of transactions 103 70 51 Cash equivalent price 11,277,690 7,365,196 7,414,263 Percent hotel (versus motel) 54 38 47 Age of property 17.1 16 13.8 Distance to airport 13.2 15.6 14.3 Distaru:e to commercial center 5 5.2 5.2 Late period (1990-1992) Number of transactions 68 76 11 Cash equivalent price 9,308,796 6,494,239 4,693,150 Percent hotel (versus motel) 55.9 42.1 36.3 Age of property 17.9 14.7 13.5 Distance to airport 13 17.7 18.7 Distance to commercial center 3.9 4.3 12.1

BUYER CLASSIFICATIONS SELECTED PROPERTY CHARACTERISTICS Institution Foreign All periods (1985-1992) Number of transactions 51 74 Cash equivalent price 20,060,977 43,721,381 Percent hotel (versus motel) 60.7 74.3 Age of property 12.8 15.9 Distance to airport 14.9 14.1 Distance to commercial center 3.7 4 Early period (1985-1986) Number of transactions 14 4 Cash equivalent price 23,353,036 64,987,500 Percent hotel (versus motel) 50 50 Age of property 11.8 24.5 Distance to airport 14.5 8.6 Distance to commercial center 4.3 1 Middle period (1987-1989) Number of transactions 18 27 Cash equivalent price 31,737,604 49,449,387 Percent hotel (versus motel) 77 74 Age of property 13.8 17.7 Distance to airport 15.9 17.3 Distaru:e to commercial center 4.7 6.9 Late period (1990-1992) Number of transactions 19 43 Cash equivalent price 6,573,182 38,146,482 Percent hotel (versus motel) 52.6 76.7 Age of property 12.7 14.1 Distance to airport 14.2 12.6 Distance to commercial center 2.2 2.5 EXHIBIT 3 Buyer and seller effects on sale prices of lodging properties

Buyers Sellers

Premium Discount

(OVERPAID) Discount Premium (UNDERSOLD) All periods Individual Gen. Partner Hotel Co. RTC 1985-1992 Ltd. Partner Real Estate Co. Corporation Life Co. (n = 781) Foreign Bank Foreign S&L

Life Co. Early period Individual Gen. Partner Bank Ltd. Partner 1985-1986 Corporation Hotel Co. Pension Gen. Partner (n = 206) Life Co. Foreign Foreign S&L

S&L Middle Individual Gen. Partner Individuals Life Co. period Ltd. Partner Bank Life Co. Ltd. Partner RTC 1987-1989 Hotel Co. S&L Hotel Co. (n = 371) Foreign Life Co. Corporation Late period Individual Ltd. Partner Ltd. Partner Bank 1990-1992 Foreign Gen. Partner Corporation S&L (n = 204) Hotel Co. Pension Life Co.

Bank RTC EXHIBIT 4 Price (implicit) premiums and discounts of buyers and sellers for selected property characteristics

Buyers Sellers

Premium Discount

(OVERPAID) Discount Premium (UNDERSOLD) Room rate Partnership None Partnership None

Bank

RTC Number Individual Foreign None Partnership of rooms Hotel Co.

Real Estate

Co. Age None Real Estate Co. Corporation None of property Bank Chain None None Corporation None affiliation Distance Foreign None None Bank to airport Distance to Bank None None RTC commercial center Employment Corporation None RTC Bank of local area Effective Foreign None Hotel Co. None buying income of local area

(1.) For a summary of appraisal methodology; see: Stephen Rushmore, Hotels and Motels: A Guide to Market Analysis, Investment Analysis, and Valuations (Chicago: Appraisal Institute, 1992) chapter 5.

(2) "Why Japanese Buyers Pay a Premium for Hotels," Wall Street Journal, July 9, 1991, p. B1. See also: M. Chase Burritt, "Japanese Investment in U.S. Hotels and Resorts," Cornell Hotel and Restaurant Administration Quarterly, Vol. 32, No. 3 (October 1991), pp. 60-66; and Tadayuki Hara and James J. Eyster, "Japanese Hotel Investment: A Matter of Tradition and Realty," Cornell Hotel and Restaurant Administration Quarterly, Vol. 31, No. 3 (November 1990), pp. 98-104.

(3.) G. Stacy Sirmans and C.F. Sirmans, "Property Management Designation and Apartment Rent," Journal of Real Estate Research, Winter 1991, pp. 91-98.

(4.) James D. Shilling, C.F. Sirmans, Geoffrey K. Turnbull, and John D. Benjamin, "Hedonic Prices and Contractual Contingencies," Journal of Urban Economics, July 1992, pp. 108-118.

(5) Bjorn Hanson, "An Exploratory Study of Operating Income Relative to Replacement Cost for Alternative Combination of Affiliation and Management for Mid-Size and Full-Service Hotels," Ph.D. diss., New York University, 1991.

(6) John B. Corgel, "Brand Name Affiliation and Real Estate Prices," working paper, School of Hotel Administration, Cornell University, 1992.

(7) a formal presentation of the reasons for the differences in buyer and seller behavior is found in Daniel C. Quan and John M. Quigley, "Price Formation and the Appraisal Function in Real Estate Markers," Journal of Real Estate Finance and Economics, June 1991, pp. 127-146.

(8) Brian A. Maris and Fayez A. Elayan, "A Test for Tax-Induced Investor Clienteles in Real Estate Investment Trusts," Journal of Real Estate Research, Summer 1991, pp. 169-189.

(9) William Beaton and C.F. Sirmans, "Do Syndications Pay More for Real Estate?," Journal of the Real Estate and Urban Economics Association, Summer 1986, pp. 206-215.

(10) This measure is the output from a room-rate regression. Readers who are interested in knowing how this measure is produced should consult John B. Corgel and Jan A. deRoos, "The ADR Rule-of-Thumb as Predictor of Lodging Property Values," International Journal of Hospitality Management, No. 4, 1994, pp. 353-365.

(11.) is assumed that domestic partnerships, corporations, real-estate corporations, hotel corporations, and financial institutions are more informed buyers than individuals and foreign buyers.

John B. Corgel, Ph.D., is Baker Professor of Finance and Real Estate at the Cornell University School of Hotel Administration (jc81). Jan A. deRoos, Ph.D., is an associate professor of properties management at the Cornell University School of Hotel Administration (jad10@cornell.edu).

Buying High and Selling Low Revisited:

The "Quiet Industry

It is quieter now that the "noise traders" are absent from the hotel real-estate market!

BY JOHN B. CORGEL AND JAN A. DEROOS

Hotel buyers and sellers in the past were subject to "noise" due to the lack of evenhanded information about hotel prices, often combined with some form of duress for buying or selling. That has changed, as additional sources of information have grown up in the past ten years and would-be hotel buyers and sellers have gained sophistication in their transaction motivations. Thus, while the recent hotel-industry recession seemed at first to be an echo of the downturn ten years earlier--with the attendant expectations of distressed property--buyers who expected a fire sale were frustrated. Sellers did not panic, and institutional buyers stepped in with a lung-term approach that allowed for reasonable valuations.

In the December 1994 issue of Cornell Hotel and Restaurant Administration Quarterly, we published an article with the ironic title, "Buying High and Selling Low in the Lodging-property Market." The purpose of that article was to test the so-called "law of one price" in the special case of the hotel real-estate market. This well-known economics principle states that goods or services that are either of equal quality or are perfect substitutes (for each other) will sell at the same price. This principle is founded oil the assumptions that the market is perfectly competitive, and that the buyers and sellers who are involved in transactions, being equally informed and totally free to deal, have no effect on settlement prices. Stated differently in the context of hotel transactions, a hotel located in city X at the corner of Y Street and Z Street will command the same price per room regardless of whether the seller is either a large REIT or a small limited-liability corporation, and whether the buyer is a hotel-operating company or an individual investor. All that really matters with respect to property pricing are the fundamentals of the property, such as the number of rooms and location, that underlie the hotel's ability to generate stable net operating income.

In addition to the two assumptions above, the law of one price comes with a set of restrictive assumptions about the character of the market. The most important of those restrictions are that information costs are not prohibitively high so as to provide unfair advantages for large-scale participants and that the parties in transactions are not under duress.

Because of the location monopoly of a real-estate parcel, it is commonly held that only imperfect substitutes exist in real-estate markets and that information costs are naturally high. In addition, real-estate market participants frequently find themselves under pressure to sell too cheaply or to buy too dearly. Given these endemic conditions in the hotel real-estate market, we fully expected going into the 1994 study that the law of one price would be rejected in the case of hotel real-estate markets. We expected to find that some investors were buying high and some owners were selling low. Indeed, that is exactly what we found! Beyond testing the law of one price, our specific interests were to identify the "renegade" traders and estimate the magnitude of their errors (clearly not for our gain--we're researchers!).

Hypothesis testing in our study involved the development of a hedonic (i.e., regression) pricing model incorporating important fundamental variables. With the fundamentals held constant, we introduced a series of indicator variables representing various types of hotel buyers and sellers. The significance and size of the coefficients on these buyer and seller variables allowed us to determine who overpaid and who undersold their property, and by how much. A large data base of hotel transactions completed during the period 1985 through 1992 that we maintained then at Cornell was used to derive parameter estimates. The following two points summarize our key findings (remembering that this is a picture of the industry in the late 1980s and early 1990s).

* Foreign buyers (institutions and individuals), especially Japanese buyers, substantially overpaid for hotels. These buyers were new to the U.S. real-estate markets and really did not understand asset pricing and the market distortions that occurred during the 1980s.

* Federally regulated institutions, especially the RTC, substantially undersold hotel property because of pressure by Congress to quickly rid their portfolios of commercial real-estate exposure.

The Hotel Real-estate Market Since '92

The hotel real-estate market has not undergone structural changes during the past ten years. From 1992 through 1997 hotel property prices rose steadily as a number of influences played out. These are:

(1) The mid-1990s was a period characterized by rising personal 'incomes and employment and, consequently, increasing RevPARs throughout the United States. Property prices followed the resulting upward movement of hotel income.

(2) As the ugliness of the early 1990s' real-estate crisis became an increasingly distant memory, capital availability became less of an issue for hotel investors and developers.

(3) The demand for REIT shares experienced an unprecedented rise as institutional investors sought liquidity. Along with growth, hotel REITs became increasingly aggressive bidders, creating an arbitrage opportunity for private market sellers. So, by 1995, both price-per-room and transaction volume were accelerating.

The hotel property market began cooling down well before the recession of 2001, as all of the positive influences mentioned above exhibited signs of fatigue. Investors in existing assets, capital suppliers, and developers simultaneously and instinctively began slowing down the pace of the market in 1999. A graph from a recent Merrill Lynch industry report shows the slowdown in supply growth starting at the end of 1999 (see Exhibit 1). The situation in that time period is different from that of the early 1990s, when it took almost two years for supply to adjust to the downturn in demand. These reactions provide the first real-world evidence of the market discipline that analysts and academics had been expecting for some time.

[GRAPHIC OMITTED]

Disciplined Markets Begin with Sophisticated Participants

The cliche that "experience is the best teacher" became a reality in real-estate markets during the late 1990s. Everyone learned a great deal about how these markets operate from the experiences dating back to the late 1980s. Substantial learning occurred because this period represents the first time in the history of real-estate trading that reliable data were available to study market behavior through a complete cycle. With availability came accessibility to even the smallest hotel investors. For example, Hotel Brokers International (then Hotel Brokers Association of America) in the mid-1990s began producing the Transactions report that provides details of all hotel transactions closed through its membership. These reports continue to be available to the public for a modest charge. Other innovations in the hotel industry that promoted market discipline since the early 1990s include:

(1) Occupancy, ADR, demand, and supply data. Smith Travel Research continues to increase market coverage and reporting frequency.

(2) Construction activity. Lodging Econometrics, and recently Smith Travel Research with the F.W. Dodge Company and Property and Portfolio Research, began to offer detailed reports on hotel-construction pipeline activity by brand and local market.

(3) Econometric forecasts. PricewaterhouseCoopers and (recently) the Hospitality Research Group with Torto-Wheaton Research, produce forecasts of hotel financial performance using sophisticated statistical models.

(4) Operating-expense data. The Hospitality Research Group of PKF Consulting extended its efforts to supply timely and accurate benchmarking data, and Smith Travel Research initiated a service to benchmark hotel financial performance to the NOI line.

What We Think Now

In light of the ongoing changes to the investment climate, the transparency that comes from enhanced data availability, and the continuing evolution of the capital markets' understanding of lodging, we believe that the lodging real-estate market will continue to become more efficient--and thus, based less on "noise." The following are among the most important changes.

* Availability of an ever-broader range of capital sources will continue to ensure that hospitality real estate does not face a liquidity crisis and ensure that hotels are fairly priced. As an example, over the past two years, the principals of many opportunistic funds thought they could repeat their success of the early 1990s, when they took advantage of the combined effects of an industry downturn and a liquidity crisis by buying low and selling high. The majority of these funds have sat on the sidelines this time around as investors with lower required rates of return, such as the REITs, both public and private, and the large institutional investors purchased properties that met their investment criteria.

* Debt capital will continue to provide market discipline. The current environment is dominated by first-mortgage providers who will underwrite a loan with a 60-percent loan-to-value ratio, meaning that equity providers (i.e., owners) must have a substantial stake in their investments. Those investors who use the so-called mezzanine debt market might be able to achieve debt leverage of 80 percent, but only by pledging the majority of excess cash flow to the mezzanine lender; this creates incentives for investors to consider only deals that are economically viable.

* Financial innovations are changing the nature of lodging income. Globally, the use of leases with hotel operators or the willingness of operators to guarantee a minimum return on investment (or at least to subordinate their fees to achieve a minimum return on investment) have the effect of transforming what was a risky flow of net operating income to a much less risky flow. This risk reduction allows for lower required rates of return and higher pricing for hotels.

Just earn it. In summary, while there may be some potential for extraordinary profits from investing in hotels, we believe that the ability to simply buy low and sell high as a result of lodging market cycles or capital market cycles will be greatly diminished in the future. Opportunities to take advantage of noise traders (that is, those whose motivations are based on factors other than the economics of the deal) are gone, and there is no evidence of distressed selling in the current environment, even though the challenges to the industry have been great. Disciplined equity and debt capital, smart underwriting, and broad capital markets will continue to weaken the ability for noise trading to exist in the market for hotels as investment property. Paraphrasing John Houseman's words in the old Smith Barney advertisement, in today's lodging market, you have to make money the old fashioned way, you have to earn it.

John B. (Jack) Corgel, Ph.D., is a professor of real estate at the Cornell University School of Hotel Administration (jc81@cornell.edu), where

Jan A. deRoos, Ph.D., is the HVS International Professor of Finance and Real Estate (jad10@cornell.edu).