Real Estate and Economies of Scale: The Case of REITs

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1 Real Estate and Economies of Scale: The Case of REITs Brent W. Ambrose University of Kentucky Michael J. Highfield Louisiana Tech University Peter D. Linneman University of Pennsylvania October 2, 2003 Contact Author: Brent W. Ambrose is the Endowed Kentukcy Real Estate Professor, Professor of Finance, and Director of the Center for Real Estate Studies at the University of Kentucky. Address: Finance Area, University of Kentucky, 445 Business & Economics Building, Lexington, Kentucky, Office phone: Fax: Electronic mail: Michael J. Highfield is an Assistant Professor of Finance at Louisiana Tech University. Address: Department of Economics and Finance, College of Administration and Business, Post Office Box 10318, Louisiana Tech University, Ruston, Louisiana, Office phone: Fax: Electronic mail: Peter D. Linneman is the Albert Sussman Professor of Real Estate / Professor of Finance and Business and Public Policy at the University of Pennsylvania. Address: Real Estate Department, The Wharton School, University of Pennsylvania, Lauder-Fischer Hall, 256 South 37th Street, 3rd Floor, Philadelphia, Pennsylvania, Office phone: Fax: Electronic Mail: linnemap@wharton.upenn.edu. The authors thank Fred Carr and Steve Sakwa for helpful comments and suggestions. Financial Support for this project was provided by the Real Estate Research Institute (RERI) at the University of Kentucky and the Center for Real Estate Studies at Louisiana Tech University and the Louisiana Real Estate Commission.

2 Real Estate and Economies of Scale: The Case of REITs Abstract Building on past research in REIT organizational structures and the economies of scale debate, we test for economies of scale in REITs by examining growth prospects, revenue and expense measures, profitability ratios, systematic risk, and cost of capital measures. Overall, our results suggest that small REITs have available efficiency gains in the area of growth, and we find that implicit capitalization rates fall as REITs grow larger. Examining revenue and expense measures, our results suggest that large REITs are succeeding at lowering costs, specifically G&A expenses, and increasing revenues. Thus, it is no surprise to find a direct relationship between firm profitability and firm size. Looking at risk, we find an inverse relationship between betas and firm size, and for all cost of capital measures we find significant economies of scale. Overall, our results support the notion of available economies of scale in real estate through growth and consolidation in REITs. JEL Classification: G19; L85 Keywords: REITs, REOCs, Real Estate, Economies of Scale

3 Real Estate and Economies of Scale 1 Real Estate and Economies of Scale: The Case of REITs 1. Introduction The phrase Economies of Scale simply implies that efficiency in production and operations increase with size. In an effort to capture these efficiency gains, firms in various industries seek scale economies by expansion and consolidation. As suggested by many economists during the previous decade, the real estate industry is an example of an industry where economies of scale abound, and larger, publicly traded Real Estate Investment Trusts (REITs) are an excellent tool to take advantage of these efficiency opportunities. During the past decade investors and managers of such REITs have increased investment in income producing real estate using mergers and acquisitions as the primary source of growth. For example, the number of publicly traded REITs declined from a peak of 226 in 1994 to 177 as of November 2002 according to the National Association of Real Estate Investment Trusts. Rating agencies have also taken note of the relationship between real estate and economies of sale. For example, on September 6, 2000, Legg Mason analyst Rod Petrick initiated coverage of Equity Residential Properties with a buy investment opinion and the following statement: Given the company s economies of scale, sound capital structure, and financial flexibility, we believe the stock should trade closer to the average multiple of 10.3 [FFO]. 1 More recently, on January 7, 2002, this buy investment opinion on Equity Residential was lowered to a market performance investment opinion by Legg Mason analysts Rod Petrik and David M. Fick. 1 Legg Mason press release obtained through SNL Financial LC s News OnLine (

4 Real Estate and Economies of Scale 2 In the past we believed a premium multiple was justified due to above-average earnings growth, economies of scale, and lower cost of capital. Those benefits have recently been mitigated. [Instead,] [t]he company has had increasing expenses, and we expect flat FFO growth for If economies of scale exist, costs should increase at a decreasing rate and efficiency gains should be reflected in higher returns. Some have questioned the efficiency gains available through economies of scale. For example, on March 13, 2002, Standard & Poor s stated the following regarding Equity Residential: Equity Residential has established itself as the dominant multifamily landlord, primarily through nearly $10 billion of acquisitions since While the company has concurrently developed an operating infrastructure to manage the integration of this growth, the economic benefits of this growth have not yet to be fully realized in the form of better returns. The company s large size affords it certain economies of scale (leverage with suppliers and vendors), as well as a platform for which to pursue ancillary businesses, but this scale does not appear to result in superior efficiency measures, on a comparative basis. 3 From this statement it appears that S&P agrees with the idea that economies of scale are possible and maybe even present in some of today s larger REITs, but the full realization remains elusive. Along this line, as noted in a SNL commentary by Keith E. Pomroy, some industry experts believe that economies of scale and cheaper access to capital are only part of the story. The following is an excerpt from his commentary regarding Equity Office Properties: As mercury partners analyst Brian O Flanagan puts it, [Equity Office Properties Trust] has become so large that it has come to resemble an index fund. No matter how experienced and skillful EOP s senior managers might be, they cannot know their properties as intimately as can the managers of a REIT one-tenth as large. In practice, a company like EOP must rely upon an army of local-level mangers who know their own markets. While it is true that EOP only has to employ one senior management team, it is not as obvious that there is a clear advantage between the economies of scale in employing 2 Legg Mason press release obtained through SNL Financial LC s News OnLine ( 3 S&P press release obtained through SNL Financial LC s News OnLine (

5 Real Estate and Economies of Scale 3 many local managers over the entrepreneurial qualities inherent in a group of independent small-reit top-management teams. 4 The argument for economies of scale in commercial real estate continues to gain momentum, but as shown in the above commentary, disagreements and arguments against the concept of scale economies continue to exist. Against this backdrop, this paper examines the case for scale economies in REITs on a more complete level than ever attempted before. Our goal is to revisit the analysis first presented in Ambrose and Linneman (2001) who examined the growth of REITs between 1990 and Given the relatively short time-frame of their study and the explosion of REIT size during this period, Ambrose and Linneman (2001) found mixed results supporting the conclusion that significant economies of scale exist in the public real estate market. 5 We revisit their analysis with the advantage of incorporating an additional five years of data, the importance of which cannot be understated. A serious limitation of the earlier studies of REIT economies of scale is the inability to separate size related advantages versus a period of rapidly expanding, strong markets. Thus, our updated analysis now covers an eleven year period that includes a full market cycle (significant market expansion followed by contraction). In addition to the size of our dataset, we also improve on other REIT economies of scale studies by using only real dollar amounts and leveraging SNL data with news-reported information on merger activity. This is important as the costs of integrating a merger occur in the first year or so, while efficiencies are realized largely subsequently. In the following section, we examine the background of consolidation and 4 SNL Extra Commentary obtained through SNL Financial LC s News OnLine ( 5 In related studies, Bers and Springer (1997, 1998) also find empirical support for REIT economies of scale in several cost categories. Furthermore, Capozza and Seguin (1998) find economies of scale in REIT general and administrative expenses.

6 Real Estate and Economies of Scale 4 economies of scale arguments in real estate while defining our expectations. Next we discuss the data and hypotheses. This is followed by a discussion of our empirical results and conclusion. 2. Background and Expectations Following the banking deregulation in the 1980s, real estate investment, which was already heavily debt financed, surged through the use of debt provided by banks and savings and loans. However, the debt crunch of the early 1990s increased the amount of equity capital required to own and operate real estate, forcing many industry lenders to turn to public capital markets. Some observers argued that the real estate industry would have to follow the example of other capitalintensive public firm dominated industries and enter a period of significant consolidation, with publicly traded companies leading the consolidation effort (e.g., Linneman, 1997, 2002). Since 1994 industry watchers have routinely predicted a wave of consolidation in the industry. The period of was a particularly noticeable consolidation period in almost every property sector. 6 For example, in September 1997, Equity Office Properties (EOP) announced a $4 billion merger with Beacon Properties that added 18.8 million square-feet of property to EOP. The combined holding of 33.4 million square-feet of office space made EOP the largest office owner in the U.S., with 245 properties in 21 states and the District of Columbia. In another transaction, in April 1998 Security Capital Pacific Trust of Denver announced its acquisition of Security Capital Atlantic Inc. for $1.6 billion, creating the third-largest apartment REIT in the country, Archstone Communities, with 90,166 apartments and a total expected investment of $5.6 billion in apartment communities. Another example of REIT consolidation was the September 1998, $5.8 billion acquisition of Corporate Property Investors by Simon Property Group. At the completion of the merger, Simon held 241 properties in 35 states, and a staggering 6 See Campbell, Ghosh, and Sirmans (2001) for a discussion of the REIT merger and acquisition activity during the 1994 to 1998 period.

7 Real Estate and Economies of Scale 5 $1.3 billion EBITDA. And in October 1999, Equity Residential Properties Trust acquired Lexford Residential Trust in a merger valued at about $732.8 million. While the number of REIT mergers and acquisitions has slowed in recent years, it has not died out. While the dot-com bubble was bursting in early 2000 and investors finally abandoned overvalued companies with little-to-no tangible assets, real estate stood out as a relatively strong and stable investment. In fact, REITs averaged a 26 percent return for the year, and 2000 was the first year for REITs to outperform both the Nasdaq and DJIA. Thus, with the increase in funds and popularity, REITs again consolidated. While the rate over the past three years has not been as substantial as the period, consolidation has continued. For example: In February 2000 EOP announced a $4.6 billion merger agreement with Cornerstone Properties; In late February 2001, EOP announced a $7.2 billion acquisition of Spieker Properties, Inc., at that time the largest REIT merger and acquisition transaction in history; In December 2001 GE Capital initiated the $8 billion takeover of Security Capital Group; becoming the largest REIT merger and acquisition transaction in history. In fact, 2001 was the third-busiest year for REIT and REOC merger and acquisitions activity, falling behind 1997 and 1998, respectively. So, consolidation must have benefits, right? In a market test sense the answer is clearly yes. Linneman (1997) argued that the typical $ million public REITs were not efficient, and the market has clearly proven this to be true. Although this point has often been lost in the shuffle of history, even as late as 1995 the average REIT total capitalization, adjusted for inflation, was only roughly $500 million. By 2001, average REIT total capitalization was more than three times higher, over $1.6 billion.

8 Real Estate and Economies of Scale 6 Unfortunately, as was the case for banking and other industries in the early phases of their consolidation, it is extremely difficult to identify the presence of economies of scale in the real estate industry. This problem arises for two main reasons. First, given the relatively similar size of most REITs and their recent integration, the statistical technology available to accurately measure economies of scale is not sufficiently precise to fully capture cross sectional variations. Second, the effort required by growing firms to capture scale economies is difficult and time consuming, with the pain of integration generally occurring prior to the realization of the benefits. Thus, exploring cross sectional variations in the presence of significant merger and acquisition activity understates the benefits of scale. Moreover, the consolidation activities described above have been almost continuous in the real estate industry. Also, the market is not static as leading firms merge and achieve competitive advantages, their competitors respond, making it difficult to capture the effect of scale economies cross-sectionally. Not surprisingly, limited statistical evidence of scale economies exists based on data from the 1970s and 1980s, a period when debt was plentiful and the largest players were small by today s standards. Research conducted in the late1980s identified positive REIT stock price movements in reaction to merger announcements, suggesting that market participants felt that larger REITs would be able to achieve economies of scale through better asset utilization. 7 However, these results were countered by the presence of the small-firm effect noted by McIntosh, Liang, and Thompkins (1991). In addition, other studies that examined the impact of announcements concerning property acquisitions on REIT share prices found limited support for economies of scale. For example, McIntosh, Ott, and Liang (1995) find no significant price reaction to asset acquisitions on the part of REITs. In fact, they found a positive and significant price increase for 7 See Allen and Sirmans (1987).

9 Real Estate and Economies of Scale 7 REITs that sell properties. As a result, the early evidence appeared to suggest that significant consolidation of property assets had not clearly created significant gains in shareholder wealth. It is critical to remember that this early research focused on the set of very small REITs that existed from the early 1970s and 1980s, which bear little resemblance to today s fully integrated REITs. For example, in the 1970s and early 1980s the average equity REIT had a market capitalization of only $28 million. Similarly, in 1990, the average equity REIT had an inflation-adjusted market capitalization of just $95 million. Furthermore, regulations during this earlier period (such as shareholder concentration rules) severely restricted the ability of REITs to raise sufficient capital to expand and capture any meaningful economies of scale. It is not surprising that researchers using REIT data from the same period find positive stock price reaction to announcements of asset sales and attributed this to the belief that scale economies do not exist for REITs, as these companies had no scale. Research utilizing data from the 1980s and early 1990s appears to suggest that scale economies exist, at least for larger REITs (e.g., Bers and Springer, 1997; Capozza and Seguin, 1998; and Ambrose and Linneman, 2001). These more recent studies attempt to isolate the effect of economies of scale in REIT expenses, revenue growth, and capital costs and build on the hypothesis that larger REITs have higher earnings growth potential (see Zell, 1997). For example, evidence indicates that the non-discretionary component of general and administrative (G&A) expenses increases at a decreasing rate as REIT size increases. 8 Other evidence indicates that scale economies exist in REIT management costs. However, the studies that examine various REIT expense items (G&A, interest, management fees, operating expenses) find that economies of scale are most present in smaller expense items, suggesting that while economies of scale exist, the 8 See Bers and Springer (1997, 1998) and Capozza and Seguin (1998).

10 Real Estate and Economies of Scale 8 gains from realizing these economies may be insufficient to lead to massive consolidation in the REIT industry. 9 Ambrose et al. (2000) compared REIT income growth and profitability relative to changes for the market to explore economies of scale using data from the 1990s. The results indicate that small REIT net operating income (NOI) growth rates exceed average growth rates in the markets in which they held properties, and thus small REITs appear to be generating revenue and operating economies. However, this does not seem to be the case for the largest REITs. This research indicates that NOI gains, relative to the market, were large prior to 1996, but are no longer so, with REITs at the end of the 1990s outperforming the market primarily via revenue enhancement, not cost reduction. Thus, the results from the Ambrose et al. (2000) study call into question the ability of large REITs to generate sufficient economies of scale based on income growth. However, this conclusion must be interpreted with caution since the study was based on a small sample of residential REITs. Additional research has tested for economies of scale in REIT capital costs, improving on previous studies by examining REITs that invest in multiple property segments (residential, industrial/office, and retail) and focusing on the primary driver of REIT expansion, namely capital. Since REITs are very capital intensive and the primary source of REIT expansion lies in their ability to access capital, significant consolidation may be motivated by scale economies in capital costs. Based on capital costs for equity REITs from 1997 and 1998, the evidence indicates that REITs realized significant scale economies with respect to capital costs. Although all REITs appear to generate scale economies in capital costs, the results from this study find that the scale economies in capital for large REITs are almost twice as large as the scale economies for small 9 Yang (2001) presents evidence for non-linear economies of scale suggesting that diseconomies of scale may exist for large REITs.

11 Real Estate and Economies of Scale 9 REITs. As argued by Linneman (1997), the natural implication is that large REITs are in a position to utilize their economies of scale in capital costs their main input cost to further consolidate the real estate industry. In reconciling the conflicting research regarding REIT scale economies, it seems clear that capital costs are the primary factor determining REIT growth. Thus, consistent with research that focused on other capital-intensive industries, it appears that large REITs do have scale economies in capital costs. As a result, additional growth potential exists within the REIT sector to capitalize on this advantage. As a capital-intensive industry, as mentioned by Linneman (1997), REITs seeking economies of scale should focus on managerial vision, low long-term capital costs relative to competitors, low overhead costs relative to competitors, enhanced revenue opportunities relative to competitors, and successful risk management. We examine each of these topics in turn. However, with this in mind, it should be noted at this point that bigger need not always be better. As stated by Linneman (2002), a large public company is not a silver bullet that will solve all problems, and moreover, it should not be the goal of all REITs to simply become larger. Our data shows that some small companies ($ million capitalization) continue to survive. A large, inefficient REIT is simply a wasted opportunity, and just increasing size will never guarantee success. 3. Data We examine a sample of 187 equity, operating, or hybrid REITs trading on the Nasdaq, New York Stock Exchange (NYSE), or American Stock Exchange (AMEX) From January 1990 through December The sample is restricted to REITs with financial data available from the SNL REIT Datasource and monthly returns available from the Center for Research in Securities Prices (CRSP) database. Appendix A provides greater detail on the REITS contained in the

12 Real Estate and Economies of Scale 10 sample. In addition to the SNL REIT Datasource and CRSP data, we also used SNL Interactive and the Dow Jones News Service to examine all REIT-related press-releases from January 1988 through December From these press releases we compiled a listing of historical mergers and the size of those mergers. Due to possible variations in risk across different firms, property types, or organizational structures, we estimate each REIT s equity beta, a measure of systematic variation in returns relative to the market, using the CAPM framework. Using CRSP we obtain the monthly returns for each REIT in the sample and the CRSP value-weighted market index. We use the 3-month T-Bill secondary market rate as a proxy for the risk-free rate. 10 After converting the T-Bill yearly rate to a monthly rate, we estimate REIT equity betas by regressing the previous 24 months REIT daily returns against the market index using the following model: R it = α + β R + ε (1) i i where R i,t and R m,t represent the monthly returns for REIT i and the market portfolio in excess of the risk-free rate for the 24 prior months, α i is the regression intercept, β i is the estimated equity beta for REIT i, and ε i,t is the standard error term. 11 In addition to looking at the systematic risk of REITs, we also examine the relationship between a REIT s cost of capital and its size. Similar to Ambrose and Linneman (2001), we calculate each REIT s weighted average cost of capital (WACC) as follows: mt it WACC = k d TD TC + k p PE + k TC e CE TC (2) 10 T-Bill rates were obtained from the FRED database at the Federal Reserve Bank of St. Louis ( 11 For example, December 2001 betas are estimated by regressing the REIT returns less the risk-free rate against the CRSP value-weighted market index less the risk-free rate for the period from January 2000 to December 2001.

13 Real Estate and Economies of Scale 11 where TC = TD + PE + CE and k d, k p, and k e are the cost of debt (TD), preferred equity (PE), and common equity (CE), respectively. The cost of debt and preferred equity are estimated as the ratio of total interest expense to book value of debt and the ratio of preferred dividends to book value of preferred stock, respectively. The cost of equity is estimated via the CAPM using the beta calculated in (1). In addition to the WACC for each firm, we also calculate the return on capital (ROC) and Economic Value Added (EVA ) for each REIT. Again, similar to Ambrose and Linneman (2001), EVA is defined as net operating profit after taxes minus the capital charge, where the capital charge is simply the REIT s WACC multiplied by its capital employed. 4. Methods and Results 4.1. Comparison 1996 and 2001 REITst To gain perspective on the changes in REITs between 1996 (last year in the Ambrose and Linneman (2001) study) and 2001 (the last year of data in this study), we report in Table 1 the descriptive statistics for REIT capitalization, growth prospects, revenue and expense measures, and profitability measures for all equity REITs in existence at the end of 1996 and ** Table 1 About Here ** In 1996 the average REIT had a total capitalization of approximately $684 million, this compares to the average REIT market capitalization of approximately $1.683 billion in 2001, an increase of almost $1 billion. 13 Examining growth prospects, in 1996 the average REIT had an implied capitalization rate (ICR) of 9.4 percent and Funds From Operations (FFO) yield of All dollars are expressed in real, 2001 dollars as adjusted by the Bureau of Labor Statistics Consumer Price Index for All Urban Consumers. 13 In Table 1 and all following tables we use the total capitalization of the firm. This is defined as the market value of equity plus the market value of debt plus the market value of preferred stock. In addition to this size metric, we also explored additional size measures including total revenue, total equity capitalization, and total assets. The results in the regression analysis are robust to the size measure.

14 Real Estate and Economies of Scale 12 percent; both significantly lower than the 2001 averages of 11.2 percent and 11.7 percent, respectively. Regarding revenue and expenses, in 1996 net operating income (NOI) averaged 67 percent of total revenue, rental revenue averaged 82.1 percent of total revenue, and general and administrative expenses (G&A) averaged 6.4 percent of total revenues. Although not statistically different from the 1996 figures, the 2001 figures are 65.1 percent, 79 percent, and 7 percent, respectively. Turning to profitability, the 1996 average return on equity (ROE) was approximately 7.2 percent, statistically indistinguishable from the 2001 ROE of 7.8 percent. However, the average 1996 payout ratio of 82.9 percent was significantly larger than the 2001 payout ratio of 66.5 percent. Table 1 also displays the mean, standard deviation, difference in means, and the t-statistic for differences in means for both 1996 and 2001 observations across operating structures. While there are no statistically significant differences between 1996 externally-advised REITs and their 2001 counterparts, the same can not be said for other operating structures. During this five year period we have seen a significant decrease in implied capitalization rates, FFO yields, and payoutratios for self-advised REITs. Alternatively, in addition to significantly increasing in total capitalization, both self-managed and externally-managed REITs registered higher implied capitalization rates and FFO yields in And while both managing structures had a decline in payout ratios, only externally-managed REITs suffered a decline in return on equity over the five year period. When we examine self-advised and self-managed (SASM) REITs we find that the 2001 observations have larger total capitalizations, higher implied growth rates, higher FFO yields, and lower payout ratios than the 1996 observations.

15 Real Estate and Economies of Scale The Entire Sample and Organizational Structures It s fairly obvious that REITs continue to change over time. But the evidence in Table 1 also suggests that organization structure impacts the evolution of REITs. To more effectively analyze this issue, we examine the entire sample, isolating REITs by organizational structure. Panel A of Table 2 presents the means and standard deviations for all observations in our sample, grouped by operating structure, and combinations of operating structures. ** Table 2 About Here ** Noting the difference between self-advised (SA) REITs and externally-advised (EA) REITs in addition to the difference between self-managed (SM) REITs and externally-managed (EM) REITs across the variables covered, Panel B shows the difference in means for each operating structure versus the overall sample. Similar to Ambrose and Linneman (2001), we find that EA, EM, and externally-advised or externally-managed (EAOEM) firms have significantly smaller market capitalizations than the overall sample. On the other hand, SM and self-advised and selfmanaged firms (SASM) have significantly larger market capitalizations (at the 5% level) than the overall sample. Thus, REIT size appears to be closely related to its organizational structure choice. In examining growth prospects, EA, EM, and EAOEM firms have higher implied capitalization rates and FFO yields than sample as a whole, and, more specifically, their SA, SM, and SASM counterparts. Under revenue and expense measures, EA REITs display significantly lower NOI and Rental Revenue as a percentage of revenues. Lastly, we find no differences across organizational structures for profitability measures. Looking more closely at differences between paired organizational structures, Panel C breaks down differences between SA versus EA, SM versus EM, and SASM versus EAOEM. The results show that in each case the SA, SM, or SASM REITS have market capitalizations that

16 Real Estate and Economies of Scale 14 exceed their external counterparts by more than $1 billion. However, as suggested by the results in Panel B, growth prospects for the internally advised and managed groups lag behind the externally-advised and managed groups. All other comparable categories are not statistically different, with the exception of revenue statistics for the SA versus EA comparison. In this case we find that SA REITs exceed EA REITs in both NOI as a percentage of Revenues and Rental Revenues as a percentage of Revenues Differences across the Sample Period In examining differences over time, we report the means for REIT capitalization, growth prospects, revenue and expense measures, and profitability measures across the sample period of These results are provided in Table 3. ** Table 3 About Here ** After adjusting for inflation, during the sample period the total capitalization for an average REIT increased at a compound annual rate of approximately 22 percent (from $194 million in 1990 to $1,683 million in 2001). Panel B displays the difference in means for each year in the sample period versus the overall sample. Noting the general increase in total capitalization in Panel A, it is not surprising to find average total capitalization from 1990 to 1996 is significantly lower than the overall average, while those after 1997 are significantly above average. Perhaps the most notable finding in this table, however, is the decline in payout ratios during the sample period. The payout ratio in 1990 and 1991 was and percentage points higher than the mean for the entire sample, respectively, while the payout ratio in 2000 and 2001 was 7.3 and 10.7 percentage points lower than the mean for the entire sample, respectively.

17 Real Estate and Economies of Scale 15 Panel C of Table 3 presents the difference in means for each year relative to the mean in Based upon market test outcomes, it is no surprise that in each year from 1993 to 2001 the average REIT total capitalization was significantly higher than the average total capitalization in Looking at growth prospects, the implied capitalization rate (ICR) appears to have no significant change over time, and significant changes in the FFO yield appear to alternate sign. With the exception of rental revenue as a percentage of total revenue in 1999, all revenue and expense measures across the sample are indistinguishable from their levels in Profitability, on the other hand, exhibits the trend seen in Panel B with the payout ratio in 1993 and falling significantly below its 1990 level. To more effectively capture differences across time, Panel D examines changes in these variables from year to year. The total capitalization of REITs increases each year from 1992 to 1994 and again from 1995 to With regard to growth prospects, it appears that implied capitalization rates significantly decreased from 1995 to 1996, and increased in each year from 1997 to 2000 before undergoing a significant decline in Our other growth measure, FFO yield, however, varies substantially from year to year. None of the revenue and expense measures have significant changes from year to year, and the same is true for the profitability measures studied with the exception of ROE in Differences Across Property Types In Table 4, we display REIT capitalization, growth prospects, revenue and expense measures, and profitability measures across ten different property types. Although all of the firms are publicly traded, most have a specific property focus (such as hotels, residential properties, or self-storage facilities), with each sector effectively a separate industry with its own operating and competitive dynamics.

18 Real Estate and Economies of Scale 16 ** Table 4 About Here ** For example, recreation REITs typically have the smallest total capitalization, approximately $358 million, while office REITs have the largest market capitalization, approximately $1.6 billion (see Panel A). With regard to growth prospects, residential REITs post the lowest ICR at 9.7 percent, but the somewhat similar hotel REITS have the highest average ICR at 12.8 percent. FFO yields range from 6.6 percent for restaurants, to a high of 10.2 for self-storage REITs. Looking at revenue and expense measures, diversified REITs have the lowest NOI to revenues ratio, 57.9 percent, and healthcare REITs have the highest NOI to revenues ratio. The rental revenue to total revenue varies from 54.9 for hotels to 95.7 for self-storage REITs. While maximizing rental revenue, selfstorage REITs also minimize general and administrative (G&A) expenses as a percent of total revenue at 3.7 percent, while recreation REITs face the highest G&A ratio. It does not cost much to manage cubic space. Lastly, regarding profitability, restaurants have the lowest ROE (-0.7 percent) and highest payout ratio (134.7 percent), while residential and retail REITS have the highest ROE (11.5 percent). Self-storage REITs provide the lowest payout ratios among the groups considered. Panel B displays the difference in means for property focus groups versus the overall sample and provide t-statistics for differences in means. Recreation, restaurant, diversified, and healthcare REITs are significantly smaller than the overall sample in terms of total capitalization. On the other hand, hotel and office REITs are significantly larger total capitalization than the overall sample. FFO yields for restaurant, industrial, residential and office REITs are significantly lower than the FFO yields for the entire sample, but Hotels have FFO yields significantly higher than the mean for the overall sample.

19 Real Estate and Economies of Scale 17 Looking at revenue and expense measures, diversified, residential, self-storage, and hotel REITs have relative low NOI to revenues ratios, and healthcare, retail, restaurant, and recreation REITs have relatively high NOI to revenues ratios. Diversified, healthcare, and hotel REITs have significantly smaller rental revenue to total revenue ratios than recreation, retail, residential, selfstorage, and office REITs. G&A expenses as a percent of total revenue are relatively high for restaurant, recreation, and diversified REITs, but relatively low for healthcare, retail, residential, and self-storage REITs. Regarding profitability, restaurant, industrial, and hotel REITs have statistically low ROE means while healthcare and residential REITs post statistically high ROE means. Lastly, self-storage, hotel, and residential REITs provide lower than average payout ratios, but restaurant and healthcare REITs provide payout ratios significantly higher than the sample mean Regression Analysis As discussed above, the results reveal notable differences across organizational structure, time, and property focus. So, are changes in growth prospects, revenues and expenses, and profitability due to economies of scale or is it organizational structure, time, and property focus that drives these accounting and financial performance measures? ** Table 5 About Here ** Growth Prospects Table 5 provides the multivariate regression results for the impact of size on growth prospects controlling for industry, year, and organizational structure effects. We include the natural log of total capitalization in order to test the hypothesis that the market places a premium on larger REITs. For example, we find a significantly negative coefficient for on firm size and significantly positive coefficient for the quadratic effect in the ICR regression indicating that as

20 Real Estate and Economies of Scale 18 REIT total capitalization increases there is a corresponding non-linear decrease in ICRs. Based on these regression coefficients we calculate that the minimum (?Y/?X = 0) implied capitalization rate occurs at a total capitalization of $9 billion. As suggested by Linneman (1997), and shown in Ambrose and Linneman (2001), this implies a strong value generating scale effect with nine REITs (5 percent) exceeding this turning point in capitalization. Indeed, the market test continues to indicate that there are value-generating benefits obtainable by increasing size because as these firms become larger they become more efficient and the market places a premium on larger REITs. ** Figure 1 About Here ** In addition to size, other factors contribute to the determination of implied capitalization rates. We find that higher asset growth rates and greater amounts of short-term debt both lower implied capitalization rates. Conversely, higher debt usage has the opposite effect. We find no evidence that mergers affect implied capitalization rates; however, development activity levels tend to lower implied capitalization rates in the current year while increasing rates in the following year. The F-statistics indicate that we can reject the hypothesis that the coefficients on industry focus are equal; however, we cannot reject the hypothesis that the coefficients across years are equal. Next we consider the effect of size on FFO yield. Using the natural log of total capitalization we find strong support for the theory that size influences FFO yield. Again, the results indicate a non-linear effect, with FFO Yield increasing as total capitalization increases. The estimated maximum FFO yield occurs at a market capitalization of $1.13 billion. Moreover, as discussed in the previously, we find that organizational structure and time may influence FFO yield. ** Figure 2 About Here **

21 Real Estate and Economies of Scale Revenue and Expense Measures One of the main driving forces behind consolidation in the real estate industry is the belief that larger REITs should obtain some measure of efficiency gains in improving profit margins, increasing revenues, and lowering expenses. Estimates of these effects are presented in Table 6. ** Table 6 About Here ** The ratio of net operating income (NOI) to total revenue is a popular proxy for firm profitability. We find that property focus, organizational structure, and year effects are significant in determining NOI as a percent of total revenue, but we also find a positive and significant coefficient on firm size and a statistically negative coefficient for the quadratic size effect. Thus, firm NOI increases at a decreasing rate as the firm grows larger with the maximum occurring for relatively small REITs with total capitalizations of $352 million. In fact, operating efficiency being achieved at such a small scale is consistent with many small private operations. Capital is the key. Examining rental revenue, we find that property focus, organizational structure, and year effects are significant in explaining rental revenue as a percent of total revenue. Similar to the results for NOI, we find a strong positive relationship between firm size and rental revenue as a percentage of sales, with a maximum percentage occurring at a total capitalization of approximately $9.7 billion. In addition, we find that asset growth tends to increase rental revenue, but current year mergers tend to lower rental revenue. ** Figure 3 About Here ** Another popular argument for economies of scale in real estate is that as a REIT grows larger it should decrease its portion of G&A expenses as a percent of revenue. In other words, it has more properties across which it can spread its G&A expenses. As shown in Table 6, property focus, organizational structure, and time each show significant explanatory power in determining

22 Real Estate and Economies of Scale 20 the ratio of G&A expenses to total revenues. Also, the negative and significant coefficient on firm size and the positive and statistically significant coefficient on the quadratic of firm size suggests that larger REITs are increasing shareholder value by lowering expense ratios; evidence of economies of scale. In this case derivative suggests that the G&A ratio can basically be driven to zero as the firm increases in size, the minimum point does not occur until firms reach a total capitalization in the trillions. ** Figure 4 About Here ** Profitability Measures Turning to profitability measures in Table 7, specifically net income to total equity (ROE), we find evidence that larger firms achieve higher returns for shareholders. The positive and significant size coefficient and the negative and significant quadratic coefficient suggest that ROE increases at a decreasing rate with the maximum occurring at roughly $6.1 billion in total capitalization, a level obtained by 17 of 180 REITs (9.4 percent) in our 2001 sample year. Again, this result is not surprising given the findings for size effects on revenues and expenses. This is shown by the negative coefficient on ICR and G&A as a percent of total revenue. We also find strong evidence that property focus affects ROE. ** Table 7 About Here ** ** Figure 5 About Here ** In addition to ROE, we find strong, positive evidence that firm size affects payout ratios in a similar, non-linear way, but the payout ratio appears to reach its maximum at a relatively small size of $78 million in total capitalization. Although we find that current year development lowers payout ratios, this issue as a whole is driven by dividend discipline of the board rather than operating or capital market issues.

23 Real Estate and Economies of Scale 21 **Figure 6 About Here ** Betas Equity betas measure the systematic variation in returns for a stock relative to the market as a whole. With this in mind, in Table 8 we provide the results of a regression estimating the impact of REIT size on beta controlling for growth effects, capital structure, industry, year, and organizational structure effects. ** Table 8 About Here ** Industry, year, and organizational structure appear to impact equity betas, and we find significant coefficients for growth measures, payout ratios, and capital structure ratios. We also find a marginally statistically significant negative coefficient on firm size and a positive but insignificant coefficient on the quadratic of firm size, implying that larger firms have smaller betas. This suggests that larger REITs enjoy less systematic variation in stock returns relative to the market. ** Figure 7 About Here ** Capital Costs Turning to capital costs, Table 8 reports the results of three regressions estimating the impact of REIT size on WACC, ROC, and EVA Spread controlling for growth effects, capital structure, industry, year, and organizational structure effects. First, consistent with Linneman (1997) and Ambrose and Linneman (2001) we find that the coefficient on firm size is statistically significant and negative, confirming that larger firms enjoy lower costs of capital. We also find that this result is non-linear as evidenced by the positive and significant coefficient on the quadratic of firm size, and the minimum occurs at the relatively small size of $180 million. This is due primarily to the fact that REITs are increasing their WACC as they add additional debt. There

24 Real Estate and Economies of Scale 22 appears to be no significant relationship between WACC and industry focus, organizational structure, or time. ** Figure 8 About Here ** Examining return on capital, we find that industry, year, and organizational structure impact REIT ROC. We also find negative and significant coefficients for asset growth, total debt to total capitalization, and G&A to total revenue. However, we also find a statistically significant positive coefficient on firm size and a negative statistically significant coefficient on the quadratic of firm size. The derivative suggests that ROC increases at a decreasing rate with the turning point occurring at roughly $473 million in total capitalization. ** Figure 9 About Here ** Finally, we find that capital structure, industry, year, and organizational structure effects do impact EVA Spreads, but firm size also plays an important part in the relationship. In fact, we find that larger REITs have higher EVA Spreads, but again, this relationship increases at a decreasing rate with a turning point occurring at approximately $860 million in total capitalization. This is consistent with Ambrose and Linneman (2001) and supplies additional evidence of economies of scale in capital costs. ** Figure 10 About Here ** In summary, looking at Table 8 we see that larger firms are less risky, as measured by equity betas, than their smaller counterparts, and these larger firms enjoy lower costs of capital, as measured by WACC, while generating profits in excess of their cost of capital, as measured by ROC and EVA Spread. Other results are also noteworthy. First, choice of capital structure does impact overall risk and cost of capital. Second, high payout ratios decrease systematic risk. Finally, looking at the tests of equality presented at the bottom of each regression, it is interesting to note

25 Real Estate and Economies of Scale 23 the relatively small variation in WACCs across property segments, time, and organizational structures. We also find little to no variation in EVA Spreads across time. The market has proven that REITs have dramatically increased in size over the past decade, and they will continue to do so. In 1990 a $300 million REIT was a large company, but now a $300 million company is one of the smallest. However, we cannot misinterpret our results as a projection of doom and gloom for small REITs. While our turning point estimations do suggest a maximum or minimum size that is best for that particular operating or capital measure, as suggested by Stigler (1964), there is no single, magical, optimal firm size. Just because a REIT is smaller or larger than our estimates does not mean that it cannot compete. In fact, some small, well managed REITs are sustaining competitive advantages over large, poorly managed REITs. The real point here is that economies of sale are visible in REITs with part of this effect due to increases in operating efficiency, and the remainder a reward to capital. As a result, the market has generally forced REITs to expand and consolidate. 5. Conclusions Real estate investment trusts (REITs) have experienced significant growth and received increased attention in the financial literature during the past decade. With this increased attention and growth, many experts have raised the possibility of economies of scale in real estate, and theory suggests that as REITs have grown and merged they provide an almost perfect laboratory for examining any such scale economies. Building on past research in REIT organizational structures and the economies of scale debate, we test for economies of scale in REITs by examining growth prospects, revenue and expense measures, profitability ratios, systematic risk, and cost of capital measures. Utilizing REIT property data from the SNL REIT Datasource as well as REIT and market return data from the

26 Real Estate and Economies of Scale 24 CRSP database, we look at differences in REITS across organizational structures, across time, and across property focus. We then estimate multivariate regression models to determine if REITs are gaining economies of scale with respect to firm size. A serious limitation of the earlier studies of REIT economies of scale is the inability to separate size related advantages versus a period of rapidly expanding, strong markets. Thus, our updated analysis now covers an eleven year period that includes a full market cycle (significant market expansion followed by contraction), the importance of which cannot be understated. In addition to the size of our dataset, we also improve on other REIT economies of scale studies by using only real dollar amounts, leveraging SNL data with news-reported information on merger activity, and specifically controlling for REIT property focus. As a whole, our results suggest that small REITs have available efficiency gains in the area of growth. We find that small, externally-advised or externally-managed REITs have larger implied capitalization rates than their larger internally advised or internally managed counterparts. Turning to revenue and expense measures, the results here suggest that large REITs are succeeding at lowering costs, specifically G&A expenses, and increasing revenues. In fact we find that NOI as a percent of sales increases with REIT size, and we also find evidence that larger firms have an increased proportion of rental revenue to total revenue. Thus, it is no surprise that there is a direct relationship between firm profitability, as measured by return on equity, and firm size. On the other hand, we find no evidence of economies of scale in payout ratios. With respect to equity betas, we find an inverse relationship between betas and firm size indicating that as REITs grow larger they are finding ways to lower systematic risk. These findings are supported by the inverse relationship between REIT size and WACC. In fact, for all cost of