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2010
V38
2: pp. 257–284
REAL ESTATE
ECONOMICS
Banking Relationships and REIT Capital
Structure
William G. Hardin III∗ and Zhonghua Wu∗∗
This article examines the evolution of real estate investment trust (REIT) capital
structure in the new REIT era with a focus on the effects of banking relationships on REIT capital structure. Using a unique sample of REITs from 1992 to
2003, we find that, after controlling for firm characteristics, REITs with banking
relationships are more likely to obtain long-term debt ratings and subsequently
issue public debt. Moreover, REITs with banking relationships tend to use less
secured debt and have lower leverage. These findings support the notion that
banking relationships facilitate REITs’ access to the public debt markets and
help explain why REITs shift from traditional mortgage financing to bank debt
and public capital market financing. The results also support the proposition
that firm leverage should be positively related to the amount of a firm’s secured
debt.
Introduction
Capital structure has been an interesting research topic in the real estate investment trust (REIT) literature. REITs provide a unique laboratory to examine
capital structure issues for at least two reasons. First, REITs do not pay corporate taxes, so there is no obvious tax advantage associated with the use of
debt. This isolates, to some extent, the tax-motivated arguments found in capital structure research. Second, REITs are capital-intensive firms constrained
by mandated dividend payout requirements. Hence, they have to go to external
capital markets more frequently to raise capital than other firms. This implies
that the pecking order rationale for use of debt is partially silent.
Previous research on REIT capital structure has largely focused on public debt
and equity offerings (Brown and Riddiough 2003) or the signaling effect of bank
debt (Howe and Shilling 1988, Elayan, Meyer and Li 2004). Little empirical
analysis has been done on the optimal mixture of debt or the dynamics of REIT
capital structure in the new REIT era. As Brown and Riddiough (2003) point
out, many interesting questions remain to be explored including which specific
∗
Department of Finance and Real Estate, Florida International University, Miami, FL
33199 or [email protected].
∗∗
Department of Finance and Real Estate, Florida International University, Miami,
FL 33199 or [email protected].
C 2010 American Real Estate and Urban Economics Association
258 Hardin and Wu
types of debt and equity are optimal, why REITs use debt at all given minimal
tax benefits and how much debt REITs should use in total.
One remarkable trend in REIT financing structure over the past 15 years is a
dramatic increase in the use of bank debt.1 This is largely due to the fact that
the REIT industry has experienced rapid growth with property acquisitions,
development, and mergers representing the core growth strategies employed.
Given that REITs have limited ability to retain internal cash flows due to required dividend payouts, REITs have relied heavily on the liquidity provided
by banks when making property acquisitions and developing new properties.2
Also, REITs have developed banking relationships through repeated borrowing
from the same bank or banks. The use of bank debt for liquid capital and the
development of banking relationships has become the present industry norm.
Concurrently, REITs have reduced their reliance on mortgages and have increasingly gone to banks and the public capital markets to raise capital (Table 1).
The shift in REIT funding sources and capital structure is apparent. The capital
sources available to the REIT industry have expanded from an initial narrow
range limited to secured debt (mortgages, for example) and equity to an expanded range of capital sources that includes bank lines of credit and capital
market debt along with common and preferred equity.
Although bank debt has become an integral source of capital for REITs, there
has been little research regarding the effects of bank debt use and banking
relationships on REIT capital structure. Given that banks provide firms with
efficient monitoring services and banking relationships help firms mitigate
capital market frictions (Diamond 1984, Boot 2000), it is both interesting and
necessary to examine how the use of bank debt and the development of banking
relationships influence REIT capital structure.
This article examines the evolution of REIT capital structure in the new REIT
era with a focus on the effects of banking relationships and the use of bank debt
on REIT capital structure. Specifically, the following questions are addressed.
First, are REITs with banking relationships more likely to have access to
public debt markets? Second, does the development of banking relationships
help reduce the use of secured debt in a REIT’s liability structure? Third,
do REITs with banking relationships have higher or lower leverage? These
questions are closely related. For example, if REITs with banking relationships
are more likely to have access to public debt markets, one would expect that
1
Since 1992, bank lines of credit outstandings of REITs in our sample have increased
from $329 million to $13,405 million in 2003, with peak outstandings of $17,649 million
in 1998. See Table 1 for more details.
2
In theory, banks provide external-source liquidity to firms which relaxes the firms’
liquidity constraints (Holmstrom and Tirole 1998).
Banking Relationships and REIT Capital Structure 259
Table 1 Capital sources of equity REITs from 1992 to 2003.
Year
SEO
PublicDebt
BankDebt
Mortgage
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
853
3,275
3,492
6,486
10,210
24,926
18,557
6,298
2,313
2,536
4,649
9,389
489
2,621
3,191
3,867
4,752
10,534
14,166
9,604
6,044
8,650
8,353
10,642
329
370
2,918
3,230
4,291
11,724
17,649
15,279
13,233
11,658
12,162
13,405
911
1,159
1,029
1,536
1,976
2,647
2,601
2,650
1,790
1,760
1,254
1,717
The table reports the measures of capital for equity REITs in the sample each year from
1992 to 2003. SEO includes seasoned common and preferred equity issuance in year t.
PublicDebt is public debt issuance in year t, including long-term notes and mortgagebacked securities. BankDebt is the total amount of bank debt borrowed (net borrowing)
from bank credit lines at the end of year t. Mortgage is the total amount of mortgage
debt borrowed at the end of year t. The data source for SEO and Public Debt is the
NAREIT capital offering database. The bank debt and mortgage data are from the SNL
REIT database. Only equity REITs registered with the NAREIT are included in the
sample. All numbers are in millions of dollars.
these REITs should have lower secured debt ratios. Essentially, the first two
questions ask whether banking relationships influence debt structure, whereas
the last question is directly focused on the overall capital structure of REITs.
A brief review of theory and existing empirical studies in the related literature
helps develop propositions regarding these questions. First, Diamond (1991)
argues that banks provide efficient monitoring services and help young and
small firms build track records, which in turn facilitates their access to the
public capital markets. Also, banking relationships, developed through repeated
interactions between lenders and borrowers, further help firms mitigate capital
market frictions and improve their overall capital acquisition process (Boot
2000).3 In the case of REITs, many firms are relatively young and small,
and the REIT industry has experienced a dramatic wave of growth. As such,
information asymmetry and agency-related problems can be serious issues for
REITs’ capital providers.4 Thus, banking relationships can potentially improve
3
To some extent, banking relationships provide a better metric to assess the effects of
bank debt use on capital structure.
4
Arguably, the information asymmetry issues in the REIT sector are largely unresolved
(see Han 2006 and Feng, Ghosh and Sirmans 2007). For small and young REITs and
260 Hardin and Wu
REITs’ access to the public capital markets. Although REITs did use debt
financing prior to the emergence of the bank debt standard, this debt financing
was typically mortgage debt with liens against specific properties. This type
of debt, while perhaps allowing for greater leverage at the property level,
limits management’s operating and strategic options by the creation of loan
and property specific constraints on property acquisition and disposition. Bank
debt in the form of a line of credit is very different from mortgages in that these
loans are more flexible and can be issued against a firm’s future cash flows and
not cash flows from a specific property. Thus, a role of bank debt, especially
bank lines of credit, as opposed to mortgage debt, is to effectively monitor and
certify the REIT management’s acquisition strategy. Because public debt is
often unsecured, arms-length debt, public bondholders care about the REITs’
acquisition strategy and thus value the bank lender’s certification. This form
of debt reduces the capital market frictions and also provides a mechanism
for timely access to public capital markets as proposed by Ooi, Ong and Li
(2010).
Moreover, with the repeal of the Glass-Steagall Act in 1999, a major regulatory
hurdle limiting the ability of commercial banks in their provision of investment
banking services was eliminated. Commercial banks can now directly underwrite public securities,5 which further helps REITs gain access to public capital
markets based on their lending relationships. When REITs gain better access
to public debt markets (mostly for unsecured debt),6 one would expect that
REITs with banking relationships have lower secured debt ratios. As banking
relationships mitigate capital market frictions, these REITs are less likely to be
required to provide collateral for their borrowings when their bank–borrower
relationships strengthen (see Boot and Thakor 1994).
Regarding the effect of banking relationships on leverage, existing theory
offers ambiguous predications. One might argue that REITs with banking
those with an UPREIT structure, information asymmetry can still be a serious issue in
the capital markets. Also, it is difficult to determine the fair market value of real property
transactions that include a wide range of heterogeneous, illiquid assets.
5
Commercial banks could partially conduct underwriting business before 1999 by
setting up Section 20 Branches.
6
According to a Moody’s Investor Services special report titled “Moody’s Views on
Secured versus Unsecured Debt in REITs’ Capital Structures” (April 2002), mortgages
and secured debt are less flexible for a variety of reasons including their limited ability
to be restructured or paid down. Also, encumbered assets are more difficult to sell.
Conversely, unsecured debt is an efficient, flexible and cost-effective financing when
implementing a growth strategy. This is because unsecured debt affords a rated firm
considerable financial and strategic flexibility by maintaining the liquidity of the firm’s
assets. Unsecured debt, furthermore, enhances a firm’s access to funding sources and
entails a faster borrowing process.
Banking Relationships and REIT Capital Structure 261
relationships should have higher leverage. As banking relationships mitigate
capital market frictions that would force firms to have lower leverage, REITs
with banking relationships should have better access to the debt markets in
general (Johnson 1998).7 On the other hand, Brown and Marble (2007) show
that the asset substitution problem decreases with the proportion of the original
debt that is secured, and thus firms with lower secured debt would have lower
leverage due to the concerns related to asset substitution. The characteristics
associated with secured lending underwritten to a single property and the ability
to more readily assess the value of real estate collateral and to control the cash
flow from a collateral property also point toward lower leverage with the use of
unsecured bank lines of credit. The trade-off to REITs is increased operating
flexibility. This is especially relevant to REITs, as REITs have experienced a
dramatic wave of industry growth requiring active property acquisitions, development and disposition strategies. Thus, from a lender perspective, less secured
debt implies more potential risk. From a REIT perspective, higher leverage may
not always be the optimal financing strategy given that there exist no tax benefits
from borrowing and many REITs are incented to improve their credit ratings
(Brown and Riddiough 2003), which facilitates access to public capital markets. Hence, one can also argue that REITs with banking relationships should
have lower leverage. The issue then is an empirical question.
Based on a unique sample of REITs, the main findings of this article are summarized as follows. First, after controlling for firm characteristics such as firm size
and age, REITs with banking relationships are more likely to have a long-term
bond rating and subsequently issue public debt. This result supports Diamond
(1991). Second, REITs with banking relationships have lower secured debt
ratios and use less leverage. This finding is robust across different specifications, e.g., whether we use different measures of the secured debt ratio and the
leverage ratio or use different econometric methods including an instrumental
variable approach. Finally, evidence that REITs often use proceeds from bank
debt and equity to fund property acquisitions and then issue public securities
to reconfigure capital structure (see Brown and Riddiough 2003) is provided.
Bank debt can be conceptualized as a form of “bridge financing.”
These findings provide new insights on REIT capital structure research. First,
our results support the notion that the development of banking relationships
helps REITs shift from mortgages and secured debt toward more corporate-like,
unsecured debt financing. The use of more unsecured debt reflects a greater
integration of REITs into the capital markets and is reflective of a more mature
industry. Second, this article also sheds light on the big question of why REITs
7
Note that Johnson (1998) uses a cross sectional data set (instead of a panel data set) to
test this relation.
262 Hardin and Wu
use debt at all given no obvious tax advantage. The findings suggest that at
least one reason for REITs to use debt is to obtain financial liquidity through
banks to take quick action in property acquisitions. Third, the finding that
REITs with banking relationships have lower leverage supports Brown and
Marble (2007), which shows that firms with lower secured debt ratios also
have lower leverage. This finding is also consistent with Brown and Riddiough
(2003). If public debt issuers tend to target leverage to maintain their credit
ratings, it is not surprising that REITs with banking relationships have lower
leverage.8 Although this result differs from Johnson’s (1998) study of nonREIT firms, such a difference is largely due to the unique characteristics and
operating environment of REITs. It is important to recognize that REITs use
bank debt and then public debt financing to improve financing and operating
flexibility rather than just source additional debt capital. By using bank credit
facilities, REITs effectively control leverage while maintaining adequate levels
of liquidity.9
Our results are also largely consistent with the recent capital structure literature. Faulkender and Petersen (2006) argue that the source of capital affects
capital structure. With an increased use of bank debt and the development of
banking relationships, REITs gain access to the public capital markets and also
have lower secured debt ratio and leverage ratio. This implies that the source
of capital (bank debt) and banking relationships can influence capital structure. Moreover, the results support Hackbarth, Hennessy and Leland’s (2007)
proposition that mature firms tend to use mixed debt financing (bank debt and
market debt). Finally, to our best knowledge, this is the first article to explore
the link between banking relationships and corporate capital structure. REIT
debt structures evolve through at least three stages. The initial stage includes
secured single-asset liabilities such as mortgages, the second stage includes
revolving bank debt which is now typically unsecured, and the third stage
includes arms-length, unsecured public debt. Banks are clearly an important
player in the evolution of REIT liability structures. Although it is difficult to
see this evolution clearly in a sample of non-REIT firms, the creation of the
modern REIT industry provides an outstanding way to demonstrate a bank’s
role in the evolution.
This article is organized as follows. The section “Literature and Theoretical
Background” discusses the theoretic background and the related literature. In
8
Although banking relationships facilitate REITs’ access to public capital markets, to
some extent they also serve as a discipline mechanism for REITs as banks can effectively
monitor firms and specify various loan covenants to control agency issues.
9
The unused bank lines of credit represent the available liquid capital to REITs, but
they are not part of a firm’s leverage ratio.
Banking Relationships and REIT Capital Structure 263
the section “Data and Preliminary Analysis” the data are described and the
results of a preliminary analysis are reported. The section “Empirical Results”
discusses the main empirical results. The section “Conclusion” provides a
conclusion.
Literature and Theoretical Background
REIT Capital Structure
Two main factors make REITs a unique laboratory to examine issues in capital
structure. First, REITs do not pay corporate taxes, so there is no obvious tax
advantage to use debt compared with other real estate firms. Howe and Shilling
(1988) argue that REITs should borrow little or no debt to fund investment as
they cannot compete with taxpaying entities.10 To some extent, this isolates
the tax factor in capital structure research. Second, REITs are capital-intensive
firms constrained by the 90% dividend payout regulation.11 Hence, they have
to go to external capital markets more frequently to raise capital, which makes
the pecking order rationale partially silent on the use of debt.
Previous literature on REIT capital structure largely focuses on the signaling
effects of bank debt (Howe and Shilling 1988, Elayan, Meyer and Li 2004)
or equity and public debt offerings of REITs (Brown and Riddiough 2003).
Howe and Shilling (1988) find a positive stock price reaction to debt offerings,
but a negative reaction to equity issuances. They argue that this lends support
to signaling as the explanation for these effects. Elayan, Meyer and Li (2004)
further investigate the signaling effect and find that the announcement of bank
debt by a REIT sends a positive signal of management’s superior information
regarding the firm’s true equity value. Brown and Riddiough (2003) examine
REIT liability structure and whether REITs target longer-run debt ratios by
focusing on equity and public debt offerings. They show that REITs that issue
public debt are likely to target a longer-run leverage ratio to keep an investmentgrade credit rating. Ooi, Ong and Li (2010) further investigate targeted debt
ratios and the timing of public offerings in REITs and find that REITs time
market activities within a general targeted debt ratio environment. Although
researchers have probed different areas in REIT capital structure, there exists
10
However, Jaffe (1991) claims that as long as REIT investors can borrow and lend at
the same rate as REITs, it does not matter whether REITs use leverage because REIT
investors can always undo a REIT’s leverage decision by lending their personal funds
to the capital markets if they believe that the REIT borrows too much.
11
By tax law, REITs are regulated to pay out at least 90% of taxable income as dividends,
which limits their ability to hold cash. The payout requirement was as high as 95% before
2001. Even when Funds From Operations (FFOs) are considered, most of the REITs
pay out 65%–90% of their FFOs (Kallberg, Liu and Srinivasan 2003).
264 Hardin and Wu
little research on the details of debt structure and how the use of bank debt and
the development of banking relationships affect the dynamics of REIT capital
structure.12 The studies of public debt and equity activities assume that firms
can be managed to position themselves for capital market transactions, but do
not address the mechanics of such positioning.
A recent trend in the capital structure research is to examine the optimal mixture
and the priority structure of liabilities. For example, Hackbarth, Hennessy
and Leland (2007) investigate why different firms have different debt priority
structures and show that large or mature firms tend to employ mixed debt
finance, i.e., a mixed debt structure with bank debt and market debt. Faulkender
and Petersen (2006) examine the link between where firms obtain their capital
(private vs. public debt markets) and their capital structure and find that the
source of capital affects capital structure. These findings suggest that, not only
does the overall capital structure matter, but debt priority structure and the
source of capital are also important aspects in capital structure decisions. This
new trend of capital structure research brings additional dimensions for REIT
capital structure research.
Taken together, given the limited amount of existing work on bank debt use
and a new direction on capital structure research, a detailed examination on the
effects of bank debt use and banking relationships on REIT capital structure
warrants further analysis.
Bank Debt and Effects of Banking Relationships
Bank debt is a unique financing instrument, which provides firms with liquid
capital, mitigates informational asymmetries in the capital markets and adds
monitoring benefits to shareholders (see Diamond 1984, James 1987, Houston
and James 2001). One important feature associated with bank debt use is that
borrowers and banks can develop lending relationships through repeated interactions over time, which further helps mitigate capital market frictions13 and
reduces bank loan pricing and public security underwriter fees for borrowers
(Datta, Datta and Patel 1999, Drucker and Puri 2005, Yasuda 2005).
Diamond (1991) argues that banks provide efficient monitoring services and
help young and small firms build sufficient track records to access public
12
Ooi (2000) examines use of bank debt among property companies listed in the UK
and identifies key factors influencing the firm’s decision to use bank loans. Hardin and
Hill (2008) incorporate bank line of credit usage into REIT dividend policy, but they do
not address capital structure.
13
See Boot (2000) for an excellent review on the theoretical aspects of banking
relationships.
Banking Relationships and REIT Capital Structure 265
markets. Once these firms establish a good credit history or reputation, they are
better able to acquire financing from the public debt markets. This has direct
implications on REITs as many firms are relatively young and small compared
with other public firms. Bank debt use and banking relationships could help
REITs build track records and are likely to be important determinants of capital structure for an industry as new as the modern REIT industry. Although
REITs used debt financing prior to the modern REIT era, this debt financing
was typically mortgage debt with liens against specific projects. Bank debt in
the form of revolving credit facilities is different from mortgages in that these
bank loans are more flexible and are often issued against the firm’s future cash
flows and not just the cash flows from a specific property. Thus, the role of bank
debt, as opposed to mortgage debt, is that bank lenders can effectively monitor
and certify the REIT management’s acquisition strategy. Because public debt is
often unsecured, arms-length debt, public bondholders care about the REITs’
acquisition strategy and thus value the bank lender’s certification. With the
repeal of the Glass-Steagall Act in 1999, a major regulatory hurdle limiting the
ability of commercial banks in their provision of investment banking services
was eliminated. This repeal allows commercial banks to directly underwrite
public securities. One can then hypothesize that REITs with banking relationships will be more likely to gain access to the public debt markets based on
their lending relationships.
An important related issue is the effect of banking relationships on a REIT’s
secured debt ratio. Boot and Thakor (1994) show that collateral is useful in the
early stages of a banking relationship in mitigating capital market frictions. As
the relationship strengthens and the borrower demonstrates success in undertaking investment projects, the bank then reduces the collateral requirements.
Dennis, Nandy and Sharpe (2000) provide evidence that collateral is more
likely to be required in the presence of capital market frictions. The REIT
industry provides an excellent opportunity to evaluate the relationship between
secured lending and capital market frictions. Expansion of the industry and
the development of substantial knowledge of the industry and firms within the
industry can be linked with a change in the composition of debt provided on
both a secured or unsecured basis. Informational asymmetries and other capital
market frictions between REITs and lenders are reduced allowing for a greater
use of more flexible unsecured debt. Hence, we expect that REITs with banking relationships should use more unsecured debt (see the Moody’s Investor
Services special comment [April, 2002] for more details).
As for the effect of banking relationships on REIT leverage, theory offers different predications. Given REITs do not pay corporate taxes and thus there exist
no tax benefits from borrowing, the standard trade-off theory would predict that
REITs with banking relationships should use less leverage. More important,
266 Hardin and Wu
Brown and Marble (2007) show that the asset substitution problem decreases
in the proportion of the original debt that is secured implying that firms with
lower secured debt ratio would also have lower leverage. This is especially
relevant to REITs as REITs have experienced a dramatic wave of industry
growth with property acquisitions and mergers being the core growth strategies
employed. Consequently, the asset substitution problem could be a serious concern for lenders. Thus, from the lenders’ perspective, less secured debt implies
more potential risks. Bank lenders may specify restrictions through the use
of loan covenants to control REIT leverage and reduce the asset substitution
problem. From the REIT perspective, higher leverage may not always be the
optimal financing strategy given that there exist no tax benefits from borrowing and many REITs have incentives to improve their credit ratings (Brown
and Riddiough 2003). Taken together, one could argue REITs with banking
relationships should have lower leverage.
On the other hand, others might argue that REITs with banking relationships should have higher leverage. Johnson (1998) contends that asymmetric information-related problems lower optimal leverage of firms. When firms
repeatedly borrow from the same banks and gain benefits from banking relationships, one would expect a higher leverage for those with banking relationships
because banking relationships mitigate capital market frictions. Given the different theoretical predictions, we believe that it is an empirical question whether
REITs with banking relationships have higher or lower leverage.
Data and Preliminary Analysis
Data
To conduct the empirical analysis on the effects of banking relationships, three
data sources are used to obtain information on REIT bank loans and public
security offerings as well as firm financial information. The first is Loan Pricing
Corporation’s (LPC’s) DealScan database. DealScan is a leading data source
for the global commercial loan market. A number of recent studies on banking
relationships use this database including Drucker and Puri (2005) and Bharath
et al. (2007). For each loan, the database provides information on loan terms
such as loan amount, loan maturity, loan spread as well as detailed lender
information.14 Based on the four-digit SIC code of REITs (6798), 1,434 REIT
bank loans are identified from the database. The data set includes 1,061 bank
lines of credit and revolvers, 303 term loans and 70 other loans for the period
of 1992–2003.
14
For example, one can obtain detailed lender and borrower information on a loan,
which is used to construct the banking relationship variables.
Banking Relationships and REIT Capital Structure 267
The data source for the public security offerings is the SDC Global New
Issues database. This database is also widely used in the literature (e.g., Yasuda
2005). For each offering, available information includes offer price, yield,
underwriting fees, offer amount and information on underwriters, dating as
far back as 1970. Again, using the SIC code 6798, two samples of public
security offerings of REITs are generated: one for public debt offerings, which
includes 769 nonconvertible REIT public debt offerings, and the other for equity
offerings, including 885 equity offerings issued between 1992 and 2004.15
Because neither the DealScan nor the SDC databases provide adequate firmlevel financial information, these data sets are merged into the SNL REIT
database to construct measures on banking relationships and security offerings
of REITs for a given year.16 The SNL database provides detailed firm-level
information. Using this database, one can identify whether a firm is an equity
REIT, its property-type focus and the detailed financial information, such as
total assets, real estate investments and market capitalization. To be included
in the sample, REITs have to meet the following criteria: (1) be listed on the
NYSE, AMEX or NASDAQ and have elected REIT tax status at the beginning
of the sample year (1992); (2) be registered with NAREIT and (3) be an equity
REIT.
Table 2 presents the summary statistics (mean and standard deviation) for the
sample based on whether a firm has a banking relationship. Note that the firm
size of the REITs with banking relationships is significantly larger than those
without. However, the firm ages of the two groups are similar. These results
suggest that it is not necessarily the case that older firms are more likely to
have banking relationships. In addition, REITs with banking relationships are
more likely to have long-term debt ratings, issue more public debt and have
lower secured debt ratios. Although the leverage ratios are similar for these
two groups, the standard deviation for REITs with banking relationships is
lower. Overall, these descriptive statistics support the propositions that the
development of banking relationships facilitate REITs’ access to public debt
markets and lower their secured debt ratios.
Descriptive Analysis on Capital Sources of REITs
Table 1 reports capital sources for the REITs in the sample. First, bank debt has
become a significant source of REIT capital. The total amount of outstanding
15
REIT public offerings in 2004 are also included so that more data are available to
measure the banking relationships of REITs.
16
For example, Relation and Duration are constructed for each REIT in a given year using information from the DealScan and SDC databases. More details on these measures
will be discussed in the next section.
268 Hardin and Wu
Table 2 Summary statistics of the REIT sample.
Variable
Relation
No-Relation
Test Statistics
Size
12.11
(0.982)
2.198
(0.671)
1.216
(0.240)
0.064
(0.051)
0.001
(0.095)
0.333
(0.471)
0.306
(0.461)
0.413
(0.126)
0.536
(0.348)
0.237
(0.185)
666
10.56
(1.429)
2.256
(0.747)
1.200
(0.415)
0.057
(0.074)
0.005
(0.165)
0.108
(0.310)
0.079
(0.270)
0.424
(0.199)
0.770
(0.335)
0.347
(0.218)
594
22.61∗∗∗
(−2.11)∗∗
−1.43
(−1.24)
0.82
(−2.98)∗∗∗
1.98∗∗
(−3.05)∗∗∗
−0.50
(−3.05)∗∗∗
9.90∗∗∗
(2.31)∗∗
10.50∗∗∗
(2.92)∗∗∗
−1.26
(−2.33)∗∗
−12.09∗∗∗
(1.08)
−9.67∗∗∗
(−1.39)
Age
MTB4
Profit
Volatility
Rating
PCdummy
Leverage
Securedratio
SecureMarket
N
The table reports the summary statistics (mean and standard deviation (in parentheses))
for the REIT sample. There are 202 individual REITs in the sample. Relation is a dummy
variable equal to 1 if a REIT establishes a repeat lending relationship with a bank prior
to year t, and 0 otherwise. Size is the natural log of a REIT’s total revenue. Lnage is
the natural log of a REIT’s age. MTB is the ratio of market value to book value of
assets. Profit is the ratio of total cash flow (net income + depreciation) over total assets.
Volatility is the first difference of asset returns between year t and year t − 1. Rating is a
dummy variable, equal to 1 if a REIT has a S&P long-term issuer rating in year t, and 0
otherwise. PCdummy is equal to 1 if a REIT issues public debt in year t, and 0 otherwise.
Leverage is the ratio of total debt to the market value of the firm’s assets. Securedratio
is the ratio of a REIT’s secured debt over its total debt. SecureMarket is the ratio of
a REIT’s secured debt to its market value of assets. The first two columns report the
summary statistics for the samples with and without banking relationships, respectively.
The third column reports the test statistics for equality based on the numbers from the
first two columns. ∗∗∗ , ∗∗ and ∗ indicate statistical significance at the 0.01, 0.05 and 0.10
levels, respectively.
bank debt (net borrowing) is only $329 million in 1992. However, the amount
of bank debt in 1998 reaches $17,649 million. Since 1998, this amount has
remained above $10 billion each year or about 33%–55% of total capital issued
each year, which indicates that bank debt has become an important source
Banking Relationships and REIT Capital Structure 269
of capital for REITs.17 The increased use of short-term bank debt is largely
due to the fact that REITs need liquid capital for their property acquisitions
and development. It is also consistent with Myers’ (1977) argument that highgrowth firms tend to use more short-term debt to mitigate under-investment
problems. Moreover, simply looking at the outstanding balances of bank debt
underemphasizes the importance of the capital as these facilities are drawn
down and then repaid with other sources of capital and then drawn down again.
This reduces both property market and capital market frictions.
Although outstanding bank debt has increased dramatically, other public
sources of capital have also expanded. Seasoned equity issuance tends to fluctuate from year to year, but access to public debt and equity markets is available
throughout the period. It is likely that bank debt provides financial liquidity
for property acquisitions and allows for a firm’s capital structure to be adjusted
when capital market conditions are more beneficial to the firm as shown by
Ooi, Ong and Li (2010). Another notable fact from Table 2 is that mortgage
financing has become less important to REITs. Specifically, during this period, outstanding mortgage debt has never been more than $2,650 million. It
implies that the ratio of mortgage debt in total debt has been decreasing over
time.
Empirical Results
Banking Relationships and Access to the Public Debt Markets
This section examines the effect of banking relationships on access to public
debt markets. Following Faulkender and Petersen (2006), a probit model is run.
The dependent variable is a dummy variable indicating whether a firm has a
bond rating as a proxy for access to the public debt markets. The rating variable
is then regressed on the banking relationship variables. To measure banking
relationships, two relationship variables are constructed based on the banking
relationship literature (see Berger and Udell 1995). The first is a dummy variable, indicating whether a REIT repeatedly enters into borrowing facilities with
the same bank. Specifically, Relation is equal to 1 if a REIT borrows from the
same bank at least twice by year t, and 0 otherwise. The second variable, Duration, is a continuous measure of the strength of the bank–borrower relationship,
17
Admittedly, outstanding bank debt can be borrowed from short-term revolving facilities, which means that REITs may drawn from their facilities repeatedly within a year.
Yet, over time the amount of outstanding bank debt has grown and it is substantial.
270 Hardin and Wu
based on the number of years since the firm established the relationship with
the bank.18,19
The empirical model used here is largely based on the previous literature
(Johnson 1998, Faulkender and Petersen 2006). We choose a relatively parsimonious specification and focus on the effects of banking relationships. Models
(1) and (2) of Table 3 present the results of the basic specifications, including
the relationship variables and other firm characteristics. As expected, the coefficients for the relationship variables (Relation and Duration) are positive (0.206
and 0.04, respectively) and statistically significant at the 5% level, indicating
REITs with banking relationships are more likely to subsequently have access
to public debt markets. Regarding the economic magnitude of the effects,20
when a REIT changes from no relationship to a relationship, the probability of
having a bond rating increases by 5%, whereas increasing duration from the
10th percentile to the 90th percentile raises the probability of having a bond
rating by 6.8%.
In addition, following Faulkender and Petersen (2006), we also add two instrumental variables (NYSEdummy, indicating whether a REIT is traded on the
New York Stock Exchange, and Age ≤ 5, indicating whether a REIT’s age is
less than five years) and estimate the first-stage instrumental regression. The
results in Models (3) and (4) are similar when compared with Models (1) and
(2). There exists a positive relationship between the two relationship variables
and Rating. Other control variables have the expected signs. For example, large
REITs are more likely to have access to the public debt markets, as shown by
the positive coefficients of the firm size variable (Size). Overall, the estimation
results support the proposition that the development of banking relationships
facilitates REITs’ access to the public debt markets.
To conduct robustness checks (Table 4), two additional variables are used as
the relationship measures. Multiple and Mduration are constructed based on
18
We use loan maturity information when constructing the two relationship measures.
For example, if a REIT has a loan from a bank only in 1993 and 1994 and no other loans
thereafter, and the 1994 loan has a maturity of two years, then Relation will be equal to
1 from 1994 till 1995. Based on the DealScan database, a typical revolving bank line of
credit has maturity ranging from one year to three years. Similarly, in this case Duration
will be 2 in 1995, and 0 thereafter.
19
One concern is that the relationship variables may be endogenous with firms’ access
to public capital markets. We argue that it takes time for firms to develop banking
relationships. In fact, the relationship variables are constructed in such a way that
usually at least two years are needed before a REIT can have a banking relationship
with a bank. To some extent, this mitigates the potential endogeneity.
20
We compute the marginal probability following Faulkender and Petersen (2006).
Banking Relationships and REIT Capital Structure 271
Table 3 Banking relationships and access to the public debt markets.
Variable
Model (1)
Model (2)
NYSE
Age ≤ 5
Relation
0.206
(0.10)∗∗
Duration
MTB
Size
Lnage
Profit
Volatility
Prop. Dummies
McFadden’s R 2
N
−0.187
(−0.19)
0.622
(0.05)∗∗∗
0.292
(0.07)∗∗∗
−2.775
(2.60)
0.732
(0.37)∗
Yes
0.254
1,260
0.040
(0.02)∗∗
−0.188
(−1.87)
0.611
(0.05)∗∗∗
0.254
(0.07)∗∗∗
−2.465
(2.52)
0.721
(0.37)∗
Yes
0.254
1,260
Model (3)
Model (4)
−0.089
(0.19)
−0.280
(0.14)∗∗
0.217
(0.10)∗∗
−0.068
(0.19)
−0.222
(0.14)
−0.141
(0.18)
0.617
(0.05)∗∗∗
0.161
(0.09)∗
−2.724
(2.50)
0.729
(0.36)∗∗
Yes
0.257
1,260
0.035
(0.018)∗
−0.157
(0.18)
0.615
(0.05)∗∗∗
0.154
(0.09)
−2.407
(2.43)
0.715
(0.35)∗∗
Yes
0.256
1,260
This table reports the results from a probit model where the dependent variable is
Rating, equal to 1 if a REIT has a S&P long-term issuer rating in year t, and 0 otherwise.
Models (1) and (2) are the base models. Models (3) and (4) report the first-stage estimates
for the instrumental variable regressions (Tables 5–7). Relation is a dummy variable
equal to 1 if a REIT establishes a repeat lending relationship with a bank prior to year t,
and 0 otherwise. Duration is the number of years since a firm repeatedly borrows from
the same bank. NYSE is a dummy variable equal to 1 if a REIT is traded on the NYSE,
and 0 otherwise. Age ≤ 5 is a dummy variable equal to 1 if a REIT is less than 5 years
old, and 0 otherwise. MTB is the ratio of market value to book value of assets. Size is the
natural log of a REIT’s total revenues. Lnage is the natural log of a REIT’s age. Profit
is the ratio of total cash flow (net income + depreciation) over total assets. Volatility
is the first difference of asset returns between year t and year t − 1. The regressions
also include property type dummies. Standard errors are listed in the parentheses. White
heteroscedastic consistent standard errors are reported in parentheses. ∗∗∗ , ∗∗ and ∗
indicate statistical significance at the 0.01, 0.05 and 0.10 levels, respectively.
whether a REIT has multiple relationships with different banks. Specifically, a
REIT has a multiple banking relationship when it repeatedly borrows from the
same banks over time. Similarly, Mduration measures the duration of a REIT’s
banking relationships with the same banks. Models (1) and (2) of Table 4
present the results based on these two variables. As expected, the effects of
banking relationships on access to the public debt markets are stronger. The
coefficients for the two variables are positive (0.319 and 0.059, respectively)
272 Hardin and Wu
Table 4 Robustness banking relationships and access to the public debt markets.
Variable
Model (1)
Multiple
0.319
(0.10)∗∗∗
Mduration
Model (2)
Model (3)
0.059
(0.02)∗∗
Relation
0.502
(0.11)∗∗∗
Duration
MTB
Size
Lnage
Profit
Volatility
Prop. Dummies
McFadden’s R 2
N
Model (4)
−0.177
(0.18)
0.594
(0.05)∗∗∗
0.261
(0.07)∗∗∗
−2.212
(2.49)
0.676
(0.38)∗
Yes
0.258
1,260
−0.207
(−0.18)
0.609
(0.05)∗∗∗
0.246
(0.07)∗∗∗
−2.026
(2.41)
0.692
(0.37)∗
Yes
0.256
1,260
0.584
(0.15)∗∗∗
0.439
(0.05)∗∗∗
0.012
(0.07)
0.486
(0.67)
−0.141
(0.37)
Yes
0.197
1,260
0.042
(0.02)∗∗∗
0.550
(0.15)∗∗∗
0.475
(0.05)∗∗∗
−0.035
(0.07)
0.560
(0.63)
−0.139
(0.36)
Yes
0.183
1,260
This table reports the results from a probit model where the dependent variable is
Rating, equal to 1 if a REIT has a S&P long-term issuer rating in year t, and 0 otherwise.
Models (1) and (2) are the base models using relationship variables based on multiple
banking relationships, and Models (3) and (4) use a dependent variable based on public
debt issuance (Pcdebtdummy). Multiple is a dummy variable equal to 1 if a REIT
maintains multiple repeat lending relationships with different banks prior to year t, and
0 otherwise. There are 361 firm-year observations with multiple relationships. Mduration
is the number of years since a firm repeatedly borrows from the different relationship
banks. MTB is the ratio of market value to book value of assets. Size is the natural log
of a REIT’s total revenues. Lnage is the natural log of a REIT’s age. Profit is the ratio
of total cash flow (net income + depreciation) over total assets. Volatility is the first
difference of asset returns between year t and year t − 1. The regressions also include
property type dummies. White heteroscedastic consistent standard errors are reported
in parentheses. ∗∗∗ , ∗∗ and ∗ indicate statistical significance at the 0.01, 0.05 and 0.10
levels, respectively.
and statistically significant at the 5% level. The marginal probability analysis
shows that when a REIT has multiple bank relationships, the probability of
having a bond rating increases by 8%, whereas increasing multiple duration
from the 10th percentile to the 90th percentile raises the probability by 5.9%.
Moreover, instead of using Rating as a proxy for access to the public debt
markets, an alternative measure based on REIT public debt issuance information
Banking Relationships and REIT Capital Structure 273
is constructed for an additional robustness check. PCdummy is equal to 1 if a
REIT has a public debt offering in year t, and 0 otherwise. Columns (3) and
(4) of Table 4 present the results based on the new dependent variable. Again,
the results for the banking relationship variables are qualitatively similar.21
REITs with banking relationships are more like to subsequently issue public
debt. When a REIT changes from a no relationship to a relationship status,
the probability of having a public debt offering increases by 10.5%, whereas
increasing duration from the 10th percentile to the 90th percentile raises the
probability by 5.8%.
Finally, additional descriptive evidence is presented in Appendix to support
the proposition regarding the effects of the banking relationships. As shown
in Appendix, there exists a clear timing pattern between the development of a
REIT’s banking relationship and its first public debt issuance. In many cases,
after a REIT establishes a relationship with a bank, the firm gains access
to the public debt markets. Interestingly, many banks who repeatedly lend
to REITs are also part of the underwriter team for the REITs’ first public
debt issuance. This provides direct evidence to support Diamond’s (1991)
postulate that banks help firms establish track records and that the development of banking relationships facilitates firms’ access to the public debt
markets.
Banking Relationships and Use of Secured Debt
The focus in this section is to examine whether REITs with banking relationships use less secured debt. To examine this relationship, two measures of
secured debt ratios are used. One is Securedratio, defined as the ratio of a
REIT’s secured debt to its total debt (see Table 5), and the other is SecureMarket, defined as the ratio of a REIT’s secured debt to its market value of total
assets (Table 6).22 Besides the standard control variables such as firm size and
age, a proxy for access to the public debt markets is also included in the regression for control purposes (see Faulkender and Petersen (2006), which shows
that access to public debt market (rating is used as a proxy) affects leverage).
Dependent on different specifications, two rating variables are used. One is the
21
One notable difference is that the coefficients for MTB are negative in Table 3, whereas
the coefficients in Models (3) and (4) of Table 4 are positive. The negative coefficients
are consistent with Faulkender and Petersen (2006), which also uses public debt ratings
as a proxy for access to public debt markets. Given that many REITs are relatively
young and small, there may exist a difference between their actual public debt issuances
and credit ratings, which likely causes the different results.
22
Market value of total assets include book value of debt, book value of any preferred
issued by the company or subsidiaries and the market value of common stock including
the effect of any convertible subsidiary equity, using SNL KeyField: 6137.
274 Hardin and Wu
Table 5 Banking relationships and secured debt ratios (fraction secured).
(1)
(2)
(3)
−0.155
(−3.62)∗∗∗
−0.155
(−6.54)∗∗∗
−0.158
(−3.51)∗∗∗
−0.240
(−6.38)∗∗∗
MTB
−0.062
(−1.16)
Size
−0.061
(−3.84)∗∗∗
Lnage
−0.032
(−1.18)
Profit
−0.196
(−0.70)
Volatility −0.002
(−0.02)
Adj. R 2
0.319
Method OLS
N
1,260
−0.141
(−1.50)
−0.058
(1.66)∗
−0.073
(−5.92)∗∗∗
−0.041
(−2.78)∗∗∗
0.171
(0.68)
−0.019
(−0.28)
0.261
IV
1,260
−0.124
(−0.88)
−0.056
(−0.99)
−0.074
(−4.02)∗∗∗
−0.041
(−1.39)
−0.160
(−0.59)
−0.020
(−0.29)
0.305
IV
1,260
Relation
Duration
Rating
(4)
(5)
(6)
−0.031
(−3.89)∗∗∗
−0.228
(−6.04)∗∗∗
−0.063
(−1.17)
−0.064
(−4.18)∗∗∗
−0.018
(−0.70)
−0.184
(−0.66)
−0.008
(−0.12)
0.320
OLS
1,260
−0.035
(−7.93)∗∗∗
−0.026
(−0.26)
−0.054
(1.54)
−0.085
(−6.61)∗∗∗
−0.034
(−2.31)∗∗
−0.118
(−0.48)
−0.042
(−0.60)
0.268
IV
1,260
−0.035
(−3.69)∗∗∗
−0.024
(−0.14)
−0.054
(−0.92)
−0.086
(−4.53)∗∗∗
−0.034
(−1.10)
−0.116
(−0.43)
−0.042
(−0.63)
0.278
IV
1,260
This table reports the regression results of the effects of banking relationships on secured
debt ratio. The dependent variable is Securedratio or Fraction Secured, defined as
the ratio of a REIT’s secured debt over its total debt. Models (1) and (4) are basic
OLS regressions. Models (2) and (5) are the second-stage OLS regressions using use
the predicted rating from the first-stage instrumental regression in Table 3 (Model 3).
Models (3) and (6) use the predicted rating from the first-stage instrumental regression
as an instrument in the second stage (Wooldridge 2002). T-statistics based on White
heteroscedastic consistent standard errors, corrected for correlation across observations
of a given firm, are reported in parentheses, except for Models (2) and (5), which only
report the T-statistics based on White heteroscedastic consistent standard errors. All
models also include year dummy variables and property type dummy variables. Rating,
a dummy variable, is equal to 1 if a REIT has a S&P long-term issuer rating in year
t. Relation is a dummy variable, equal to 1 if a REIT establishes a repeat lending
relationship with the same bank in year t, and 0 otherwise. Duration is a relationship
strength variable, measured by the number of years since a firm repeatedly borrows
from the same bank. MTB is the ratio of market value to book value of assets. Size is the
natural log of a REIT’s total revenues. Lnage is the natural log of a REIT’s age. Profit is
the ratio of cash flow over total assets. Volalitity is the first difference of asset returns in
year t and year t − 1, used as a proxy for asset volatility. ∗∗∗ , ∗∗ and ∗ indicate statistical
significance at the 0.01, 0.05 and 0.10 levels, respectively.
original rating variable constructed from the S&P long-term rating. The other
variable used is the predicted rating from the first-stage instrumental variable
regression (Table 3) to mitigate the potential endogeneity between access to
public capital markets and leverage.
Banking Relationships and REIT Capital Structure 275
Table 6 Robustness: banking relationships and secured debt ratios.
(1)
(2)
(3)
−0.085
(−3.73)∗∗∗
−0.079
(−6.40)∗∗∗
−0.084
(−3.74)∗∗∗
−0.119
(−5.52)∗∗∗
MTB
−0.165
(−5.40)∗∗∗
Size
−0.022
(−2.10)∗∗∗
Lnage
−0.017
(−1.22)
Profit
−0.419
(−2.40)∗∗
Volatility −0.014
(−0.29)
0.351
Adj. R 2
Methed
OLS
N
1,260
−0.194
(−3.25)∗∗∗
−0.171
(−6.79)∗∗∗
−0.014
(−1.52)
−0.014
(−1.57)
−0.451
(−2.58)∗∗
−0.004
(−0.11)
0.314
IV
1,260
−0.172
(−1.85)∗
−0.168
(−5.35)∗∗∗
−0.016
(−1.00)
−0.013
(−0.83)
−0.436
(−2.45)∗∗
−0.005
(−0.10)
0.342
IV
1,260
Relation
Duration
Rating
(4)
(5)
(6)
−0.017
(−3.69)∗∗∗
−0.112
(−5.29)∗∗∗
−0.166
(−5.35)∗∗∗
−0.025
(−2.37)∗∗
−0.010
(−0.71)
−0.414
(−2.35)∗∗
−0.017
(−0.36)
0.349
OLS
1,260
−0.016
(−6.69)∗∗∗
−0.148
(−2.33)∗∗
−0.169
(−6.55)∗∗∗
−0.020
(2.14)∗∗
−0.009
(−1.08)
−0.430
(−2.48)∗∗
−0.014
(−0.31)
0.244
IV
1,260
−0.016
(−3.29)∗∗∗
−0.136
(−1.30)
−0.167
(−5.20)∗∗∗
−0.022
(−1.36)
−0.008
(−0.52)
−0.422
(−2.35)∗∗
−0.013
(−0.26)
0.314
IV
1,260
This table reports the regression results of the effects of banking relationships on secured
debt ratio. The dependent variable is SecureMarket, defined as the ratio of a REIT’s
secured debt over its market value of total assets. Models (1) and (4) are basic OLS
regressions. Models (2) and (5) are the second-stage OLS regressions using use the
predicted rating from the first-stage instrumental regression in Table 3 (Model 3). Models
(3) and (6) use the predicted rating from the first-stage instrumental regression as
an instrument in the second stage (Wooldridge 2002). T-statistics based on White
heteroscedastic consistent standard errors, corrected for correlation across observations
of a given firm, are reported in parentheses, except for Models (2) and (5), which only
report the T-statistics based on White heteroscedastic consistent standard errors. All
models also include year dummy variables and property type dummy variables. Rating,
a dummy variable, is equal to 1 if a REIT has a S&P long-term issuer rating in year
t. Relation is a dummy variable, equal to 1 if a REIT establishes a repeat lending
relationship with the same bank in year t, and 0 otherwise. Duration is a relationship
strength variable, measured by the number of years since a firm repeatedly borrows
from the same bank. MTB is the ratio of market value to book value of assets. Size is the
natural log of a REIT’s total revenues. Lnage is the natural log of a REIT’s age. Profit is
the ratio of cash flow over total assets. Volalitity is the first difference of asset returns in
year t and year t − 1, used as a proxy for asset volatility. ∗∗∗ , ∗∗ and ∗ indicate statistical
significance at the 0.01, 0.05 and 0.10 levels, respectively.
There are six empirical specifications in Tables 5 and 6. The first three columns
are based on Relation, and the last three columns are based on Duration.
Columns (1) and (4) are basic OLS regressions with the original rating variable, whereas the other four specifications are the second-stage regressions
276 Hardin and Wu
with the predicted rating variable.23 Specifically, following Petersen (2008), in
columns (3) and (6) we correct for correlation across observations of a given
firm and use the predicted rating from the first-stage instrumental regression
as an instrument in the second stage (see Wooldridge 2002). For comparison
purposes, columns (2) and (5) are the second-stage OLS regressions using the
predicted rating variable, but without clustering at the firm level.24
The results show that there exists a strong negative relation between banking
relationships and secured debt ratios for the two measures of secured debt
ratios. Specifically, Table 5 shows that, across the different specifications, the
coefficients of Relation range from −0.155 to −0.158 and those of Duration
range from −0.031 to −0.035, all being statistically significant at the 1%
level. In addition, the coefficients for the control variable, Rating, are negative,
consistent with the notion that REITs with better access to the public debt
markets have lower secured debt ratios.25 Another confirmatory result is that
large REITs use less secured debt, as shown by the negative coefficients of
the firm size variable (Size). Table 6 reports the estimates with SecureMarket
as the dependent variable. The results are qualitatively similar: the coefficients
of Relation range from −0.079 to −0.085 and those of Duration range from
−0.016 to −0.017, and are all statistically significant at the 1% level. Overall,
these results suggest that REITs with banking relationships have lower secured
debt ratios and that the development of banking relationships helps integrate
REITs into the capital markets.26
Banking Relationships and Leverage
In this section, we examine whether REITs with banking relationships have
higher or lower leverage using a similar model specification as in the previous
23
The predicated rating variable is based on Model (3) in Table 3.
24
One concern about the empirical specifications is the collinearity between rating and
the relationship variables. We compute the variance inflation factors (VIFs) for the
rating and relationship variables. The VIFs are all less than a threshold of 10. Also,
our regression results (not reported here) show that the coefficients of the relationship
variables are similar across the different specifications, with or without the Rating
variables, which suggests that it is less likely that the main results are driven by the
collinearity.
25
According to the special report from Moody’s Investor Services (2002), there is a
negative relation between the secured debt ratio and the issuer’s public credit rating.
26
As an additional robustness check, we also conduct instrumental variable regressions
focusing on the relationship variable, Relation. That is, we use NYSEdummy and an age
dummy variable as well as other exogenous variables to obtain the predicted Relation
from the first-stage instrumental regressions and use it as an instrument in the second
stage regressions (Wooldridge 2002). The results on Relation from the second-stage
regressions are qualitatively similar to the previous results.
Banking Relationships and REIT Capital Structure 277
section. The dependent variable is market leverage, Leverage, defined as a ratio
of a firm’s total debt over its market value of total assets.27 Again, the variables
of interest are the two relationship variables, Relation and Duration. Similarly,
we include the original and predicted rating variables for control purposes and
estimate the three models for each relationship variable.
The first three columns of Table 7 show that the coefficients of Relation are
negative, ranging from −0.032 to −0.037, and statistically significant at the
5% level. When Duration is used (columns (4)–(6)), the results remain similar
and the coefficients for Duration range from −0.004 to −0.017. These results
provide evidence suggesting that REIT leverage is inversely related to banking relationships, which is different from the existing literature (see Johnson
1998). Other variables with significant coefficients are MTB, Profit and Rating.
The negative coefficients on MTB and Profit are consistent with the existing
literature, whereas the negative coefficients on Rating differ from Faulkender
and Petersen (2006).
The finding that REITs with banking relationships have lower leverage supports research by Brown and Marble (2007), which shows that firms with lower
secured debt ratios also have lower leverage. Also, the finding is consistent
with Brown and Riddiough (2003) in that, if public debt issuers tend to target
leverage to maintain their credit ratings, it is not surprising that REITs with
banking relationships have lower leverage.28 Although this result is different
from Johnson (1998), we believe that it is largely due to the unique characteristics and operating environment of REITs and to real estate. It is important to
recognize that REITs use bank debt and then public debt financing to improve
financing and operating flexibility rather than just source additional debt capital. By using bank credit facilities, REITs can effectively control their leverage
while maintaining an adequate level of financing liquidity. In other words, even
though REITs with banking relationships could use more leverage, it may be
counterproductive for them to do so if it has any potential impact on access
to the public capital markets. Overall, the fundamentally different characteristics of REITs compared to other public firms help explain the seemingly
contradictory result.
27
We follow Faulkender and Petersen (2006), which uses market leverage as the dependent variable. However, we also conduct estimation using book leverage. The results
are qualitatively similar.
28
Banking relationships may serve as a discipline mechanism for REITs. In contrast,
REITs without banking relationships face less monitoring and constraints in raising
their leverage ratios.
278 Hardin and Wu
Table 7 Banking relationships and market leverage.
Relation
(1)
(2)
(3)
−0.037
(−2.54)∗∗
−0.032
(−3.99)∗∗∗
−0.035
(−2.47)∗∗
−0.125
(−2.25)∗∗
−0.197
(−6.51)∗∗∗
0.016
(1.84)∗
0.002
(0.23)
−0.498
(−3.45)∗∗∗
−0.025
(−0.67)
0.354
IV
1,260
−0.110
(−1.18)
−0.196
(−6.22)∗∗∗
0.015
(0.99)
0.002
(0.16)
−0.488
(−3.30)∗∗∗
−0.025
(−0.58)
0.323
IV
1,260
Duration
−0.032
(−2.39)∗∗∗
MTB
−0.192
(−6.11)∗∗∗
Size
0.005
(0.61)
Lnage
−0.004
(−0.36)
Profit
−0.464
(−3.20)∗∗∗
Volatility −0.037
(−1.02)
0.355
Adj. R 2
Methed
OLS
N
1,260
Rating
(4)
(5)
(6)
−0.017
(−1.96)∗∗
−0.030
(−2.12)∗∗
−0.192
(−6.02)∗∗∗
0.036
(0.38)
−0.001
(−0.11)
−0.465
(−3.15)∗∗∗
−0.038
(−1.04)
0.351
OLS
1,260
−0.004
(−2.73)∗∗∗
−0.123
(−2.13)∗∗
−0.197
(−6.46)∗∗∗
0.014
(1.57)
0.004
(0.56)
−0.499
(−3.39)∗∗∗
−0.025
(−0.67)
0.350
IV
1,260
−0.004
(−1.21)
−0.114
(−1.08)
−0.196
(−6.16)∗∗∗
0.013
(0.84)
0.005
(0.37)
−0.492
(−3.23)∗∗∗
−0.024
(−0.55)
0.315
IV
1,260
This table reports the regression results of the effects of banking relationships on secured
debt ratio. The dependent variable is Leverage, defined as the ratio of a REIT’s total
debt to its market value of total assets (market value of equity plus book value of debt).
Models (1) and (4) are basic OLS regressions. Models (2) and (5) are the secondstage OLS regressions using use the predicted rating from the first-stage instrumental
regression in Table 3 (Model 3). Models (3) and (6) use the predicted rating from the
first-stage instrumental regression as an instrument in the second stage (Wooldridge
2002). T-statistics based on White heteroscedastic consistent standard errors, corrected
for correlation across observations of a given firm, are reported in parentheses, except
for Models (2) and (5), which only report the T-statistics based on White heteroscedastic
consistent standard errors. All models also include year dummy variables and property
type dummy variables. Rating, a dummy variable, is equal to 1 if a REIT has a S&P
long-term issuer rating in year t. Relation is a dummy variable, equal to 1 if a REIT
establishes a repeat lending relationship with the same bank in year t, and 0 otherwise.
Duration is a relationship strength variable, measured by the number of years since
a firm repeatedly borrows from the same bank. MTB is the ratio of market value to
book value of assets. Size is the natural log of a REIT’s total revenues. Lnage is the
natural log of a REIT’s age. Profit is the ratio of cash flow over total assets. Volalitity
is the first difference of asset returns in year t and year t − 1, used as a proxy for asset
volatility. ∗∗∗ , ∗∗ and ∗ indicate statistical significance at the 0.01, 0.05 and 0.10 levels,
respectively.
Interaction between Bank Debt and Public Debt Offerings
In this section, we examine the interactions among bank debt, public debt and
equity of REITs to provide additional evidence about the evolution of REIT
capital structure. Table 8 presents descriptive statistics based on the stated
Banking Relationships and REIT Capital Structure 279
Table 8 Statistics of REIT public debt, equity and bank loan issuance.
Public Debt
Equity
Bank Loan
Purpose
N
%
Size
N
%
Size
N
%
Size
Acquisition
General purpose
Capital structure
Working capital
Others
17
291
231
1
229
2.2
37.8
30.0
0.01
29.8
117.7
79.6
132.8
400.0
38.5
109
366
322
9
79
12.2
41.4
36.4
1.0
8.9
105.1
93.6
87.8
98.7
151.9
325
448
438
137
86
22.7
31.2
30.5
9.6
6.0
205.2
148.5
207.8
193.0
124.3
The table reports descriptive statistics for REITs’ public debt, equity and bank loan
issuance by stated purpose. The public security offerings data are from SDC Global
New Issues database for the period of 1992 to 2004, and the bank loan data are from
Loan Pricing Corporation’s (LPC’s) DealScan database for the period of 1992 to 2003.
N denotes the number of issuances for each financial instrument. % is the reported
percentages indicating ratio of each instrument over the total number of issuances. Size
is the average size for each issuance in millions of dollars.
issuance purposes for REIT bank loans, public debt and equity offerings. About
30% of the public debt offerings and 36.4% of the equity offerings are issued
to pay down bank debt (i.e., for capital structure purposes). Meanwhile, 30.5%
of the bank loans are issued for capital structure purposes. Although a stated
purpose of “General Purpose” gives ambiguity as to the use of the capital
acquired, these statistics suggest that a large percentage of public security
offerings are used to pay down bank debt. Also of note is the fact that bank
loans are more often used for direct acquisitions than are proceeds from public
debt offerings. The percentage of bank loans for acquisition purpose is 22.7%
compared with only 2.2% for public debt offerings. These results are consistent
with Brown and Riddiough (2003) that proceeds from public debt are often used
to reconfigure liability structure whereas bank loans and equity offerings are
more often used to fund acquisitions and investment. The findings are also
consistent with Ooi, Ong and Li’s (2010) assessment of the market timing of
REIT capital market activities. Bank debt can be conceptualized as a form of
“bridge financing.”
To further examine the relation among bank debt, public debt issuance and
equity issuance, a simple Tobit model is estimated.29 In this model, REITs’
equity and public debt issuances are used as the dependent variables and bank
debt usage is used as the independent variable of interest. The basic idea is
that, if there exists a negative relation between public debt issuance and bank
debt use in year t, or a negative relation between public debt issuance in year t
29
The left-truncated Tobit model is used as many REITs in the sample do not issue
equity and public debt every year. We use a parsimonious model as our focus is on the
relationship between public debt issuances and use of bank debt.
280 Hardin and Wu
Table 9 Timing pattern of REIT capital issuance.
PCDebt Issuance
Variable
(1)
Loc
−0.307
(0.09)∗∗
Loc
MTB
Lnage
Edummy
0.137
(0.04)∗∗∗
−0.003
(0.02)
0.135
(0.02)∗∗∗
SEO Issuance
(2)
−0.473
(0.09)∗∗∗
0.146
(0.04)∗∗∗
−0.001
(0.02)
0.126
(0.02)∗∗∗
PCdummy
N
R2
1,465
0.167
1,444
0.180
(3)
(4)
0.506
(0.15)∗∗∗
0.110
(0.06)∗
−0.054
(0.03)∗∗
0.233
(0.20)
0.128
(0.06)∗∗
−0.062
(0.03)∗∗
0.103
(0.03)∗∗∗
1,465
0.170
0.090
(0.03)∗∗∗
1,444
0.161
This table reports the estimation results for the Tobit model. The dependent variables
are either PCDebt, the ratio of public debt issued in year t to total assets in Models (1)
and (2), or SEO, the ratio of seasoned equity issued in year t to total assets in
Models (3) and (4). Loct is the ratio of bank debt borrowed in year t to total assets.
Loc is the difference between Loct and Loct−1 . Size is the natural log of a REIT’s total
revenues. MTB is the ratio of market value to book value of assets. Lnage is the natural
log of a REIT’s age. Edummy (PCdummy) is a dummy variable equal to 1 if a REIT
issues seasoned equity (public debt) in year t, and 0 otherwise. White heteroscedastic
consistent standard errors, corrected for correlation across observations of a given firm,
are reported in parentheses. All models also include year dummy variables. McFadden’s
R 2 is presented. ∗∗∗ , ∗∗ and ∗ indicate statistical significance at the 0.01, 0.05 and 0.10
levels, respectively.
and the change of bank debt use from year t − 1 to t, we can make inference
on the evolution of REIT capital structure. To measure bank debt use, two
variables are used. They are bank debt use in year t(Locit ) and a change of
bank debt use from year t − 1 to t(Loc), both scaled by the total assets at
the beginning of year t. SEO and PCdebt are the ratios of seasoned equity
and public debt issuances in year t to the total assets at the beginning of year
t, respectively. As shown in Table 9, the coefficients of Locit and Loc are
positive in the estimation of seasoned equity offerings while the coefficient
of Loc is not statistically significant (columns (3) and (4)). However, in
the models of public debt offerings, the coefficients of Locit and Loc are
both negative and significantly significant (columns (1) and (2)). These results
indicate that REITs do not simultaneously increase their bank debt use and
public debt issuance during the same year, which implies that there exists a
total debt limit for REITs and that public debt issuers tend to control their debt
ratios. Again, these findings are consistent with the notion that REITs with
Banking Relationships and REIT Capital Structure 281
banking relationships may have a lower leverage ratio. However, bank debt
has limitations (Houston and James 2001). That is why many REITs have a
mixed debt structure (bank debt and market debt), which supports Hackbarth,
Hennessy and Leland (2007).
Conclusion
This article combines the banking relationship literature and the capital structure literature to examine the effects of banking relationships on REIT capital
structure, using a unique sample of REITs. To our best knowledge, this is
the first article to explore the link between the development of banking relationships and firm capital structure. Although previous literature examines the
relation between bank debt use and capital structure (Johnson 1998), we argue
that focusing on banking relationships provides a better metric to assess the
effects of bank debt use on the optimal mixture of debt and overall capital
structure. REIT debt structure progresses from an initial stage where debt is
composed primarily of mortgages to a stage that includes both unsecured bank
debt and arms-length unsecured public debt. Banks are clearly an important
player in the evolution of REIT liability structures. We believe that the REIT
laboratory provides an outstanding way to demonstrate the bank’s role in the
evolution. It is difficult to see this evolution so clearly in a sample of non-REIT
firms. Thus, it adds to the capital structure literature.
We find that banking relationships help REITs gain access to the public debt
markets. This finding provides support to Diamond (1991). Consistent with the
first finding, we show that REITs with banking relationships have lower secured
debt ratios. These results support the proposition that banking relationships
help REITs shift from mortgages and secured debt toward more corporatelike, unsecured debt financing. Moreover, REITs with banking relationships
use less leverage. This finding is consistent with Brown and Marble (2007),
which show that firms with lower secured debt ratios also have lower leverage.
The rationale is that asset substitution problem decreases in the proportion to
the original debt that is secured. In addition, the results support Brown and
Riddiough (2003), which show that public debt issuers target leverage ratios
in order to preserve a minimum investment-grade credit rating. Because bank
debt provides financial flexibility to REITs, this enables them to control their
leverage while maintaining an adequate amount of liquid capital through bank
credit facilities. Meanwhile, REITs with lower secured debt ratio and leverage
can obtain favorable financing terms in the public capital markets as investors
and rating agencies recognize lower risks of these REITs.
The findings of this article also shed light on the big question of why REITs use
debt at all given no obvious tax advantage. Our results suggest that at least one
reason for REITs to use debt is to obtain financial liquidity to reduce property
282 Hardin and Wu
market frictions and take quick action in property acquisitions. Our findings
are also consistent with the recent capital structure literature. Faulkender and
Petersen (2006) show that the source of capital affects a firm’s capital structure. Use of bank debt helps REITs gain better access to the public capital
markets, and REITs with banking relationships have lower secured debt ratio
and leverage. This implies that the source of capital (bank debt) and banking
relationships influence the capital structure of REITs. Our findings also support
Hackbarth, Hennessy and Leland (2007) in that mature REITs tend to use a
mixed debt financing (bank debt and market debt).
This study has relevant policy implications for REITs regarding the design of
efficient financing policies. Bank debt plays an important role in REIT capital
structure, and banking relationships improve the overall capital acquisition
process of REITs. Moreover, bank lines of credit and other bank credit facilities
are integral to the management of REITs. By subjecting themselves to the
monitoring required to acquire bank loans, REITs obtain a source of needed
liquid capital. The results also imply that this additional monitoring benefits
REITs in the provision of capital from public debt and equity offerings.
The authors thank Dennis Capozza, Juan Esteban Carranza, Stephen Malpezzi,
François Ortalo-Magné, Milena Petrova, Timothy Riddiough, James Seward,
James Shilling and the seminar participants at the 2007 AREUEA Annual
conference and the University of Wisconsin-Madison for helpful comments.
References
Berger, A.N. and G.F. Udell. 1995. Relationship Lending and Lines of Credit in Small
Firm Finance. Journal of Business 68(3): 351–381.
Bharath, S., S. Dahiya, A. Saunders and A. Srinivasan. 2007. So What Do I Get? The
Bank’s View of Lending Relationships. Journal of Financial Economics 85(2): 368–419.
Boot, A. 2000. Relationship Banking: What do We Know? Journal of Financial Intermediation 9(1): 7–25.
Boot, A. and A. Thakor 1994. Moral Hazard and Secured Lending in an Infinitely
Repeated Credit Market Game. International Economic Review 35(4): 899–920.
Brown, D.T. and H. Marble. 2007. Secured Debt Financing and Leverage: Theory and
Evidence. Working Paper, University of Florida.
Brown, D.T. and T.J. Riddiough. 2003. Financing Choice and Liability Structure of Real
Estate Investment Trusts. Real Estate Economics 31(3): 313–346.
Chan, S.H., J. Erickson and K. Wang. 2003. Real Estate Investment Trust: Structure,
Performance, and Investment Opportunities. Oxford University Press: New York, NY.
Datta, S., M. Datta and A. Patel. 1999. Bank Monitoring and the Pricing of Corporate
Public Debt. Journal of Financial Economics 51(3): 435–449.
Dennis, S., D.K. Nandy and I.J. Sharpe. 2000. The Determinants of Contract Terms
in Bank Revolving Credit Agreements. Journal of Financial and Quantitative Analysis
35(1): 87–110.
Diamond, W.D. 1984. Financial Intermediation and Delegated Monitoring. Review of
Economic Studies 51: 393–414.
Banking Relationships and REIT Capital Structure 283
Diamond, W.D. 1991. Monitoring and Reputation: The Choice Between Bank Loans
and Directly Placed Debt. Journal of Political Economy 99(4): 689–721.
Drucker, S. and M. Puri. 2005. On the Benefits of Concurrent Lending and Underwriting.
The Journal of Finance 60(6): 2763–2799.
Elayan, F.A., T.O. Meyer and J.Y. Li. 2004. Creditworthiness or Management Signal?
An Empirical Investigation of Loan Commitments Obtained by Non-Taxable Firms.
The Journal of Real Estate Finance and Economics 28(1): 59–79.
Faulkender, M. and M. Petersen. 2006. Does the Source of Capital Affect Capital
Structure? Review of Financial Studies 19(1): 45–79.
Feng, Z., C. Ghosh and C.F. Sirmans. 2007. On the Capital Structure of Real Estate
Investment Trusts. The Journal of Real Estate Finance and Economics 34(1): 81–105.
Hackbarth, D., C. Hennessy and H. Leland. 2007. Can the Trade-Off Theory Explain
Debt Structure? Review of Financial Studies 20(5): 1389–1428.
Han, B. 2006. Insiders Ownership and Firm Value: Evidence from Real Estate Investment Trusts. The Journal of Real Estate Finance and Economics 32(4): 471–493.
Hardin III, W.G. and M.D. Hill. 2008. REIT Dividend Determinants: Excess Dividends
and Capital Markets Trusts. Real Estate Economics 36(2): 349–369.
Holmstrom, B. and J. Tirole. 1998. Private and Public Supply of Liquidity. Journal of
Political Economy 106(1): 1–40.
Houston, J. and C. James. 2001. Do Relationship Have Limits: Banking Relationships,
Financial Constraints, and Investment. Journal of Business 74(3): 347–374.
Howe, J. and J. Shilling. 1988. Capital Structure Theory and REIT Security Offerings.
The Journal of Finance 43(4): 983–993.
Jaffe, J.F. 1991. Taxes and the Capital Structure of Partnerships, REITs and Related
Entities. The Journal of Finance 46(1): 983–993.
James, C. 1987. Some Evidence on the Uniqueness of Bank Loans. Journal of Financial
Economics 19(2): 217–235.
Johnson, S. 1998. The Effect of Bank Debt on Optimal Capital Structure. Financial
Management 27(1): 47–56.
Kallberg, J., C. Liu and A. Srinivasan. 2003. Dividend Pricing Models and REITs. Real
Estate Economics 31(3): 435–451.
Moody’s Investors Services. 2002. Moody’s Views on Secured vs. Unsecured Debt in
REITs’ Capital Structures. Special Comment, April.
Myers, S. 1977. Determinants of Corporate Borrowing. Journal of Financial Economics
5(2): 147–175.
Ooi, J. 2000. Corporate Reliance on Bank Loans: An Empirical Analysis of UK Property
Companies. Journal of Property Investment and Finance 18(1): 103–120.
Ooi, J., S. Ong and L. Li. 2010. An Analysis of the Financing Decisions of REITs: The
Role of Market Timing and Target Leverage. The Journal of Real Estate Finance and
Economics 40(2): 130–160.
Wooldridge, J. 2002. Econometrics Analysis of Cross Section and Panel Data. MIT
Press: Boston, MA.
Yasuda, A. 2005. Do Bank Relationships Affect the Firm’s Underwriter Choice in the
Corporate Bond Underwriting Market? The Journal of Finance 60(3): 1259–1292.
Appendix
See Table A1.
Goldman Sachs, JP Morgan (12/1996)
JP Morgan, First Union Capital Markets (08/1997)
Goldman Sachs, NationsBank (09/1994)
Bank of America, Fleet Securities, Solomon Brothers
(06/2002)
Bank of America Securities, CSFB (04/2001)
JP Morgan, Salomon Brothers (11/1996)
First Chicago, Lehman Brothers (05/1995)
First Chicago, Merrill Lynch, JP Morgan (09/1995)
Merrill Lynch (10/1997), Merrill Lynch and NationsBank
Securities (11/1997)
First Chicago, Goldman Sachs, UBS (11/1997)
Bankers Trust Securities, Merrill Lynch (07/1997)
Lehman Brothers (08/1997)
JP Morgan, Goldman Sachs (11/1996)
First Union, NationsBank Capital Markets, Goldman Sachs
(01/1997)
JP Morgan, Chase Manhattan, Goldman Sachs (09/1998)
Merrill Lynch, Morgan Stanley, Bank of America Securities
(06/1997)
JP Morgan, NationsBank Capital Markets, PaineWebber
(02/1996)
Lehman Brothers, First Chicago Capital Markets (04/1998)
JP Morgan, Goldman Sachs (06/1998)
Underwriters & Time of First Public Debt Issuance
Note: The table presents additional evidence on the effects of banking relationships on access to the public debt markets based on a partial list of REITs in our
sample. The banks listed here are the lead or agent banks of the loans, and the underwriters of public debt offerings are the major underwriters of the offerings.
The month and year of the issuance time are included in the parentheses.
Spieker Properties
Summit Properties
United Dominion
Vornado Realty
Pan Pacific Properties
Simon Property Group
First Industrial Properties
JDN Realty Corporation
Liberty Properties
Oasis Residential Realty
Developers Diversified Realty
Duke Realty
Equity Residential
CenterPoint Properties
Camden Properties
Archstone Properties
BRE Properties
First Chicago, Lehman Brothers (10/1996), First Chicago
(11/1997)
First Chicago (05/1995), Lehman Brothers (11/1995)
First Chicago (04/1994), First Chicago (04/1995)
Merrill Lynch (05/1994), NationsBank and Wells Fargo
(03/1994), NationsBank (07/1997)
First Chicago (06/1994), First Chicago (05/1995)
Bankers Trusts (03/1994), Bankers Trust (05/1995)
BankBoston (12/1996), BankBoston (06/1997)
Wells Fargo (01/1995), Wells Fargo, Morgan Guarantee
Trust (09/1995)
Bank of America (12/1999), Bank of America (11/2000)
Citibank (03/1994), Citibank (04/1995), Morgan Guarantee
Trust (08/1995) , (06/1996)
Wells Fargo (04/1995), Wells Fargo (11/1995)
First Union Bank (11/1996), (03/1998)
Signet Bank (10/1991), Signet Bank, NationsBank (12/1992)
Chase Manhattan (02/1998), Chase Manhattan, Bank of
America, Citibank (03/2000)
Morgan Guarantee Trust (JP Morgan), NationsBank
(10/1997), NationsBank (04/1998)
Wells Fargo (06/1990), Wells Fargo, First Union and
NationsBank (12/1995)
Chase Manhattan, Morgan Guarantee Trust (07/1998)
Bank of America (04/1996), Bank of America (10/1996,
02/1997)
NationsBank (08/1994), NationsBank (03/1996)
AMB Properties
American Health Properties
Lenders and Time of Bank Loans
REITs
Table A1 Banking relationships and the first public debt offerings of REITs
284 Hardin and Wu