Corporate Liquidity Management and Financial

Constraints ∗

Zhonghua Wu †

Yongqiang Chu‡

This Draft: June 2007

Abstract

This paper examines the effect of financial constraints on corporate liquidity man-agement by investigating how firms adjust cash holdings and bank line holdings inresponse to their cash flows. We first present a simple liquidity demand model, inwhich firms face costly external finance and future investment uncertainty. To hedgeagainst potential capital shortfalls, firms design cash policy and bank debt policy toensure financial liquidity based on their financial conditions. The model predicts thatconstrained firms will increase cash holdings but reduce bank line holdings when theyexperience positive cash flow innovations, while unconstrained firms do not exhibit sucha pattern. Using simultaneous equation systems, we then test these predictions basedon a unique sample of real estate investment trusts (REITs). The results strongly sup-port our predictions. In addition, we provide evidence showing that dividend policy issticky and plays a passive role in corporate liquidity management.

∗ We are grateful to Timothy Riddiough, Francois Ortalo-Magne, James Seward and James Shilling fortheir helpful comments. In addition, We benefited from discussion with Jim Clayton, Mike Mihelbergel, ToniWhited and seminar participants at the University of Wisconsin-Madison.

† Department of Finance, Florida International University, RB 208, 11200 SW 8th Street, Miami, FL33199; e-mail: Wuz@fiu.edu.

‡ Department of Real Estate and Urban Land Economics, University of Wisconsin-Madison, 975 Univer-sity Avenue, Madison., WI 53706; e-mail: Yongqiangchu@wisc.edu.

1 Introduction

Corporate liquidity management has been a growing research area in corporate finance during

the past ten years. Meanwhile, the effect of financial constraints on corporate behaviors

remains to be a topic of continued interest.1 Despite the extensive research on each subject,

few studies have been done by combining these two research lines to examine the effect of

financial constraints on corporate liquidity management.2

Previous literature in corporate liquidity management and financial constraints have

largely concentrated on the role of cash holdings (we call it as “internal liquidity”). For

instance, Opler et al. (1999) examine the determinants and implications of holdings of cash

and find that firms with strong growth opportunities and riskier cash flows hold more cash.

Almeida, Campello, and Weisbach (2004) show that the effect of financial constraints can

be captured by the firm’s propensity to save cash out of cash flows (“cash flow sensitivity of

cash”). However, these studies do not consider the role of bank lines of credit (we call it as

“external liquidity”).3 Given that bank lines of credit serve as a viable liquidity substitute

to firms and help reduce capital market frictions (Holmstrom and Tirole (1998)), it would be

surprising if one does not take into account the external liquidity when studying the effect

of financial constraints on corporate liquidity management.

A recent paper by Sufi (2006) examines the factors that determine whether firms use

bank lines of credit or cash in corporate liquidity management. The author finds that firms

with low cash flow are less likely to obtain a line of credit and thus rely more heavily on

cash. Sufi’s paper is one of the first empirical studies on the role of bank lines of credit

in corporate finance, however, it does not explicitly examine how firms optimally manage

financial liquidity using both cash and bank lines of credit. Rather, Sufi focuses on firms’

1A partial list of the liquidity management literature includes Kim, Mauer, and Sherman (1998), Holm-strom and Tirole (1998), Opler et al. (1999), and Faulkender and Wang (2006). Also, the representativestudies in the financial constraint literature include Fazzari, Hubbard, and Petersen (1988) and Almeida,Campello, and Weisbach (2004).

2Indeed, as pointed out by Almeida, Campello, and Weisbach (2004), corporate liquidity management andfirms’ financial conditions are closely linked. If firms have unlimited access to external capital markets at fairprices, financial liquidity is irrelevant. In contrast, if firms are financially constrained, liquidity managementbecomes an important issue in their investment and financial policies.

3In the case of Almeida, Campello, and Weisbach (2004), their focus is to develop a new test of theeffect of financial constraints on corporate behaviors in general, instead of investigating the effect of financialconstraints on corporate liquidity management.

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cross-sectional variation in use of cash or bank lines and concludes that use of bank lines of

credit is, to some extent, determined by banks based on firms’ cash flows.

As documented in Sufi (2006), over 80% of firms across different industries have access

to bank lines of credit during the period of 1996-2003. Given this fact, it is interesting to

ask how these firms manage financial liquidity by holding cash and acquiring bank lines in

order to hedge against future capital shortfalls for potential investment. In particular, one

can argue that, although banks have certain degree of power in controlling firms’ use of bank

lines, essentially it is firms themselves that design optimal cash policy and bank debt policy

to meet financial liquidity needs. Moreover, for the majority of firms, a key determinant

in financial liquidity management is the hedging cost associated with liquid capital from

different sources. Thus, one would expect that these firms should manage financial liquidity

to hedge against future capital shortfalls while minimizing hedging costs based on their

financial conditions.

This paper investigates how firms with different financial conditions adjust two sources of

liquid capital (i.e., cash holdings and bank line holdings) in response to their cash flows. Our

focus is to understand the effect of financial constraints on corporate liquidity management.4

We emphasize the hedging perspective of corporate liquidity management, that is, firms

dynamically adjust cash holdings and bank line holdings to hedge against potential capital

shortfalls.5 The effect of financial constraints is captured by the different responses of the

two sources of liquidity to cash flow innovations by firms with different financial conditions.

Besides, we also explore issues related to dividend policy in the context of corporate liquidity

management.6 Dividend policy is relevant here because paying out more dividends reduces

firms’ internal cash flow and thus affects their liquid capital holdings. By examining dividend

4Specifically, we consider that a firm is financially constrained when it faces a cost gap between internalcash and external capital due to capital market frictions. That is, for financially constrained firms, the costof obtaining external funds is significantly higher than that of internal cash. According to this classification,perhaps a large portion of firms are financially constrained. However, we believe it is difficult to exactlydistinguish constrained and unconstrained firms. Instead, it is the degree of financial constraint that matters,which depends on firms’ financial conditions.

5For this purpose, we measure financial liquidity using unused bank lines and total cash holdings at theend of the fiscal year.

6A common feature shared by the previous studies is that the role of dividend payout in corporate liquiditymanagement is often ignored.

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payout behaviors in the context of liquidity management, we provide new insights about

corporate dividend policy.

We first present a simple liquidity demand model in which firms face capital market

frictions and future investment uncertainty. Since it is costly for firms to issue securities

through the public capital markets when they need capital to fund new investment projects

(Myers and Majluf (1984)), firms desire to hold liquid capital ex ante to hedge against future

capital shortfalls (Kim, Mauer, and Sherman (1998)). Moreover, it is assumed that firms can

endogenously determine how much cash or bank lines of credit to hold to ensure financial

liquidity. However, the hedging costs of holding cash and bank lines of credit vary for firms

with different financial conditions. Thus, firms have to design cash policy and bank debt

policy based on their financial conditions to ensure financial liquidity while controlling the

hedging costs.

The main prediction from the model is that financially constrained firms will reduce bank

line holdings but increase cash holdings when experiencing positive cash flow innovations.

That is, there is a positive relation between cash holdings and realized cash flows (“cash

flow sensitivity of cash”) and a negative relation between bank line holdings and realized

cash flows (“bank line sensitivity of cash”) for constrained firms. In contrast, for those

unconstrained firms, there is no such a systematic pattern. We argue this stark contrast

reflects the effect of financial constraints on corporate liquidity management. Moreover,

our model implies that when constrained firms increase cash holdings, they do not increase

dividend payout simultaneously. However, it is not necessarily the case for unconstrained

firms.

We then use a sample of Real Estate Investment Trusts (REITs) to test our predictions.

REITs provide us with a natural laboratory to conduct the empirical tests for the following

reasons. First, by tax law REITs have to pay out 90% of taxable income in form of dividend

to shareholders, which limits their abilities to retain cash.7 Consequently, they have to

7In this sense, REITs are considered financially constrained because of the exogenous dividend restric-tion. However, they do have some discretionary power in retaining cash. Wang, Erickson and Gau (1993)documents that the 90% restriction is not a binding constraint for REITs, although it limits their ability toretain cash, because REITs’ cash flow is often much higher than the taxable income due to large depreciationwrite-off of real assets. Moreover, Kallberg, Liu, and Srinivasan (2003) shows that REITs pay out 60%-85%of Funds From Operations (FFOs) as dividend.

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carefully manage financial liquidity by both holding cash and acquiring bank lines in order

to meet their capital needs. Second, REITs are more transparent than other firms (Capozza

and Seguin (1999)). Their cash flows are largely determined by current rental leases thus

contain less noisy information (Ruah (2004)). Finally, REITs are public traded firms with

most of the assets being tangible, and default risks of REIT bank debt are fairly low. Also,

REITs generally have a higher level of before-dividend cash flows. As such, access to bank

lines is not an issue for most of the REITs. All of the characteristics of REITs contribute to

a unique environment for examining the roles of cash and bank lines in providing financial

liquidity and the effect of financial constraints on corporate liquidity management.

As firms are likely to determine their cash holdings and bank line holdings jointly, we use

simultaneous equation models to capture the joint determination process of the two liquid

capital holdings (Acharya, Almeida, and Campello (2006)).8 Specifically, a two-equation

system (cash holdings and bank line holdings equation) and a three-equation system (cash

holdings, bank line holdings, and dividend equation) are estimated, based on both the full

sample and the subsamples classified by financial constraint criteria.9 Overall, the results

strongly support our predictions. Constrained firms save cash out of cash flows (“cash flow

sensitivity of cash”) and reduce bank line holdings when experiencing positive cash flow

innovations (“bank line sensitivity of cash”). In contrast, no such a systematic pattern

exists for those unconstrained firms. In addition, the results show that, when constrained

firms increase cash holdings, they do not increase dividend payout simultaneously.

This paper provides new understandings about corporate liquidity management and how

financial constraints affect corporate policies. Specifically, we distinguish two sources of liq-

uid capital (cash and bank lines of credits) and examine optimal responses of these liquid

capital to cash flow innovations to understand the effect of financial constraints on corporate

liquidity management. To a large extent, the estimation bias problem in traditional finan-

cial constraint literature is sidestepped (Fazzari, Hubbard, and Petersen (1988), and Hoshi,

8Acharya, Almeida, and Campello (2006) focus on the interplay between cash policy and general debtpolicy, however, they do not explicitly examine bank line policy.

9The details on these criteria will be discussed in the next section.

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Kashyap, and Scharfstein (1991))10 and our results provide further support to Almeida,

Campello, and Weisbach (2004). We argue that the “bank line sensitivity of cash”, jointly

with “cash flow sensitivity of cash”, serve as good metrics to identify the effect of financial

constraints on corporate policies. Moreover, dividend policy, along with cash policy and

bank debt policy, is examined in the context of corporate liquidity management. Previous

literature in corporate liquidity often ignore dividend policy. In this paper, the interactions

among cash policy, bank debt policy, and dividend policy are explored. We present evi-

dence showing that dividend policy is sticky and plays a passive role in corporate liquidity

management.

The rest of the paper is organized as follows. The next section presents and analyzes a

liquidity demand model that provides directly testable empirical predictions. The empirical

results and their interpretations based on the theoretical model are presented in the third

section. Finally, we conclude and discuss possible directions for future research.

2 The Model

In this section, we set up a simple liquidity demand model to illustrate the effect of financial

constraints on firms’ liquidity management. The model is a representation of a dynamic

problem of a firm facing investment and financing decisions in imperfect capital markets.

In this setting, we analyze how a firm adjusts cash holdings and bank line holdings in

response to cash flow innovation. While our model is in the spirit of Almeida, Campello,

and Weisbach (2004), there exist important differences between these two models. First,

their model focuses on the role of cash holdings while we consider both cash holdings and

bank line holdings as viable liquidity sources. Moreover, in their model, it is the tradeoff

between the marginal benefit and marginal cost of holding cash (i.e., use cash to invest now

or later) that drives the central results, while in our model different hedging costs of liquid

capital influence firms’ decision in holding cash or bank lines in the presence of financial

constraints.

10Previous literature on financial constraint has focused on relationships between investment and cashflow (“investment sensitivity of cash”). This approach has been criticized on both theoretical ground andempirical basis (Kaplan and Zingales (1997), Erickson and Whited (2000)).

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2.1 Structure

In our setup, a firm faces costly external finance due to the capital market imperfections,

and its future investment opportunities are uncertain. Thus, the firm is concerned about

maintaining a desirable level of liquid capital to hedge against potential capital shortfalls

when profitable investment opportunities arise. Financial liquidity can be important to the

firm because of the capital markets frictions (Kim, Sherman, and Mauer (1998)). In other

words, due to informational asymmetry, a firm pays significant deadweight costs for security

offerings when it has to secure capital to fund investment projects (Myers and Majluf (1984)).

If the firm does not issue securities, it may miss the profitable investment opportunity and

thus suffers the under-investment problem. However, holding bank lines of credit can solve

this problem (Holmstrom and Tirole (1998)), as the liquid capital can be used to fund

investment projects without incurring deadweight costs. As such, the firm can invest in any

profitable projects to maximize its value.

There are two ways that a firm can maintain liquid capital holdings. It can hold cash

or acquire lines of credit from banks.11 However, the costs associated with the two liquid

capital sources are different for firms with different financial conditions. Specifically, we

assume that the cost difference between holding cash and holding bank lines is α.12 One

way to justify the cost difference is that the firm has to pay a commitment fee ex ante to

maintain a bank credit facility for future use. In this case, a natural question to ask is

why the firm wants to hold more expensive bank lines relative to cash. The main reason is

that if an investment opportunity arises, the capital required is always larger than the firm’s

cash holdings. Besides, the firm prefers to borrow from bank lines as these credit facilities

provides quick access to capital.

There are three dates, 0, 1 and 2. Assume that the firm has assets in place, which

produces a deterministic cash flow c0 at date 0 and a stochastic cash flow c1 at date 1. Let

c1 = c1H if the state tomorrow is H, and c1 = c1L if the state tomorrow is L. Assume

11In this case, we assume that the firm have access to bank lines of credit, which is different from Sufi(2006), where a firm may not be able to access bank lines due to low cash flow.

12Kim, Sherman, and Mauer (1998) consider that holding cash is costly because cash earns a lower returncompared to project return. Here, our emphasis is the cost difference between internal liquidity and externalliquidity, so we normalize the cost of holding cash to be zero and make the cost difference to be α.

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c1H > c1L. With probability p, the state will be H, and with probability (1 − p), the state

will be L. At date 0, the firm has access to an investment opportunity that requires I0

today and pays off g(I0) at date 2. Additionally, the firm expects to have access to another

investment opportunity at date 1, which requires capital input I1. Assume I1 > C. The

payoff of date 1 investment I1, which will be realized at date 2, is f(I1).

The firm chooses to finance investment either through internal cash or debt borrowed

from bank lines of credit. The internal cash comes from its cash holdings. In order to

borrow from bank lines, the firm has to maintain its credit facility by paying a total upfront

commitment fee of αB where B is the upper limit of its bank lines or capacity of bank lines.

Assume α << 1.

2.2 Analysis

The firm’s objective is to maximize the expected sum of dividends subject to various budget

and financial constraints. The problem can be written as

maxC,B,d,I,b

d0 + [pd1H + (1− p)d1L] + [pd2H + (1− p)d2L] (1)

s.t.

d0 = c0 − I0 − C − αB (2)

d1S = c1S + b1S − I1S + C, for S=H, L (3)

d2S = g(I0) + f(I1S)− b1S, for S=H, L (4)

b1S ≤ B, for S=H, L (5)

where C− cash holdings

B− total bank line capacity (i.e., unused bank lines)

d0− dividend at date 0

d1S− dividend at date 1 if the date 1 state is S

d2S− dividend at date 2 if the date 1 state is S

b1S− bank lines drawn at date 1 if the state is S

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2.2.1 Unconstrained Firm

To start the analysis, we first investigate the case where the firm is financially unconstrained.

Under this circumstance, the firm can always acquire liquid capital from the capital markets

to fund its investment projects. In other words, we can think of the cost difference between

internal cash and external finance, α being equal to zero. Thus, whenever the firm has a

profitable investment opportunity, it can obtain liquid capital from the capital markets at a

fair price to fund the investment. In this case, financial liquidity is irrelevant. We can show

that, for an unconstrained firm, it is able to invest at the first-best level both at time 0 and

1. Thus, we have the following first-order conditions:

g′(IFB0 ) = 1 (6)

f ′(IFB1S ) = 1 (7)

To achieve first-best investment level, the firm has to be unconstrained, i.e. it does not

incur more costs to raise external funds than internal cash. Thus, the following conditions

must be satisfied:

c0 > IFB0 + CFB (8)

c1S + CFB > IFB1S (9)

A necessary but sufficient condition for firm to be unconstrained is

c0 + c1S > IFB0 + IFB

1S (10)

2.2.2 Constrained Firm

In the case where the firm is financially constrained, it has to borrow from bank lines to

finance its investment projects, due to insufficient cash holdings and inability to secure other

source capital from the capital markets at fair prices. Under these circumstances, we can

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show that the firm will not pay dividends at date 0 and date 1, i.e., d0 = 0, and d1S = 0.13

Another observation is that b1L = B, given that the firm’s cash flow is low in L state, it tends

to use up the full capacity of its bank lines. Under these assumptions, the firm’s problem

can be rewritten as:

maxC,B,b1H

g(I0) + p[f(I1H)− b1H ] + (1− p)[f(I1L)−B] (11)

s.t.

I0 = c0 − C − αB (12)

I1L = c1L + C + B (13)

I1H = c1H + C + b1H (14)

The solution can be characterized by the following first-order conditions:

g′(I0) = pf ′(I1H) + (1− p)f ′(I1L) (15)

g′(I0)α = (1− p)(f ′(I1L)− 1) (16)

f ′(I1H) = 1 (17)

Some observations from the above first-order conditions are: (1) In state H, the firm

can achieve first best investment, which follows from equation (17); (2) I1L < IFB1L , which

follows from equation (16) that f ′(I1L) > 1; (3) I0 < IFB0 , which follows from (15) that

g′(I0) = p + (1− p)f ′(I1L) > p + (1− p) = 1.

We now state and prove the central results of our model. That is,

Proposition 1: For firms that are financially constrained, their liquidity management

policy depends on the realized cash flows in the following way.

(1) The optimal cash holdings, C, increase with realized date 0 cash flows c0, i.e., ∂C/∂c0 > 0,

the positive cash flow sensitivity of cash;

13Alternatively, we can normalize the firm’s dividend payout and assume that the firm will maintainthe same level of dividend it pays during the previous period. In this case, we have d0 = d0 − d = 0,¯d1S = d1S − d = 0. This will not change the final results of our model.

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(2) The optimal bank line holdings, B, decrease with date 0 cash flow c0, i.e., ∂B/∂c0 < 0,

the negative bank line sensitivity of cash.

Proof: Combine (15) and (16) , we get,

(1− α)g′(I0) = 1 (18)

Differentiate both sides of (18) with respect to date 0 cash flow c0, we get,

(1− α)g′′(I0)(1−∂C

∂c0

− α∂B

∂c0

) = 0 (19)

thus,∂C

∂c0

+ α∂B

∂c0

= 1 (20)

Then differentiate both sides of (16), we get,

(1− p)f ′′(I1L)(∂C

∂c0

+∂B

∂c0

) = 0 (21)

thus,∂C

∂c0

+∂B

∂c0

= 0 (22)

Combine (20) and (22), we get,

∂C

∂c0

=1

1− α> 0, since α < 1 (23)

and∂B

∂c0

= − 1

1− α< 0 (24)

The basic intuition from the above results can be summarized as follows. For constrained

firms, they have to carefully manage cash holdings and bank line holdings to ensure financial

liquidity while controlling the hedging costs. Because external finance is more expensive

to them, reducing financing costs is an important factor in their liquidity management.

Specifically, as the hedging costs of using bank lines are higher than those of using cash, these

firms would rationally save more cash out of cash flow, instead of holding more bank lines,

when experiencing positive cash flow innovations. However, for unconstrained firms, external

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liquidity is less expensive and they are more concerned about hedging against potential

capital shortfalls. Hence, liquid capital holdings of unconstrained firms are expected to be

less responsive to cash flow shocks.

Based on Proposition 1, the first hypothesis is stated as follow.

Hypothesis 1: Financially constrained firms will increase cash holdings but reduce bank

line holdings when experiencing positive cash flow innovations, i.e., there exists positive cash

flow sensitivity of cash and negative bank line sensitivity of cash. However, unconstrained

firms will not exhibit such a pattern. Specifically, for constrained firms, we have,

(∂C

∂c0

)constrained

> 0,(∂B

∂c0

)constrained

< 0 (25)

In addition, the analysis above implies that constrained firms will restrain their dividend

payout when they anticipate new investment opportunities, since paying more dividend

reduces the firm’s financial liquidity and add to the need for external liquidity. Similarly,

when constrained firms increase their cash holdings, they do not acquire more bank line

holdings simultaneously. Thus, we expect that constrained firms would not increase dividend

payout when they increase cash holdings. The second hypothesis is stated as follows.

Hypothesis 2: Constrained firms do not increase dividend payout and bank line holdings

when they increase their cash holdings. However, for unconstrained firms, it may not be the

case.

3 Empirical Tests

In this section, empirical tests are conducted based on the hypotheses from the previous

section. The focus is on how firms’ cash holdings and bank line holdings respond to the

fluctuation of their cash flows. Both the full sample and the subsamples of REITs classified

by various financial constraint criteria are used to show the effect of financial constraints on

corporate liquidity management. In addition, the role of dividend payout in the corporate

liquidity management is also examined.

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3.1 Methodology

We follow the literature of cash flow sensitivity of cash (Almeida, Campello, and Weisbach

(2004)) to specify our estimation equations. In their paper, a general form of cash equation

is estimated as follows:

∆Cit = β0 + β1 ∗ CFit + β2 ∗ TQit−1 + εit (26)

where the dependent variable is the change of Cit from year t-1 to year t (∆Cit), and Cit

is the cash holdings scaled by total assets. The independent variables include CFit (the

cash flow measure), scaled by total assets, and TQ (the Tobin’s q measure). When different

samples of firms based on certain financial constraint criteria are estimated, β1 can be used

as an indicator of the effect of financial constraints on corporate policies.

As cash holdings and bank line holdings are likely to be determined jointly by firms, a

two-equation simultaneous system is used to estimate the response of liquid capital holdings

to cash flow. To capture the dynamic relationships, we use change of cash holdings and

change of bank line holdings as the dependent variables. The key independent variable is

firms’ cash flow. Besides, we add two variables, i.e., the bank line holdings and the cash

holdings in year t-1, to identify the two equation system. A Tobin’s Q measure and firm size

are also included in the system as control variables. Finally, we add year and property-type

fixed effects to capture the sources of variation from different years and property types of

firms. As such, our primary empirical model is given as follows:

∆Lit = β0 + β1 ∗NCFit + β2 ∗ TQit−1 + β3 ∗∆CSit + β4 ∗ Lit−1 + β5 ∗ Intait + εit (27)

∆CSit = γ0 + γ1 ∗NCFit + γ2 ∗ TQit−1 + γ3 ∗∆Lit + γ4 ∗ CSit−1 + γ5 ∗ Intait + ξit (28)

where Lit is the ratio of bank line holdings over total assets in year t, and ∆Lit is the net

increase of the ratio from year t-1 to t. Similarly, ∆CSit is the net increase of the ratio (cash

holdings over total assets) from year t-1 to year t, NCFit is the total cash available after

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paying out dividend in year t, scaled by the total assets.14 Dit−1 is the total cash dividend

paid at the end of year t-1, scaled by total assets. Beginning-of-year Tobin’s Q (TQit−1),

defined as the total market cap of a REIT plus total debt divided by the total assets at the

end of year t-1, serves as a proxy for growth opportunity of a REIT. The β1 and γ1 in the

equation are the coefficients of particular interest, as they indicate how a REIT adjusts bank

line holdings and cash holdings based on its realized cash flow.

Moreover, to examine the role of dividend policy in corporate liquidity management, we

allow dividend payout to be an endogenous variable. This also serves as a robustness check

for our primary two-equation estimation. Thus, we estimate a three-equation system by

adding the dividend equation with the change of dividend payout as the dependent variable.

That is,

∆Lit = β0 + β1CFit + β2TQit−1 + β3∆CSit + β4∆Dit + β5Lit−1 + β6Intait + εit (29)

∆Dit = β0 + γ1CFit + γ2TQit−1 + γ3∆CSit + γ4∆Lit + γ5Lit−1 + γ6Intait + ϑit (30)

∆CSit = γ0 + α1CFit + α2TQit−1 + α3∆Lit + α4∆Dit + α5CSit− 1 + α6Intait + ξit (31)

where CFit is the total cash available in year t, scaled by the total assets. The bank line

holdings, the cash holdings, and the dividend payout variable in year t-1, all scaled by total

assets, are used to identify the three-equation system.

First, the two equation and the three equation system are estimated using the full REIT

sample. By so doing, we can test how the two liquid capital holdings as well as dividend

payout respond to cash flow innovations. Next, we classify the full sample based on three

financial constraint criteria and estimate the two systems using each of the six subsamples.

The idea is to further examine the effect of financial constraints on firms’ financial policies,

in particular, corporate liquidity management and dividend policy.

14Essentially, NCFit is the net cash flow available. In addition, Sufi (2006) argues that, instead of usingtotal assets as a scalar, one should use total assets minus cash holdings. Otherwise, there will a mechanicalbias on the relevant coefficients. We use the alternative measure according to Sufi (2006), the estimationresults are very similar to the ones otherwise. Hence, we do not report the alternative results.

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3.2 Financial Constraint Criteria

To classify the full sample, we follow the methodology used in the financial constraint lit-

erature (e.g., Fazzari, Hubbard, and Petersen (1988)) by splitting the full sample based

on various priori measures of financial constraints. Specifically, three financial constraint

criteria are used.

� Scheme # 1: Firm size. Firm size is considered an important criterion for financial

constraint as small firms are more likely to face borrowing constraint from the public capital

markets than larger firms (See Whited (1992), Almeida, Campello, Weisbach (2004)). Also,

larger firms have lower external financing costs because of the scale of economies from lower

fixed cost of security issuance. Thus, we sort the sample based on total assets of REITs,

and assign the top one third and the bottom one third as the constrained and the uncon-

strained group, respectively. This classification results in 476 firm-year observations in each

subsample.

� Scheme # 2: Bond Ratings. If a firm issues a public debt offering and has a bond

rating for its public debt, it shows that the market recognizes the firm’s credit quality.

Thus, the firm is likely to have better access to the capital markets than those otherwise.

Previous studies such as Whited (1992) often use this criterion to characterize the degree of

financial constraint. Here, we classify the sample based on whether a firm issues a public

debt or not. The firms that issued a public debt and obtained a bond rating are classified

as the unconstrained group. There are 809 (596) firm-year observations in the constrained

(unconstrained) subsample.

� Scheme # 3: Banking relationships. Diamond (1989) shows that firms establish rela-

tionships with banks before they can access the public capital markets. In fact, REITs rely

more on bank lines of credit to obtain financial liquidity to fund investment due to their

limited abilities to retain earnings. Hence, a REIT with good banking relationship is less

likely to be financially constrained. Sufi (2006) argues that lack of access to a bank line is

a powerful measure of financial constraints. However, we believe whether a firm can repeat-

edly access bank lines should be a better measure of financial constraints. If a firm develops

a close banking relationship through repeated interactions with banks, the firm is likely to

14

have ready access to the capital markets. We follow the literature (see Bharath et al. (2005))

and classify the full sample into two groups based on a dummy variable, called “banking

relationship dummy”. The REITs that have not established a close banking relationship are

assigned into the constrained group, and those with a banking relationship are assigned into

the unconstrained group. There are 750 (679) firm-year observations in the unconstrained

(constrained) group.

One should not be surprised that the groups based on the three different schemes15 are

to some extent correlated. For example, large firms are more likely to have a bond rating.

However, based on the number of observations in each subsample, these cross correlations

are not very strong.

3.3 Data and Descriptive Analysis

We construct a unique data set of REITs from three different data sources: 1. SNL REIT

Financial database; 2. NAREIT Capital Offering database; and 3. LPC’s DealScan Com-

mercial Loan database. The primary data used is from the SNL REIT database, which

provides detailed firm classification and financial information of REITs. For example, we

can identify whether a REIT is an equity REIT, and which property type a REIT focuses

on. More important, besides financial information such as total assets, asset growth rate

and market capitalization, the database also provides bank line usage information, i.e., bank

line holdings at the end of a given year, the amount of debt drawn from bank credit lines

during a given year, and average drawn ratio of bank lines for a REIT each year. To be

included in our sample, a REIT has to meet the following criteria: (1) listed on NYSE,

AMEX or NASDAQ, and elected REIT tax status; (2) registered with the National Real

Estate Investment Trust Association (NAREIT); and (3) must be an equity REIT.

The original sample from the SNL REIT database has 3,667 firm-year observations.

To add REIT capital offering information, we obtain REIT capital offering data from the

NAREIT database, which consists of 1,401 seasoned equity offerings, 950 public debt offer-

ings, and 156 IPOs of REITs. Then, we hand match the capital offering data into the SNL

15We do not choose dividend payout ratio as one criteria here as REITs have the 90% dividend payoutrule which complicates REITs’ dividend payout behaviors.

15

REIT sample. The final data set consists of 1,429 REIT firm-year observations from 1990 to

2003.16 To classify the full sample based on banking relationship and bond rating, we obtain

the bank loan information from the DealScan loan database of Loan Pricing Corporation.

There are 1,248 REIT bank loans in the sample. Also, REITs’ bond rating information is

obtained from the NAREIT’s Capital Offering database.

[Insert Table 1 and 2 here]

Summary statistics for the full sample and the subsamples are presented in Table 1

and Table 2, respectively. There are six subsamples based on the three financial constraint

criteria: firm size, bond rating, and banking relationship status. First, note that cash

holdings statistics of REITs are much less than those non-REIT public firms. For example,

the average cash holdings of REITs is 2.19%. However, the regular public firms on average

hold about 10% of cash (see Achaya et al. (2006)). Second, the constrained REITs tend to

hold more cash flow compared to the unconstrained REITs. This is consistent with the notion

that the constrained firms are more likely to save more cash to ensure financial liquidity for

investment while the unconstrained firms may use more bank lines as a liquid capital source.

Another interesting fact is that the unconstrained REITs have higher Tobin’s Q than the

constrained REITs. Specifically, REITs with banking relationships and large REITs have

higher Tobin’s Q than those without banking relationships and with small size. This finding

is consistent with the argument of Han (2004). Moreover, the constrained REITs do not cut

their dividend over years, i.e., ∆Dit are all positive while in general being a small percentage.

This is consistent with Capozza and Seguin (1998) that REITs maintain a stable, growing

dividend stream over years as cutting dividends may result in severe punishment from the

stock markets.

3.4 Cash, Bank Lines, and Cash Flows - Full Sample

Table 3 shows the regression results from the two simultaneous equation models based on

the full sample. The first model includes two equations: bank line holdings equation and

16Following the investment-cash flow literature (see Cleary (1999)), we winsorize the data, e.g., Tobins qmeasure is limited between 0 and 4.

16

cash holdings equation (see Column (1)-(2)). In particular, dividend payout is assumed

exogenous and does not play an active role in firms’ liquidity management. Hence, we

subtract dividend from firms’ cash flow and obtain the net cash flow measure (NCF ). The

second model includes three equations: bank line holdings equation, cash holdings equation,

and dividend payout equation (see Column (3)-(5)). Here, dividend payout is endogenized

in the sense that we assume it plays an active role in firms’ financial decision making. By so

doing, we can examine how dividend policy interacts with cash policy and bank line policy

and how it is influenced by firms’ cash flow.

[Insert Table 3 here]

The results of the first model (Column (1) - (2)) show that there exists a positive relation-

ship between firms’ net cash flow and the change in cash holdings. That is, REITs increase

cash holdings when they receive more net cash flows. This is consistent with Almeida et

al. (2004) that, as a group of constrained firms, REITs tend to save more cash out of cash

flow. On the other hand, a negative relationship is observed between firms’ net cash flow

and bank line holdings. That is, when REITs’ net cash flows increase, they tend to reduce

bank line holdings, or equivalently, boost their debt capacities for external liquidity. The

latter result is interesting and new to the literature, implying that, for constrained firms,

saving debt capacities is an equivalent mechanism to ensure financial liquidity compared

with saving more cash out of cash flow.

Next, Column (3) - (5) of Table 3 show the results for the three equation model. We

find a similar pattern regarding how bank line holdings and cash holdings respond to cash

flow innovations as in the first model. That is, when REITs receive more cash flow, they

tend to save more cash while reducing bank line holdings or increasing bank line capacity.

These results confirm our previous findings, i.e., no matter whether we treat dividend payout

endogenous or exogenous, the main results regarding liquid capital holdings and cash flow

innovations are similar. In addition, Column (3) shows that the coefficient of ∆CS is signifi-

cantly negative, suggesting that when REITs increase cash holdings, they often reduce their

bank line holdings. This supports the second hypothesis regarding the relationship between

cash holdings and bank line holdings.

17

3.5 Cash, Bank Lines, and Cash Flow - SubSamples

To further examine the effect of financial constraint on firms’ financial policies, we compare

the coefficients of the key variables (cash holdings and bank line holdings) for the constrained

and the unconstrained firms. First, we look at the bank line holdings equation of the two

equation model. For the constrained firms across the three different groups, the coefficients

of net cash flow (NCF ) are all negative and at the 1% significance level (see Panel A of Table

4), indicating that the constrained firms reduce bank line holdings upon a higher level of cash

flow. However, the coefficients for the unconstrained firms are all positive and insignificant.

Moreover, the coefficients of ∆CSit are negative and significant for the constrained groups,

but not for the unconstrained groups. Taken together, these sharp contrasts indicate that

the constrained firms dynamically adjust their bank line holdings based on their cash flow

and cash holdings, but the unconstrained REITs do not. We argue that it is the effect of

financial constraints that results in such a systematic pattern on firms’ liquidity management

behaviors.

[Insert Table 4 here]

Second, we examine the cash holdings equation of the two equation model. Unlike the

bank line holdings equation, for the constrained firms across the three different groups,

the coefficients of net cash flow (NCF ) are significantly positive (see Panel B of Table

4), suggesting that when REITs have positive cash flow innovations, they increase cash

holdings. In contrast, the coefficients for the unconstrained firms are all negative. Again,

these results imply that the constrained firms are more responsive to cash flow shocks than

the unconstrained firms, which is consistent with Almeida, Campello, and Weisbach (2004).

However, the change of bank line holdings does not seem to have a significant impact on

the cash holdings. One possible explanation is that there exists an asymmetric relationship

between cash holdings and bank line holdings - as one of the external finance vehicles, bank

lines are more costly than cash. Consequently, constrained firms would rather hold more

cash when they face investment uncertainty.

Next, we examine the three equation system, in which dividend payout is considered one

of the endogenous variables. In general, we find similar patterns in the relationships among

18

bank line holdings, cash holdings and cash flow. That is, when firms have positive cash

flow innovations, the constrained firms reduce bank line holdings (see Panel A of Table 5),

but increase their cash holdings (see Panel C of Table 5). In contrast, the unconstrained

firms reduce cash holdings and increase bank line holdings upon receiving more cash flows.

To sum up, we argue that firms’ financial status has a significant impact on their liquidity

management, and the effect of financial constraints is captured by the systematically different

liquidity management behaviors between the constrained and the unconstrained firms.

[Insert Table 5 here]

The other control variables in the three equations also have expected signs while some of

them are not statistically significant. For example, in the bank line holdings equation, the

coefficients of TQit−1 for the constrained group are all positive and significant, suggesting that

firms with good investment opportunities are more likely to increase their bank line holdings

to fund investment. On the other hand, in the cash holdings equation, the coefficients of

TQit−1 for the less constrained group are all positive and significant, implying that the less-

constrained firms are more likely to increase cash holdings to ensure liquid capital when they

have good investment opportunities.

3.6 The Role of Dividend Policy

In this section, the role of dividend policy in corporate liquidity management is examined.

First, we investigate how firms’ dividend payout responds to their cash flow innovation and

whether or not the responses are different for the constrained and the unconstrained group.

Column 4 of Table 3 shows that there is a positive relationship between cash flow and

dividend payout. That is, when cash flows increase by 1%, dividend paid tend to increase by

0.30%. Moreover, the subsample estimation also confirms the same results. Panel B of Table

5 shows that the coefficients of CFit are all significantly positive, suggesting that positive

cash flow innovation has a positive impact on dividend payout. This is consistent with the

agency theory of dividend policy (see Wang et al. (1993)).

Moreover, the interactions among dividends, cash holdings, and bank line holdings are

investigated in the context of corporate liquidity management. Column 4 of Table 4 indicates

19

that an increase in cash holdings as well as an increase in bank line holdings are inversely re-

lated to firms’ dividend payout level. Specifically, when bank line holdings and cash holdings

increase by 1%, their dividend payout decreases by 0.04% and 0.08%, respectively. However,

dividend payout does not have a significant impact on cash holdings and bank line holdings.

Specifically, while the signs of ∆D are negative (-0.054 and -0.06, respectively), the coef-

ficients are not significant. The results based on the subsamples are similar: Panel A and

Panel C of Table 5 indicate that the coefficients of ∆CS in the cash holdings equation and

bank line equation are insignificant for the constrained firms and the unconstrained firms,

while the coefficients of ∆CS and ∆L in the dividend equations are generally negative and

significant.

One possible explanation for such relationships is that, to a large extent, REITs are

exogenously capital constrained. Because liquid capital is crucial for them to take quick

action in property acquisition, they have to carefully manage cash holdings and bank line

holdings when anticipating investment opportunities. Thus, they have less incentives to

increase dividend payout during the period when they increase cash holdings and bank line

holdings. Interestingly, the coefficients of ∆CS and ∆L are often larger for the constrained

firms than for the unconstrained firms. This pattern further supports the notion that the

constrained firms are more likely to limit their dividend payout than unconstrained firms

when they expect good investment opportunities.

These results are also consistent with the findings in Brav et al. (2005), which argue

that firms prefer to set conservative dividend policy. That is, when there are more cash

flows available, firms tend to increase dividend payout. However, as paying more dividend

reduces firms’ financial liquidity available, constrained firms do not increase dividend at the

cost of reducing cash flow holdings or bank line holdings. Put it another way, constrained

firms do not treat dividend payout as a priority over firms’ liquid capital holdings and thus

investment funding needs. Taken all together, these results suggest that there exist dynamic

relationships among dividend policy, bank debt policy, and cash holding policy. However,

dividend payout is sticky and a secondary decision relative to cash policy and bank debt

policy.

20

In addition, we find that the change of dividend payout from year t to t-1 is negatively

related to the dividend payout in year t-1. Column (4) shows that the coefficient of Dit−1

is negative at the 1% significance level. That says, if firms pay relatively high dividends

for the previous period, they will not significantly increase dividend payout during the next

period. This is consistent with the notion that REITs might target their dividend payout.

If a firm’s dividend payout reaches a certain ratio, it might restrain its dividend payout level

during the next period so that the firm can maintain a stable dividend stream over years.

In other words, the significantly negative coefficients of Dit−1 show that dividend payout of

REITs in year t are highly correlated to their dividends paid in year t-1. These findings

provide further support for our previous results that dividend payout is sticky and, unlike

cash holdings and bank line holdings, it does not play an active role in corporate liquidity

management.

The other control variables in the dividend equations (see Column (4) and Panel B of

Table 5) also have expected signs while some of them are not statistically significant. For

example, the coefficients of TQit−1 for the constrained group are generally positive and

significant, suggesting that firms with good investment opportunities tend to increase their

dividend payout. On the other hand, the coefficients of Lntait for both the constrained

group and the unconstrained group are negative, implying that larger firms are less likely to

make more dividend payout. Overall, these results provide strong support for the empirical

predictions regarding dividend policy.

4 Conclusion Remarks

This paper examines the effect of financial constraints on corporate liquidity management

by investigating how firms manage cash holdings (internal liquidity) and bank line holdings

(external liquidity) based on their financial conditions to ensure financial liquidity. We

present a simple liquidity demand model in which firms face costly external finance and future

investment uncertainty. In this setting, firms design cash policy and bank debt policy to

hedge against potential capital shortfalls for future investment projects. The model predicts

that constrained firms will increase cash holdings but reduce bank line holdings when they

21

experience positive cash flow innovations, while unconstrained firms do not exhibit such a

pattern. In addition, when constrained firms increase cash holdings and bank line holdings,

they do not increase dividend payout simultaneously.

We then test these predications using a unique data set from REITs. REITs provide us

with a unique environment to examine these issues because they are exogenously constrained

but have ready access to bank lines of credit. Based on simultaneous equation estimation

method, the results strongly support our model predications, suggesting that constrained

firms dynamically adjust cash holdings and bank line holdings to ensure financial liquidity

based on their financial conditions, and financial constraints have a significant impact on

firms’ cash policies and bank debt policies. Moreover, the results show that when the con-

strained firms increase cash holdings and bank line holdings, they do not pay more cash

dividends. However, dividend payout does not have a significant impact on either cash hold-

ings or bank line holdings. These results imply that dividend policy is sticky and plays a

passive role in corporate liquidity management.

This paper provides new understandings about corporate liquidity management and how

financial constraints affect corporate policies. Specifically, we distinguish two sources of

financial liquidity (cash versus bank lines of credits) and examine responses of these two

liquid capital holdings to cash flow innovations to detect the effect of financial constraints on

corporate liquidity management. To a large extent, we sidestep the estimation bias problem

in traditional financial constraint literature (Fazzari, Hubbard, and Petersen (1988)) and

provide further evidence to support Almeida, Campello, and Weisbach (2004). We argue

that the “bank line sensitivity of cash”, jointly with “cash flow sensitivity of cash”, serve as

good metrics to identify the effect of financial constraints on corporate policies. Moreover,

dividend policy, along with cash policy and bank debt policy, is examined in the context

of corporate liquidity management. Previous literature in corporate liquidity management

often ignores dividend policy. In this paper, the interactions among cash policy, bank debt

policy, and dividend policy are explored. We provide evidence suggesting that dividend

policy is sticky and plays a passive role in corporate liquidity management.

Admittedly, our findings and empirical results are based on a single industry - REITs,

which are operated in a constrained environment. To better understand firms’ optimal

22

liquidity management strategies and the effect of financial constraints on corporate policies,

a further examination using data from other industries can be fruitful.

23

Table 1. Summary Statistics for the Full REIT Sample

Variable N Mean Min Max Std

NCFit 1429 0.0141 -0.3456 0.2149 0.0305

CFit 1429 0.0589 -0.2107 0.3104 0.0355

Lit−1 1429 0.1689 0 1.3875 0.134

CSit−1 1421 0.0219 0 0.5820 0.0433

Dit−1 1429 0.0421 0 0.7378 0.0353

∆Lit 1429 -0.0031 -1.0668 1.0868 0.1075

∆Dit 1429 0.0026 -0.5413 0.4372 0.0325

∆CSit 1421 -0.0017 -0.5566 0.4049 0.0465

TQit−1 1429 1.2196 0.0915 3.7441 0.3270

Intait 1429 13.3066 8.5644 17.0662 1.4431

The table presents the number of observations, mean, Min, Max and standard deviation for eachof the following variables: NCF is net cash flow (income before extraordinary items plus depreci-ation minus dividend payout) in year t. CF is cash flow (income before extraordinary items plusdepreciation) at year t. L is the bank line holdings at the end of year t-1, CS is the cash holdings,measured by a firm’s cash and cash equivalents, D is the dividend increase from year t-1 to t. ∆L,∆CS, and ∆D are the changes from t-1 to t. All the variables above are scaled by total assets inyear t-1. TQ is a Tobin’s Q measure, i.e., market to book ratio. Lnta is the natural log of a firm’stotal assets. Moreover, T stats are listed in the parentheses.

24

Tab

le2.

Sum

mar

ySta

tist

ics

for

the

Subsa

mple

s

Var

iabl

eN

NC

Fit

CF

itL

it−

1C

S it−

1D

it−

1∆

Lit

∆D

it∆

CS

itT

Qit−

1Lnt

a it

Fir

mSiz

e

Smal

l47

60.

0083

0.05

780.

1516

0.03

710.

0436

0.00

860.

0060

-0.0

024

1.19

7411

.686

3

[0.0

083]

[0.0

421]

[0.0

520]

[0.1

705]

[0.0

497]

[0.1

409]

[0.0

420]

[0.0

617]

[0.4

432]

[0.9

904]

Lar

ge47

60.

0187

0.05

850.

1487

0.01

240.

0391

-0.0

087

-0.0

014

-0.0

017

1.20

7814

.771

0

[0.0

168]

[0.0

199]

[0.0

747]

[0.0

256]

[0.0

177]

[0.0

504]

[0.0

141]

[0.0

267]

[0.2

028]

[0.6

320]

Bon

dD

um

my

No

Bon

d81

70.

0131

0.05

580.

1611

0.02

620.

0393

-0.0

002

0.00

340.

0002

1.18

0312

.685

3

[0.0

377]

[0.0

430]

[0.1

465]

[0.0

461]

[0.0

417]

[0.1

108]

[0.0

399]

[0.0

499]

[0.3

439]

[1.3

965]

Bon

d59

60.

0155

0.06

290.

1812

0.01

590.

0458

-0.0

072

0.00

15-0

.003

91.

2773

14.1

751

[0.0

164]

[0.0

209]

[0.1

157]

[0.0

386]

[0.0

239]

[0.1

038]

[0.0

186]

[0.0

411]

[0.2

967]

[1.0

079]

Rel

atio

nsh

ip

No

Rel

.67

90.

0099

0.05

590.

1395

0.03

340.

0401

0.00

560.

0059

-0.0

025

1.20

9112

.439

4

[0.0

396]

[0.0

456]

[0.1

439]

[0.0

557]

[0.0

438]

[0.1

303]

[0.0

404]

[0.0

602]

[0.3

901]

[1.3

954]

Wit

hR

el.

750

0.01

790.

0615

0.19

560.

0116

0.04

39-0

.010

9-0

.000

3-0

.001

01.

2292

14.0

918

[0.0

179]

[0.0

226]

[0.1

191]

[0.0

235]

[0.0

253]

[0.0

807]

[0.0

230]

[0.0

291]

[0.2

567]

[0.9

534]

The

tabl

epr

esen

tth

em

ean

and

stan

dard

devi

atio

nfo

rea

chof

the

follo

win

gva

riab

les:

NC

Fis

net

cash

flow

(inc

ome

befo

reex

trao

rdin

ary

item

spl

usde

prec

iati

onm

inus

divi

dend

payo

ut)

inye

art.

CF

isca

shflo

w(i

ncom

ebe

fore

extr

aord

inar

yit

ems

plus

depr

ecia

tion

)in

year

t.L

isth

eba

nklin

eho

ldin

gsat

the

end

ofye

art-

1,C

Sis

the

cash

hold

ings

,m

easu

red

bya

firm

’sca

shan

dca

sheq

uiva

lent

s,D

isth

edi

vide

ndin

crea

sefr

omye

art-

1to

t.∆

L,∆

CS

,an

d∆

Dar

eth

ech

ange

sfr

omt-

1to

t.A

llth

eva

riab

les

abov

ear

esc

aled

byto

tala

sset

sin

year

t-1.

TQ

isa

Tob

in’s

Qm

easu

re,i

.e.,

mar

ket

tobo

okra

tio.

Lnta

isth

ena

tura

llog

ofa

firm

’sto

talas

sets

.M

oreo

ver,

Tst

ats

are

liste

din

the

pare

nthe

ses.

25

Table 3. Relationships on Bank Line Holdings, Cash Holdings and Dividend (Full Sample)

Two Equation System Three Equation System

(1) (2) (3) (4) (5)

Dep. Variable ∆Lit ∆CSit ∆Lit ∆Dit ∆CSit

NCFit −0.640 0.078

(−7.68)∗∗ (2.18)∗

CFit −0.166 0.296 0.075

(−2.01)∗ (15.49)∗∗ (2.14)∗

Lit−1 −0.376 −0.369

(−19.64)∗∗ (−18.76)∗∗

CSit−1 −0.635 −0.637

(22.78)∗∗ (−22.90)∗∗

Dit−1 −0.755

(−42.03)∗∗

∆Lit 0.073 −0.043 0.079

(3.16)∗∗ (−3.50)∗∗ (3.39)∗∗

∆CSit −0.240 −0.322 −0.084

(−2.49)∗ (−3.29)∗∗ (−3.63)∗∗

∆Dit −0.054 −0.060

(−0.48) (−1.27)

TQit−1 0.032 0.008 0.035 0.018 0.056

(3.85)∗∗ (2.21)∗ (3.83)∗∗ (8.52)∗∗ (1.43)

INTAit −0.0004 −0.007 −0.002 −0.002 −0.007

(−0.20) (−7.68)∗∗ (−1.03) (−4.12)∗∗ (−7.79)∗∗

Obs. 1421 1421 1421 1421 1421

Adj. R2 0.30 0.30 0.32 0.32 0.32

The models are two-way (year and property type) fixed effect model using REIT firm-year data(1990 - 2003). The independent variables include the following. NCF is net cash flow (incomebefore extraordinary items plus depreciation minus dividend payout) in year t. CF is cash flow(income before extraordinary items plus depreciation) in year t. Lt is the bank credit line holdingsat the end of year t, CS is the cash holdings, measured by a firm’s cash and cash equivalents, D isthe cash dividend payout in year t. ∆L, ∆CS, and ∆D are the changes of bank line holdings, cashholdings, and dividend payout from t-1 to t. All the variables above are scaled by total assets atthe end of year t-1. TQ is a Tobin’s Q measure, i.e., market to book ratio. Lnta is the natural logof a firm’s total assets. ∗∗ and ∗ indicate statistical significance at the α = .01 and α = .05 level,respectively. T-statistics are listed in parenthesis. The cut off value for the small and large groupare 408 and 1,158 million dollars. Classification for bank relationship is based on whether a REITborrows a bank loan from the same bank twice within a five year period. Classification for bondrating is based on whether a REIT has issued a public debt offering and obtained a bond ratingbefore year t.

26

Tab

le4.

Ban

kLin

eC

apac

ity

and

Cas

hH

oldin

gsby

Fir

mC

har

acte

rist

ics

-T

wo

Equat

ion

Syst

em

Pan

elA

:B

ank

Lin

eE

quat

ion

Dep

ende

ntV

aria

ble:

∆L

itN

CF

itL

it−

1∆

CS

itT

Qit−

1In

tait

NA

dj.

R2

Fir

mSiz

eSm

all

−0.

861

−0.

377

−0.

556

0.02

40.

021

476

0.33

(−6.

14)∗∗

(−9.

75)∗∗

(−3.

08)∗∗

(1.7

8)(3

.17)

∗∗

Lar

ge0.

073

−0.

329

0.02

60.

048

−0.

017

476

0.56

(0.5

7)(−

10.6

4)∗∗

(0.2

7)(3

.62)

∗∗(−

4.61

)∗∗

Bon

dR

atin

gN

oB

ond

−0.

732

−0.

334

−0.

529

0.03

10.

005

809

0.27

(−7.

88)∗∗

(−13

.36)

∗∗(−

3.51

)∗∗

(2.8

9)∗∗

(1.7

0)B

ond

0.02

9−

0.59

40.

156

0.00

6−

0.03

459

60.

54(0

.13)

(−17

.59)

∗∗(1

.34)

(0.4

4)(−

6.60

)∗∗

Rel

atio

nsh

ipN

oR

el.

−0.

795

−0.

431

−0.

371

0.02

20.

009

671

0.32

(−7.

15)∗∗

(−13

.10)

∗∗(−

2.73

)∗∗

(1.8

6)(2

.62)

∗∗

Wit

hR

el.

0.10

7−

0.47

2−

0.04

90.

038

−0.

032

750

0.44

(0.7

6)(−

18.5

9)∗∗

(−0.

41)

(3.3

6)∗∗

(−9.

58)∗∗

The

empi

rica

lsp

ecifi

cati

onof

the

fixed

-effe

ctm

odel

isas

follo

ws:

∆L

it=

γ0

+γ1∗

NC

Fit

+γ2∗

Lit−

1+

γ3∗

∆C

Sit

+γ4∗

TQ

it−

1+

γ5∗

Inta

it+

ε it

(32)

The

mod

els

are

two-

way

(yea

ran

dpr

oper

tyty

pe)

fixed

effec

tm

odel

usin

gR

EIT

firm

-yea

rda

ta(1

990

-20

03).

The

inde

pend

ent

vari

able

sin

clud

eth

efo

llow

ing.

NC

Fis

net

cash

flow

(inc

ome

befo

reex

trao

rdin

ary

item

spl

usde

prec

iati

onm

inus

divi

dend

payo

ut)

inye

art.

Lt

isth

eba

nkcr

edit

line

hold

ings

atth

een

dof

year

t,C

Sis

the

cash

hold

ings

,mea

sure

dby

afir

m’s

cash

and

cash

equi

vale

nts,

Dis

the

cash

divi

dend

payo

utin

year

t.∆

L,∆

CS

,an

d∆

Dar

eth

ech

ange

sof

bank

line

hold

ings

,ca

shho

ldin

gs,an

ddi

vide

ndpa

yout

from

t-1

tot.

All

the

vari

able

sab

ove

are

scal

edby

tota

las

sets

atth

een

dof

year

t-1.

TQ

isa

Tob

in’s

Qm

easu

re,i.e

.,m

arke

tto

book

rati

o.L

nta

isth

ena

tura

llo

gof

afir

m’s

tota

las

sets

.∗∗

and∗

indi

cate

stat

isti

calsi

gnifi

canc

eat

the

α=

.01

and

α=

.05

leve

l,re

spec

tive

ly.

T-s

tati

stic

sar

elis

ted

inpa

rent

hesi

s.T

hecu

toff

valu

efo

rth

esm

alla

ndla

rge

grou

par

e40

8an

d1,

158

mill

ion

dolla

rs.

Cla

ssifi

cati

onfo

rba

nkre

lati

onsh

ipis

base

don

whe

ther

aR

EIT

borr

ows

aba

nklo

anfr

omth

esa

me

bank

twic

ew

ithi

na

five

year

peri

od.

Cla

ssifi

cati

onfo

rbo

ndra

ting

isba

sed

onw

heth

era

RE

ITha

sis

sued

apu

blic

debt

offer

ing

and

obta

ina

bond

rati

ngin

year

t.

27

Tab

le4.

Ban

kLin

eC

apac

ity

and

Cas

hH

oldin

gsby

Fir

mC

har

acte

rist

ics

-T

wo

Equat

ion

Syst

em

Pan

elB

:C

ash

Hol

ding

Equ

atio

n

Dep

ende

ntV

aria

ble:

∆C

Sit

NC

Fit

CS i

t−1

∆L

itT

Qit−

1In

tait

NA

dj.

R2

Fir

mSiz

eSm

all

0.15

1−

0.54

80.

029

0.06

8−

0.01

447

60.

33(2

.54)

∗(−

10.7

9)∗∗

(0.6

4)(1

.50)

(−5.

31)∗∗

Lar

ge−

0.13

7−

0.85

30.

043

0.02

10.

002

476

0.56

(−2.

93)∗∗

(−28

.45)

∗∗(1

.29)

(4.2

8)∗∗

(2.3

0)∗

Bon

dR

atin

gN

oB

ond

0.16

4−

0.51

90.

051

0.00

8−

0.00

880

90.

27(3

.77)

∗∗(−

12.3

4)∗∗

(1.3

3)(1

.76)

(−6.

47)∗∗

Bon

d−

0.40

9−

0.86

40.

041

0.01

80.

002

596

0.54

(−5.

13)∗∗

(−28

.50)

∗∗(2

.35)

∗(4

.21)

∗∗(1

.61)

Rel

atio

nsh

ipN

oR

el.

0.10

6−

0.60

30.

051

0.01

2−

0.00

967

10.

32(2

.07)

∗(−

14.5

8)∗∗

(1.3

9)(2

.21)

∗(−

5.91

)W

ith

Rel

.−

0.01

3−

0.84

9−

0.02

0.01

10.

001

750

0.44

(−0.

28)

(−24

.91)

∗∗(−

1.20

)(2

.91)

∗∗(1

.51)

The

empi

rica

lsp

ecifi

cati

onof

the

fixed

-effe

ctm

odel

isas

follo

ws:

∆C

Sit

=β

0+

β1∗

NC

Fit

+β

2∗

CS

it−

1+

β3∗

∆L

it+

β4∗

TQ

it−

1+

β5∗

Inta

it+

ξ it

(33)

The

mod

els

are

two-

way

(yea

ran

dpr

oper

tyty

pe)

fixed

effec

tm

odel

usin

gR

EIT

firm

-yea

rda

ta(1

990

-20

03).

The

inde

pend

ent

vari

able

sin

clud

eth

efo

llow

ing.

NC

Fis

net

cash

flow

(inc

ome

befo

reex

trao

rdin

ary

item

spl

usde

prec

iati

onm

inus

divi

dend

payo

ut)

inye

art.

Lt

isth

eba

nkcr

edit

line

hold

ings

atth

een

dof

year

t,C

Sis

the

cash

hold

ings

,mea

sure

dby

afir

m’s

cash

and

cash

equi

vale

nts,

Dis

the

cash

divi

dend

payo

utin

year

t.∆

L,∆

CS

,an

d∆

Dar

eth

ech

ange

sof

bank

line

hold

ings

,ca

shho

ldin

gs,an

ddi

vide

ndpa

yout

from

t-1

tot.

All

the

vari

able

sab

ove

are

scal

edby

tota

las

sets

atth

een

dof

year

t-1.

TQ

isa

Tob

in’s

Qm

easu

re,i.e

.,m

arke

tto

book

rati

o.Inta

isth

ena

tura

llo

gof

afir

m’s

tota

las

sets

.∗∗

and∗

indi

cate

stat

isti

calsi

gnifi

canc

eat

the

α=

.01

and

α=

.05

leve

l,re

spec

tive

ly.

T-s

tati

stic

sar

elis

ted

inpa

rent

hesi

s.T

hecu

toff

valu

efo

rth

esm

alla

ndla

rge

grou

par

e40

8an

d1,

158

mill

ion

dolla

rs.

Cla

ssifi

cati

onfo

rba

nkre

lati

onsh

ipis

base

don

whe

ther

aR

EIT

borr

ows

aba

nklo

anfr

omth

esa

me

bank

twic

ew

ithi

na

five

year

peri

od.

Cla

ssifi

cati

onfo

rbo

ndra

ting

isba

sed

onw

heth

era

RE

ITha

sis

sued

apu

blic

debt

offer

ing

and

obta

ina

bond

rati

ngin

year

t.

28

Tab

le5.

Cas

hH

oldin

gs,B

ank

Lin

eC

apac

ity

and

Div

iden

dby

Fir

mC

har

acte

rist

ics

Pan

elA

:B

ank

Lin

eE

quat

ion

Dep

ende

ntV

aria

ble:

∆L

itC

Fit

Lit−

1∆

Dit

∆C

Sit

TQ

it−

1In

tait

NA

dj.

R2

Fir

mSiz

eSm

all

−0.

417

−0.

349

−0.

118

−0.

658

0.04

20.

017

476

0.33

(−3.

12)∗∗

(−8.

37)∗∗

(−0.

60)

(−3.

51)∗∗

(2.7

3)∗∗

(2.4

9)∗

Lar

ge0.

193

−0.

334

−0.

561

−0.

032

0.04

2−

0.01

747

60.

56(1

.57)

(−10

.65)

∗∗(−

2.07

)∗(0

.33)

(2.9

8)∗∗

(4.5

5)∗∗

Bon

dR

atin

gN

oB

ond

−0.

219

−0.

322

−0.

003

−0.

670

0.03

80.

001

809

0.46

(−2.

35)∗

(−12

.37)

∗∗(−

0.02

)(−

4.27

)∗∗

(3.1

1)∗∗

(0.6

0)B

ond

0.09

5−

0.59

2−

0.14

30.

159

0.00

3−

0.03

459

60.

60(0

.42)

(−17

.10)

∗∗(−

0.47

)(1

.34)

(0.1

9)(6

.39)

∗∗

Rel

atio

nsh

ipN

oR

el.

−0.

340

−0.

418

−0.

150

−0.

467

0.03

50.

007

671

0.46

(−2.

96)∗∗

(−12

.13)

∗∗(−

0.88

)(−

3.30

)∗∗

(2.6

1)∗∗

(1.9

0)W

ith

Rel

.0.

442

−0.

481

0.19

4−

0.05

10.

018

−0.

030

750

0.61

(3.4

7)∗∗

(−19

.01)

∗∗(1

.49)

(−0.

43)

(1.4

7)(−

8.97

)∗∗

The

empi

rica

lsp

ecifi

cati

onof

the

fixed

-effe

ctm

odel

isas

follo

ws:

∆L

it=

β0

+β

1∗

CF

it+

β2∗

CS

it−

1+

β3∗

∆D

it+

β4∗

∆C

Sit

+β

5∗

TQ

it−

1+

β6∗

Inta

it+

ε it

(34)

The

mod

els

are

two-

way

(yea

ran

dpr

oper

tyty

pe)

fixed

effec

tm

odel

usin

gR

EIT

firm

-yea

rda

ta(1

990

-20

03).

The

inde

pend

ent

vari

able

sin

clud

eth

efo

llow

ing.

CF

isca

shflo

w(i

ncom

ebe

fore

extr

aord

inar

yit

ems

plus

depr

ecia

tion

)in

year

t.L

tis

the

bank

cred

itlin

eho

ldin

gsat

the

end

ofye

art,

CS

isth

eca

shho

ldin

gs,m

easu

red

bya

firm

’sca

shan

dca

sheq

uiva

lent

s,D

isth

eca

shdi

vide

ndpa

yout

inye

art.

∆L

,∆C

S,a

nd∆

Dar

eth

ech

ange

sof

bank

line

hold

ings

,ca

shho

ldin

gs,an

ddi

vide

ndpa

yout

from

t-1

tot.

All

the

vari

able

sab

ove

are

scal

edby

tota

las

sets

atth

een

dof

year

t-1.

TQ

isa

Tob

in’s

Qm

easu

re,i.e

.,m

arke

tto

book

rati

o.Inta

isth

ena

tura

llo

gof

afir

m’s

tota

las

sets

.∗∗

and∗

indi

cate

stat

isti

cal

sign

ifica

nce

atth

eα

=.0

1an

dα

=.0

5le

vel,

resp

ecti

vely

.T

-sta

tist

ics

are

liste

din

pare

nthe

sis.

The

cut

offva

lue

for

the

smal

lan

dla

rge

grou

par

e40

8an

d1,

158

mill

ion

dolla

rs.

Cla

ssifi

cati

onfo

rba

nkre

lati

onsh

ipis

base

don

whe

ther

aR

EIT

borr

ows

aba

nklo

anfr

omth

esa

me

bank

twic

ew

ithi

na

five

year

peri

od.

Cla

ssifi

cati

onfo

rbo

ndra

ting

isba

sed

onw

heth

era

RE

ITha

sis

sued

apu

blic

debt

offer

ing

and

obta

ina

bond

rati

ngin

year

t.

29

Tab

le5.

Cas

hH

oldin

gs,B

ank

Lin

eC

apac

ity

and

Div

iden

dby

Fir

mC

har

acte

rist

ics

(con

tinues

)

Pan

elB

:D

ivid

end

Equ

atio

n

Dep

ende

ntV

aria

ble:

∆D

itC

Fit

Dit−

1∆

CS

it∆

Lit

TQ

it−

1In

tait

NA

dj.

R2

Fir

mSiz

eSm

all

0.26

7−

0.73

2−

0.13

7−

0.07

50.

024

−0.

002

476

0.53

(8.7

9)∗∗

(−24

.56)

∗∗(−

2.80

)∗∗

(−3.

01)∗∗

(6.7

5)∗∗

(−1.

46)

Lar

ge0.

289

−0.

561

−0.

011

−0.

029

0.00

8−

0.00

247

60.

54(9

.96)

∗∗(−

17.6

1)∗∗

(−0.

46)

(−1.

33)

(0.2

6)(−

1.59

)B

ond

Rat

ing

No

Bon

d0.

292

−0.

772

−0.

180

−0.

057

0.02

3−

0.00

380

90.

46(1

1.22

)∗∗

(−30

.28)

∗∗(−

3.85

)∗∗

(−2.

54)∗∗

(6.9

2)∗∗

(−3.

72)∗∗

Bon

d0.

321

−0.

670

0.03

3−

0.02

20.

005

−0.

003

476

0.54

(10.

75)∗∗

(−27

.38)

∗∗(2

.11)

∗(−

2.91

)∗∗

(2.5

7)∗

(−4.

27)∗∗

Rel

atio

nsh

ipN

oR

el.

0.28

7−

0.72

1−

0.09

3−

0.03

40.

019

−0.

002

671

0.46

(10.

13)∗∗

(−26

.33)

∗∗(−

2.55

)∗(−

1.71

)(5

.91)

∗∗(−

1.84

)W

ith

Rel

.0.

328

−0.

877

−0.

043

−0.

035

0.01

4−

0.00

475

00.

61(1

3.89

)∗∗

(−44

.01)

∗∗(−

1.98

)∗(−

3.63

)∗∗

(5.9

6)∗∗

(−6.

66)∗∗

The

empi

rica

lsp

ecifi

cati

onof

the

fixed

-effe

ctm

odel

isas

follo

ws:

∆D

it=

γ0

+γ1∗

CF

it+

γ2∗

Dit−

1+

γ3∗

∆C

Sit

+γ4∗

∆L

it+

γ5∗

TQ

it−

1+

γ6∗

Inta

it+

ϑit

(35)

The

mod

els

are

two-

way

(yea

ran

dpr

oper

tyty

pe)

fixed

effec

tm

odel

usin

gR

EIT

firm

-yea

rda

ta(1

990

-20

03).

The

inde

pend

ent

vari

able

sin

clud

eth

efo

llow

ing.

CF

isca

shflo

w(i

ncom

ebe

fore

extr

aord

inar

yit

ems

plus

depr

ecia

tion

)in

year

t.L

tis

the

bank

cred

itlin

eho

ldin

gsat

the

end

ofye

art,

CS

isth

eca

shho

ldin

gs,m

easu

red

bya

firm

’sca

shan

dca

sheq

uiva

lent

s,D

isth

eca

shdi

vide

ndpa

yout

inye

art.

∆L

,∆C

S,a

nd∆

Dar

eth

ech

ange

sof

bank

line

hold

ing,

cash

hold

ings

,an

ddi

vide

ndpa

yout

from

t-1

tot.

All

the

vari

able

sab

ove

are

scal

edby

tota

las

sets

atth

een

dof

year

t-1.

TQ

isa

Tob

in’s

Qm

easu

re,i.e

.,m

arke

tto

book

rati

o.Inta

isth

ena

tura

llo

gof

afir

m’s

tota

las

sets

.∗∗

and∗

indi

cate

stat

isti

cal

sign

ifica

nce

atth

eα

=.0

1an

dα

=.0

5le

vel,

resp

ecti

vely

.T

-sta

tist

ics

are

liste

din

pare

nthe

sis.

The

cut

offva

lue

for

the

smal

lan

dla

rge

grou

par

e40

8an

d1,

158

mill

ion

dolla

rs.

Cla

ssifi

cati

onfo

rba

nkre

lati

onsh

ipis

base

don

whe

ther

aR

EIT

borr

ows

aba

nklo

anfr

omth

esa

me

bank

twic

ew

ithi

na

five

year

peri

od.

Cla

ssifi

cati

onfo

rbo

ndra

ting

isba

sed

onw

heth

era

RE

ITha

sis

sued

apu

blic

debt

offer

ing

and

obta

ina

bond

rati

ngin

year

t.

30

Tab

le5.

Cas

hH

oldin

gs,B

ank

Lin

eC

apac

ity

and

Div

iden

dby

Fir

mC

har

acte

rist

ics

(con

tinues

)

Pan

elC

:C

ash

Hol

ding

Equ

atio

n

Dep

ende

ntV

aria

ble:

∆C

Sit

CF

itC

S it−

1∆

Dit

∆L

itT

Qit−

1In

tait

NA

dj.

R2

Fir

mSiz

eSm

all

0.14

6−

0.56

6−

0.07

10.

046

0.00

3−

0.01

347

60.

53(2

.66)

∗∗(−

10.9

7)∗∗

(−0.

89)∗∗

(0.9

9)(0

.51)

(−5.

11)∗∗

Lar

ge−

0.16

5−

0.85

40.

042

0.02

80.

025

0.00

247

60.

54(−

3.77

)∗∗

(−28

.72)

∗∗(0

.42)

(0.8

3)(4

.92)

∗∗(2

.04)

∗

Bon

dR

atin

gN

oB

ond

0.14

2−

0.53

1−

0.07

20.

072

0.00

4−

0.08

809

0.46

(3.3

3)∗∗

(−12

.59)

∗∗(−

1.25

)(1

.85)

(0.7

1)(−

6.08

)∗∗

Bon

d−

0.36

2−

0.88

8−

0.28

30.

025

0.02

70.

001

596

0.60

(−5.

05)∗∗

(−27

.99)

∗∗(−

2.88

)∗∗

(1.3

9)(5

.38)

∗∗(−

0.43

)R

elat

ionsh

ipN

oR

el.

0.12

2−

0.60

4−

0.08

70.

055

0.00

8−

0.00

967

10.

46(2

.40)

∗(−

14.7

0)∗∗

(−1.

16)

(1.4

9)(1

.37)

(−5.

81)∗∗

Wit

hR

el.

−0.

086

−0.

853

0.03

5−

0.02

50.

015

0.00

175

00.

61(−

2.03

)∗(−

25.1

1)∗∗

(0.8

0)(−

1.48

)(3

.46)

∗∗(1

.13)

The

empi

rica

lsp

ecifi

cati

onof

the

fixed

-effe

ctm

odel

isas

follo

ws:

∆C

Sit

=γ0

+γ1∗

CF

it+

γ2∗

CS

it−

1+

γ3∗

∆D

it+

γ4∗

∆L

it+

γ5∗

TQ

it−

1+

γ6∗

Inta

it+

ξ it

(36)

The

mod

els

are

two-

way

(yea

ran

dpr

oper

tyty

pe)

fixed

effec

tm

odel

usin

gR

EIT

firm

-yea

rda

ta(1

990

-20

03).

The

inde

pend

ent

vari

able

sin

clud

eth

efo

llow

ing.

CF

isca

shflo

w(i

ncom

ebe

fore

extr

aord

inar

yit

ems

plus

depr

ecia

tion

)in

year

t.L

tis

the

bank

cred

itlin

eho

ldin

gsat

the

end

ofye

art,

CS

isth

eca

shho

ldin

gs,m

easu

red

bya

firm

’sca

shan

dca

sheq

uiva

lent

s,D

isth

eca

shdi

vide

ndpa

yout

inye

art.

∆L

,∆C

S,a

nd∆

Dar

eth

ech

ange

sin

bank

line

hold

ings

,ca

shho

ldin

gs,an

ddi

vide

ndpa

yout

from

t-1

tot.

All

the

vari

able

sab

ove

are

scal

edby

tota

las

sets

atth

een

dof

year

t-1.

TQ

isa

Tob

in’s

Qm

easu

re,i.e

.,m

arke

tto

book

rati

o.Inta

isth

ena

tura

llo

gof

afir

m’s

tota

las

sets

.∗∗

and∗

indi

cate

stat

isti

cal

sign

ifica

nce

atth

eα

=.0

1an

dα

=.0

5le

vel,

resp

ecti

vely

.T

-sta

tist

ics

are

liste

din

pare

nthe

sis.

The

cut

offva

lue

for

the

smal

lan

dla

rge

grou

par

e40

8an

d1,

158

mill

ion

dolla

rs.

Cla

ssifi

cati

onfo

rba

nkre

lati

onsh

ipis

base

don

whe

ther

aR

EIT

borr

ows

aba

nklo

anfr

omth

esa

me

bank

twic

ew

ithi

na

five

year

peri

od.

Cla

ssifi

cati

onfo

rbo

ndra

ting

isba

sed

onw

heth

era

RE

ITha

sis

sued

apu

blic

debt

offer

ing

and

obta

ina

bond

rati

ngin

year

t.

31

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