Journal of Business Finance & Accounting, 34(7) & (8), 1051–1072, September/October 2007, 0306-686X
doi: 10.1111/j.1468-5957.2007.02023.x
Bank Relationships and the Value
Relevance of the Income Statement:
Evidence from Income-Statement
Conservatism
Wooseok Choi∗
Abstract: This study examines the effects of a firm’s debt financing decision on the informativeness of the income statement. This study specifically examines the association between a firm’s
bank dependence and the value relevance of the income statement by investigating the incomestatement conservatism of firms with bank loans. Focusing on relatively small businesses, this study
finds that income-statement conservatism, measured as timely loss recognition, is increasing in a
firm’s bank dependence. This study also finds that the value relevance of the income statement is
increasing in a firm’s bank dependence. The findings of this paper suggest that the usefulness of
the income statement varies with a firm’s bank dependence, indicating that the value relevance
of the income statement is a function of a firm’s debt financing decision. The findings further
suggest that bank relationships affect the value relevance of the income statement through their
influence on income-statement conservatism.
Keywords: bank relationships, debt financing, income statement conservatism, value relevance
1. INTRODUCTION
The choice between bank and public debt is a critical financing decision for a firm.
In economics and finance, therefore, banks, bank loans, and bank relationships are
widely studied. In accounting, however, little is known about the effects of a firm’s
debt financing decision on financial reporting. This study examines these effects by
investigating the value relevance of the income statement in the context of a firm’s
∗
The author is from Korea University, Seoul, Korea. He appreciates helpful comments and suggestions from
Joseph Anthony, Marilyn Johnson, Jun-Koo Kang, Tom Linsmeier, Christian Mastilak, Vicent O’Connell,
Kathy Petroni, and workshop participants at Michigan State University, Korea University, and the 2003
American Accounting Association Annual Meeting. He is also grateful to Martin Walker (editor) and an
anonymous referee for their constructive suggestions. He acknowledges the financial support provided by
Korea University, Michigan State University, and California State University at Los Angeles. (Paper received
February 2005, revised version accepted December 2006. Online publication May 2007)
Address for correspondence: Wooseok Choi, Korea University Business School, Anam-Dong Seongbuk-Gu,
Seoul, Korea 136-701.
e-mail: choiw@korea.ac.kr
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debt financing decision. Specifically, this study examines the association between a
firm’s bank dependence, income-statement conservatism, and the usefulness of the
income statement.
Prior academic and anecdotal evidence suggest that lenders such as banks prefer
accounting conservatism in the presence of information asymmetries to reduce (1)
the risk that borrowers’ financial positions are overstated and (2) an agency conflict
between bondholders and shareholders (e.g., FASB, SFAC No. 2, 1980; Leftwich, 1983;
Ahmed et al., 2002; Holthausen and Watts 2001; and Watts, 2003a and 2003b). However,
few studies provide empirical evidence about banks’ preference for accounting
conservatism. One important way to measure accounting conservatism is the timeliness
of economic loss recognition (Basu, 1997; and Ball and Shivakumar, 2005). Timely loss
recognition is particularly important in debt contracts because it affects the efficiency of
debt agreements that utilize financial statement variables (Ball and Shivakumar, 2005).
Ball and Shivakumar specifically mention that ‘timely income statement incorporation
of economic losses more quickly transfer decision rights from loss-making managers to
lenders.’ Considering the wide use of income-statement variables in debt agreements, it
is highly likely that banks prefer income-statement conservatism as measured by timely
loss recognition. Therefore, it is expected that banks prefer timelier loss recognition
and thus provide borrowers with incentives to maintain a high level of income statement
conservatism. 1 Accordingly, the first hypothesis specifically examines the association
between a firm’s bank dependence and timely loss recognition, predicting that the
timeliness of economic loss recognition increases when a firm’s bank dependence
increases.
Prior research including Ball and Shivakumar (2005) also states that timely loss
recognition is related to the concept of value relevance, implying a positive association
between timely loss recognition and value relevance. In the case of debt contracts,
timelier income statement recognition means that the income statement provides more
useful information in loan agreements, implying higher value relevance of the income
statement. As predicted in the first hypothesis, if a firm has a higher level of bank loans,
the firm is likely to have a higher level of timely loss recognition. Therefore, the second
hypothesis predicts that the higher a firm’s bank dependence, the more useful the
income statement is in explaining a firm’s value because of the higher level of timely
loss recognition.
The second hypothesis is also related to the traditional role of the income
statement. The income statement provides information about a firm’s abnormal
earnings opportunities while the balance sheet provides information on liquidation or
abandonment value (Burgstahler and Dichev, 1997; and Barth, Beaver and Landsman,
1998). The value-relevance literature indicates that investors are more interested in a
firm’s growth potential, information from the income statement, when default risk is
lower. Prior research shows how a significant relationship with a bank helps a firm to
reduce its probability of default by: (a) increasing the ease of renegotiation (Gilson,
John and Lang, 1990), (b) lowering the cost of monitoring (Diamond, 1984; and
Fama, 1985), and (c) providing liquidity during periods of economic stress (Kashyap,
Rajan and Stein, 2002; and Saidenberg and Strahan, 1999). Collectively, the bank
dependence research suggests that the uniqueness of banks and bank loans enables a
1 The incentives might include higher loan amounts, lower interest rates, lower contracting costs, and
increased renewal capacities.
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firm to continue its business with less worry of default risk, making income statement
information more important. This argument is consistent with the second hypothesis
that when a firm’s bank dependence is high, the income statement will be more valuerelevant than when a firm’s bank dependence is low.
The analysis in this paper is based on 3,992 firm-year observations from publicly
traded, non-regulated Mid-Cap companies (i.e., small companies with sales between 1
million and 500 million dollars) during 1988–2004. This paper focuses on relatively
small firms because small firms obtain most of their external funding from financial
intermediaries, primarily commercial banks, unlike large firms that tend to rely
more heavily on public capital markets. Therefore, the firm-creditor relationships are
expected to be especially important for small firms (Diamond, 1991; and Core, Wolken
and Woodburn, 1996). Bank dependence is measured as the dollar value of the bank
loan from the lead bank divided by the total assets of the borrower.
As hypothesized, the results indicate that the timeliness of economic loss recognition
increases as a firm’s bank dependence increases. The results also show that the value
relevance of the income statement increases as a firm’s bank dependence increases.
The results hold even after formally controlling for a firm’s default risk. This suggests
that bank relationships affect the value relevance of the income statement in a way
other than just default risk. Overall, the empirical results provide strong support for
the argument that the conservatism and usefulness of the income statement varies with
a firm’s bank dependence.
A possible alternative explanation is the bank’s ex-ante screening of borrowers. In
this case, bank dependence might proxy for firm-specific characteristics. The most
common screening device used by banks is collateral (Stiglitz and Weiss, 1981; and
Bester, 1985). Although recent bank competition makes bank screening more difficult
(Shaffer, 1998), the sample firms’ collateral levels are further analyzed to explore the
validity of this alternative explanation. The mean and median values of four proxies for
collateral are significantly greater for the low bank-dependent firms than for the high
bank-dependent firms, which is inconsistent with ex-ante screening. Two profitability
measures are also tested to examine the possibility of ex-ante screening based on the
profitability of a firm. Similar to collateral measures, the results show that the mean
and median values of the profitability measures for the low bank-dependent firms are
significantly greater than those for the high bank-dependent firms. Overall, the results
from the tests for the alternative explanation show that ex-ante screening does not drive
the findings of this paper.
The primary contribution of this paper is to introduce the role of the bank
relationship into the accounting literature. Although bank relationships are widely
studied in economics and finance literature, to my knowledge there is no study on bank
relationships in the accounting literature. Given the fact that a firm’s debt financing
decision is critical and that banks and bank loans play a unique role in financing
businesses, it is important to understand the effect of the firm-bank relationship on
financial reporting. This study provides evidence that the conservatism and value
relevance of the income statement is associated with a firm’s bank dependence.
This study also adds to the literature that examines accounting conservatism. There
is theoretical evidence of a lender’s preference for accounting conservatism, but few
studies provide empirical evidence. This paper fills this gap by providing empirical
evidence regarding the association between firm-bank relationships and incomestatement conservatism.
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Finally, unlike prior studies that generally focus on the importance of the balance
sheet, this study finds a situation under which the income statement plays an important
role in explaining firm value.
The paper proceeds as follows: Section 2 motivates and develops the hypotheses.
Section 3 describes the sample and presents the research design and measures. Section 4
presents empirical results. Section 5 examines the validity of an alternative explanation
for the results. Section 6 summarizes and concludes the paper.
2. HYPOTHESIS DEVELOPMENT
(i) Bank Loans and Accounting Conservatism
For banks, borrowers’ abilities to generate future cash flows are of great concern
because of their abilities’ influence on credit risk. Credit risk is the risk to a bank’s
earnings and capital that a borrower will fail to repay the loan principal and interest
as agreed. It is the primary cause of bank failure and the most visible risk facing bank
managers (Fraser, Gup and Kolari, 2001). Therefore, banks have incentives to reduce
the risk that borrowers’ financial positions are overstated, thereby reducing credit risk.
With respect to financial reporting, banks prefer accounting conservatism to reduce
the risk that their assessment of a borrower’s ability to generate future cash flows is
overstated due to overstatement of the borrower’s financial position.
Consistent with this notion, prior academic and anecdotal evidence suggest that
lenders prefer conservative accounting in the presence of information asymmetries.
For example, Watts (2003a and 2003b) suggests that lenders such as banks are
concerned with the lower bound of the earnings and new asset distributions, and use
the lower bound measures during the loan period to monitor the borrower’s ability
to pay. He further suggests that conservatism can be used to address moral hazard,
constraining management’s opportunistic behavior in financial reporting. Leftwich
(1983), Ahmed et al. (2002) and Watts (2003a) argue that accounting conservatism
plays an important role in efficient debt contracting. Finally, FASB’s SFAC No. 2 (1980)
states that conservatism in financial reporting is desirable to bankers because a higher
degree of conservatism provides a greater margin of safety for the assets that serve as
loan security.
Lenders also prefer accounting conservatism to reduce an agency conflict between
bondholders and shareholders. For example, it is likely that firms with large amounts of
bank debt have high bondholder-shareholder conflicts and prefer more conservative
financial reporting. Prior research including Ahmed et al. (2002) confirms this view by
demonstrating that conservatism can be used as a mechanism for resolving this type of
agency conflict.
Although prior studies on the use of accounting conservatism in debt contracting
focus on public debt, the same argument can be used in private bank debt as well.
First, as Holthausen and Watts (2001) stated, SFAC No. 2 attributes the development of
conservatism to bankers and other lenders, suggesting that banks are concerned with
accounting conservatism in their lending agreements as are other lenders. Second, one
of the most important reasons why lenders prefer accounting conservatism is that it
makes debt covenants more binding. Recent evidence, including Dichev and Skinner
(2002), finds that private lenders set debt covenants tightly and use them as a screening
device, suggesting that accounting conservatism can be importantly used in private debt
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contracting. Moreover, syndicated private loans generally use more debt covenants than
public loans. Most bank loans are syndicated loans, further implying that accounting
conservatism is an important concern to banks.
In summary, prior evidence on future cash flows, credit risk, and accounting
conservatism suggests that banks have significant credit risk due to the risk of
overstatement and, therefore, prefer conservatism in financial reporting for the
purpose of effective credit risk management.
(ii) Timely Loss Recognition and Bank Relationships- Hypothesis 1
One important way to measure accounting conservatism is the timeliness of economic
loss recognition (Basu, 1997; and Ball and Shivakumar, 2005). Basu (1997) interprets
conservatism as an asymmetric verification requirement for recognizing good versus
bad news in financial statements, suggesting that earnings reflect bad news more quickly
than good news. He states that debt holders demand more timely information about
bad news that might adversely affect future cash flows because they have an asymmetric
loss function. Ball and Shivakumar (2005) state that accounting income is a key factor
for evaluating financial reporting in general, suggesting that timely income-statement
recognition implies timely revision of all financial statement variables. With respect
to debt agreements, they specifically suggest that timely loss recognition is related to
the efficiency of the debt agreement by affecting both ex ante loan pricing and ex post
violation of covenants based on financial statement variables. Ball and Shivakumar
further mention that ‘timely income statement incorporation of economic losses more
quickly transfer decision rights from loss-making managers to lenders.’
Therefore, as suggested by bank loans, accounting conservatism, and timely
loss recognition literature, it is highly likely that banks prefer income-statement
conservatism as measured by timely loss recognition and thus provide borrowers with
incentives to maintain a high level of income-statement conservatism. 2 Accordingly,
the first hypothesis of this paper is as follows (stated in alternative form):
H 1 : Ceteris paribus, the timeliness of economic loss recognition is increasing in a firm’s
bank dependence.
(iii) Income-statement Conservatism, Bank Relationships, and the Value Relevance
of the Income Statement – Hypothesis 2
Prior research including Ball and Shivakumar (2005) states that timely loss recognition
is related to the concept of value relevance. It suggests that timelier recognition implies
a higher correlation of accounting numbers with market values, suggesting a positive
association between timely loss recognition and value relevance. In other words, timelier
recognition implies higher financial reporting quality. 3 In the case of debt contracts,
2 I am grateful to the referee for suggesting the link between borrowings and income-statement conservatism
for refining the link between bank relationships and the value relevance of the income statement.
3 Prior studies generally have two views about the association between accounting conservatism and value
relevance. Consistent with the argument in this paper, prior studies, such as Watts (2003a) and Ball and
Shivakumar (2005), suggest a positive relation between accounting conservatism and value relevance. On
the other hand, other studies including Lev and Zarowin (1999) suggest a negative relation. However, this
paper does not focus on issues related to whether or not accounting conservatism is good or bad. It focuses
on the role of accounting conservatism in debt contracts and its relation to the usefulness of the income
statement in loan agreements.
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therefore, a timelier income statement incorporation of economic losses means that the
income statement provides more useful information in loan agreements, implying the
higher value relevance of the income statement. As predicted in the first hypothesis, if
a firm has a higher level of bank loans, the firm is likely to have a higher level of timely
loss recognition. Therefore, it can be predicted that if a firm has more bank loans,
the income statement of the firm provides more useful (i.e., more value relevant)
information in explaining firm value because of more timely loss recognition.
This prediction is also related to the traditional role of the income statement. For
example, using an adaptation option model, Burgstahler and Dichev (1997) show that
information from the income statement (i.e., earnings) is more important when the
firm’s current activities are successful since the information provides a measure of the
performance of a business. Barth et al. (1998) investigate the relative valuation roles
of equity book value and net income as a function of financial health. They argue that
the income statement increases in importance as the probability of default and the
importance of assessing liquidation value decrease. Their results imply that the income
statement’s primary role is to provide information about a firm’s abnormal earnings
opportunities. In general, the value-relevance literature indicates that investors are
more interested in a firm’s growth potential, information from the income statement,
when default risk is lower.
Related to default risk, the banking literature provides several explanations as to
why bank dependence affects a firm’s default risk. Prior studies show that the bank
relationship reduces information asymmetries and the firm’s cost of financial distress
by (a) increasing the ease of renegotiation (Gilson, John and Lang, 1990), (b) lowering
the cost of monitoring (Diamond, 1984; and Fama, 1985); 4 and (c) providing liquidity
during periods of economic stress (Kashyap, Rajan and Stein, 2002; and Saidenberg
and Strahan, 1999). Collectively, the bank dependence research suggests that a firm
with a higher level of bank loan has a lower level of default risk, making the firm’s
growth potential, information from the income statement, more informative. This
argument is consistent with the prediction that when bank dependence is high, the
income statement will be more value relevant than when bank dependence is low.
Therefore, as suggested by income-statement conservatism, bank dependence, and
value relevance literature, the second hypothesis of this paper is as follows (stated in
alternative form):
H 2 : The higher a firm’s bank dependence, the more useful the income statement is
in explaining firm value.
3. SAMPLE AND RESEARCH DESIGN
(i) Sample and Descriptive Statistics
The sample comprises 3,992 firm-year observations from publicly traded Mid-Cap
companies (i.e., small companies with sales between 1 million and 500 million dollars),
4 Fama (1985) specifically argues that a bank loan could be considered a type of inside debt which is
similar to internally generated funds, allowing a firm to avoid the underinvestment problem associated
with information asymmetries. The underinvestment problem is caused by debt overhang, the inability of
a company with profitable investment opportunities to finance them because it has excessive levels of debt
relative to its assets (Milgrom and Roberts, 1992).
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which meet the following requirements (see the Appendix for a further discussion of
the sample selection):
1. The largest lender is a bank.
2. The firm (i.e., the borrower) is a non-financial institution and non-utility
company.
3. The bank (i.e., the lender) is a lead lender and has the largest share of the bank
loan.
4. Financial data is available from the Compustat database during the loan period.
Compared to large firms, small companies are less likely to be followed by analysts and
monitored by rating agencies or the financial press, implying that they rarely borrow
in the public capital markets. Therefore, small firms obtain most of their external
funding from financial intermediaries (i.e., commercial banks) and, in turn, firmcreditor relationships are expected to be especially important in small firms (Diamond,
1991; and Core, Wolken and Woodburn, 1996). For similar reasons, bank relationship
literature often focuses on small businesses (Petersen and Rajan, 1994; and Berger and
Udell, 1995).
Due to missing values, the sample has an unbalanced panel data structure. Although
3,992 firm-year observations are selected using the above criteria, the actual number
of observations used in each analysis varies, depending on the model specification
(e.g., pooled OLS estimation, lag variables, Altman-Z score, etc.) and missing firm-year
observations. If the largest lender is not a bank, then the firm is dropped. 5
Information on the borrower-lender relationship is collected from the DealScan
database for the years 1988–2004. Constructed by the Loan Pricing Corporation (LPC),
DealScan contains deal terms and conditions on over 72,000 loans since 1988. Deals in
the database are often comprised of different ‘facilities’. For example, a deal might
include a term loan facility and a line of credit facility. Similar to prior research, each
facility is treated as one observation (see the Appendix for further discussion of the
DealScan database).
Panel A of Table 1 reports descriptive statistics for all firm-year observations, and
Panel B of Table 1 reports descriptive statistics for high and low bank-dependent
firms. Firms are divided into high and low bank-dependent groups based on their
bank dependence. Consistent with bank relationship literature, bank dependence is
measured as the dollar value of the bank loan from the lead bank divided by the total
assets of the borrower (Hoshi, Kashyap and Scharfstein, 1990; Petersen and Rajan,
1994; and Kang, Shivdasani and Yamada, 2000). This measure captures the closeness of
a firm to its main lender and the concentration of a firm’s borrowing across blockholder
lenders. It also measures how important a bank loan is to a firm. 6
5 The focus of this study is on firm-bank relationships. Therefore, this study drops all observations when the
largest lender is not a bank. By using this criterion, this study achieves a homogenous sample which is ideal
from the perspective of addressing the core research questions outlined earlier.
6 There are several reasons why the bank loan is scaled by the borrower’s total assets rather than the
bank’s total assets. First, this scaler measures the extent to which borrowers are influenced by banks,
which is consistent with the research questions of this paper. Second, for a lead bank, reputation is very
important. Therefore, a lead bank will perform monitoring activities to maintain a certain level of accounting
conservatism in a borrower’s income statement, regardless of the relative size of the bank loan to its total
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Table 1
Sample Description
Panel A: Descriptive Statistics for All Sample Firm-year Observations
25%
Median
Mean
Percentile
Bank loans
Maturity
Market value of equity
Book value of equity
Net income
AltmanZ score
Total Assets
Bank share (%)
20.00
15.00
86.94
50.74
27.73
4.45
111.47
9.42
43.80
31.60
206.96
74.44
20.93
92.26
155.15
13.17
7.91
6.00
30.50
19.95
−14.31
2.53
46.90
5.07
75%
Percentile
55.00
34.01
237.38
111.14
10.68
11.04
243.81
16.69
N
3,922
3,921
3,833
3,921
3,914
3,381
3,922
3,922
Panel B: Descriptive Statistics for High vs. Low Bank-dependent Firm-year Observations
Low Bank-dependent
High Bank-dependent
Bank loans
Maturity
Market value of equity
Book value of equity
Net income
AltmanZ score
Total Assets
Bank share (%)
Median
Mean
Median
Mean
10.00
37.00
139.35
76.42
40.43
4.66
177.72
5.07
29.50
45.00
292.64
95.55
27.83
95.48
200.12
5.00
18.50
36.00
58.29
35.80
19.15
4.27
74.47
16.69
36.90
42.00
120.78
53.32
14.01
89.06
110.14
21.34
Notes:
Bank loans, market value of equity, book value of equity, net income, and total assets represent
dollars in millions. Maturity is in months. The high and low bank-dependent groups are classified based on
a firm’s median bank share.
Bank loans are total bank loans (facility amounts) in dollars in each firm-year. Maturity is a maturity of
the bank loan. The Altman Z Score is a measure of a firm’s financial health, calculated as [1.2 (working
capital/total assets) + 1.4 (retained earnings/total assets) + 3.3 (earnings before interest and taxes/total
assets) + 0.6 (market value of equity/book value of liabilities) + 1.0 (sales/total assets)]. Bank share is the
dollar value of the bank loan from the lead bank divided by the total assets of the borrower.
The maturity is similar between high and low bank-dependent firms. The Altman-Z
scores for both groups are in the safe zone. 7 The median and mean values of market
value of equity, book value of equity, net income, and total assets for the low bankdependent firms are larger than those values for the high bank-dependent firms.
The median and mean values generally show that the bank’s screening process and,
therefore, a firm’s specific characteristics do not affect the findings of this study. This
issue will be further explored with extensive sensitivity analyses in Section 5.
Panel A of Table 2 presents the industry composition of the sample. Both
high and low bank-dependent groups have similar industry distributions to the
Compustat dataset. Panel B of Table 2 reports the exchange listings of the sample
assets. Finally, transaction costs of switching to another bank are associated with the relative size of the bank
loan to the firms’ total assets.
7 The interpretation of the Altman Z score is as follows: (i) Z > 2.99 means the firm is safe, (ii) Z < 1.80
means the firm is financially distressed, and(iii) 1.80 < Z < 2.99 means the firm is in the ‘grey’ zone.
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Total
100.00
0.41
5.37
1.05
53.31
6.34
11.02
22.50
1,962
3
76
30
1,089
105
200
459
1,962
Total
100.00
0.16
3.88
1.53
55.50
5.35
10.19
23.39
1,960
301
145
1,265
249
0
%
100.00
0.67
6.88
0.56
51.10
7.34
11.85
21.60
Low Bank-dependent
1,949
13
134
11
996
143
231
421
N
High Bank-dependent
3,922
768
349
2,382
420
3
Full Sample
100.00
0.51
7.00
1.49
43.32
4.82
7.65
22.67
%
Compustat Year 2001
Notes:
Industry membership is determined by two-digit Statistical Industrial Classification (SIC) codes. Out of the total 3,922 firm-year observations, 11 high bankdependent firm-year observations are omitted in the table because they are classified as non-operating establishments (SIC 9995). Sample firms are divided into two
groups, high and low bank-dependent, based on a firm’s bank share.
Exchange listing is determined by the Compustat exchange listing code (ZLIST).
467
204
1,117
171
3
New York Stock Exchange
American Stock Exchange
NASDAQ
Over-the-counter
Others (regional)
Panel B: Distribution of Firm-year Observations by Exchange Listing
Stock Exchange
High Bank-dependent
16
210
41
2,085
248
431
880
Agriculture
Mining
Construction
Manufacturing
Wholesale trade
Retail trade
Services
%
N
%
Industry Description
N
Low Bank-dependent
Panel A: Distribution of Firm-year Observations by Industry
All Sample
Table 2
Distribution of Firm-year Observations
BANK RELATIONSHIPS AND THE INCOME STATEMENT
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firms. There is little difference in the exchange listing between high and low
bank-dependent firms. The NASDAQ has the largest number of sample firm-year
observations, followed by the New York Stock Exchange and the American Stock
Exchange.
Panel A of Table 3 presents the Pearson correlations between the independent
variables used in equation (1). The largest variance inflation factor (VIF) value among
all independent variables is 5.06. The smallest tolerance (1/VIF) is 0.20. Both VIF
and 1/VIF values indicate that there is no severe multicollinearity problem among the
independent variables in equation (1).
Panel B of Table 3 presents the Pearson correlations between the independent
variables used in equation (2). The largest variance inflation factor (VIF) value among
all independent variables is 7.83. The smallest tolerance (1/VIF) is 0.13. Similar to
equation (1), both VIF and 1/VIF values indicate that there is no severe multicollinearity
problem among the independent variables in equation (2).
Finally, Panel C of Table 3 presents the Pearson correlations between the independent variables used in equation (3). Two out of seven VIF values are larger than
10, but smaller than 20. This indicates that there might be a slight multicollinearity
concern. However, the mean VIF (5.64) is less than 6. In addition, the conditional
number (9.58) is less than 15. 8 Both the mean VIF and the conditional number indicate
that there is a little multicollinearity problem among the independent variables in
equation (3).
(ii) Model Specification – Hypothesis 1
The first hypothesis examines the relation between timely loss recognition and
bank dependence. Similar to Basu (1997) and Ball and Shivakumar (2005), the
first hypothesis is tested by estimating the coefficients in the following regression
model:
NIit = α0 + α1 D NIit−1 + α2 NIit−1 + α3 (D NIit−1 × NIit−1 )
+ α4 SHAREi + α5 (SHAREi × D NIit−1 ) + α6 (SHAREi × NIit−1 )
+ α7 (SHAREi × D NIit−1 × NIit−1 ) + εi
(1)
where:
i denotes firms, t denotes years for 1988–2004, NI t is the change in earnings from year
t−1 to year t, standardized by total assets at the end of year t−1, NI t −1 is the change
in earnings from year t−2 to year t−1, standardized by total assets at the end of year
t−2, D NI is an indicator variable that equals 1 if NI is negative and 0 otherwise, and
SHARE is the bank dependence measured as the dollar value of the bank loan from
the lead bank divided by the total assets of the borrower. 9
As Basu (1997) stated, α 2 + α 3 < 0 indicates timely recognition of economics losses,
implying that they are recognized as transitory income decreases and hence reversed.
8 The conditional number is another method to test multicollinearity among independent variables. It equals
the square root of the largest eigenvalue divided by the smallest eigenvalue. In general, if the conditional
number is larger than 15, multicollinearity is a concern. If it is greater than 30, multicollinearity is a serious
concern.
9 Standard errors in equations (1), (2), and (3) are computed based on clustering to mitigate potential
cross- and serial-correlations in the dependent variables.
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(0.00)
−0.40
(0.00)
−0.39
(0.00)
SHARE i × D NI it −1
SHARE i × NI it −1
SHARE i × D NI it −1 × NI it −1
−0.75
(0.00)
0.03
(0.17)
0.62
(0.00)
−0.51
(0.00)
−0.48
(0.00)
R it × DR it
SHARE i
SHARE i × DR it
SHARE i × R it
SHARE i × DR it × R it
1.00
−0.69
(0.00)
R it
DR it 1
Panel B: Equation 2 – Independent Variables
DR it 1
0.03
(0.31)
SHARE i
−0.50
(0.00)
−0.47
(0.00)
NI it −1
1.00
D NI it −1 × NI it −1
D NI it −1
0.43
(0.00)
0.71
(0.00)
−0.43
(0.00)
0.66
(0.00)
0.50
(0.00)
−0.47
(0.00)
−0.03
(0.19)
R it × DR it
−0.05
(0.03)
0.43
(0.28)
0.70
(0.00)
−0.32
(0.00)
0.03
(0.23)
0.61
(0.00)
0.40
(0.00)
−0.30
(0.00)
−0.02
(0.37)
1.00
−0.44
(0.00)
0.12
(0.00)
0.56
(0.00)
1.00
SHARE i
D NI it −1 ×
NI it −1
1.00
1.00
R it
1.00
NI it −1
0.66
(0.00)
0.66
(0.00)
Panel A: Equation 1 – Independent Variables
D NI it −1
−0.37
(0.00)
0.13
(0.00)
0.51
(0.00)
1.00
−0.69
(0.00)
−0.47
(0.00)
1.00
SHARE i ×
D NI it −1
−0.79
(0.00)
−0.51
(0.00)
1.00
SHARE i × DR it
SHARE i
0.55
(0.00)
1.00
SHARE i × R it
0.58
(0.00)
1.00
SHARE i ×
NI it −1
Table 3
Pearson Correlations Between Independent Variables (Significance levels in parentheses)
1.00
SHARE i × DR it × R it
1.00
SHARE i × D NI it −1 ×
NI it −1
BANK RELATIONSHIPS AND THE INCOME STATEMENT
1061
1.00
0.30
(0.00)
0.27
(0.00)
0.10
(0.00)
0.62
(0.00)
0.25
(0.28)
0.07
(0.00)
−0.13
(0.00)
−0.07
(0.00)
0.19
(0.00)
−0.17
(0.00)
0.03
(0.05)
1.00
0.94
(0.00)
0.18
(0.00)
0.66
(0.00)
0.02
(0.36)
1.00
NI it
0.09
(0.00)
0.57
(0.00)
−0.00
(0.97)
1.00
NI × DNEGI it
0.29
(0.00)
0.03
(0.13)
1.00
BVE × SHARE it
0.02
(0.12)
1.00
NI × SHARE it
1.00
ALT Z it
Notes:
Panel A:
i denotes firms, t denotes years for 1988–2004, NI t −1 is change in earnings from year t−2 to year t−1, standardized by total assets at end of year t−2, D NI is an
indicator variable that equals 1 if NI is negative and 0 otherwise, and SHARE is the dollar value of the bank loan from the lead bank divided by the total assets of the
borrower.
Panel B:
i denotes firms, t denotes years for 1988–2004, R is the buy-and-hold returns from nine months before fiscal year-end to three months after fiscal year-end, DR is an
indicator variable that equals 1 if R is negative, and 0 otherwise, and SHARE is bank dependence measured as the dollar value of the bank loan from the lead bank
divided by the total assets of the borrower.
Panel C:
i denotes companies, t denotes years for 1988–2004, BVE is book value of equity, NI is net income, DNEGB is an indicator variable that equals 1 if BVE is negative and
0 otherwise, DNEGI is an indicator variable that equals 1 if NI is negative and 0 otherwise, SHARE is the dollar value of the bank loan from the lead bank divided by
the total assets of the borrower, and ALT Z is the Altman Z score measured as [1.2 (working capital/total assets) + 1.4 (retained earnings/total assets) + 3.3 (earnings
before interest and taxes/total assets) + 0.6 (market value of equity/book value of liabilities) + 1.0 (sales/total assets)].
ALT Z it
NI × SHARE it
BVE × SHARE it
NI × DNEGI it
NI it
BVE it
BVE × DNEGB it
Panel C: Equation 3 – Independent Variables
BVE it
BVE × DNEGB it
Table 3 (Continued)
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α 3 < 0 implies that economic losses are recognized in a more timely manner than
gains. 10 The first hypothesis predicts that the coefficient on SHARE i × D NI it −1 ×
NI it −1 , α 7 , is negative, meaning that high bank-dependent firms are more likely to
recognize economic loses in a timely manner than the low bank-dependent firms.
Similar to Ball and Shivakumar (2005), there is no prediction on a difference in gain
recognition between high and low bank dependent firms, offering no prediction on
α 6.
Equation (1) measures accounting conservatism as the transitory component of
changes in net income. It has a potential limitation because the transitory component
of changes in net income can arise either from noise that reverses over time or from
conservatism. Therefore, to mitigate this limitation and check the robustness of the
results from equation (1), the first hypothesis is re-examined by using an alternative
measure of conservatism. 11
The alternative measure is Basu’s (1997) reverse regression of earnings on stock
returns. The estimation model is as follows:
X it /Pit−1 = α0 + α1 DRit + α2 Rit + α3 (Rit × DRit ) + α4 SHAREi + α5 (SHAREi × DRit )
(2)
+ α6 (SHAREi × Rit ) + α7 (SHAREi × DRit × Rit ) + εit
where:
i denotes firms, t denotes years for 1988–2004, X is the earnings per share measured
as income before extraordinary items/(number of shares outstanding × stock split
adjustment factor), P is the price per share at the beginning of the fiscal year divided
by the stock split adjustment factor, R is the buy-and-hold returns from nine months
before the fiscal year-end to three months after the fiscal year-end, DR is an indicator
variable that equals 1 if R is negative, and 0 otherwise, and SHARE is bank dependence
measured as the dollar value of the bank loan from the lead bank divided by the total
assets of the borrower.
Based on the sign of the returns, Basu divides the sample into a ‘good news’ group
(i.e., firm-year observations with positive returns) and a ‘bad news’ group (i.e., firmyear observations with negative returns). He predicts that under conservatism, the
coefficient on R ∗ DR, α 3 , will be significantly positive, suggesting that the earningsreturn relation is stronger during bad news periods. He also predicts that α 0 and α 2
will be positive and significant. This paper further predicts that α 7 will be positive and
significant, indicating that the extent to which earnings reflects bad news more quickly
than good news is increasing in a firm’s bank dependence.
(iii) Model Specification – Hypothesis 2
The second hypothesis examines the association between bank dependence and the
informativeness of the income statement. It is tested by using a revised version of Barth
10 As for economic gains, timely recognition implies α 2 < 0 while untimely recognition implies α 2 >
0. Untimely recognition implies that economic gains are recognized as persistent positive components of
accounting income that are unlikely to be reversed.
11 I am grateful to the referee for indicating the potential limitation and suggesting the alternative measure.
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et al. (1998). Specifically, the following regression model is tested:
MVEit = α0 + α1 BVEit + α2 (BVE × DNEGB)it + α3 NIit + α4 (NI × DNEGI)it
+ α5 (BVE × SHARE)it + α6 (NI × SHARE)it + α7 ALT Zit
+ α8 (BVE × ALT Z)it + α9 (NI × ALT Z)it + εit
(3)
where:
i denotes companies, t denotes years for 1988–2004, MVE is the market value of equity,
BVE is the book value of equity, NI is the net income, DNEGB is an indicator variable that
equals 1 if BVE is negative and 0 otherwise, DNEGI is an indicator variable that equals
1 if NI is negative and 0 otherwise, SHARE is bank dependence measured as the dollar
value of the bank loan from the lead bank divided by the total assets of the borrower,
and ALT Z is the Altman Z score measured as [1.2 (working capital/total assets) +
1.4 (retained earnings/total assets) + 3.3 (earnings before interest and taxes/total
assets) + 0.6 (market value of equity/book value of liabilities) + 1.0 (sales/total
assets)].
The Altman Z score is included to formally control for the probability of default.
The control for the probability of default is important for the following reason: This
paper argues that bank relationships affect the value relevance of the income statement
because of the impact of these relationships on income-statement conservatism. The
paper further argues that the impact of bank relationships on the value relevance
of the income statement is a function of the traditional importance of the income
statement as in the context of predicting default risk. Therefore, to directly examine
only the effect of income-statement conservatism on value relevance, this paper
formally controls for the probability of default using the Altman Z score. The
negative net income indicator is included since prior research suggests that loss
firms have different pricing multiples (Hayn, 1995; Barth et al., 1998; and Collins
et al., 1999). The second hypothesis predicts that the coefficient on NI∗ SHARE,
α 6 , is positive since the importance of NI increases as a firm’s bank dependence
increases.
4. EMPIRICAL RESULTS
The results of the tests for the first hypothesis are reported in Table 4 and Table 5.
The tests focus on the association between income-statement conservatism and bank
dependence. Table 4 reports results from equation (1). Specifically, it reports the
findings from the test of differences in timely loss recognition conditional on a firm’s
bank dependence. The findings are consistent with this study’s main prediction.
Consistent with the first hypothesis that the timeliness of economic loss recognition
increases with a firm’s bank dependence, the coefficient on SHARE i × D NI it −1 ×
NI it −1 , −1.6246, is negative and statistically significant at less than 1% significance
level (p-value < 0.01). As stated before, the current paper makes no predictions about a
difference of gain recognition between high and low bank-dependent firms. Therefore,
no prediction is provided for the coefficient on SHARE i × NI it −1 . Similar to Basu
(1997) and Ball and Shivakumar (2005), the F -test for α 2 + α 3 shows that the sum of
the coefficients is negative and statistically significant (F-statistic = 10.22 and p-value
< 0.01). In addition, the F -test for α 3 + α 7 shows that the sum of the coefficients
is negative and statistically significant (F-statistic = 8.72 and p-value < 0.01). Both
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Table 4
Income Statement Conservatism and Bank Dependence
NI
it
Regression of equation (1):
= α0 + α1 D NIit−1 + α2 NIit−1 + α3 (D NIit−1 × NIit−1 ) + α4 SHAREi + α5 (SHAREi × D NIit−1 )
+ α6 (SHAREi × NIit−1 )+ α7 (SHAREi × D NIit−1 × NIit−1 ) + εi
Independent Variables
Coefficient
−0.0056
−0.1435
−0.0857
−0.0106
−0.0380
0.1762
−1.6246
R2
0.0870
N
1,558
D NI it −1
NI it −1
D NI it −1 × NI it −1
SHARE i
SHARE i × D NI it −1
SHARE i × NI it −1
SHARE i × D NI it −1 × NI it −1
t-statistics
−0.56
−2.11∗∗
−0.90
−0.27
−0.54
0.53
−2.66∗∗∗
Notes:
∗ , ∗∗ and ∗∗∗ indicate significance at the 1%, 5% and 10% levels, respectively, for two-tailed tests.
The regression is winsorized at 1% on each side for NI t and NI t −1 .
i is a company index, and t is a year index. NI t is the change in earnings from year t−1 to year t,
standardized by total assets at end of year t−1. Other variables are defined in Table 3.
results indicate that for bank-dependent firms, economic losses are recognized in a
timelier manner than gains as transitory income increases. Unlike Basu (1997) and
Ball and Shivakumar (2005), the coefficient on NI it −1 is negative and statistically
significant, implying that for bank-dependent firms, economic gains are also recognized
in a timely fashion although the degree of timeliness is less than that for economic
losses. 12
Table 5 reports results from equation (2) using an alternative measure of conservatism. The results are also consistent with the first hypothesis. The coefficient on
SHARE i × DR it × R it , 0.4868, is positive and statistically significant (p-value = 0.095),
implying that the extent to which earnings reflects bad news more quickly than good
news increases as a firm’s bank dependence increases. Similar to Basu (1997), the
coefficients on the intercept, R, and R ∗ DR variables are all significantly positive. These
results confirm the first hypothesis that the timeliness of economic loss recognition is
increasing in a firm’s bank dependence. 13
The results from the test of the second hypothesis are shown in Table 6. The
coefficient on NI × SHARE, 6.3487, is positive and statistically significant (p-value =
0.019). Consistent with the second hypothesis, this result indicates that the value
12 One caution for this interpretation is that this result might be due to the limitation of the estimation
model, equation (1), discussed in Section 3.
13 In addition, Ball and Shivakumar’s (2006) non-linear regression of accruals on cash flows is examined
although it is not reported. The results are also consistent with the first hypothesis.
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Table 5
Income Statement Conservatism and Bank Dependence – Alternative Measure of
Conservatism
Regression of equation (2):
X it /Pit−1 = α0 + α1 DRit + α2 Rit + α3 (Rit × DRit ) + α4 SHAREi + α5 (SHAREi × DRit )
+ α6 (SHAREi × Rit ) + α7 (SHAREi × DRit × Rit ) + εit
Independent Variables
Intercept
DR it
R it
R it × DR it
SHARE i
SHARE i × DR it
SHARE i × R it
SHARE i × DR it × R it
R2
N
Coefficient
0.0436
0.0092
0.0229
0.2131
−0.0390
0.0023
−0.1181
0.4868
t-statistics
4.63∗∗∗
0.48
2.02∗∗
4.79∗∗∗
−0.48
0.02
−1.13
1.67∗
0.1090
2,290
Notes:
∗∗∗ , ∗∗ and ∗ indicate significance at the 1%, 5% and 10% levels, respectively, for two-tailed tests.
The regression is winsorized at 1% on each side for X it /P it −1 and R it .
i is a company index, and t is a year index. X is the earnings per share measured as income before
extraordinary items/(number of shares outstanding ∗ stock split adjustment factor) and P is the price
per share at the beginning of the fiscal year divided by a stock split adjustment factor. Other variables are
defined in Table 3.
relevance of NI increases as a firm’s bank dependence increases. 14, 15 The coefficient
is positive and significant after controlling for default risk (i.e., Altman Z score) in
the estimation model, implying that bank relationships affect the value relevance
of the income statement in ways which extend beyond the impact of default risk.
These findings are consistent with the intuition underlying the first hypothesis that the
impact of bank relationships on income-statement conservatism may be of sufficient
importance to simultaneously impact the value relevance of the income statement.
Finally, similar to prior studies, the coefficients on BVE and NI are both positive and
significant, indicating that the balance sheet and income statement generally play
important roles in explaining firm value.
In summary, the results from the test of the second hypothesis show that the higher
a firm’s bank dependence, the greater the weight placed on the income statement in
14 Although there is no prediction for the coefficient on BVE × SHARE, the negative and significant
coefficient on BVE × SHARE might indicate that the importance of BVE decreases as a firm’s bank
dependence increases. In addition, consistent with prior studies, the coefficient for negative net income
∗
observations (NI DNEG) is negative and statistically significant, reflecting the transitory nature of losses.
Barth et al. (1998) specifically state that the coefficient for negative net income observations is negative
because ‘the limited liability feature of common shares suggests each incremental dollar of loss has a
diminishing relation with share prices.’
15 The coefficients on BVE and NI are similar to prior studies in terms of magnitude and significance. The
coefficient on the book value of equity in prior studies ranges from 0.16 to 0.92 and that on earnings ranges
from 3.44 – 9.31.
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BANK RELATIONSHIPS AND THE INCOME STATEMENT
Table 6
Bank Dependence and the Value Relevance of the Income Statement
Regression of equation (3):
MVEit = α0 + α1 BVEit + α2 (BVE × DNEGB)it + α3 NIit + α4 (NI × DNEGI)it
+ α5 (BVE × SHARE)it + α6 (NI × SHARE)it + α7 ALT Zit
+ α8 (BVE × ALT Z)it + α9 (NI × ALT Z)it + εit
Independent Variables
Coefficient
BVE it
BVE × DNEGB it
NI it
NI × DNEGI it
BVE × SHARE it
NI × SHARE it
ALT Z it
BVE × ALT Z it
NI × ALT Z it
1.4657
0.8506
12.0431
−13.7649
−8.2941
6.3487
0.0305
0.0003
−0.0003
R2
N
t-statistics
3.22∗∗∗
1.87∗
7.12∗∗∗
−8.17∗∗∗
−3.04∗∗∗
2.34∗∗∗
1.02
0.68
−0.86
0.3288
3,381
Notes:
∗∗∗ , ∗∗ and ∗ indicate significance at the 1%, 5% and 10% levels, respectively, for two-tailed tests.
i is a company index, and t is a year index. MVE is market value of equity. Other variables are defined in
Table 3.
explaining firm value. Overall, these findings suggest that the usefulness of the income
statement varies with a firm’s bank dependence.
5. AN ALTERNATIVE EXPLANATION – EX-ANTE SCREENING
A possible alternative explanation for the results reported in Section 4 is the bank’s
ex-ante screening of borrowers. In this case, bank dependence might proxy for the firm
characteristics used by banks to screen loan applicants. The most common screening
device used by banks is collateral (Stiglitz and Weiss, 1981; and Bester, 1985). Commonly
used collateral includes real property, equipment, inventories, accounts receivable,
and securities and savings accounts. Since a collateral’s value varies by items (e.g.,
90 percent of the value of high-graded municipal bonds is counted as collateral but
only 75 percent of the value of major common stock is included (Freixas and Rochet,
1997)), four proxies for a firm’s collateral value are used: (i) receivables, (ii) inventories,
(iii) property, plant, and equipment, and (iv) book value of equity. Then, whether
the collateral value is different between high bank-dependent firms and low bankdependent firms is examined. If the alternative explanation is valid, the collateral
values of the high bank-dependent firm should be greater than those of the low bankdependent firm, implying that banks ex-ante screen borrowers based on the borrowers’
collateral values.
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Table 7
Mean and Median Tests for the Alternative Explanation – Ex-ante Screening
Panel A: Test for the Difference of Collateral Between the Low and High Bank-dependent Firms
Median Test b
Mean Test a
Variables
Sample
Mean
p-value
Median
p-value
σ
Receivables
Low
High
36.58
21.71
<0.01
23.62
11.97
<0.01
38.43
27.66
Inventories
Low
High
32.30
20.52
<0.01
13.92
7.85
<0.01
44.63
33.80
Property, plant, &
equipment
Low
High
113.56
65.95
<0.01
63.08
32.94
<0.01
136.47
92.74
Book value of equity
Low
High
95.55
53.32
<0.01
76.42
35.80
<0.01
91.56
59.30
Panel B: Test for the Difference of Profitability Between the Low and High Bank-dependent Firms
Median Test b
Mean Test a
Variables
Net income/Total
assets
Retained earnings/
Total assets
Sample
Mean
Low
High
Low
High
p-value
σ
0.04
0.03
0.04
0.25
0.35
0.14
0.10
<0.01
0.74
1.30
p-value
Median
−0.01
−0.04
<0.01
−0.02
−0.17
<0.01
Notes:
a The mean test refers to the standard t-test for differences in means. It assumes unequal variances.
b The median test refers to Wilcoxon two-sample tests.
Receivables, inventories, property, plant, & equipment, and book value of equity represent dollars in
millions. Sample firms are divided into two groups, high and low bank-dependent, based on a firm’s bank
loan. Low represents low bank-dependent firms. High represents high bank-dependent firms.
Panel A of Table 7 presents the mean and median tests for the low and high bankdependent samples. 16 The mean and median values of all four proxies for the low bankdependent firms are significantly greater than those for the high bank-dependent firms,
which is inconsistent with the alternative explanation. Therefore, the results indicate
that the screening process based on collateral values does not explain the findings of
this paper.
The profitability measures between high bank-dependent firms and low bankdependent firms are further examined because it is also possible that banks ex-ante
screen borrowers based on the borrowers’ profitability. Two measures are used: net
income divided by total assets and retained earnings divided by total assets. Similar
to collateral measures, the result shown in Panel B of Table 7 shows that the mean
16 The high and low bank-dependent groups are classified based on a firm’s median bank share. The results
are unaffected if the classification is based on quartiles. The mean and median tests refer to the standard
t-test for differences in means and Wilcoxon two-sample tests, respectively.
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and median values of the profitability measures for the low bank-dependent firms are
significantly greater than those for the high bank-dependent firms, which is inconsistent
with the alternative explanation.
In addition, recent bank competition makes bank screening more difficult. Prior
studies, including Shaffer (1998), show that there is a negative relationship between
bank competition and the degree of screening. Therefore, in today’s competitive
banking environment, it is less likely that the ex-ante screening process influences the
nature of a firm’s business.
Overall, the tests show that firm-specific characteristics such as collateral and
profitability are not the alternative explanation for the findings of this paper.
Therefore, bank dependence is not a proxy for other firm attributes that influence
the informativeness of the income statement.
6. SUMMARY AND CONCLUSION
This paper examines the effects of a firm’s debt financing decision on the informativeness of the income statement by investigating the association between a firm’s
bank dependence and income statement conservatism. Prior academic and anecdotal
evidence suggest that banks prefer accounting conservatism to secure their loans and
reduce credit risk. Banks particularly value borrowers’ timely loss recognition for the
purpose of efficient debt contracting. As a consequence, banks provide borrowers
with incentives to maintain a high level of income-statement conservatism measured
as timely loss recognition. Therefore, this study predicts that the more a firm is bankdependent, the higher the timeliness of economic loss recognition is in the firm’s
income statement. Prior research further indicates that there is a positive association
between timely loss recognition and the value relevance of financial statements. In
other words, timelier loss recognition in the income statement implies higher value
relevance of the income statement. Therefore, combining this argument with the first
prediction, this study also predicts that the value relevance of the income statement is
increasing in a firm’s bank dependence. The second prediction is also related to the
role of the income statement in value relevance literature. According to the literature,
information from the income statement is more value relevant when a firm’s default
risk is lower. The uniqueness of the bank loan, such as the ease of renegotiation, lower
cost of monitoring, and liquidity provision, enables a firm to continue its business
with less worry about the risk of default. Therefore, when a firm’s bank dependence
is higher, the firm’s default risk would be lower, making the income statement more
value relevant. This argument is consistent with the second prediction.
Focusing on relatively small businesses, the analyses report consistent results with
the two predictions. The results show that the timeliness of economic loss recognition
is increasing in a firm’s bank dependence. In addition, the results show that the higher
a firm’s bank dependence, the more useful the income statement is in explaining firm
value. This result indicates that the value relevance of the income statement increases
as bank dependence increases. Overall, the findings of this paper suggest that the
usefulness of the income statement varies with a firm’s bank dependence. The findings
suggest that the value relevance of the income statement is a function of a firm’s debt
financing decision. This paper specifically argues that the effect of a bank relationship
on the value relevance is mainly due to the effect of the bank relationship on income
statement conservatism.
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This study contributes to the accounting literature by introducing the role of
the bank relationship in financial reporting. Given the importance of a firm’s debt
financing decision and the uniqueness of banks and bank loans, it is important to
understand the effect of the bank relationship on financial reporting. By investigating
the effect of bank dependence on the usefulness of the income statement, this study
sheds light on the role of a firm’s financing decision in financial reporting.
It also adds to the literature examining accounting conservatism by providing
empirical evidence of a lender’s preference for accounting conservatism. In addition,
compared to prior studies that generally focus on the importance of the balance sheet,
this study focuses on a situation where the income statement plays a major role in
valuing a firm.
There are several ways to expand this study. First, this paper generally focuses
on the positive side of bank relationships. There is, however, a dark side to bank
relationships. For example, banks might earn quasi-rents from borrowers, making
the diversification of financing sources more beneficial to certain firms. Therefore,
in addition to the positive side, exploring the dark side of bank relationships might
also be important to better understand the effect of bank relationships on financial
reporting. Second, to investigate the association in an international setting will provide
us with another insight. Unlike the US, which is a capital market-centered economy,
there are many bank-centered economies such as Japan and Germany. By comparing
the two systems (bank-centered and capital market-centered), we might be able to gain
additional significant insights into the effect of the financing methods on financial
reporting in relation to international accounting standards. Finally, a more extensive
examination of accounting conservatism using large samples, different motivations,
and different measures could further our understanding of the association between
bank relationships and accounting conservatism.
APPENDIX
Sample Selection
The sample firm-year observations are selected from the DealScan database by using
the following sample selection procedure:
1. Facilities that meet the following requirements:
(1)
(2)
(3)
(3)
(4)
(13,737 firm-year observations)
The borrower (the firm) is public.
The lender is a lead lender.
The lender is a bank.
Bank share information is available from the DealScan database.
Facility-end-date is no later than December 31, 2004.
2. Among 13,737 observations from 1, facilities that meet the following requirements:
(7,890 firm-year observations)
(1) Financial data for the borrower is available from Compustat during the loan
period.
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3. Among 7,890 observations from 2, facilities that meet the following requirements:
(3,992 firm-year observations)
(1) The borrower (the firm) is a Mid-Cap company.
(2) The borrower (the firm) is a non-financial institution and non-utility
company.
The DealScan database lists each credit facility as a separate record field. Therefore,
it is possible that a single borrower may have a credit facility that is syndicated among
multiple banks or multiple facilities among multiple banks (Dahiya et al., 2003). If a
borrower has multiple bank-lead lenders, only one lead lender that has the largest share
is selected as a lead lender for the borrower. The largest lead lender for a facility is the
same for a loan period because a bank share is not changed during the loan period.
Each facility during the loan period is treated as one observation.
Note that the largest lender is selected based only on the information from the
DealScan database. Therefore, it does not mean that the largest lender has the largest
share for a borrower’s total liability. It means that the largest bank-lender has the largest
bank loan share for a specific borrower during a loan period.
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