Bank loans and corporate debt ownership: some evidence from an economy in transition.
Rajagopal, Sanjay
INTRODUCTION
Theoretical and empirical work in finance indicates that firms
weigh the costs and benefits of private debt financing, and arrive at an
optimal mix of private ("inside") and public
("arms-length") debt (e.g., Rajan, 1992; Diamond, 1993;
Houston & James, 1996; Johnson, 1997a). In particular, the evidence
suggests that, among other factors, the degree of information asymmetry and monitoring need exhibited by a firm affects the relative weights of
the two types of debt in the firm's financing structure, since
private debt tends to mitigate the adverse selection and moral hazard problems that accompany external financing.
Some of the existing models, however, single out banks rather than
other private lenders as being uniquely positioned to produce ex-ante
information and/or provide ex-post monitoring (Diamond, 1984; Fama,
1985). Several empirical studies also lend support to the argument that
banks are "special" in this regard (James 1987; Lummer &
McConnell, 1989; Hull & Moellenberndt, 1994). If bank debt is more
effective than non-bank private debt in overcoming problems of adverse
selection and moral hazard, then studies of the ownership structure of
corporate debt should distinguish between the two sources of private
financing.
While a few existing studies, notably Houston & James, 1996,
and Johnson, 1997a, 1997b, make this distinction, filing requirements
for U.S. firms--their population of interest--preclude the possibility
of measuring total bank debt. For these firms, only long-term bank debt
can directly be measured. Yet, in some models, costs to bank financing,
such as a distortion of investment incentives and suboptimal liquidation, stem from short-term bank loans (Rajan, 1992; Diamond,
1991).
The present paper contributes to the study of the ownership
structure of corporate debt by examining the cross-sectional regularity
in the use of private, bank, and non-bank private debt among Indian
firms. The available data for these firms permits the use of both
short-term and long-term bank debt in the empirical treatment of the
subject. Furthermore, the Indian context is an interesting one because
its banking sector, traditionally monopolized by the state, has seen
significant (though not complete) privatization, has acquired some
transparency, and has increasingly been exposed to market discipline.
The process of reform in India has certainly not brought its financial
system yet to the levels of competition, efficiency and relative
transparency found in developed countries (see indications of this in,
for example, the Guha-Khasnobis & Bhaduri, 2000, study). This paper
asks whether banks and other private lenders, in this state of the
country's "partial adjustment" towards a competitive
financial system, play a monitoring role similar to the one observed in
the U.S. The study's findings are potentially significant in
assessing the progress the country has said to have achieved in the
reform of its financial sector.
A final distinguishing feature of the present study is that it
incorporates information from the equity ownership structure of the
firm. Specifically, it considers the influence of banks' equity
stake in the company on the firm's preference for bank financing.
The inclusion of this variable is motivated by the Rajan, 1992, model,
in which the preference for bank debt (and bank debt maturity) is
influenced by the firm's bargaining power with the bank. A
suggested proxy for this bargaining power is the bank's equity
position in the firm, a piece of information which is unavailable for
U.S. firms. Even though the proxy used in the present study is an
approximation, its inclusion represents a useful increment in the
direction of empirically examining a hitherto untested proposition.
The paper is organized as follows. The section below reviews the
literature on the firm's private/public debt choice, and on the
special role of bank financing. The next section provides an overview of
recent financial sector reforms in India. Following that, the data and
variables used in the study are discussed, and the criteria for sample
selection described. This section also provides a discussion of the
hypothesized relationships. Next, regression results pertaining to
private, bank, and non-bank private debt usage are reported and
discussed. The final section carries the conclusions and implications of
the study, along with suggestions for further research.
BANKS, FIRM ATTRIBUTES, AND THE MIX OF LENDERS
Over the last decade, a segment of financial research has
hypothesized and documented a systematic link between firm-level
characteristics and the corporation's placement choice of debt.
Much of the work has demonstrated a unique role for lenders in the
private debt market. This special role is argued partly to stem from a
more concentrated ownership of private debt which reduces free-rider
problems and makes information production and monitoring more
economically feasible than in the case of diffusely held public debt
(Diamond, 1984; Berlin & Loeys, 1988; Diamond, 1991; Easterwood
& Kadapakkam, 1991). Typically, there is also a greater flexibility
to the renegotiation of contract terms in the case of private debt. The
superior ex-ante information among those with a private claim, and their
greater control over the borrower's investment and liquidation
decisions mitigates the problems of adverse selection and moral hazard
associated with credit generation (see, for example, Smith & Warner,
1979; Diamond, 1984; Blackwell & Kidwell, 1988; Berlin & Loeys,
1988). However, there are also costs to private debt in the form of
monitoring costs, bank regulatory taxes, premiums for reduced liquidity,
and agency costs of delegated monitoring (Zwick, 1980; Berlin &
Loeys, 1988; Diamond, 1991). The tradeoff of benefits and costs, in
turn, argues the existence of an "optimal" level of private
debt. This line of reasoning suggests that for firms with larger
information asymmetries and greater monitoring need, the benefits of
private debt will, ceteris paribus, tend to outweigh the costs of
private lender monitoring.
Several studies examine the precise factors affecting a firm's
choice of public versus private debt (e.g., Diamond, 1991; Rajan 1992;
Diamond 1993; Houston & James, 1996; Johnson 1997a; Krishnaswami et
al., 1999). The Diamond, 1991, study stresses a "reputational
capital" effect in the debt source choice, wherein larger firms,
with established reputations (at stake) are more likely to access the
public debt market since they do not need to rely now on the monitoring
role of banks. The study by Rajan, 1992, stresses possible "hold
up" problems when firms borrow from a single bank (which might have
an informational monopoly), which makes reliance on bank debt less
likely for firms with high quality projects. In contrast, in Yosha,
1995, firms with high quality projects avoid public debt so as to
conceal sensitive information and preclude competitive responses from
rivals.
Some models focus on considerations of efficiency in liquidation,
and the impact of these concerns on the choice of debt source (e.g.,
Berlin & Loeys, 1988; Berlin & Mester, 1992). These argue that
firms with projects of low liquidation value--for whom early liquidation
would therefore be onerous--will tend to avoid bank or other private
debt because they have harsher covenants than public debt; covenants are
harsher since renegotiation is easier.
Linking a firm's chance of distress to the value it places on
forestalling liquidation, Chemmanur & Fulghieri, 1994, suggest that
riskier firms will be attracted to bank financing since such debt is
more easily renegotiated; safer firms, who do not require this contract
feature, will lean towards public debt and avoid pooling. One of the
predictions of the Hoshi, Kashyap & Scharfstein, 1993, model--which
focuses on managers' investment behavior--is that firms with lower
leverage use public debt because their higher equity-at-risk constrains
inefficient investment. Greater collateral-at-risk performs a similar
bonding function, so firms with more valuable assets-in-place will
employ public debt. More assets-in-place implies a smaller potential for
asset substitution problems, and a lesser need for monitoring (Johnson,
1997a).
Easterwood & Kadapakkam, 1991, study the effect of transactions
costs and leverage-related costs on the private/public debt choice, and
find that larger firms, with their larger issue sizes, save on
transactions costs (the large "fixed" cost portion being
spread over a large issue size), and tend to lean on public debt more
than do medium-sized firms. While it is their conjecture that
information asymmetry are also likely to be important to the
private/public debt choice, they do not directly test this proposition.
Houston & James, 1996, find evidence consistent with Rajan's,
1992, "hold up" problems model, a problem mitigated by
establishing multiple-banking relationships. Johnson, 1997a, finds that
firms have a greater reliance on public debt if they face lower
information and monitoring costs. Krishnaswami et al., 1999, also find
evidence consistent with the hypothesis that younger firms, and those
with greater potential information asymmetries, will tend to rely on
private debt.
While the aforementioned information-production and monitoring
benefits are attributable to private borrowing in general, some models
single out banks as having a comparative advantage in information
gathering and ex-post monitoring (e.g., Myers, 1977; Fama, 1985). It is
argued that the deposit-taking function of banks allows them a degree of
monitoring not available to other private lenders. Banks possibly are
more efficient at screening and monitoring on account of a repeated
generation of varied loans over time.
Several studies provide empirical evidence of a special monitoring
role for banks (e.g., James, 1987; Lummer & McConnell, 1989; Slovin
& Young, 1990; Hull & Moellenberndt, 1994; Johnson, 1997a;
Johnson, 1997b). While most security offerings elicit a negative or
neutral stock market response, James, 1987 and Lummer & McConnell,
1989, show that the market reacts positively to new bank loans and
renewals of existing lending arrangements. Slovin & Young, 1990,
provide evidence that IPO under-pricing is mitigated by the use of bank
debt. Hull & Moellenberndt, 1994, find that the negative stock
market response to equity issues is more severe when the proceeds are
intended for the retirement of bank debt. Johnson, 1997a, finds that
(long-term) bank debt use and non-bank private debt use are related in
opposite ways to three firm-level attributes, namely, leverage, the
fixed asset ratio, and the market-to-book ratio. In Johnson, 1997b, bank
debt increases optimal firm leverage.
In summary, several models hypothesize cross-sectional regularities
in the mix of private and debt, and extant research documents these
patterns among U.S. firms. Information asymmetry, potential asset
substitution problems and monitoring need, concerns of inefficient
liquidation, and leverage appear to be among the factors that affect
significantly the tradeoff between the costs and benefits of privately
negotiated financing. There is also evidence that banks in particular
possess a special information-production and monitoring role, so that a
study of the ownership structure of corporate debt ought to distinguish
between bank financing and other private debt. Few studies distinguish
between bank and non-bank private debt in their empirical analysis
because of data availability issues. The couple of studies that make the
distinction must limit themselves to a study of long-term bank debt,
since total bank data is unavailable for U.S. firms. The present study
proposes
to extend the study of debt placement by incorporating total bank
debt (short-term and long-term), and by focusing on an emerging
("bank-oriented") economy, India, which has experienced
substantial financial sector reform over the last decade. The following
section describes the reform process in that country.
REFORM OF THE INDIAN FINANCIAL SECTOR
Financial sector reform has been an integral part of the new
economic policy adopted by India beginning in 1991 (see, for example,
Guha-Khasnobis & Bhaduri, 2000). This process of financial reform
has entailed, among other things, a significant reduction in the cash
reserve requirement (CRR) and the statutory liquidity ratio (SLR).
Between 1991 and 1998, for instance, the SLR declined from 38.5% to 25%,
and the CRR has declined from about 25% to 10.5% (for a more detailed
discussion of the reforms, see Ahluwalia, 1999; Beim & Calomiris,
2001; and Laeven, 2003, from which much of the discussion in this
section is adapted, and which are also the source for the data quoted
here). Thus, the proportion of incremental resources to banks (from
deposits) that was pre-empted by the government was roughly 65% prior to
the reforms; that number now stands at about 36%. Put another way, the
"tax" on financial intermediation has significantly been
reduced over the 1990s.
Interest rate controls have also been eased progressively, moving
the loan market away from a regime of subsidized rates and towards a
more rational, market-based system. Banks are relatively freer to price
loans on the basis of fund costs and credit risk. The easing of entry
restrictions to a traditionally state-controlled banking sector, which
occurred in 1993, is reflected in the fact that between 1991 and 1997,
the market share of private and foreign banks increased from roughly 11%
to approximately 18%. Another significant development has been the
introduction of capital adequacy standards for banks. Prudential norms
somewhat similar to the ones recommended by the Basle Committee were
phased in by 1996, which, in addition to lending some transparency to
the balance sheets of banks, lean on the institutions to improve asset
quality. Bank supervision has also been strengthened, with the
establishment of the Board for Financial Supervision within the Reserve
Bank of India (RBI), India's central bank. The role of internal
controls and audit, and that of external auditors have been shored up,
and the time taken for the inspection and follow-up cycle has been cut
in half.
Despite the improvements described above, though, the question
which is of particular relevance to the current paper is how the new,
reformed standards compare with international practice. As Ahluwalia,
1999, notes, the government-appointed Committee on Banking Sector
Reforms (CBSR) has reported several deficiencies with regard to the
comparability of the new Indian banking norms with international
standards. For instance, capital-to-risk-weighted-assets for banks
continue to be below international standards. Indian standards are more
lax with regard to the reclassification of "substandard" and
"doubtful" assets; a greater period of delinquency is allowed
by Indian banks before such assets are downgraded. "Directed credit
policies", which require banks to earmark 40% of their commercial
loans to "priority" sectors identified by the government,
remain in place. Significantly, the government still maintains a
majority ownership of public sector banks (which account for a
significant share of the market). This public ownership "involves
'politicization' and 'bureaucratization' of
banking" (Ahluwalia, 1999, p.44). Thus, it is quite possible that
Indian banks, despite the recent progress in liberalization, are beset by "cronyism" in loan making, and an impaired ability to
respond to commercial and customer needs (or dictates of the market).
It is this "transitional" nature of the Indian financial
sector that provides the context for the current paper, and motivates
the question as to whether the determinants of (a) the private/public
debt choice, and (b) the bank-versus-non-bank private debt choice,
identified for firms in developed economies also play a significant
explanatory role in India. For example, if banks are operating in an
environment divorced from the pressures of the market, are making credit
decisions not on the basis of a rational assessment of risk but for the
sake of political expediency, and have little incentive to monitor the
borrower, or generate information that is economically valuable to loan
making, then the role of firm attributes, such as information asymmetry,
leverage, or growth opportunities, might not be significant factors in
the Indian context, while they appear to be relevant to the
private/public debt choice among U.S. firms. Put another way, if private
lending practices are not "fair" and "economically
rational", then we are unlikely to observe economically sensible
patterns in the private/public debt choice or the use of bank financing
among Indian firms. The expected patterns in private and bank debt use
are described in the next section.
DATA, VARIABLES, METHOD, AND HYPOTHESIZED RELATIONSHIPS
The data used in this study are collected from a publicly available
database compiled by the Center for Monitoring the Indian Economy
(CMIE). This dataset provides a comprehensive coverage of firms
operating in India's industrial sector, and carries substantial
financial statement information and some market data. All the income
statement data in this study pertain to the year ending December 2002,
and all the balance sheet information is as of December 31, 2002. Market
data are averaged over the 365 days ending December 31, 2002.
In order to enter the sample, a firm had to meet the criteria
listed below. The four restrictions yield a sample of 303 firms for
Models 1, 3, and 5, and 266 firms for Models 2, 4, and 6 shown in Tables
1 and 2.
Criteria for Entry into the Sample
1. The firm is categorized as a manufacturing firm in the CMIE
dataset.
2. The firm is publicly traded.
3. The firm has public, bank, and non-bank private debt in its
capital structure.
4. There is firm-specific data available on the variables of
interest for the time period considered.
This study employs the ten variables listed below. The first three
are alternatively used as regressands, while the remaining seven enter
as explanatory variables.
Variables: Acronyms and Definition
PVTDEBT This is ratio of the firm's total private debt to the
firm's total debt outstanding. Book values are used.
This serves as the dependent variable in Models 1 and
2 below.
BANKDEBT This is ratio of the firm's total bank debt to the
firm's total debt outstanding. Book values are used.
This serves as the dependent variable in Models 3 and
4 below.
PVTNON-BANK This is ratio of the firm's total non-bank private
debt to the firm's total debt outstanding. Book values
are used. This serves as the dependent variable in
Models 5 and 6 below.
AGE Age is the number of years since the firm's
incorporation, as of the year 2002.
FAR The fixed asset ratio (FAR) is calculated as the ratio
of the firm's net fixed assets to total assets.
MB The market value-to-book ratio (MB) is the firm's the
sum of the book value of liabilities plus market
capitalization, divided by the book value of total
assets.
SD This measure of stock volatility is the standard
deviation of the firm's daily returns average over a
365-day period.
LNASS This is the natural log of the firm's total assets,
and is used as a proxy for firm size.
LEV Leverage (LEV) is calculated as the ratio of the book
value of total liabilities over the book value of
total assets.
BANKOWN This is the proportion of common stock of the firm
owned by banks.
As the criteria for sample selection indicate, this study considers
those firms that have public debt outstanding. The motivation for such a
focus lies in the fact that India is still a "bank-oriented"
economy (Aivazian et al., 2003, employ this particular term for India in
their international comparisons of dividend policy). Indian firms have
historically been dependent on state-owned banks and other private
credit for their financing, and have had little access to a
well-developed public debt market. For example, of the 900 or so
manufacturing firms for which data is available, only about 70 firms are
without bank debt in their capital structure, and almost all of these 70
firms have no public debt either. As suggested above, about 300 firms
have public debt, which means roughly 600 firms, or 67% of the total, do
not carry any public debt whatsoever. As suggested by several
theoretical models, accessibility to public debt is likely limited to
firms on the higher end of the credit quality spectrum. The question the
present study addresses is whether these firms can benefit from the
screening and monitoring role of private debt and, more specifically,
bank debt, even though they have access to public debt. In other words,
does "reputation" substitute perfectly for
"monitoring"? As in Johnson, 1997a, 1997b, the present study
uses the absence of public debt as a proxy for a lack of access to
public debt.
Three continuous variables are used alternatively as dependent
variables in OLS regressions. First, in Models 1 and 2 below, the
proportion of the firm's private debt (PVTDEBT) is regressed on
several variables suggested by earlier empirical studies of the debt
placement choice. Those variables are discussed in greater detail below.
Next, the firm's private debt is partitioned into bank debt
(BANKDEBT) and non-bank private debt (PVT NON-BANK). The former is
employed as a regressand in Models 3 and 4, while the latter is the
regressand in Models 5 and 6. The purpose of this step is to determine,
as in Johnson, 1997a, whether bank debt and other private debt differ in
their relationship with firm-specific attributes such as leverage,
information asymmetry, and growth opportunities.
The choice of the independent variables listed above is based on
the fact that in several of the studies discussed in the literature
review section, firm-specific factors such as age, size, leverage,
growth opportunities, and information asymmetry appear systematically to
affect the ownership structure of corporate debt. Johnson, 1997a, uses
"age", or the number of years since incorporation, as a proxy
for reputation to test the Diamond, 1991, hypothesis regarding the role
of reputational capital and choice of public debt. Since the
reputational capital of older firms ensures that they will avoid actions
harmful to creditors even if unmonitored (given that their reputation is
valuable and represents a large investment at risk if tarnished), it is
expected that AGE will be negatively related to the use of private debt.
Numerous studies employ the natural logarithm of a firm's
total assets (LNASS) as a proxy for information availability and/or
economies of scale in flotation costs (as found in Easterwood &
Kadapakkam, 1991). Some of the studies employing this proxy include
Krishnaswami et al.,1999, and Hadlock & James, 2002. Since size is
used as a positive measure of information availability and economies in
floatation costs, it is expected that LNASS will be negatively related
to the use of private debt.
Krishnaswami et al., 1999, employ the residual volatility in a
firm's stock returns as a proxy for information asymmetry. Hadlock
& James, 2002, argue that firms with greater stock return volatility
are more likely to possess large information asymmetry between insiders
and outsiders. The latter measure this volatility as the standard
deviation of the firm's daily stock returns. Since private
creditors are argued to possess an advantage in information production,
it is expected that there will be a positive relationship between the
volatility measure, SD, and the firm's dependence on privately
placed debt.
Several studies use the market-to-book ratio (MB) as a proxy for
the firm's growth options (e.g., Barclay & Smith, 1995;
Krishnaswami et al., 1999; Hadlock & James, 2002). Most of these
studies also recognize that growth options may be difficult to value,
and MB could therefore proxy for asymmetric information as well. To the
extent that MB is a measure of intangible assets, it could also be a
proxy for potential asset substitution problems. Given the special role
attributed to private lenders in theoretical models, it might then be
expected that MB will be positively related to the use of private debt.
However, if "hold up" problems of the kind suggested in Rajan,
1992, apply to private debt, then firms with higher growth options will
tend to avoid such debt. MB would then be negatively related to private
debt use. This negative relationship can also be predicted if MB is a
proxy for low liquidation values (as in Johnson, 1997a, for example). A
greater proportion of the value of high MB firms is derived from future
cash flows rather than assets-in-place, and they are therefore likely to
have lower liquidation value. As argued earlier, firms with projects of
low liquidation value will attempt to avoid the harsher covenants of
private debt. Given these arguments, there is no clear 'a
priori' expectation with regard to the direction of relationship
between MB and the use of private debt.
Johnson, 1997a, 1997b employs the ratio of fixed assets to total
assets (FAR) as a proxy for the assets that can be used as collateral to
reduce the asset substitution problem associated with debt. A mitigation
of this problem implies a reduced need for ex-post monitoring, which in
turn suggests that FAR should be negatively related to use of private
debt. On the other hand, FAR can also be used as a proxy measure for
project liquidation values, in which case FAR should be positively
related to the use of private debt. As such, there is no clear 'a
priori' expectation with regard to the direction of relationship
between FAR and the use of private debt.
Theory suggests that firms with lower leverage would tend to have
public debt, since the greater equity-at-risk for these firms tends to
bond managers' investment behavior (Hoshi, Kashyap &
Scharfstein, 1993). Therefore, it is expected that there will be a
positive relationship between LEV and the use of private debt. It
should, however, be noted here that including leverage directly in the
equation as an explanatory variable is problematic, because capital
structure studies have demonstrated it to be related to such factors as
firm size, asset collateral value, and growth opportunities--factors
that are also included here as explanatory variables. Along the lines of
Johnson, 1997a, therefore, the present study uses, for LEV, the
residuals from regressing leverage on the other explanatory variables,
these residuals representing the "exogenous" part of leverage.
Finally, this study includes the proportion of the firm's
equity owned by banks (BANKOWN) as an explanatory variable. This is
motivated by the Rajan, 1992, "lock-in" model, which indicates
that a firm's preference for bank debt (and bank debt maturity) is
partly a function of its bargaining position vis-a-vis the lender. A
suggested proxy for bargaining power is the bank's ownership of the
firm's equity. Given data restrictions, this study takes the total
proportion of equity owned by banks as an approximation of this
bargaining power. Rajan's model suggests that the distortion of the
owner/manager's incentives from short-term bank borrowing increases
as his/her bargaining power decreases; in this case, the firm chooses
"arms-length" debt or long-term bank debt in order to correct
the incentives for effort. Among the sample firms, bank borrowing is
predominantly short-term. Accordingly, a negative relationship between
BANKOWN and private debt use and/or bank debt use would be consistent
with the Rajan model. It should be reiterated, though, that the proxy
measure employed here is a very crude measure of the bargaining power
discussed in Rajan, 1992, and the results should therefore be
interpreted with caution; this study includes the ownership variable
merely as a first step towards empirically examining a hitherto untested
proposition. The hypothesized relationships are summarized in Exhibit 1.
PATTERN OF PRIVATE DEBT USE: REGRESSION RESULTS
This section reports the cross-sectional regularities found in the
use of private debt, bank debt, and non-bank private debt among the
sample firms. While three sets of models are therefore estimated, each
set includes two regressions--one with the BANKOWN variable, the other
without--for a total of six models. Models 1 & 2, shown in Table 1
below, pertain to the use of private debt. The relationships for the two
components of private debt, namely, "bank" and
"non-bank" private financing, are seen in Models 3 through
Model 6, reported in Table 2.
As can be seen in Table 1, four of the six variables in the private
debt equation (Model 1) are significant, and possess the hypothesized
directions of relationship with private debt use. Firms with greater
information asymmetry (as reflected in smaller asset size, LNASS, and
larger volatility of stock returns, SD) appear to depend more on private
debt. More levered firms (those with higher values of LEV) depend more
on private debt (and therefore less on public debt), which is consistent
with the notion that in high leverage firms, the lower equity-at-risk
distorts investment incentives, and such firms will require monitoring.
The negative coefficient for MB is consistent with the idea that firms
with more valuable growth opportunities (or those with lower liquidation
values), try to stave off bank hold-up problems (or avoid inefficient
liquidation). Neither AGE nor FAR is significantly related to the degree
of private debt use among the sample firms. Model 2, which differs only
in its inclusion of BANKOWN, shows qualitatively similar results. In
addition, the estimated equation indicates that there is no significant
relationship between a firm's dependence on private debt and the
proportion of its equity that is owned by banks.
Table 2 reveals clear differences in the pattern of bank and
non-bank private debt use. No factor has a common influence on the two
types of debt. AGE, FAR, and BANKOWN appear now as significant factors
(albeit AGE marginally so in Model 5), but with opposite signs in the
two sets of equations. LNASS and MB are significant in the
"bank" equation, but not in the "non-bank" equation.
SD and LEV are significant in the "non-bank" equation, but not
in the "bank" equation.
It might have been argued that the positive (negative) sign for AGE
in the bank (non-bank) equation is consistent with the "reputation
building" process in Diamond, 1991, were it not for the fact that
the sample firms have access to public debt, suggesting that they
already possess "reputational capital". Thus, the estimated
relationship for AGE is puzzling.
One measure of information asymmetry (LNASS) plays a significant
role in the "bank" equation, while the other measure (SD)
possesses explanatory power in the "non-bank" equation. If
larger firms have economies in public debt issuance, then flotation cost considerations, rather than information asymmetry, may explain the
negative effect of LNASS in the "private" and "bank"
equations. Taken in this light, the positive influence of AGE and the
insignificant coefficient for SD in the "bank" equation hint
at a rule-bound banking system that plays no appreciable role in the
mitigation of the adverse selection problem. The continuation of
government-mandated "directed credit" policies could explain
this observed relationship.
The "hold-up" problems associated with bank information
monopolies in Rajan, 1992, are linked both to bank debt maturity and to
the number of lending banks, factors not explicitly accounted for in the
present study. Therefore, the significantly negative coefficient for MB
in the "bank" equation is more safely interpreted as
reflecting the strategy by firms with high MB ratios to avoid
inefficient liquidation. An implication of this argument is that bank
debt covenants, rather than simply "private debt" covenants,
tend to be harsh and more likely to force early liquidation.
The negative effect of FAR in the "bank" equation
suggests that firms with potentially greater asset substitution problems
(i.e. those with a smaller FAR) will lean more heavily on bank
financing. According to this interpretation, banks play a useful ex-post
monitoring role. However, LEV is not significant in the "bank"
equation, whereas it is significantly positive in the
"non-bank" model. The latter result indicates that firms with
less collateral-at-risk, who had been seen in Models 1 and 2 to depend
on private debt, specifically rely on "non-bank" private debt.
This points to a monitoring role for non-bank private debt as well.
Finally, a greater control by lending banks, as approximated by larger
values for BANKOWN, seems to induce firms to lean more towards non-bank
private debt, and less towards bank financing. There is, therefore, at
least prima facie evidence that the ownership structure of
equity--especially with respect to banks' claims--has a bearing on
the ownership structure of corporate debt. Since bank debt in the sample
is predominantly short-term, the reported results are consistent with
Rajan, 1992, though more detailed research is required before a
definitive statement can be made in this regard.
CONCLUSIONS AND IMPLICATIONS
One of the contributions of the present study is that it documents
the existence of cross-sectional regularities in the degree of private
versus public debt use in an emerging economy. Information asymmetry,
asset substitution problems, concerns of inefficient liquidation, and
bonding of managerial investment behavior, appear to affect the
private/public debt mix in the firm's debt structure. Specifically,
firms with greater information asymmetry, larger liquidation values,
smaller fixed assets ratios, and higher leverage make greater use of
private debt. A separate analysis of bank debt use suggests that Indian
banks play a greater role in combating moral hazard via ex-post
monitoring and control than in mitigating the adverse selection problem
via information production ex-ante. Proxies for potential asset
substitution problems tend to be significant in the "bank
debt" equation, but proxies for information asymmetry appear
significant in the "non-bank debt" equation. As mentioned
earlier, state intervention, such as mandatory directed credit policies,
could account for the unexpected results relating to the proxies for
information asymmetry.
The fact that the estimated models reveal meaningful and
significant patterns in corporate debt does indicate that the Indian
firm attempts--and the institutions in India at least partially allow--a
process of economic optimization anticipated by mainstream finance
theory. Nevertheless, the findings reported above point to the need for
a continued reform of the Indian banking sector. Also, this paper makes
a first attempt at empirically examining hitherto untested propositions
of the link between bank control and corporate preferences for bank
financing. It documents a significantly negative effect of bank
ownership on a firm's dependence on bank debt. The study also
demonstrates that vastly different relationships can exist between firm
characteristics and the use of "bank" debt on the one hand,
and "non-bank" private debt on the other. Existing models do
not predict all the differences in the relationships for bank and
non-bank private debt observed in this and previous studies (such as in
Johnson, 1997a). It would be fruitful for future empirical, and, more
importantly, theoretical research on the structure of corporate
borrowing to distinguish between the different sources of private debt.
Subject to the availability of data, future research should also
partition bank debt into its short-term and long-term components in an
attempt to test existing hypotheses with regard to the maturity
preference of bank debt.
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Sanjay Rajagopal, Montreat College
Table 1: Regression Models for Private Debt
Variable Model 1 Model 2
Intercept 0.9640 *** 0.9200 ***
Age 0.0003 0.0003
LNASS -0.0204 ** -0.0195 **
SD 0.0132 *** 0.0183 ***
Mkt/Bk -0.1851 *** -0.1796 ***
FAR 0.0554 0.0697
LEV 0.4164 *** 0.3863 ***
Bankown -- 0.0001
N 303 266
F 18.34 *** 15.27 ***
Adj. R-Sq. 0.26 0.27
Each cell shows the estimated coefficient.
LEV is the residual from the regression of leverage on the other
explanatory variables.
*** significant at the .01 level
** significant at the 0.05 level
* significant at the 0.10 level.
Table 2: Regression Models for Bank Debt (Models 3 & 4) and Non-Bank
Private Debt (Models 5 & 6)
Variable Model 3 Model 4 Model 5 Model 6
Intercept 0.7917 *** 0.7274 *** 0.1722 ** 0.1927 **
Age 0.0012 ** 0.0014 ** -0.0009 -0.0011 **
LNASS -0.0220 ** -0.0152 0.0016 -0.0044
SD 0.0011 0.006 0.0121 ** 0.0123 **
Mkt/Bk -0.1784 *** -0.1760 *** -0.0067 -0.0036
FAR -0.3098 *** -0.2656 *** 0.3652 *** 0.3353 ***
LEV -0.0285 -0.0697 0.4449 *** 0.4559 ***
Bankown -- -0.0030 ** -- 0.0032 **
N 303 266 303 266
F 10.37 *** 8.72 *** 15.20 *** 12.05 ***
Adj. R-Sq. 0.16 0.17 0.22 0.23
Each cell shows the estimated coefficient.
LEV is the residual from the regression of leverage on the other
explanatory variables.
*** significant at the .01 level
** significant at the 0.05 level
* significant at the 0.10 level.
Exhibit 1
Variables: Hypothesized Direction of Relationship with Private Debt
Variable Hypothesized Influence on Proportion of Private Debt
AGE Negative
LNASS Negative
SD Positive
MB ?
FAR ?
LEV Positive
BANKOWN Negative