Trade Credit and the Speed of Leverage Adjustment Journal: Management Decision Manuscript ID MD-04-2019-0530 Manuscript Type: Original Article… [623009]

Management Decision
Trade Credit and the Speed of Leverage Adjustment
Journal: Management Decision
Manuscript ID MD-04-2019-0530
Manuscript Type: Original Article
Keywords: Trade Credit, Capital structure, Short term loans, Speed of Adjustment

Management Decision

Management DecisionABSTRACT:
This paper examines the impact of trade credit on the speed of adjustment of short-term leverage.
Bankruptcy cost is higher for over-levered firms, generating a good incentive to use trade credit as a
lower cost substitute; hence, firms adjust capital more quickly.
Firm-level data is used from five countries, in two different economic orientations, during the period
2000–2017: bank-oriented economies include France, Germany, and Japan, and market-oriented
economies include the United Kingdom and the United States. First, using the two-step GMM the
study estimates the target short-term leverage ratio. Then it examines the impact of trade credit on
the speed of adjustment of the actual leverage toward the target leverage ratio.
It finds a positive impact of a low amount of trade credit (high capacity) on the speed of adjustment
for over-levered firms. This is in line with the substitution effect, where the bankruptcy cost is higher
for over-levered firms, which leads them to substitute bank loans with trade credit.
The study uses data from publicly traded firms; data from non-listed and small firms may be
considered as a good opportunity for future research.
The policy implication that can be derived from the empirical results is that firms’ management
should recognise the relationship between trade credit and deviation from target short-term
leverage. During periods of high short-term leverage firms should use trade credit as a source of
finance when adjusting the short-term leverage toward the target ratio.
CUST_SOCIAL_IMPLICATIONS_(LIMIT_100_WORDS) :No data available.
This study is the first to examine the influence of trade credit on the speed of adjustmentPage 1 of 22 Management Decision
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Management DecisionTrade Credit and the Speed of Leverage Adjustment
JEL Classifications Numbers:
G31
G32
P34
Keywords:
Trade Credit
Capital structure
Short term loans
Speed of Adjustment
SubstitutePage 2 of 22 Management Decision
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Management Decision1. Introduction
Decades after the seminal work of Modigliani andMiller (1958) – the “irrelevance theory of
capital structure” – several theoretical models and empirical studies attempt to answer what
determinesa firm’s debt ratio. The trade-off theory (Myers, 1984; Flannery andRangan, 2006)
postulates that firms have an optimal capital structure, where the firmsbalance the benefits of
additional dollars of debt, such as the tax shield and avoiding the free cash flow problem,
with the cost of debt, such as the distress cost (bankruptcy cost). According to the trade-off
theory firms set a target debt ratio and move toward this target ratio. The alternative point of
view, the pecking order theory, assumes that firms do not have a target debtratio andis based
on the asymmetric information problem; thus, firms use internal funds followed by debt, and
equity is the last choice for financing. A large body of literature examines the factors that
affect capital structure decisions (Titman andWessels, 1988; Rajan andZingales, 1995; Fama
andFrench, 2002; Chen, 2004; Bancel andMittoo, 2004; Booth, Aivazian, Demirguc‐Kunt,
andMaksimovic, 2001; Faulkender andPetersen, 2005; Wald, 1999; Frank andGoyal, 2009;
Céspedes, González, andMolina, 2010). The literature shifts toward the question of whether
firms have a target ratio and how fast firms move toward this target (Barclay andSmith Jr,
1999; Hovakimian, Opler, andTitman, 2001; Ozkan, 2001; Chen, 2004; Flannery andRangan,
2006; Antoniou, Guney, andPaudyal, 2008; Titman andTsyplakov, 2007; Huang andRitter,
2009). In recent years, the focus of the capital structure choice has shifted further toward
whichfactors influence the speed of adjustment (SOA) toward the target debt ratio (Byoun,
2008; Faulkender, Flannery, Hankins, andSmith, 2012; Mukherjee andWang, 2013; Lockhart,
2014; Fier, McCullough, andCarson, 2013; Dang, Kim, andShin, 2014; Liao, Mukherjee,
andWang, 2015; Nadarajah, Ali, Liu, andHuang, 2018; Brisker andWang, 2017; Li, Wu, Xu,
andTang, 2017; Fitzgerald andRyan, 2018; He andKyaw, 2018; Dufour, Luu, andTeller,
2018; Kang, Wang, andXiao, 2018). The speed of adjustment depends on the adjustment
cost; thus, firms balance between the cost of being off target and the cost of moving toward
the target. Thus, under-levered firms lose the benefits from tax shields, whereas over-levered
firms suffer from the bankruptcy cost. If there are no adjustment costs, the target and actual
leverageratio should be the same. So far, studies of the impact of adjustment costs on a firm’s
speed of adjustment have used a proxy as an instrument to account for adjustment costs,
whereby they assume these proxies can affect the cost of speed of adjustment differently for
over-levered and under-levered firms. For example, internal cash flow has alow marginal cost Page 3 of 22 Management Decision
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Management Decisionof leverage adjustment;Byoun, (2008) finds that above-target (below-target) firms move more
quickly toward their target when they face financial surplus(deficit). Consistentwith this
argument Faulkender et al. (2012), who extend the work of Byoun, find that the adjustment
cost is affected by large operating cash flow realisations, where firms with a large amount of
cash flow realisationadjust their deviated capital toward target more quickly. Dufour et al.
(2018), however,find that the cash flow affects the speed of adjustment of short-term leverage
for SMEs, but not long-term speed of adjustment.Mukherjee andWang (2013) conclude that
the asymmetry of adjustment speed, where distance from the target leverage affects the speed
of adjustment; they find that over-levered firms more quickly adjust the deviated leverage
than under-levered firms becausethe cost of not adjusting increaseswith increasing rate for
over-levered firms. They also find that the fixed cost of not adjusting may make the firm
offtarget if the deviation from target is small, which is consistent with the findings of Welch
(2004).Tax shields make debt attractive as a funding source; thus, most of the literature
argues that the motivation of firms adjusting their capital structure is balancing between the
cost and benefits of debt.
Short-term loans are mainly used to finance the deficit of short-term investment (for example,
inventory purchase, inventory, and cash).The short-term bank cost is not the same for all debt
levels; the probability of distress increases as bank loans increase. Thus, banks increase the
interest rates and impose terms that affect a firm’s financial flexibility. Therefore, the cost of
bankruptcy is greater than the cost of moving toward the target ratio; firms with a high level
of debt find it better to reduce the debt and move toward target. In this case, due to the high
cost of debt, firms should use a good substituteto finance a short-term deficit.One of the
available alternative sources of finance is trade credit . Trade credit is a loan that a supplier
provides to its customers in conjunction with product(Nilsen, 2002). Many firms use trade
credit beside bank loans (Wilner, 2000).Trade credit is considered a costly source of
finance.The cost of trade credit is higher than the cost of bank loans if the firm pays after the
discount period. For example, ‘2/10 net 30’ means the firm will earn 2% discount if it pays
within 10 days an invoice which is due in 30 days; this is equal to 44% annualised(Smith,
1987).Thus, the question is when should firms start to consider trade credit as a good
substitute for a bank loan? This study postulates that the bankruptcy cost for over-levered
firms is high and the availability of trade credit will lower the adjustment cost, and the speed
of adjustment will be higher because firms will replace bank loans with trade credit. Thus,
trade credit will have the substitution effect, sincethe adjustment cost that is embodied in Page 4 of 22 Management Decision
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Management Decisionusing trade credit is lower than the bankruptcy cost associated withbank loans for over-
levered firms. Therefore, the availability of trade credit for over-levered firms will induce a
faster speed of adjustment.
This paper examines the impact of trade credit on the leverage speed of adjustment. Thus, it
examines whether trade credit is a substitute for short-term leverage. The results indicate that
over-levered firms find it is better to move toward their target leverage by replacing leverage
with trade credit. This paper postulates that for over-levered firms the bankruptcy cost is
high, which makes the cost of trade credit lower than leverage.
This paper makes a number of contributions. First, it attempts to extend the empirical work of
the capital structure literature and provide more evidence of the trade-off theory, especially
for short-term leverage using data from market-oriented and bank-oriented economies.
Second, it also findsevidenceofthe role of trade credit as a financing source. Third, it finds
evidence consistent with the substitution hypothesis of trade credit, where trade credit is used
when marginal bankruptcy cost for over-levered firms generates good incentive for firms to
shift toward using trade credit. Fourth, it finds evidence of the impact of trade credit on the
leverage speed of adjustment using data from bank-based countries and market-based
countries. This is the first research that examines the moderating effect of trade credit on the
leverage speed of adjustment toward a target ratio.
This paper is organised as follows. Section 2 discusses the impact of trade credit on the
leverage speed of adjustment and proposes the hypothesis.Section 3 discusses the
econometric methods, describes the data, and provides the descriptive statistics. Section 4
reports and interprets the empirical results. Finally, Section 5 concludes.
2. Does the availability of trade credit influence the leverage speed of adjustment?
The aim of receiving trade credit from a supplier is to finance working capital needs at a
lower cost. Trade credit has very low cost compared with bank loans. However, the cost of
trade credit is dependent on the agreement terms with suppliers; if the firm pays within the
discount period the cost of trade credit will be lower than bank loans, but if the payment is
madeafter the discount period the cost of trade credit will be high. Thus, if the firm can pay
within the discount period and take advantage of the discount, the trade credit can be
considered a complement to a bank loan because it has lower cost than bank loans. When the Page 5 of 22 Management Decision
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Management Decisionfirm faces a cash deficit and bank loans are not available, firms may not pay the trade credit
within the discount period, and hencetrade credit is then considered as an expensive cost of
financing and can be viewed as a substitute to bank loans. Cash surplus occurs if a trade
credit lender gives the firm more time to repay accounts payable than the time required for
collecting accounts receivable from selling inventory. On other hand, when firms haveavery
low levelof accounts payable compared to investment in accounts receivable and inventory,
the firm facesa short-term deficit; thus, bank loans and lines of credit are used to cover this
deficit.
There is agrowing empirical and theoretical literature that examines the relationship between
bank loans and trade credit. However, there is no agreement on this relationship. Trade credit
can be used as a substitutefor bank loans if the firm is denied to access to bank loans
(Engemann, Eck, andSchnitzer, 2014).Similarly,Nilsen (2002) finds that small and large
firms without access to the bond market use trade credit as a substitute for bank loans.
Recently, during the financial crisis, when there was a shortage of short-term bank loans,trade
creditwas used as a good substitute.(Coulibaly, Sapriza, andZlate, 2013; Casey andO’Toole,
2014; Carbó‐Valverde, Rodríguez‐Fernández, andUdell, 2016; McGuinness andHogan, 2016;
McGuinness, Hogan, andPowell, 2018). Also,Love, Preve, andSarria-Allende (2007)find that
firms increased the use of trade credit immediately after the financial crisis.Levine, Lin,
andXie (2018) find that trade credit was cushioning firms’ profit and employment during the
financial crisis since it can be used as a good substitute forbank loans. The substitution effect
can be also found during periods of monetary contraction, where firms use trade credit to
overcome government restrictionsonbank loans (Bastos andPindado, 2013; Blasio, 2005).
Based on survey data for U.S. firms,Danielson andScott (2004) find that firms use trade
credit if banks deny them the appropriate amount of funds to finance working capital needs,
which supports the substitution effect of trade credit.
2.1 Hypotheses
The previous studiesgenerally examine the usage of trade credit when bank loans are
restricted but do not, however,examinehow trade credit affectsthe leverage speed of
adjustment toward target.This study differs from the literature above-mentioned in that it
emphasises the importance of trade credit as a substitute that affects the adjustment speed.
The adjustment toward the target leverage ratio occurs if the adjustment cost is lower than the
cost of not adjusting. Mukherjee andWang (2013) show that for over-levered firms the rate of Page 6 of 22 Management Decision
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Management Decisionbankruptcy cost risesfaster than therate of the benefits tax shield as the leverage deviatesfrom
the target;thus, the cost of not adjusting, increases with deviation.
According to the substitution effect firms use bank loans first, and then trade credit is used to
cover the deficit occurring due tothe difficulty of accessing bank loans. The substitution
effect means that firms have to choose between two sources of funds;thus, it means that firms
choose trade credit to replace bank loans.
The testof the current paper is based on the leverage speed of adjustment model, the
rationaleof which isas follows: adjustment toward a target leverage ratio can be asymmetric,
where firms give different weights to the same amount of positive or negative deviation of
the actual leverage from the target. Firms with above-target leverage would suffer from high
marginal bankruptcy cost, thusmaking the firm reduce leverage and move quickly toward its
target ratio, which can be done by substituting bank loans with trade credit. Thus, over-
levered firms with a low amount of trade credit have the capacity to use trade credit, because
the cost of not adjusting may exceed the cost of trade credit. It is expected that firms with a
low amount of trade credit have a low implicit financial cost. The marginal bankruptcy cost
for firms belowtarget debt is lower than the marginal cost forover-levered firms. Thus,
below-target firms may not consider trade credit a goodsubstitute for a bank loan; thus, the
speed of adjustment toward target would be lower than for over-target firms. Hence, in
accordance with the substitution effect hypothesesit is expected that the speed of adjustment
relates to the availability of trade credit. Thus, the substitution effect means that:
H1a. For an over-levered firm, the speed of leverage adjustment toward target should be
quicker for firms with a low amount of trade credit;a significant result would support the
substitution effect of trade credit.
H1b. For an under-levered firm, the speed of leverage adjustment toward target should be
slower for firms with low trade credit;a significant result would support the substitution
effect of trade credit.
3. Method and data:
3.1 The model
This study uses the partial adjustment leverage model, which is based on the trade-off theory,
where firms set their target leverage ratio and move toward this ratio by a trade-off between
the cost of being deviated from the target and the cost of moving toward the target. Following Page 7 of 22 Management Decision
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Management Decisionthe literature (Flannery andRangan, 2006; Huang andRitter, 2009; Faulkender et al., 2012;
Warr, Elliott, Koëter-Kant, andÖztekin, 2012; Fier et al., 2013), a two-step analysis
procedure is adopted. The first step is to find the target leverage ratio Lev*.This target is
dependenton some firm-specific variables, thus Lev* is the predicted value from the
restriction that:
Lev*=βX i,t-1 (1)
Lev i,t=У βX i,t-1+(1-У) Lev i,t+εi,t (2)
Thus, Eq. (2) is estimated first to obtain the β coefficient, then the target leverage Lev* is
calculated as in Eq. (1).X is a standard set of firm’s characteristics that are assumed in the
previous literature toaffect the firm’s leverage ratio, similar to those used byFama andFrench
(2002), Ozkan (2001), Frank andGoyal (2009), Faulkender et al. (2012), Li et al. (2017),and
Liao et al. (2015). Specifically,large firms have more leverage because the asymmetric
information is low and more diversified; thus, they have more favourable interest rates. The
Tobin’s Q measures the opportunity investment for firms. Firms with a high investment
opportunity require more debt. On other hand, Myers (1984), and Titman andWessels
(1988)postulate that firms in growing industries expect to have higherbankruptcy cost which
lowersthe leverage ratio. The assets tangibility measures the ability of the firm to offer
valuable collateral for banks, whichincreases the ability of the firm to raise debt (Antoniou et
al., 2008). Profitability affects the firm’s leverage; according to pecking order theory, firms
use internal funds followed by external funds, thus profitable firms are expected to have a
lower leverage ratio because they use their retained earnings. Ind_Median controls for
industry characteristics that other firm-specific factors cannot control (Flannery andRangan,
2006).
The second step of analysis is to find the deviation from the target leverage ratio. The
leverage adjustment model assumes that a firm starts with a leverage ratio that has deviated
from the target and moves partially toward this target as follows:
Lev i,t- Lev i,t-1 = λ(Lev* i,t- Lev i,t-1)+ ε i,t (3)
Lev* i,t- Lev i,t-1represents the leverage deviation, andλis the annual speed of adjustment to that
target. Eq. (2) can be calculated using Ordinary Least Squares (OLS); however, it yields
biased estimates because it cannot control for the invariant firm-specific effect. The fixed-
effect estimator would also be biased and give inconsistent estimates because the lagged Page 8 of 22 Management Decision
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Management Decisionvalue of the dependent variables is correlated with the error term. Thus, the two-step GMM
estimator proposed by Blundell andBond (1998) is used. This estimator overcomes the
endogeneity problem between the independent variable and the dependent variables;thetime-
specificeffect is included inthe model to capture economy-wide factors that affect all firms in
a specific year. This methodology is widely used inrelated literature(Flannery andHankins,
2013; Lockhart, 2014; Li et al., 2017).
In order to examine the impact of trade credit on the leverage speed of adjustment, firms are
categorised into low trade credit firms and high trade credit firms, where firms with a trade
credit below the industry-year median are considered as low trade credit firms and firms with
an above industry-year median are considered as high trade credit firms. Thus, Eq. (4) is used
to measure the impact of trade credit on the leverage speed of adjustment:
∆Lev i,t=α0+β1LevDev i,+β2 LevDev i,t × TCDummy i,t+εi,t (4)
∆Lev i,tis the difference between the current and last year’s leverage ratio(Lev i,t-Lev i,t-1)and
LevDev is the leverage gap between the target leverage ratio and the actual leverage ratio
(Lev* i,t- Lev i,t-1). TCLDummy is a dummy variable which equals one if the firm is located in
the low trade credit category (and zero otherwise).TCHDummy is a dummy variable which
equals one if the firm is located in the high trade credit category (and zero otherwise).
3.2 Data and variables
This paper uses firm-level annual data covering five major economies of the world: France,
Germany, Japan, the U.K., and the U.S. The sample contains solelynon-financial firms,
publicly trading in the Stock Exchange Market of the sample countries. Due to the
availability of data, the sample period is from 2000 to 2017. Since the System-
GMMestimator for dynamic panel modelis used each firm should have at least five
consecutive annual observations. Financial data was extracted from the Osiris Database,
which was developed by Bureau Van Dijk. Also, firms with an abnormal financial ratio are
excluded, such as firms with a leverage to assets ratio of higher than one, or firms with
negative total assets. The final sample includes 6,862 firms (390 French, 405 German,
2,591Japanese, 700 U.K., and 2,776 U.S.) with 63,391firm-year observations (3,792French,
3,630German, 28,235Japanese, 5,804 U.K., and 21,930 U.S.). The sample’s summary
statistics are reported in Table 1, the firm characteristics that are used as a proxy to estimate Page 9 of 22 Management Decision
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Management Decisionthe target leverage ratio.LevShort is the short-term leverage ratio, i.e. short-term financial
loans to total assets. SIZE is the logarithm of total assets. PROF is the firm’s profitability
measured by earnings before interest and tax to total assets. TANG is total fixed assets (land,
buildings, property, plant andequipment, and other tangible assets) to total assets. DEP is
depreciation expenses to total assets. Q is the Tobin’s Q calculated as the sum of market
value of equity and book value of total liability to book value of total assets, andis a proxy for
the firm's investment opportunity. Ind_Median is the industry leverage, calculated as the
industry-year median leverage.Industry classifications are based on NAICS 2017 Primary
Codes: Agriculture, Forestry, Fishing and Hunting; Mining, Quarrying, and Oil and Gas
Extraction; Utilities; Construction; Manufacturing; Wholesale Trade;Retail
Trade;Transportation and Warehousing;Information; Educational Services; Health Care and
Social Assistance; Arts, Entertainment, and Recreation; Accommodation and Food
Services;and Other Services (except Public Administration). TCLDummy is a dummy variable
that equals one if the firm is located in the low trade credit category (and zero otherwise).
TCHDummy is a dummy variable that equals one if the firm is located in the high trade credit
category (and zero otherwise). Accounts payable is a measure of trade credit, thus ACCPAY
is accounts payable divided by total assets.
4. Results
4.1 Descriptive statistics
Table 1 presents the descriptive statistics for the sample. On average the highest short-term
leverage ratio is for U.S. firms (20.5%), followed by Japan (8.2%), Germany (6.5%),
theU.K.(5.5%),and France (5.4%). Frenchfirms have the highest accounts payable ratio
(15.1%), followed byJapanese firms (14.3%), U.K.and German firms (10.9% and9.7%
respectively), and the lowest ratio is for U.S. firms (8.5%).
(Insert Table 1 here)
4.2 Empirical results
The results in Table 2 show the determinants of the target short-term leverage ratio using the
two-step GMM estimation.Arellano and Bond (1991) postulate that the coefficient estimates
are only consistent if there is first order serial correlation AR(1) but not second order serial
correlation inthe differenced residuals. The results from the AR(1) test show that there is first Page 10 of 22 Management Decision
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Management Decisionorder serial correlation, where the p-value is lower than the conventional level. For the null
hypothesis, confirming no second order serial correlationin the residuals, the p-value is higher
than the conventional level. The J-test is over-identifying restrictionsfor the validity of
instruments.The results show that the instruments used in the two-step GMM estimations are
not correlated with the error term; hence, the instruments are valid.
The results are consistent with the previous literature. In the same table, one lagged leverage
ratio is positive and significant in all of the sample countries. This positive relationship
indicates that the firms have a target leverage ratio and move toward this target. These results
are consistent with the findings of Ozkan, (2001), Flannery andRangan (2006), and Antoniou
et al. (2008). The speed of adjustment is different between countries; the quickest is the U.K.
with an annual speed of 67.3%, followed by France with 58%, then Germany with 52.7%, the
U.S.with 45.7%, and the lowest is Japan with 19.7%. The results show that firms tradeoff
between the cost of adjustment toward the target and being off target; therefore, the need for
finding the factors that affect the speed of adjustment is important.
(Insert Table 2 here)
4.3 Trade credit and speed of adjustment
After estimating the target leverage ratio using Eq. (1), the difference is calculated and Eq.
(4) is used. The results are based on the fixed-effect estimator removing the firm-specific
effect.Sample firms were divided into two groups: over-levered firms and under-levered
firms. Over-levered firms are those that have actual leverage over the predicted target
leverage, and under-levered firms are those that have actual leverage under the predicted
target leverage. According to the trade-off theory, the bankruptcy cost is asymmetric, where
the bankruptcy cost is higher for over-levered firms than that for under-levered firms.
Therefore, firms may find the bankruptcy cost exceeds the tax shield benefits. Hence, firms
start to search for other sources of financing, and trade credit may be a good source of
financing. Therefore, over-levered firms with low amounts of trade credit tend to replace
bank loans with trade credit and adjust quickly toward the target leverage (H1a),the
substitution effect.In addition, under-levered firms with low amounts of trade credit move
more slowly toward the target leverage ratio than over-levered firms. Table 3 reports the
results from estimating Eq. (4), for over-leveredfirms for each country. The variable of Page 11 of 22 Management Decision
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Management Decisioninterest is the interaction term, (LevDev × TCLDummy), where LevDev is the measure of the
speed of adjustment and TCLDummy is a dummy variable equal to oneif the firm has trade
credit lower the median of industry-year trade credit, orzero otherwise. Thus, the variable of
interest (LevDev × TCLDummy) measures the extent to which lower trade credit usage
influences the SOA of short-term leverage.The results for U.K., U.S., Japanese, and
Frenchsamplesare consistent with the view of the substitution effect of trade credit (H1a);
specifically, columns 1,2,3, and 5 of Table 3 show that the coefficient on (LevDev ×
TCLDummy) is positive and statistically significant at the 1% level (it is 13.6%, 20.7%,
45.8%, and 54.4% for the U.K., the U.S., Japan, and France respectively). Thus, the speed of
adjustment for over-levered firms is affected by the low amount of trade credit. This means
that over-levered firms use trade credit to reduce the dependency on costly short-term loans.
The results for Germany show an insignificant effect of low trade credit on SOA for over-
levered firms.In addition, it was examined whether the low amount of trade credit affected
the SOA for over-levered and under-levered firms differently; the impact of trade credit on
under-levered firms was examined, and whether the coefficients are statistically different
between the two samples (H1b).The results show that the estimated coefficient of
(TCLDummy× ∆target) for over-levered firms is higher than for under-levered firms; for
France, theU.K., andthe U.S. the difference is statistically different at a conventional level(T-
statistics is statistically significant at the 1% level). However, Japanese firms show that the
impact of trade credit on SOA for under-levered firms is higher than that for over-levered
firms, which means that the Japanese under-levered firms move toward the target leverage
ratio and use more bank loans even though trade credit is available tothem, . The results
support the substitution effect of trade credit for debt as proposed by Carbó‐Valverde et al.
(2016), Casey andO’Toole (2014), McGuinness andHogan (2016), McGuinness et al. (2018),
and Nilsen (2002).
(Insert Table 3here)
According to trade-off theory the marginal bankruptcy cost of debt for under-levered firms is
lower than the benefit from the tax shield; hence, firms use leverage more in their capital
structure. One can expect firms to depend on leverage more than using trade credit because
the latter is considered a costly source of financing.The substitution effect is also measured
by examining the impact of using a large amount of trade credit on SOA for under-levered
firms. The results in Table 4 show that the SOA for under-levered firms with large usage of Page 12 of 22 Management Decision
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Management Decisiontrade credit is positive and statistically significant at a conventional level; the coefficient for
(LevDev × TCHDummy) is 4.3%, 23.1%,33.1%,and 23.6%for France, Germany, the U.K.,
and the U.S. respectively. The results show that firms with a higher usage of trade credit find
it better for them to use debt and move quickly toward their target leverage ratio.
Furthermore, no conclusive results were found that the trade credit effect on the speed of
adjustment is different between the bank-based and market-based countries.
(Insert Table 4 here)
5. Conclusions
The relationship between trade credit and the deviation from targetleverage has not, to
myknowledge, been examined in the previous literature. Data from five large
industrialmarket-oriented economies (U.K. and U.S.) and bank-oriented economies (France,
Germany, and Japan) allowed an examination of the impact of trade credit on the speed of
adjustment. Short-term leverage represents a large portion of firm leverage; trade credit also
represents a large portion of current liabilities and is considered a substitute for short-term
leverage. This study offers empirical evidence thatfirms consider trade credit as a substitute
for short-term leverage. The results show that firms have a short-term target leverage ratio
and move toward this target. Furthermore, the results suggest that firms with leverage above
the target ratio (over-levered firms) should consider trade credit a good substitute fora bank
loan only if the amount of trade credit is low. These findings indicate the importance of trade
credit on the speed of adjustment toward the target leverage ratio.The policy implication that
can be derived from the empirical results is that firms’ management should recognise the
relationship between trade credit and deviation from target short-term leverage. During
periods of high short-term leverage firms should use trade credit as a source of finance when
adjusting the short-term leverage toward the target ratio. The importance of trade credit on
short-term leverage for small businesses is a promising area of future research. Page 13 of 22 Management Decision
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Management DecisionReferences:
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Management DecisionTable 1 Descriptive summary statistics
Variable LevShort PROF SIZE TANG DEP Q Ind_Median ACCPAY
France
Mean 0.054 0.021 12.637 0.203 0.045 2.827 0.027 0.151
S.D. 0.076 0.179 2.462 0.176 0.053 3.932 0.017 0.099
Median 0.023 0.051 12.263 0.158 0.035 0.743 0.026 0.130
Germany
Mean 0.065 0.031 12.380 0.246 0.056 1.040 0.034 0.097
S.D. 0.094 0.198 2.488 0.200 0.059 1.978 0.023 0.087
Median 0.031 0.054 12.087 0.209 0.043 0.614 0.026 0.072
Japan
Mean 0.082 0.035 17.836 0.323 0.037 0.562 0.045 0.143
S.D. 0.091 0.064 1.661 0.176 0.030 0.691 0.021 0.108
Median 0.053 0.034 17.648 0.305 0.032 0.393 0.039 0.120
U.K.
Mean 0.056 0.003 12.125 0.277 0.053 27.23 0.025 0.109
S.D. 0.092 0.337 2.564 0.245 0.066 43.57 0.010 0.102
Median 0.024 0.061 11.957 0.212 0.039 1.141 0.025 0.083
U.S.
Mean 0.205 -0.067 12.868 0.295 0.056 31.92 0.177 0.085
S.D. 0.185 0.539 2.739 0.237 0.068 45.58 0.080 0.097
Median 0.176 0.054 13.133 0.223 0.039 1.436 0.149 0.058
This table shows descriptive summary statistics. The sample consists of 65,401 firm-year
observations that cover the period 2000–2017. LevShort is short-term financial loans to total
assets. SIZE is the logarithm of total assets. PROF is the firm’s profitability measured by
earnings before interest and tax to total assets. TANG is total fixed assets (land, buildings,
property, plant and equipment, and other tangible assets) to total assets. DEP is depreciation
expenses to total assets. Q is the Tobin’s Q calculated as the sum of market value of equity
and book value of total liability to book value of total assets, and is a proxy for the firm's
investment opportunity. Ind_Median is the industry leverage, calculated as the industry-year
median leverage.Page 18 of 22 Management Decision
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Management DecisionTable 2
Determinants of target short-term leverage, dependent variables : LevShort i,t
Model France Germany Japan U.K. U.S.
LevShort t-1 0.42*** 0.473*** 0.803*** 0.327*** 0.543***
(6.64) (5.62) (13.84) (7.09) (5.43)
PROF 0.0018 -0.060** 0.0007 -0.0202 0.008
(0.16) (-2.07) (0.28) (-0.84) (0.57)
SIZE -0.0038* -0.0487** 0.0001 -0.0035*** -0.008**
(-0.169) (-2.01) (0.62) (-2.96) (-2.48)
TANG -0.0069 0.111* 0.0002 -0.0128 -0.043
(-0.32) (1.71) (0.20) (-0.50) (-1.22)
DEP -0.0259 0.005 0.008 -0.0092 0.116
(-0.97) (0.05) (0.46) (-0.16) (1.62)
Q -0.0004 -0.009** -0.0002 0.0001*** 0.0001
(-0.64) (-1.92) (-1.34) (2.70) (-0.94)
Ind_Median 2.687*** 0.185 1.205*** 0.792*** 0.788**
(4.32) (0.08) (3.35) (6.17) (2.15)
P-value =0.000 P-value =0.000 P-value =0.000 P-value =0.000 P-value =0.000 AR(1)
Z=-5.33 Z=-5.35 Z=-7.41 Z=-7.25 Z=-4.63
P-value =0.219 P-value =0.848 P-value =0.327 P-value =0.401 P-value =0.063 AR(2)
Z=1.23 Z=0.19 Z=0.98 Z=0.84 Z=1.86
Chi2(12)=13.99 Chi2(12)=8.42 Chi2(108)=8.42 Chi2(15)=18.31 Chi2(84)=74.22 J-test
P-value =0.301 P-value =0.751 P-value =0.182 P-value =0.247 P-value =0.769
No. of
observations3792 3630 28235 5804 21930
Two-step System-GMM results are based on standard errors robust to heteroscedasticity corrected for
finite samples (Windmeijer’s, 2005, correction). AR(i) is a serial correlation test of order i using residuals
in first difference and second difference, asymptotically distributed as N(0,1) under the null of no serial
correlation. J-test is a test of the over-identifying restrictions, asymptotically distributed as Chi2 under the
null, degrees of freedom in brackets. *, **, and *** indicate statistical significance at the 10%, 5%, and
1% levels, respectively. See Table 1 for variables description.Page 20 of 22 Management Decision
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Management DecisionTable 3
Firms with low amount of trade credit
France Germany Japan U.K. U.S.
over-
leveredunder-
leveredover-
leveredunder-
leveredover-
leveredunder-
leveredover-
leveredunder-
leveredover-
leveredunder-
levered
∆target -0.503*** -0.089*** 0.377*** 0.731*** -0.440*** -0.171*** 0.6241*** 0.729*** -0.669*** 0.175***
(-3.94) (-4.64) (-7.87) (-9.57) (-9.08) (-4.58) (-10.26) (-8.37) (-14.98) (-2.75)
TCLDummy *∆target 0.545*** 0.142*** 0.107* -0.366*** 0.458*** 0.939*** 0.136* -0.345*** 0.207*** -0.015
(7.18) (5.47) (1.68) (-2.98) (10.15) (77.32) (1.84) (-3.72) (4.35) (-0.68)
R20.435 0.065 0.276 0.552 0.437 0.3 0.401 0.048 0.309 0.118
F-test 83.99 30.58 93.14 94.16 173.18 5979.1 177.95 71.55 118.56 3.82
No. of
Observations457 3328 2190 1450 8241 19930 3122 2690 19314 2616
t-test 5.014 3.416 10.285 4.253 4.225
Standard errors are robust to heteroscedasticity, and cluster at the firm level.
*, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Page 21 of 22 Management Decision
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Management DecisionTable 4
Firms with high amount of trade credit
France Germany Japan U.K. U.S.
over-
leveredunder-
leveredover-
leveredunder-
leveredover-
leveredunder-
leveredover-
levered under-
leveredover-
levered under-
levered
∆target -0.731*** -0.283***-
0.880***-0.793*** -0.114*** 0.040 0.755*** 0.395*** -0.878***-
0.184***
(-12.77) (-8.93) (-18.65) (-14.11) (-5.99) (-1.37) (-11.38) (-4.72) (-53.6) (-3.13)
TCHDummy
*∆target-0.103 0.043* -0.01 0.231*** -0.041 0.043 -0.133* 0.331*** -0.051*** 0.236**
(-1.18) (1.89) (-0.39) (3.52) (-1.17) (0.83) (-1.81) (3.57) (-5.19) (2.22)
R20.6798 0.247 0.644 0.69 0.185 0.0003 0.422 0.048 0.864 0.088
F-test 93.4 51.9 187.2 99.6 48.2 3.32 176.2 70.5 6826.1 10.2
No. of
observatins457 3328 2190 1450 8241 19930 3122 2690 19314 2616
t-test 1.627 3.409 1.339 3.916 2.681
Standard errors are robust to heteroscedasticity, and cluster at the firm level.
*, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Page 22 of 22 Management Decision
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