This paper aims to investigate the determinants of corporate debt maturity structure using a panel of Tunisian and French listed firms. Specifically, we focus on the relevance of market timing considerations on the choice between short- and long term debts. We find that market timing has no significant impact on the debt maturity choice. We document also that debt maturity is positively related to asset maturity and leverage. Long-term debt decreases with growth opportunities and profitability and statistically unrelated to size.
1 Introduction
The debt maturity choice may be as important as the choice of capital structure. However, it's surprising to note the lack of empirical literature relevant to this topic. Morris (1976) can be considered as the earliest investigation of the determinants of the debt maturity structure. Subsequent empirical studies are mainly reserved to the U.S firms. Previous theoretical literature suggests that the choice between short- and long-term debts is largely determined by firm-specific characteristics such as asset structure, size, profitability, growth options and leverage. Recently, the market timing theory emphasizes the intention of managers to take into account debt market conditions in order to choose the lowest-cost maturity. The existing literature on market timing behavior covers only the U.S context. In this paper, we attempt to fill this gap by extending the test of the impact of market timing implications on the borrowing behavior of Tunisian and French firms. Indeed, it seems very interesting to explore the relevance of the market timing issue in two bank-based systems like Tunisia and French since financing policies may differ completely from those in market-oriented systems like U.S. This study can be considered as the first essay to connect the choice of corporate debt maturity structure to firm-specific characteristics and debt market conditions using a panel of Tunisian and French firms.
Our results are as follows: i) Consistent with the matching principle, we find that Tunisian and French firms tend to fund long-lived assets by long-term debt. ii) Debt maturity is a decreasing function of growth opportunities and profitability. iii) A positive impact of leverage on debt maturity has been documented. High levered firms are more likely to lengthen their debt maturities to differ risk defaults. iv) The impact of size has been found out as insignificant. v) Contrary with the market timing approach, we find no evidence that managers tend to choose short-term debt when the term spread is high and lengthen their debt maturities otherwise.
The rest of this paper is structured as follows. Section 2 reviews the theoretical and empirical literature on the determinants of corporate debt maturity structure as well as the hypothesis development. Section 3 provides a description of the data used in the empirical analysis and presents estimation results. Section 4 concludes.
2 Background literature
When firms are seeking external financing, they have to choose between issuing equity and borrowing from lenders. If they choose to issue debt, they must make decision on the debt maturity. In the Modigliani and Miller's (1958) framework, there is no advantage to be taken from opportunistically switching between short- and long-term debts. However in existence of market imperfections such as agency costs, financial distress, and information asymmetry, firms are suggested to have a target optimal debt maturity structure. Previous theories predict that this optimal debt maturity susceptible to minimize the overall cost of capital is determined by firm-specific characteristics. Recently, the market timing theory has challenged previous predictions by suggesting that corporate debt maturity structure depends on credit market conditions. This theory emphasizes the mangers' ability to time the market in order to borrow cheaply. Antoniou, Guney, and Paudyal (2006) investigate the determinants of the choice of debt maturity of French, German, and UK firms. They find that debt maturity structure is determined by firm-specific and factors country's conditions. Similarly, Deesomak, Paudyal, and Pescetto (2009) examine the determinants of the debt maturity within a panel of non-financial firms belonging to four Asian countries (Thailand, Malaysia, Singapore, and Australia) over the period 1993-2001. ¶They find that these companies have an optimal debt maturity structure target determined by firm-specific factors and macroeconomic variables. ¶They show that market conditions have a significant impact on the choice of debt maturity.
2.1 Maturity matching principle
Maturity matching principle says that liabilities employed to finance assets should be repayable at the time those items can generate sufficient cash flows to pay off the debt service. Myers (1977) suggests that the correspondence between debt and asset maturities serves to resolve the problem of underinvestment. ¶He shows that the debt maturity positively depends on the asset life cycle. The long-lived assets must be financed by long-term debt whereas the short-term debt should be devoted to the financing of short-lived assets. ¶Graham and Harvey (2001) find that maturity matching is the most important factor affecting the choice between short- and long-term debts. They explain that this correspondence can be justified by risk-management practices. Firms want to align asset and liability duration to attenuate the impact of interest rate fluctuations on the amount of funds available for investment and day-to-day operations.¶¶Mturity ¶Kôrner (2007) finds that Czech firms tend to conduct the maturity matching of their balance sheet by funding fixed assets by long-term debt. Cai, Fairchild, and Guney (2008) find that asset maturity has significant impact on extending the maturity of debt employed by Chinese firms. Using a sample of 146 non-financial UK-based firms over the period 1986-1999, Correia (2008) finds evidence that managers follow a maturity matching rule.
¶The hypothesis of matching between debt and asset maturity was confirmed by the majority of empirical studies. ¶Therefore, we expect a positive relation between long-term debts and long-lived assets. ¶The first hypothesis to be tested is as follows; ¶
Hypothesis 1: ¶The debt maturity is an increasing function of the asset life cycle. ¶
2.2 Debt maturity and agency theory
Barnea, Haugen, and Senbet (1980) suggest that shortening debt maturity can resolve the problem of adverse risk incentives and asset substitution because short-term debt dissuades shareholders to undertake very high-risk projects. Myers (1977) differentiates between assets in place and growth opportunities. He shows that worthwhile agency costs can force firms to pass up positive net present value investment projects if the payments to creditors exceed the profitability of those growth options. To overcome this obstacle firms should renegotiate the debt contract with lenders or shorten debt maturity. "Debt that matures before an investment option is to be exercised does not induce suboptimal investment decision." (Myers 1977, p.159) The prediction that firms with higher growth options tend to shorten their debt in order to reduce the costs of shareholder-bondholder conflicts has been confirmed by empirical studies. Mitchell (1993) reports evidence that firms with highly profitable projects are more likely to rely on short-term debt. Barclay and Smith (1995) document that firms with few growth options have more long-term debt in their capital structure. Goyal, Lehn, and Racic (2002) have investigated the impact of growth opportunities on debt financing in a sample of 61 U.S defense firms over the period 1980-95. They find that weapons manufacturers increased their leverage level and lengthened as their growth opportunities declined by the end of the cold war. Johnson (2003) finds that the negative effect of growth opportunities on leverage can be attenuated by shortening debt maturity. Garcia-Teruel and Martinez-Solano (2007) find that short-term debt loans are more common in firms with major growth options. Kôrner (2007) finds similar results.
In this study we attempt to test the following hypothesis:
Hypothesis 2: Growth opportunities abundance shortens debt maturity.
2.3 Debt maturity and signal theory
2.3.1 Profitability
Flannery (1986) argues that short-term debt issuance is perceived by the market as good news that cannot be imitated with firms of bad quality. Investors believe that shortening debt maturity means that the firm has valuable investment. Diamond (1991) develops a model based on asymmetry information between insiders and outsiders about the firm's default risk. Firms with low risk and expected abnormal returns should shorten their debt. When the private information about future prospects reveals to the market, the firm will be able to take advantage of the improvement of its appreciation and borrow cheapest. Only higher profitable firms could choose short-term loans because they believe in their ability to refinance in opportune time. Scherr and Hulburt (2001) documented a positive relation between debt maturity and profitability.
In this paper the following hypothesis will be tested:
Hypothesis 3: The debt maturity is a decreasing function of firm's performance.
2.3.2 Size
Larger firms present a low degree of asymmetry information and for that reason they are generally low-risk. Diamond (1991) proposes that both very low-risk and very high-risk borrowers prefer short-term debt. Scherr and Hulburt (2001) find that debt maturity is negatively related to the firm's size. By contrast, Morris (1976) finds that larger firms use relatively more long-term debt since they have a superior access to the capital markets. Titman and Wessels (1988) demonstrate that small firms are more likely to use more short-term debt than larger firms. Singh (2009) finds that small unrated firms are more likely to issue short-term debt.
Our paper seeks to test the following hypothesis:
Hypothesis 4: size plays a positive role on debt maturity.
2.4 Debt maturity and leverage
Morris (1992) argues that high-levered firms tend to lengthen their debt maturities in order to postpone their exposure to bankruptcy risk. Morris (1976) finds that firms with high leverage ratios attempt to lengthen their debt maturity. Leland and Toft (1996) developed a theoretical model that predicts a positive relationship between debt maturity and leverage level. Kôrner (2007) find that leverage has a statistically significant positive impact on debt maturity structures of Czech firms. By contrast, the agency theory stipulates that debt maturity is a decreasing function of leverage. High-levered firms are more likely to employ short-term debt to mitigate stockholder-bondholder conflicts even though borrowing short increases costs of rolling over short maturity debt claims. Thus, optimal debt maturity structure can evolve as a result of the trade-off between benefits and costs of shortening.
The role played by leverage on the choice of corporate debt maturity structure is not obvious. In the present paper we assume that firms are more concerned by delaying default risk than to reducing costs of shareholders-bondholders conflicts. Hence, the following hypothesis can be formulated:
Hypothesis 5: leverage contributes in lengthening debt maturity.
2.5 Debt maturity and market timing theory
Empirical literature suggests that managers time their debt issues in order to reduce their borrowing costs. They believe in their ability to forecast future fluctuations of interest rates. In the survey conducted by Graham and Harvey (2001), market timing reveals to be the third most important determinants of the choice between short-and long-term debt. "We also find that firms issue short-term debt in an effort to time market interest rates. CFOs borrow short-term when they feel that short-rates are low relative to long rates or when they expect long-term rates to decline". (Graham and Harvey 2001, p. 223) Similarly, Baker, Greenwood, and Wurgler (2003) argue that managers time debt markets by increasing the share of long-term issues when they expect high excess bond returns. They conclude that debt market timing strategies are successful. However, they did not demonstrated if managers succeed in reducing the overall cost of capital. Guedes and Opler (1996) found that debt maturity is negatively related to the term spread (difference between long-term government bond yield and Treasury bill returns). Antoniou, Zhao, and Zhou (2009) find that market timing is the primary motivation behind corporate debt issues.
Hypothesis 6: debt maturity is a decreasing function of term spread.
3 Empirical analysis
In the previous section we have provided a literature overview of the determinants of the debt maturity structure as well as discussing our research hypothesis. In this section, first we define the dependent and explanatory variables, and then we specify the model to be estimated, present our sample, summarize descriptive statistics, report regression results, and finally interpret our findings.
3.1 Sample Selection
To form our main Tunisian sample, we start with all listed firms appearing at any point between 2000 and 2008. We restrict the sample to exclude financial firms. The final sample covers 30 publicly traded Tunisian firms. The French sample consists in 100 non-financial French firms of the Paris stock market index SBF 120. We restrict our study to non-financial firms because financial ones have their own specificity. Tunisian data were collected from Tunis Stock Exchange. French data were obtained from the database COFISEM and completed from firms' web sites.
3.2 The dependent variable
In our model the dependent variable is debt maturity DEBTMAT. Maturity is the time in years until repayment of the principal (and all remaining interest) is scheduled. Empirical studies provide different measures of the debt maturity. Guedes and Opler (1996) use two measure of debt maturity the duration and term and they find similar results. Stohs and Mauer (1996) use the weighted average of all debt maturities. Barclay and Smith (1996), and Antoniou et al. (2006) use the ratio of long-term debt reported to total debt. Kôrner (2007) and Cai et al. (2008) use the ratio of debt maturing over one year to total debt.
In our case, we use the ratio of long-term debt divided by total debt. Our motivation behind this choice is the difficulties to obtain the effective debt maturity. Financial statements provided by either Tunisian or French firms do not contain this information.
(1)
Where is long-term debt and is total debt.
3.3 Explanatory variables
3.3.1 Asset maturity
Several proxies can be employed to measure the asset maturity. The first measure is to divide fixed assets by total assets1.
(2)
Where are fixed assets including intangible asset, plant, propriety, and equipment (PPE), i.e., assets which cannot be easily converted into cash.
The second measure of asset maturity is the ratio of tangible assets reported to annual depreciation2.
(3)
Where represents tangible asset which includes PPE and inventories.
Kôrner (2007) employs an adjusted measure of asset maturity in which only excess of the fixed assets over the equity is to be funded by long-term debt.
(4)
Where is equity.
In our case, we use the first measure to compute the impact of asset maturity on the choice of debt maturity structure. Our motivation of this choice is that the first measure takes account of maturity of long-lived assets as a whole while in the second measure only tangible assets are considered.
3.3.2 Growth opportunities
The market-to-book ratio is commonly employed as a proxy of growth options and it's defined as the market value of assets divided by total balance-sheet. Market value equals total assets minus book equity value plus market capitalization.
(5)
Where represents the market value and the book value of the firm.
High values of market-to-book ratios can be interpreted as good appreciations of firm's growth options by the market.
The alternative measure of growth opportunities is the annual change in fixed assets divided by total assets.
(6)
High changes in fixed assets can reflect the will of the firm to enhance its productive capacity.
This measure is usually used in case of non-listed firms. In our case, all firms selected are listed either on Tunis Stock Exchange for the Tunisian sample or on Euronext Paris for the French sample. Thus, we have not the problem of lack of information about the firm's market value. That's why we opt for the market-to-book ratio as a proxy of growth options.
3.3.3 Size
The firm's size can be measured by several ways:
- by the natural logarithm of net sales
(7)
- by the natural logarithm of total assets
(8)
- by the natural logarithm of market value
(9)
In this study, we have tested these three measures of the size and we have found that using the natural logarithm of net sales is the most appropriate one.
3.3.4 Profitability
There are many proxies of profitability such as the return on assets (ROA), return on equity (ROE) and profit margin (PM).
- ROA is defined by earnings before interests and taxes (EBIT) scaled by total assets:
(10)
- ROE is measured by the net income reported to shareholders' equity:
(11)
- PM is defined as the net income divided by operating income:
(12)
In this paper, we have chosen the first proxy of profitability because it's the most commonly employed by recent researches.
3.3.5 Leverage
In this paper, we define leverage ratio as book debt divided by total assets in order to obtain comparative results with recent papers regarding the market timing theory. Many others proxies exist such as equity-debt ratio or market leverage but the choice of another one does not change qualitatively our results.
- The book leverage is defined as total debt scaled by total assets.
(11)
- The market leverage is defined as total debt reported to the market value of the firm. Market value is measured as total assets minus book equity plus market capitalisation. Market capitalization is obtained by multiplying shares outstanding by their current prices.
(12)
- The debt-equity ratio is calculated by dividing total debt by shareholders' equity and it reflects the relative importance of each financing mode in funding company's assets.
(13)
3.3.6 Term Spread
Following Baker, Greenwood and Wurgler (2003), we define the term spread as the difference between 10-year government bond yields and a three month Treasury bill returns3.
(14)
3.4 Descriptive statistics
Tables 1 and 2 report the descriptive statistics for the dependant and explanatory variables. Considerable insight can be obtained by comparing the average debt maturity of the firms in our two samples. In doing so, we note that the share of long-term debt in total debt is higher in French sample. This evidence indicates that French firms rely more on long-term debt. This characteristic is consistent with our prior hypothesis. First, French firms hold more long-lived assets (52.55% of total assets on average in France against 43.9% in Tunisia). Second, French firms are more levered than Tunisia firms (respectively 63.36%, 49.29%).
Table 1 Descriptive statistics of dependent and explanatory variables for Tunisia
Variables
Tunisia
Mean
Median
St. Dev.
Min.
0.3511
0.3376
0.2459
0.0000
0.4390
0.4019
0.1956
0.0627
1.43
1.14
7.01
0.24
10.42
10.55
1.23
7.42
0.0642
0.0699
0.0643
-0.1569
0.4929
0.5033
0.2023
0.0468
0.0150
0.0163
0.0035
0.0097
Table 2 Descriptive statistics of dependent and explanatory variables for France
Variables
France
Mean
Median
St. Dev.
Min.
0.4156
0.4008
0.2017
0.0027
0.5255
0.5155
0.1753
0.0403
1.65
1.30
1.1093
0.62
15.18
15.33
1.7901
7.07
0.0790
0.0732
0.0801
-0.6408
0.6336
0.6481
0.1501
0.1069
0.0118
0.0440
0.0068
0.0014
The Figure reveals a similar trend of the evolution of debt maturity over our period of study. This evidence points out that the debt maturity seems to have the same determinants in the two countries.
Figure Debt maturity evolution over the period 2000-2008
Tables 3 and 4 report the correlations matrix for explanatory variables. The coefficients of correlation of explanatory variables are generally low. Using a test of Farrar-Glauber (1967) we can accept the hypothesis of the absence of multicollinearity among our independent variables.
Table 3 Correlation matrix for explanatory variables for Tunisia
Explanatory
variables
Tunisia
assetmat
mtb
size
prof
lev
assetmat
1
mtb
0.092
1
size
0.1304
0.151
1
prof
-0.218
0.358
-0.154
1
lev
0.097
-0.169
0.435
-0.413
1
spread
0.043
-0.074
0.017
-0.075
0.058
Table 4. Correlation matrix for explanatory variables for France
Explanatory
variables
France
assetmat
mtb
size
prof
lev
assetmat
1
mtb
-0.202
1
size
0.201
-0.261
1
prof
-0.038
0.289
-0.032
1
lev
0.096
-0.269
0.421
-0.223
1
spread
-0.013
-0.208
0.083
-0.052
0.047
3.5 Estimation methods
We investigate the determinants of the corporate debt maturity choice using an unbalanced panel of Tunisian and French firms. In this regression, debt maturity is regressed on five variables which reflect firm-specific characteristics and a sixth one related to credit market conditions. The regression equation is formulated as follows:
Using panel data can enhance the quality and quantity of data. It allows us to identify some effects that cannot be detected using time-series analysis. Panel data regression provides three estimators; Pooled OLS, Fixed effects, and Random effects models. A pooled estimator takes as the same across all cross-section units. The fixed effects model assumes as a group specific term. The random effects approach takes as a group specific disturbance.
Testing the significance of the group effects
To choose between these three approaches we compute a test of homogeneity. The hypothesis of homogeneity of constants across all cross-section units can be formulated as follows:
This test of Fisher is computed as follows:
Where:
: Residues square sum of the individual effects model and
: Residues square sum of the model Pooled.
: Number of firms
: Number of explanatory variables (constant not included)
If calculated F is lower than tabulated F (p-value < 0.05), H0 is rejected and we have to choose between the fixed and the random effects model.
Hausman's test for fixed versus random effects
If the effect is assumed to be individual, the Hausman specification test is carried out in order to decide whether the fixed or the random effects model should be used. The Hausman test compares the fixed and random effects estimates of coefficients.
The tested hypothesis concerns the correlation of the individual effects and the explanatory variables.
Under the null hypothesis, the individual effects are random and we then have to choose the estimator of GLS. Under the alternative hypothesis, the individual effects are correlated to the explanatory variables and we then have to choose the model to fixed effects.
The test of Hausman compares the matrix of variance-covariance of two estimators:
The statistic H is asymptotically distributed as with K degree of freedom, where K is the number of explanatory variables. If calculated H is lower than tabulated (p-value < 0.05), H0 is rejected and individual effects are assumed fixed.
3.6 Estimation Results
The table below reports regression results for the model linking the choice of corporate debt maturity structure to five firm-specific factors and a last variable which reflects debt market conditions. Panel data analysis provides three estimators; Pooled, Fixed effects, and Random effects. The Hausman's specification test indicates that individual effects are assumed random for Tunisia and fixed for France.
Table 5 Determinants of debt maturity
Variables
Tunisia
France
Pooled
Fixed
effects
Random
effects
Pooled
Fixed
effects
Intercept
-0.0483
(-0.52)
0.8126**
(2.11)
0.3837
(1.14)
0.0802
(1.83)
-0.1012
(-0.41)
Asset
maturity
0.3275***
(6.13)
0.2772*
(1.85)
0.3030***
(2.64)
0.6689***
(9.09)
0.2151***
(3.35)
Growth
options
-0.0138
(-1.57)
-0.0178***
(-3.13)
-0.0143**
(-2.17)
-0.0074
(-0.76)
-0.0209**
(-1.98)
Size
-0.0063
(-0.82)
-0.0687**
(-2.03)
-0.0306
(-1.02)
-0.0108***
(-3.93)
-0.0039
(-0.23)
Profitability
-0.2958
(-1.39)
-0.1996**
(-2.09)
-0.2608*
(-1.74)
-0.0399
(-0.66)
-0.0451
(-0.29)
Leverage
0.4895***
(10.42)
0.2095***
(2.21)
0.2608***
(4.16)
0.2182***
(6.51)
0.5764***
(6.63)
Term
spread
-3.2539
(-0.81)
-1.3387
(-0.72)
-0.1963
(-0.07)
-1.0694
(-0.84)
-0.2624
(-0.29)
R Square
0.2989
0.8328
0.1167
0.3709
0.7921
Adjusted R square
0.2785
0.7997
0.0909
0.3643
0.7464
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.3262
Cross-section
30
30
30
100
100
Observations
213
213
213
578
578
***significant at 1% level, **significant at 5% level, *significant at 10% level, t-statistics in parentheses.
The empirical results provide a strong support to the matching principle. ¶Indeed, the coefficient of the variable is positive and significant in the two countries and for the three methods of estimate. ¶This result suggests the existence of a matching between the debt maturity and the asset life cycle. ¶This evidence indicates that Tunisian and French companies fund their acquisition of long-lived assets by long-term debts in order to guarantee some coincidence between debt services and cash flows generated by the underlying asset. ¶This association between the debt maturity and the asset life cycle can also aim to resolve the problem of underinvestment (Myers 1977). Our result confirms findings in Morris (1976) for U.S firms, ¶Cai, Fairchild, and Guney (2008) for Chinese companies, Arslan and Karan (2006) for Turkish companies, Kôrner (2007) for Czech firms. ¶ ¶
¶¶Growth opportunities have a significant negative impact on debt maturity. This evidence indicates that Tunisian and ¶French firms tend to shorten their debt if they have valuable growth options to undertake in order to avoid underinvestment problem.¶ ¶¶This result is consistent with the agency theory which predicts the existence of an inverse relationship between growth opportunities and the debt maturity since non-callable long-term debt permits to bondholders to share with shareholders in the profitable future projects. This wealth transfer problem will force firms to pass up positive NPV projects. Our findings confirm those found by Mitchell (1993), Johnson (2003), Garcia, Lehn, and Racic (2002), and Kôrner (2007).¶
Contrary to our prior predictions, ¶¶the variable size measured by the natural logarithm of net sales contributes in shortening debt maturity of Tunisian and French firms. This evidence suggests that larger firms tend to shorten their borrowings more than small firms. Our result corroborates findings in Sherr and Hulbert (2001) but it contradicts those obtained by Morris (1976), Titman and Wessels (1988), and Singh (2009).
¶¶¶¶The variable profitability is negatively related to the debt maturity. ¶This evidence is consistent with the signal theory. ¶Tunisian and French firms shorten their debts while waiting for the release of the new performances carried out. Similarly, Flannery (1986), Diamond (1991), and Sherr and Hulburt (2001) have documented a negative relation between debt maturity and profitability.
¶¶The debt maturity depends positively on the level of indebtedness. ¶Thus indicates that Tunisian and French firms lengthen their debt maturities to put off their exposure to the problem of financial distress. This result contradicts agency theory predictions but it's similar to findings in Morris (1976) and Kôrner (2007).
¶The term spread has¶he ter no significant impact on the choice of the debt maturity. ¶This evidence contradicts the market timing theory which predicts that ¶firms are more likely to choose short-term debt when the term spread is relatively high. Our result opposes to findings in Baker, Greenwood, and Wurgler (2003), and Graham and Harvey (2001). This difference in findings can be explained by the fact that we used the debt as a whole, i.e., bank and bond debts while Baker, Greenwood, and Wurgler (2003) have focused on bond debt5.
Table 6 reports a comparison between results of some papers on corporate debt maturity choice. Overall, our results are in line with our prior expectations and previous findings. There is a wide consensus that firms match their debt maturity to the useful lives of their assets. In addition, a full consensus has been reached about the positive impact of leverage on debt maturity. By contrast, a difference in findings has been documented for the remaining explanatory variables (Growth options, size, profitability and term spread) that can be explained by the diversity of approaches adopted, proxies employed and financial systems analyzed throughout these studies.
Table 6 Comparison of empirical findings
Predicted
sign
Our findings
Morris (1976)
Arslan and Karan
(2006)
Kôrner (2007)
Cai et al. (2008)
Tunisia
France
Asset maturity
+
Significant
positive
Significant
positive
Significant
positive
Significant
positive
Significant
positive
Significant
positive
Growth options
-
Significant
negative
Significant
negative
Significant
negative
Significant
negative
Insignificant
negative
Insignificant
positive
Size
+
Insignificant
negative
Insignificant
negative
Significant
positive
Significant
positive
Significant
positive
Significant
positive
Profitability
-
Significant
negative
Insignificant
negative
Insignificant
negative
Leverage
+
Significant
positive
Significant
positive
Significant
positive
Significant
positive
Significant
positive
Term spread
-
Insignificant
negative
Insignificant
negative
4 Conclusion
This paper examined the determinants of the corporate debt maturity mix in a sample of Tunisian and French publicly traded firms. Our findings suggest that debt maturity seems have the similar determinants in the two countries. The choice of debt maturity by Tunisian and French firms is straightforwardly based on the asset maturity matching, leverage, and growth options. They are more likely to lengthen their borrowing to fund long-lived asset purchases and to postpone their exposure to default risk. By contrast, Tunisian and French firms with valuable growth options tend to shorten their debts in order to mitigate the agency problem and avoid underinvestment.
Contrary to the market timing theory, we have documented no evidence that firms tend to choose long-term debt when the term spread is low. This result contradicts findings in Baker, Greenwood, and Wurgler (2003) who emphasized on the relevance of the term spread considerations on corporate debt maturity choice. This difference in findings suggests that the debt maturity choice in bank-based systems like Tunisia and France is not affected by the fluctuations of short- and long-term interest rates.
Overall, our results reveal that the debt maturity choice in Tunisia and France is mainly determined by firm characteristics and not affected by market conditions. However, this evidence does not mean that Tunisian and French managers are not implementing a debt market timing strategy since they can time their debt issuance4.
