4.2. Results of the Dynamic Panel Threshold Regression Model
In this study, the DPTR model is applied to examine the size threshold effect on the debt–performance nexus.
Table 5 reports the results obtained for the three models associated with the different performance measures (Tobin’s Q, ROA, and ROE). Using firm size (Size) as a transition variable, the threshold values of the three models are estimated at 9.126, 15.48, and 16.816, respectively. In addition, they pass the bootstrap linearity test at the 1% significance level, confirming the nonlinear relationship between debt and firm performance, and a threshold effect of firm size. This is detected through the
p-value, which is less than 5% (
Table 6), indicating the rejection of the null hypothesis of this test. Of the observations, 7.47% (Q), 87.9% (ROA), and 94.19% (ROE) fall into the lower regime; and 92.53% (Q), 12.1% (ROA), and 5.81% (ROE) into the upper regime.
To analyze the results more clearly, we will discuss the results by each performance measure (Q, ROA, and ROE). Therefore, we will start with the analysis of the first model, which takes the Tobin’s Q (market value (Q)) as a performance measure (Column 1, 2, and 3). Using Size as the transition variable, the threshold value is estimated at 9.126 (the equivalent firm size is $1 million). Furthermore, the coefficients associated with the debt variable are significant for both regimes (lower and upper). In the lower regime reflecting small firms, the estimated coefficient is positive and statistically significant, showing the existence of a positive relationship between debt and Tobin’s Q. However, in the upper regime representing large firms, the estimated coefficient is negative and statistically significant, indicating the presence of a negative relationship between leverage and Tobin’s Q. Based on our results, the lower regime appears to be the optimal regime, since the coefficient is greater than the upper regime coefficient. Specifically, a 10.0% Debt will lead to a 3.61% increase in ROA.
As for the ROA model analysis (Columns 4, 5, and 6), the threshold value is estimated at 15.48 (the equivalent firm size is $5 million). Furthermore, the coefficients of the variable (Debt) in both regimes are statistically significant at the 1% level. In the lower regime, qualifying the small firm regime, the estimated coefficient is negative and statistically significant, showing that debt exerts a negative impact on firm performance (ROA). According to these results, the optimal regime corresponds to the upper regime, since the coefficient is greater than the coefficient. Specifically, a 10.0% Debt will lead to a 4.98% increase in ROA.
Turning to the ROE model analysis (Columns 7, 8, and 9), the threshold value is estimated at 16.816. (The equivalent firm size is $20 million.) The coefficients of the variable (Debt) in both regimes are statistically significant at the 1% level. In the lower regime, the estimated coefficient is negative and statistically significant, indicating that leverage negatively affects the firm’s financial performance (ROE). Based on these results, the optimal regime corresponds to the upper regime, since the coefficient is greater than the coefficient. Specifically, a 10.0% Debt will lead to a 3.94% increase in ROE.
In addition, the coefficient of lagged performance (Q, ROA, and ROE) is statistically significant and positive in both regimes, except for the Q model in the upper regime, which shows that the current performance is affected by the increase in performance in the previous period. These results are explained by the presence of adjustment costs that are related to the financial decisions of the listed firms in the MENA region.
Certainly, the results found on the control variables have allowed for further analysis of the regressed models. Let us start with the liquidity variable (LIQ); its coefficients have opposite signs. In the lower regime (columns (1), (4), and (7)), the LIQ coefficients are positive and statistically significant. The positive relationship between liquidity and the performances of the MENA firms can be explained by their ability to meet their short-term liabilities, as they have the necessary equity to manage their activities. More specifically, in column (1), small firms perform better because they hold sufficient internal funds. They can rely on self-financing to maximize their value (Tobin’s Q). Furthermore, in columns (4) and (7), small firms rely on self-financing to increase their performance (ROA and ROE). This result is clearly in line with the pecking-order theory, where following a hierarchical financing order constitutes a drastic condition to avoid the costs arising from perfect information. However, in the upper regime (columns (2), (5), and (8)), regarding the negative relationship between liquidity and firm value (Tobin’s Q), large firms do not hold sufficient internal funds to increase their investment opportunities. In this case, the lack of liquidity reduces the firm value. Similarly, the negative relationship between liquidity and firm performance (ROA and ROE) could be explained by the fact that the internal funds needed to finance investment projects and to improve the profitability of large firms are exhausted. Consequently, they are forced to resort to debt to compensate for the lack of liquidity.
Similarly, the coefficients of the tangibility variable (TANG) are of opposite signs and are significant at the 1% level. In the lower regime (columns (4) and (7)), tangibility has a negative effect on firm performance (as measured by ROA and ROE). This result indicates that small firms do not hold sufficient tangible assets to grant them as collateral when accessing credit. By contrast, in the upper regime (column 5), tangibility has a positive effect on firm performance (ROA). This result reflects large firms’ detention of large tangible assets, and their ability to access credit to improve their profitability and reinvestment opportunities.
Except for column (2), the coefficients of the Tax variable are all negative and statistically significant at 1%. The negative effect of the non-debt tax shield on firm performance is explained by the fact that MENA firms tend to minimize the payment of income taxes through recourse to debt. In this case, to limit the massive recourse to debt and the payment of debt taxes, these firms will increase their depreciation charges. Indeed, they use their internal funds to finance their activities. This shows that the increase in financial charges has a negative impact on the MENA firm performance.
Similarly, the economic cycle variables (i.e., inflation and GDP) seem to be important determinants of the performances of MENA firms. As for the inflation variable (INF), it turns out that the signs of its coefficients are different and statistically significant. In columns (1) and (5), we find that inflation has a positive and statistically significant effect on the ROA and Tobin’s Q. The positive relationship between inflation and Tobin’s Q (ROA) indicates that increasing inflationary effects do not prevent small (large) firms from investing or from taking advantage of good growth opportunities. Moreover, this result could also be explained by lower tax rates. According to
Gonedes (
1981), the lower tax rate compensates for the negative impact of inflation on profitability. This should help MENA firms to increase their reinvestment opportunities and profitability. However, in the upper regime (see columns (2) and (8)), the negative relationship between inflation and firm value (financial profitability) reflects the inability of large firms to make profits due to increasing inflationary effects. Indeed, when the inflation rates are too high, the costs (debt costs, agency costs, transaction costs, etc.) will also be increasingly high.
The coefficients of the variable GDPG have divergent signs and are significant at the 1% level. As for the negative relationship between GDP and firm performance, it indicates that economic growth does not necessarily improve firm growth in the MENA region (see columns (1) and (5)). This result could also be attributed to the measure chosen by the researcher. In fact, GDP is a global measure. It affects all sectors. However, our sample is composed of several industrial firms, so perhaps the choice of a specific measure such as the industrial production growth rate brings about more robust results (see
Khémiri and Noubbigh 2020). On the other hand, in columns (2) and (4), the positive relationship between GDP and performance is explained by the fact that the MENA growth recovery contributes to the maximization of the profitability of non-financial firms.
4.4. Discussion
To discuss the results, we will discuss the results according to each performance measure. Regarding Tobin’s Q model, the result shows a threshold effect of firm size on the debt–performance nexus. This indicates that our Hypothesis 1 is valid. Indeed, under a lower regime, the result shows that there is no conflict of interest between the managers of small firms and their investors. Therefore, the use of debt could be an effective way for managers to disclose the financial situation of their firm to investors. They focus on this informational advantage to minimize the costs of information asymmetry. As a result, they can attract more investors and maximize shareholder wealth. These results are then explained by the fact that small firms in the MENA region are considered by investors as being good firms, since they use medium-term debt as a signal to inform the market about their management quality. Under an upper regime, this result shows that large firms are considered by investors to be risky firms because they require a higher debt than their smaller counterparts (in a lower regime). More precisely, their excessive access to credit generates costs that are too high, and conflicts of interest. In this case, medium-term debt is not a good signal for large firms because it deteriorates shareholder value. This deterioration could be explained more fully using the following two reasons. On the one hand, the massive recourse of large firms to debt generates debt costs that are too high. These costs increase progressively when the inflation rate increases. This in turn affects the firm value. On the other hand, the disclosure of financial information (debts and profits) imposes more taxes. In this case, the excessive payment of corporate tax reduces the firm’s value. In general, to choose the optimal regime, we follow
Khémiri and Noubbigh (
2020) based on the estimated coefficient. More precisely, the highest coefficient reflects the optimal regime.
Similarly, the result of the ROA model confirms the validity of our Hypothesis 1, indicating the threshold effect of firm size on the debt–performance nexus. This negative impact of leverage on ROA (the results of a lower regime) can be explained by the fact that small firms need to avoid the use of debt because they often find themselves paying back the amount of debt at maturity due to the information asymmetry problem and high costs. These firms must rely on cash flow (especially retained earnings) to invest and increase their profitability. Through this financing strategy, small firms will be able to avoid facing the financial market, providing information on their investment projects, and bearing very expensive issuance costs. This result is consistent with the one found by
Zeitun and Tian (
2014). Based on these results, the pecking-order theory is confirmed. However, the result of the upper regime suggests the ability of large firms to take on debt to improve profitability. To do so, they rely on debt to take advantage of the tax benefits that they have (tax savings). They demand credit until they reach a satisfactory level of debt, thus enhancing the maximization of their performance level. This undeniably reflects that there is a relationship of confidence between the lenders and the managers of firms in the MENA region; hence, the absence of imperfect information. This finding has been confirmed by some previous studies (
Jaisinghani and Kanjilal 2017;
Ibhagui and Olokoyo 2018;
Khémiri and Noubbigh 2020). In this case, the predictions of the trade-off theory are accepted.
Regarding the ROA model, the result shows a threshold effect of firm size on the debt–performance nexus. This indicates that our Hypothesis 1 is also valid. Indeed, under a lower regime, the negative effect of Debt on the ROE (a lower regime result) of small firms indicates their incapacity to rely on leverage financing to invest and to improve their profitability. This incapacity could be attributed to the increase in financial costs (high-interest rates). Similarly, debt is not an adequate means of financing for small firms, as they face certain risks arising from imperfect information and conflicting interests among stakeholders (especially lenders and firms). They must rely on retained earnings and depreciation allowances to maximize shareholder benefits. This implies that interest rates are higher than the ROE. They could generate a financial risk and a real deterioration of the global value of firms in the MENA region. The pecking-order theory is accepted. However, in the upper regime, the estimated coefficient is positive and statistically significant. Economically, large firms count on debt to increase their performance. Specifically, they use it to increase their investment capacity and benefit from tax savings, which in turn affects their profitability. This finding suggests that debt helps the managers of large firms to take advantage of investment and growth opportunities, which improves their performance. The trade-off theory is accepted. Finally, our results are supported by a robustness test.