Bond covenants and the speed of corporate capital structure adjustment: Evidence from China

Purpose– The purpose of this paper is to examine the role of institutional, macroeconomic, industry, and firm characteristics on the adjustment speed of corporate capital structure within the context of developing countries.Design/methodology/approach– The authors considers a sample of 986 firms drawn from nine developing countries in Africa over a period of ten years (1999-2008). The study develops dynamic partial adjustment models that link capital structure adjustment speed and institutional, macroeconomic, and firm characteristics. The analysis is carried out using system Generalized Method of Moments procedure which is robust to data heterogeneity and endogeneity problems.Findings– The paper finds that firms in developing countries do temporarily deviate from (and partially adjust to) their target capital structures. Our results also indicate that: more profitable firms tend to rapidly adjust their capital structures than less profitable firms; the effects of firm size, growth opportunities, and the gap between observed and target leverage ratios on adjustment speed are functions of how one measures capital structure; and adjustment speed tends to be faster for firms in industries that have relatively higher risk and countries with common law tradition, less developed stock markets, lower income, and weaker creditor rights protection.Research limitations/implications– Future research should focus on examination of the adjustment speed of debt maturity structure. Identification of industry-specific characteristics that affect the pace with which firms adjust their capital structure to the optimum is another possible avenue for future research.Practical implications– Our findings have practical implications for corporate managers, governments, legislators, and policymakers.Originality/value– The study focuses on firms in developing countries for which the literature on adjustment speed of capital structure is virtually non-existent. Furthermore, unlike previous works on capital structure, it explicitly models industry variable as one of the determinants of adjustment speed. Therefore, it contributes to the literature on capital structure and adjustment speed in general and to the literature on developing countries in particular.

This paper selects all non-financial listed companies in Shanghai and Shenzhen A shares from 2010 to 2022 as the research object, based on dynamic capital structure theory, high-level echelon theory and resource dependence theory, through panel regression , to explore the impact of female directors themselves on the speed of capital structure adjustment; And introducing crash risk into the extended model to test the relationship between female directors and the speed of capital structure adjustment from the perspective of crash risk. The results show that the existence of female directors in the board of directors will optimize the capital structure, and the increase in the proportion of female directors in the board of directors will improve the speed of capital structure adjustment; Due to the characteristics of conservative and cautious women, the existence of female directors in the board of directors will reduce the risk of stock price collapse; Based on the perspective of collapse risk, female directors still improve the speed of capital structure adjustment.

Debt covenants and the speed of capital structure adjustment

This paper examines the impact of debt covenants on the speed of capital structure adjustment. Overall, we find that covenants lower the speed of adjustment by 10–13%, relative to the speed of adjustment of firms without covenants. The speed of adjustment is significantly lower, by 40–50%, for firms with the most intense covenant provisions. In particular, we find that capital covenants, as opposed to performance covenants, appear to be the main mechanism that lowers the speed of adjustment, delaying the speed of capital structure adjustment by 86%. We find that the speed of adjustment is reduced more for strict capital covenants than for strict performance covenants. We also show that, for firms that are cash and financially constrained, covenants impede the speed of adjustment even more. Lastly, we show that the negative relationship between covenants and the speed of adjustment is more pronounced for firms that are over-levered.

Based on the framework of the dynamic adjustment model, this paper examines the impact of dividend policies and financing strategies on the speed of capital structure adjustment and explores the relationship between dividend distribution and financing behavior. The empirical results show that if the firm pays less cash dividends, the capital structure adjustment speed is faster, and the dividend distribution behavior conflicts with financing needs. If the firm pays more cash dividends, the capital structure adjustment speed is slower, and the high dividend policy conflicts with market timing financing strategies. In a word, the behavior of dividend distribution has a significant impact on the speed of capital structure adjustment, and the conflict between dividend distribution and financing strategy affects the speed of capital structure adjustment. This paper provides a new perspective for optimizing capital structure, regulating dividend distribution, and evaluating the rationality of financing behavior.

This paper examines the impact of trade credit on the speed of capital structure adjustment toward target leverage using an integrated dynamic partial adjustment model. Trade credit is an important substitute for debt financing and gives firms a low-cost means of adjusting leverage toward the target capital structure in China. We measure trade credit by accounts payable. Using the public listed company data from 1998 to 2016, we find that trade credit accelerates capital structure adjustment. The asymmetric impacts on the capital structure adjustment speed in different situations are also evidenced. The positive impact of trade credit on the speed of capital structure adjustment is more pronounced for over-levered firms. The trade credit also accelerates the speed of capital structure adjustment more quickly for high market share firms. Our results imply that firms use trade credit to save cash flow and restore the leverage level to the target capital structure in China.

The purpose of this paper is to test empirically the financing behavior and the adjustment speed of capital structure by information asymmetry in a integrated framework. In this paper, we use firm-size measuring-value of information asymmetry. Target leverage ratio use two way that one is estimated value and the other is average leverage ratio value. The sample of firms comes from the period of 2003∼2007. According to static tradeoff theory, an optimum financial structure exist by the tradeoff between tax saving by debt and bankrupcy costs. The main results of this study can be summarized as follows. First, Korean listed firms pursue the target capital structure. The results of this study show that Korean listed firms have a significant positive degree gap between the target leverage ratios and the actual leverage ratios. This results suggest that firms may have debt financing behavior toward the target capital structure. Second, Korean firms whose the target leverage ratio is above the actual ratio are expected to increase actual leverage ratio to meet target capital structure. Using samples of this category, there are no significant differences of the gap between the target leverage ratios and the actual leverage ratios between large firms and small firms. Low information asymmetry firms are likely to know their target capital structure compare to high information asymmetry firms. Thus, low information asymmetry firms can change the capital structure when they needed. But, the small firms with high information asymmetry have difficulties to know their target capital structure. The insignificant results may comes from their problems of capturing the target capital structure. Third, firms whose target leverage ratio is below the actual ratio are expected to reduce the actual leverage ratio. Using the average ratio as measure of the target ratio, the results indicate that the gap between the target leverage ratios and the actual leverage ratios is significant negative for the large firms of this category. The results suggest that the large firms can easily change the target capital structure compare to the small firms. Fourth, it is expected that high information asymmetry firms tend to borrow money rather than issue corporate bonds due to the costs of issue. However, the results are insignificant. This may be sampling error due to the selection limitation of the listed firms. For the finer measurement of the information asymmetry, various proxies such as analysts reports and the ratio of book and market values are recommended for the further study. Fifth, the adjustment speed of the capital structure for total Korean listed sample firms is close to 0.27. which is similar but lower than the results of the previous Korean listed firms studies. The results show the adjustment speed for the large firms is lower than that of the small firms. The adjustment speed of the capital structure for the large firms close about 24 percents of the gap between their actual and target debt ratio within one year. The adjustment speed of the capital structure for the small firms close about 36 percents of the gap between their actual and target debt ratio within one year. This results suggest that the small firms' adjustment speed of capital structure is faster than the large firms' adjustment speed of capital structure. The results are similar to the previous Korean listed firms studies. However, this is not supported by the hypothesis that the large firms have fast adjustment speed due to the low information asymmetry. When there is a gap between the target leverage ratio and the actual leverage ratio, firms are expected to reduce this gap by taking financing behavior. This paper empirically examined the financing behavior and the adjustment speed of the capital structure for Korean listed firms based on information asymmetry framework. Firm size is used as the proxy for information asymmetry.

This study has analyzed the effect of corporate social responsibility on the adjustment speed of capital structure towards the optimal or targeted one, by using data from the non-financial sector of Karachi Stock Exchange for years 2006 to 2014. The study has used structural equation modeling. The study has concluded that the relationship between CSR and speed of capital structure adjustment is significant through the mediating role of profitability. CSR has been found positively related to firm's profitability and profitability has been found negatively related to the speed of capital structure adjustment so the conclusion has been made for CSR and speed of capital structure adjustment relationship that higher the CSR is, lower will be the speed of capital structure adjustment.

This paper established dynamic adjustment model of capital structure and analyzed the factors affecting the adjustment speed of capital structure. Based on the unbalanced panel data of Chinese nonfinancial listed companies from 1997 to 2006, this empirical study shows that all dynamic tradeoff theory, pecking-order theory and market-timing theory can explain the adjustment speed of capital structure in some degree, though the three theories have different theoretical basis. If a company dynamically adjusts its capital structure, then its target capital structure is decided based on dynamic tradeoff theory, its adjustment approaches is decided based on pecking-order theory, and its adjustment time is decided based on market-timing theory. So it is necessary to combine the three theories to analyze the determinants and adjustment of capital structure.

Guo, X.; Liang, P., and Xie, Z., 2020. Executive stock ownership, dynamic adjustment of capital structure and corporate performance: Evidence from Chinese listed marine industry companies. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 300–304. Coconut Creek (Florida), ISSN 0749-0208.Taking the Chinese A-share listed companies traded at Shanghai Stock Exchange and Shenzhen Stock Exchange from 2010 to 2017 as samples and further investigating companies concerned with marine industry, this paper conducts empirical research on the impact of executive stock ownership on capital structure adjustment and corporate performance. It also verifies whether the speed of adjustment and degree of capital structure deviation have mediating effects on the relationship between executive stock ownership and corporate performance. The research found that executive stock ownership significantly promotes capital structure adjustment, which exerts a certain degree of mediating effect on executive stock ownership and corporate performance, and that on differentiated levels of corporate debts, such an effect is more obvious in the over-indebted companies. When the executive stock ownership is less than 5%, the effect is more significant. In the group concerned with marine industry, the speed of capital structure adjustment and the degree of capital structure deviation exert partial mediating effects on the relationship between executive stock ownership and corporate performance.

Balancing debt levels with capital needs is a key challenge in corporate financing decisions. The speed of capital structure adjustment (SOA) determines how efficiently firms return to their target leverage after deviations, thereby affecting risk control, the cost of capital, and strategic resilience. As artificial intelligence (AI) increasingly permeates corporate operations and governance, whether and how AI enhances SOA has become an important question. This study investigates the impact of AI on SOA using panel data on Chinese A-share listed firms from 2010 to 2023. We employ partial adjustment models and fixed effects estimation, supplemented by alternative AI proxies and leverage measures, system GMM, one- and two-year lag regressions, propensity score matching (PSM), and two-stage least squares (2SLS) methods to ensure robustness. The results show that AI significantly accelerates SOA, primarily by enhancing the information environment and mitigating operational risk. Heterogeneity analyses reveal that the effect is strongest at moderate board independence and among low-growth firms. These findings deepen our understanding of how emerging technologies influence corporate financing decisions and provide practical implications for managers and policymakers seeking to optimize capital structure in the era of AI.

Studies show that capital structure choice varies over time and across firms and that macroeconomic conditions are important factors in analyzing firms' financing choices. However, studies have largely ignored the impact of macroeconomic conditions on the adjustment speed of capital structure toward targets. Hackbarth et al. (2006) develop a contingent model for analyzing the impact of macroeconomic conditions on dynamic capital structure choice. Allowing for dynamic capital structure adjustments, their model predicts that firms should adjust their capital structure faster in booms than in recessions. We employ U.S. data over a 30 year sample period to test the relationship between macroeconomic conditions and capital structure adjustment speed using both two-stage and integrated partial adjustment dynamic capital structure models. We find evidence supporting the prediction from Hackbarth et al's theoretical framework that firms adjust to target leverage faster in good states than in bad states, where states are defined by term spread, default spread, GDP growth rate, and market dividend yield. Our results also support the pecking order theory in that under-levered firms adjust faster than firms that are over-levered. We find evidence favoring the market timing theory implication that under-levered firms have less incentive to adjust toward target leverage when stock market performance is good, as measured by dividend yield on the market and price-output ratio. Robustness tests demonstrate that our speed of capital structure adjustment cannot be simply explained by firm size, the degree of deviation from target, or by the definition of debt ratio. Our results are also robust to potential boundary issues.

Using Chinese A-share listed companies from 2008 to 2022 as the research subjects to examine the spillover effects of regulatory penalties on capital structure adjustment, that is, what impact penalties against interlocking companies have on the speed of capital structure adjustment of observing companies with whom they share directors. The study found that penalties against interlocking companies increase the speed of capital structure adjustment of observing companies. After applying robustness and endogeneity tests such as parallel trend tests, PSM-DID, system GMM estimation, placebo tests and change measures of capital structure, the conclusion remains valid. The results of heterogeneity analysis based on the characteristics of the observing companies show that the spillover effect is more significant in companies with capital structure below the target structure, companies with high degree of director network centrality, companies that receive more government subsidies, and larger companies. This paper reveals the existence of spillover effects from regulatory penalties imposed by the China Securities Regulatory Commission, provides a theoretical basis for listed companies to optimize their capital structure, and provides evidence to support the healthy development of capital.

This study evaluates the impact of firm-specific, industry-specific, and macroeconomic determinants on the speed of capital structure adjustment and to see if COVID-19 impacted these relationships. Using quarterly data of all listed non-financial firms in Pakistan for the period 2016-2021, a dynamic panel data model using the generalized method of moment (GMM) was used for estimation. It was found that firm size, growth potential, non-debt tax shield, and GDP growth positively impact firm leverage, while profitability and tangibility negatively impact leverage. The study found evidence of convergence to target leverage by Pakistani firms. These firms' capital structure adjustment speed was estimated as 16.7% per quarter. Moreover, COVID-19 was not found to affect the adjustment speed of firms, directly. Furthermore, greater distance from target leverage, growth potential, and GDP growth rate resulted in a lower speed of adjustment, whereas higher profitability and liquidity were found to increase the speed of adjustment.

Main Purpose - The research objective is to explain the factors that determine the speed of capital structure adjustment based on market concentrations on profitability, company growth, liquidity, exchange rates and inflation.Method - The research method used is the explanatory method with a causality approach. The unit of analysis for this research is non-financial sector issuers listed on the Indonesia Stock Exchange in 2009-2015.Main Findings - This research finds that the structure-conduct-performance theory can be used as a theory that explains the speed of capital structure adjustment. In addition, the results of the study also found the exchange rate to be a driving factor in increasing the speed of capital structure adjustment.Theory and Practical Implications - Research findings provide support for the structure-conduct-performance theory which indicates that market concentration is a determining factor in company behavior in adjusting capital structure.Novelty - This study uses the theory of performance-behavior structure in explaining the variables that determine the speed of capital structure adjustment.