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We expand the recent literature on the dynamics of capital structure decisions by investigating the impact of national culture on firms' optimal debt ratios and their dynamic re-adjustment process. To this end, we aim at estimating firm-specific speeds of leverage adjustment, allowing for heterogeneous dynamics in firms' capital structure.

We use dynamic panel data estimators to analyze the impact of cultural factors on the dynamics of debt ratios.

We show that national culture affects the optimal level of leverage and the dynamic rebalancing of debt ratios, both directly and indirectly, by altering the effect of firm characteristics and macroeconomic factors on firms' financing behavior. Firms converge faster towards the optimal leverage in countries with a stronger attitude to conform with the norm, while they are slower where there is a higher propensity to intellectual autonomy. A higher risk aversion and long-run propensity induce over-levered firms to reduce leverage faster, making the adjustment process strongly asymmetric. Moreover, national culture also produces indirect effects by mitigating the impact of asymmetric information on capital structure decisions. Indeed, firms in more individualistic countries display a lower speed of adjustment and a stronger effect of firm characteristics associated with higher agency costs. On the contrary, firms in countries with a higher tendency to conform to social norms, less individualistic and more long-term oriented have a higher adjustment speed and appear to suffer less from agency issues. Our results therefore highlight how national culture affects agency problems within firms, thus suggesting the adoption of country-specific corporate governance provisions accounting for the effects of local cultural traits on managers' behavior.

We expand the capital structure and governance literature by showing how cultural traits impact on the dynamics of debt ratios. In particular, we show how cultural traits may mitigate or exacerbate the role of agency issues on firms' behavior, hence suggesting that cultural factors may interact with governance rules in shaping firms' decisions. Therefore, our work highlights how policy-makers should include cultural aspects when defining regulation concerning corporate governance.

This study aims to understand how quickly Japanese banks readjust their capital ratios (leverage, regulatory capital, tier-I capital and common equity) following an economic shock.

This study uses a two-step system GMM framework to test the study's hypotheses using the annual data of Japanese commercial and cooperative banks ranging from 2005 to 2020.

The findings show that banks adjust their leverage ratio faster than regulatory capital, tier-I capital and common equity ratios. In addition to that, the results reveal that the speed of capital adjustment is higher for commercial banks than for cooperative banks, suggesting higher economic costs and implications for commercial banks. Furthermore, it is worth noting that well-capitalised (under-capitalised) banks tend to prioritise the adjustments to common equity (leverage) before considering the adjustments to leverage (common equity). According to the results, high-liquid (low-liquid) banks alter their regulatory capital and tier-I capital ratios (leverage) more quickly (more slowly) than low-liquid (high-liquid) banks.

The findings suggest that when formulating and implementing new banking regulations, particularly in assessing and adjusting specific capital requirements under Pillar II of Basel III, management (including bankers, regulators and policymakers) should consider the heterogeneity observed in the rate of capital adjustment across various bank characteristics. Additionally, bank managers should also consider the speed of adjustment when determining optimal half-life and target capital structures.

To the author's knowledge, this study represents a pioneering investigation into the rate of adjustment of capital ratios (leverage, regulatory, tier-I and common equity) within Japan's banking sector. The study employs a comprehensive dataset encompassing both commercial and cooperative banks to facilitate this analysis. A notable contribution to the existing body of literature, this study offers a detailed analysis and emphasises the varying degrees of adjustment in capital ratios. The study also highlights the heterogeneous nature of the adjustment rate in these ratios by categorising the data into well-capitalised, under-capitalised, highly liquid and low-liquid banks.

This research intends to investigate the impact of economic policy uncertainty (EPU) on the firm's leverage and its adjustment speed.

This study applies dynamic panel data modeling by using a partial adjustment model. The study is based on secondary data of the non-financial firms that are listed on the Pakistan stock exchange. For the analysis purpose, the study applies the generalized method of moments (GMM) estimation technique and uses a newly developed text-based measure of economic policy uncertainty.

The results show the negative impact of EPU on leverage decisions but a positive impact of EPU on leverage speed of adjustment for both, short-run and long-run economic policy shocks. Additional analysis reveals that the negative influence of long-run policy shocks on leverage decisions is moderated through profitability, and the negative influence of short-run policy shocks on leverage is moderated through firm size, tangibility and available growth prospects. However, the significant positive impact of EPU on the leverage speed of adjustment in both short and long-term policy shocks indicates that the speed of adjustment for these firms is not affected by policy shocks.

This research contributes to the existing literature on capital structure dynamics,by investigating the impact of EPU on firm financing decisions and estimating the adjustment speed of capital structure in a developing market context. The study also extends the existing literature by applying the concept of long-run and short-run economic policy uncertainty in the capital structure dynamic framework. Additionally, the new news-based measure of EPU is used. Moreover, it also looks into the COVID-19 effect on the relationship.

This paper aims to investigate the non-homogeneity in the speed of adjustment (SoA) of the capital structure of manufacturing companies. It also attempts to study the key determinants that accelerate the speed of adjustment towards the target leverage level.

Using the dynamic panel fraction (DPF) estimator on the partial adjustment model, the study captures the heterogeneous SoA of 2,866 firms across eight prominent sectors of the Indian manufacturing industry from 2009 to 2020. To ensure robustness, the empirical inferences of DPF are cross-verified with the estimates of panel-corrected standard errors (PCSE).

The authors find a combination of the capital structure's slow, moderate and rapid adjustment speed along with the relevance of trade-off theory. Interestingly, the lowest and fastest SoA is recorded by the dwindling textile sector and expanding food and agro sector, respectively. Profitability, firm size, asset tangibility and non-debt tax shields are the key firm-specific parameters that impact the SoA towards the target.

Availing the rarely employed estimator ‘DPF’ and the objective of documenting diverse and non-uniform adjustment speeds across the Indian manufacturing sectors marks a novel addition to capital structure literature.

This paper aims to test the empirical validity of the dynamic trade-off theory in its symmetric and asymmetric versions in explaining the capital structure of a panel of publicly listed US industrial firms over the period from 2013 to 2019. It analyzes the existence of an adjustment of leverage toward its target level and whether the speed of this adjustment is influenced by the debt measure, the model specification or/and the fact that the actual debt ratio is higher or lower than its long-term target level.

This paper uses a quantitative research methodology using panel data analysis under the partial adjustment model and the error correction model using the generalized moment method in first differences and in systems to explore the dynamic nature of firms’ capital structure behavior.

The results show that the effects of the conventional determinants of leverage are globally consistent with the trade-off theory predictions. The dynamic versions confirm that firms exhibit leverage-targeting behavior. Although this speed of adjustment (SOA) depends on the debt and model specifications, it is around 60% on average. The estimated SOA is higher for the market leverage measure compared to the book leverage. The asymmetric adjustment model reveals that firms are more sensitive to reducing leverage than increasing it when they are away from their target; overleveraged firms exhibit approximately 5% faster adjustment than underleveraged firms when book leverage is used.

The originality of this research paper lies in its development and test of an asymmetric model to allow the leverage adjustment speed to vary depending on whether the firm’s debt ratio is above or below its target level and the methodological approach as well as the different model specifications used and the insights generated through the application of rigorous econometric techniques.

This study aims to examine the impact of corporate governance on the speed of adjustment (SOA) of capital structure in a developing market, Pakistan.

The study's sample includes 173 non-financial enterprises that were listed on the Pakistan Stock Exchange (PSX) between 2011 and 2020. The capital structure of the sample companies is determined by the ratio of total debt to total debt plus the market value of equity. Corporate governance is measured by board size, independence, CEO duality, management ownership, blockholders ownership and institutional ownership. A two-step difference GMM model was used to achieve the study's objectives.

Through applying the reduced form model approach, we discovered that corporate governance variables have a considerable negative impact on the speed of targeted leverage adjustment in sample firms. Additionally, to check the robustness of results, the two-stage technique used to examine this corporate governance-SOA relationship. Furthermore, we discovered that smaller enterprises modify their capital structure more than larger firms. Furthermore, corporations prioritize short-term debt adjustment above long-term debt adjustment.

The study's findings provide further information to company managers and investors on the relationship between corporate governance quality and the pace of adjustment towards targeted leverage across Pakistani enterprises. Furthermore, this study adds new information from growing countries such as Pakistan to the existing literature, which can help regulatory authorities and policymakers improve the quality of corporate governance. It is commonly known that improving the quality of corporate governance practices improves the firm's capital structure, which benefits all stakeholders.

In the context of developing economies, the academic literature lacks research that examine the impact of corporate governance on dynamic capital structure decisions. This study intends to fill this gap.

We aim to analyze the capital structure heterogeneity for manufacturing and service sector firms. Additionally, we analyze the impact of the COVID-19 pandemic on the leverage adjustments of corporate firms.

This study applies the two-step system generalized method of moments (system-GMM) and panel data of 1,115 manufacturing and 482 service sector firms listed with the Bombay Stock Exchange (S&P BSE) from 2010 to 2023. We developed and analyzed three models. Model 1 analyzes the leverage determinants and speed of adjustment (SOA) for the manufacturing and service sectors. Model 2 evaluates the leverage SOA for various sub-sectors, and Model 3 analyzes the impact of the COVID-19 pandemic on the leverage SOA.

This study suggests the three following. First, the direction of leverage determinants suggests that manufacturing firms are highly tangible. In contrast, service sector firms are high-growth firms and recorded a higher SOA (12.01%) than manufacturing (9.09%). Second, analyzing the leverage heterogeneity, we found that SOA varies across the sub-sectors. For manufacturing, food and beverage sub-sector recorded the highest SOA (12.58%), while consumer durables reported the lowest (6.38%). Communication recorded the highest (24.15%) for services, while industrial services recorded the lowest (11.18%). Third, firms across sectors and sub-sectors increased their SOA during COVID-19 pandemic.

This in-depth analysis of leverage heterogeneity for different sectors and subsectors will assist policymakers, corporate managers and other stakeholders in making agile financial decisions.

The analysis of leverage heterogeneity for the manufacturing and service sector from the emerging Indian economy marks a novel contribution to existing literature.

The behavioural theory adds a new paradigm of analysis with the assumptions of the decision maker’s cognitive biases and their repercussions on financing decisions. The aim of the study is to analyse the repercussions of these biases on the adjustment speed of firm’s capital structure toward the optimal level.

Based on a partial adjustment model, the study uses the Dynamic Panel Fractional estimator to analyse panel data from 4,990 Portuguese entrepreneurial firms.

The results show that the cognitive overconfidence bias impacts the entrepreneurial firm’s capital structure. In fact, the firms run by overconfident managers adjust more slowly than their counterparts. Furthermore, the findings suggest that entrepreneurial firms make relatively fast adjustments toward the optimal debt level and follow a hierarchical financing order in the funding process.

The results of this paper are not only interesting to the academia, but also contain practical implications for corporate, institutional and business policy and governance. First, the paper introduces a new measure of cognitive bias in optimistic managers, which is useful for current and future academic research. Also, in practical terms, the findings of the paper reveal that when a company is contemplating hiring a manager, it should consider whether they need an optimistic or non-optimistic manager based on the company's present life cycle or situation.

The current analysis extends the existing literature. The study suggests that financial classical and behavioural paradigms should not be separated, which can provide evidence to help narrow the gap between these two major perspectives.

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

Recognizing the severity of COVID-19 on the US economy, the authors investigate the behavior of US-listed firms towards leverage speed of adjustment (SOA) during the pandemic. While prior evidence (based on an international study) shows that firm leverage increased during the pandemic leading to a higher SOA toward leverage ratios, leverage for US firms during the same period reduced drastically. Yet there is a dearth of empirical studies on the behavior of US-listed firms' SOA during the pandemic. The authors fill this void.

The study includes US-listed non-financial and non-utility firms for the period 2015Q1-2021Q4, covering a total sample of 45,213 firm-quarter observations. The authors’ empirical strategy is based on the generalized method of moments (GMM) and firm-fixed effect methodology, controlling for firm- and quarter-fixed effects.

Three main findings are established: (1) while the SOA toward book target increased during the pandemic, SOA toward market target increased significantly only for less valued and cash-constrained firms; (2) firms in states most impacted by the pandemic adjusted faster towards target ratio; and (3) while the emergence of the pandemic and the overall firm-level risk increased (decreased) the deviation from book (market) target, firm-level risk partially mediated the effect of the pandemic on how far firms deviated from target ratio.

This study enhances our understanding of leverage adjustment during the crisis and shows that risk avoidance motive and the market value of firms are key determinants of convergence rate during the crisis and further demonstrates that market leverage is more sensitive to market dynamics. As such, caution must be taken when dealing with and interpreting market leverage SOA.

Although prior evidence based on international study provides insights into how firms behave toward their leverage ratios because of the pandemic, little is known about how US firms react to the pandemic in terms of the target ratios, particularly (1) since the USA is one of the severely affected countries and (2) firms in the USA reduced their leverage ratios as against what prior evidence shows. The authors provide evidence to explain how and why US firms reacted toward their SOA during the pandemic.