Capital Structure Adjustment Research Articles

Effects of Digital Transformation on Dynamic Capital Structure Adjustment: Evidence from China

Over the past two decades, there has been a surge in digital innovation. China is the world’s second-largest digital economy entity and the national strategy to build a digital China is in full swing. Chinese enterprises have received great support while pursuing digital transformation. This study aims to explore the impact of digital transformation on firm dynamic capital structure adjustment by taking evidence from Chinese listed firms. Based on the data of 3855 Chinese A-share listed firm-year observations during 2011–2021, this study employed a panel data fixed effects model to ascertain the association between the proposed variables. The results indicate that digital transformation has a significant positive effect on accelerating capital structure adjustment speed. Furthermore, we show that digital transformation promotes dynamic capital structure adjustment through financial flexibility. The impact of digital transformation on dynamic capital structure adjustment is characterized by heterogeneity in the ownership type, asset size, and credit cycle. In addition, reduced financing constraints and growing economic policy uncertainty will moderate the relationship between digital transformation and dynamic capital structure adjustment. Our findings provide insights into how digital transformation is driving companies to accelerate their capital structure adjustment speed to the optimal, and supplements the existing literature on the determinants of dynamic capital structure adjustment.

The Speed of Adjustment Capital Structure in The Perspective of Structure-Conduct-Performance Theory

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.

Sectoral analysis of capital structure adjustment: evidence from emerging market

PurposeThis 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.Design/methodology/approachUsing 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).FindingsThe 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.Originality/valueAvailing 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.

FINANCING AND CAPITAL STRUCTURE

The capital structure denotes the composite blend of debt and equity utilized by a business entity.In the past, the concept of capital structure was commonly categorized as a highly specialized and technical aspect of corporate management that pertained to a limited number of individuals within an organization.In the perspective of a conventional business individual, the likelihood of this vicinity to produce ample profits was rather low.The generation of considerable revenue is observed to be comparatively pronounced in certain financial domains, such as appropriately identified investment initiatives, when juxtaposed with other areas of financial pursuits.In recent times, there has been a substantial transformation in the prevailing circumstance.The area of capital structure has garnered significant attention and interest within academic discourse.The present discourse concerns both the theoretical and practical aspects of finance.The utilization of said funds may be extended towards facilitating the comprehensive functioning of the enterprise and executing investment operations. The various forms of capital structure commonly recognized include equity share capital, debt financing, preference share capital, and vendor financing.The present study aims to examine various aspects related to capital structure, including the challenges associated with the precise measurement of capital structure. Additionally, individual authors suggest that there exist numerous intriguing areas for future exploration in this domain.Anticipated outcomes encompass factors such as the provision of capital from the supply side, the correlations between capital structure and labor agreements, financial contracting, the dynamic trade-off theory, and the rate of capital structure adjustments. The aforementioned concepts will be subjected to scrutiny to evaluate their potential applicability as findings for research purposes.Some emphasis is also placed on the issue of asymmetric information and moral hazard that may arise between the parties involved in a given scenarioThe role of investors and issuers of diverse securities is fundamental in the financial domain.In the following, we also examine the three fundamental principles underlying the concept of capital structure in the realm of finance. The concept of capital structure irrelevance, the significance of the debt tax shield, and the interrelationship between the financing decisions and firm value represent essential themes in the field of finance.Attention is also focused on the expected financial costs associated with insolvency and their impact on determining the optimal capital structure.These ideas try to figure out if a firm can make more money by changing how it gets its money. Each idea has a unique answer, which means capital structure is a complex but interesting subject.

Impact of risk on capital structure adjustments: Evidence from the African markets

AbstractEmploying panel data analysis, the study investigated the impact of risk on speed and costs of adjustments on target leverage on listed firms from the African markets—a panel data set of 2790 observations for 12 years spanning from 2008 to 2019. Based on the results of the Unit root test and Granger causality test, there are bidirectional relationships between risk and capital structure and vice versa. Additionally, Panel DOLS and System GMM were applied for regression and comparison analysis between the African markets and South Africa. The estimates disclose that when companies experience lower risk, the costs of adjustment toward the target are higher. Hence, companies can re‐adjust their capital structure more easily by issuing external capital over periods of stable economic environments, thereby improving their market value. Considering the case of South Africa, the first DOLS results outlined similar estimates compared to the African market. Conversely, when measured with System GMM, the estimates imply that firms incur difficulties in adjusting costs, thus reducing leverage due to unfavorable macroeconomic indicators in line with the pecking order theory stating that in African economies, companies spend more on expenses and adjust their capital structure slowly to reach their optimal target position.

Shareholder activism: Further evidence on the relationship between activists’ demands and shareholder value creation

AbstractThis research article analyses activist hedge fund campaigns and studies both shareholder value effects around the announcement of a campaign and the value creation over the entire campaign period. Further, we analyze observable returns by campaign objectives. We examine a sample of 197 international activism campaigns, initiated between 2014 and 2019. Significant Cumulative Average Abnormal Returns (CAARs) can be observed in both the short‐term and the entire engagement period event windows. The results from activism differ by an activist investor's objectives and demands. CAARs related to elimination of a general undervaluation, a maximization of shareholder value, and an adjustment of a target firm's capital structure are the highest in our sample. We do not find empirical evidence that board representation or proxy fights increase the CAARs of activist investors’ campaigns. Our study adds to the existing literature by analyzing abnormal returns not only around the announcement of the campaign but also over the entire campaign. We are of the opinion that relying exclusively on short‐term returns poses significant limitations to inferences on shareholder value from activism and therefore applying a longer‐term observation period is warranted.

Local corruption and capital structure

This paper examines how local corruption affects capital structure. With a sample of 6,156 observations from 601 firms listed in Vietnam, we find that local corruption is positively and negatively related to capital structure and capital structure adjustment speed respectively. In addition, our findings show that state ownership reduces the positive effect of local corruption on debt ratio.

Does digital transformation speed up dynamic capital structure adjustment? Evidence from China

This paper examines whether and how digital transformation impacts capital structure adjustment speed. We find that digital transformation speeds up capital structure adjustment. Furthermore, digital transformation can improve the probability of leverage upward (downward) adjustment by issuing debts and dividends (issuing equities and repaying debts). Channel tests show that reducing information asymmetry, mitigating agency problems, and alleviating financial constraints are possible mechanisms. Cross-sectional tests show that the findings are more pronounced for firms in highly competitive industries, located in provinces with high level of market development, and in years of high economic policy uncertainty.

Apital structure adjustment in Latin American firms: An empirical test based on the Error Correction Model

The objective of this article is to analyze the capital structure adjustment of Latin American firms through the pecking order and trade-off theories using a sample of 975 non-financial firms for the period 2000-2017. The results support the existence of a target capital structure. Adjustment speeds ranged between 48.9% and 74.3% and generate a rapid convergence of leverage towards its target level. Financial deficits explained less than half of the changes in debt, which contradicts the pecking order theory. The results of the error correction model indicated that companies dynamically deviate from their long-term capital structure. The convergence speeds in the partial adjustment model increased up to 69.5% and 91.7% with the error correction method. These results are relevant for firms and investors.

Two-Way Fixed Effects Estimation on the Impact of rising house prices on the capital structure of real enterprises in China

Since the implementation of China's reform and opening-up policy, rapid economic growth has led to the rapid development of the real estate market and housing prices have entered the fast lane of growth. As housing prices rise, the allocation of credit funds in China will continue to be tilted towards the real estate sector. This has a "crowding out" effect on the real economy and is not conducive to the positive optimisation of corporate capital structure. Little research exists on the lagged nature of house price inflation and its impact on the capital structure of real enterprises. To fill this gap, this paper investigates the lagged effect of house price changes on the adjustment of capital structure of real enterprises and the heterogeneity between regions based on a two-way fixed effects model with a sample of 30 Chinese provinces over the period 2000-2020. The study finds that in the short run, rising house prices do not have a significant impact on the capital structure of real enterprises. In the long run, enterprises' debt levels rise and their capital structure adjusts negatively. There is a lag in the central and western regions and no lag in the eastern regions. After a series of robustness tests, the results remain significant and robust. This study provides a reference for the government to establish a long-term mechanism for the stable development of the real estate market.

Adjustment speed of capital structure: A literature survey of empirical research

We synthesize empirical studies on the determinants of the heterogeneity in the adjustment speed (speed of adjustment; SOA) of capital structure. These determinants are categorized into six groups, namely, (1) firm-specific characteristics, (2) financial reporting and managerial incentives, (3) corporate governance, (4) informal institutions, (5) financial market attributes and (6) economy-wide attributes. From this analysis, we perceive important potential research questions linked to identifying channels associated with the costs and frictions explaining SOA heterogeneity, including financial reporting quality aspects, firm internal and external monitoring mechanisms and institutional and cultural elements. Interesting avenues for future research also include considering SOA dynamics for comparable cross-country samples and the investigation of the subsequent consequences of capital structure adjustments. JEL Classification: G30, G32, G34, M41

Moderating Role of COVID-19 Crisis on Firm Leverage Speed of Adjustments: Evidence from Pakistan

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.

Capital Structure Adjustment Speed and Ownership Structure: A Research on BIST 100 Index Food Sector Firms

In this study, the capital structure adjustment speed of 19 food sector firms in the Borsa Istanbul (BIST) 100 index has been estimated between 2010 and 2021. The effect of ownership identity on the capital structure adjustment speed has been investigated within the scope of family and non-family firms. The seven firms have been classified as non-family firms (NFF) and twelve as family firms (FF). The capital structure adjustment speed for family and non-family firms has been composed of the classical dynamic partial adjustment model. The Generalized Moments Method (GMM) model has been used as the econometric model in estimating the models. The results obtained from the study revealed that there is no significant difference between the debt ratios of family companies and non-family firms. The adjustment speed of family firms has been determined as 68%, and the adjustment speed of non-family firms has been approximately 56%. The capital structure adjustment speed of family firms is higher than non-family firms. The results show that family firms are less exposed to financial constraints than other firms increasing their borrowing capability, thus enabling them to reach the target debt level faster. The findings suggest that ownership structure plays a vital role in capital adjustment behavior.

Governance of non-state-owned shareholders and corporate capital structure decision: A mechanism test from the opportunistic behavior of management.

It is an important measure in the reform of state-owned enterprises to improve the efficiency of capital operation by introducing non-state-owned shareholders. This paper explores the impact of non-state shareholder governance on capital structure decision-making by using the data of 2008-2021 A-share state-owned listed companies from the perspective of the speed and deviation of capital structure adjustment. The results reveal that only non-state shareholding has no significant impact on the capital structure adjustment of a company. However, the appointment of senior management by non-state shareholders can speed up the capital structure adjustment and lower the degree of capital structure deviation. Moreover, when the capital structure goes down, the appointment of non-state-owned shareholders plays a larger role in accelerating the capital structure adjustment, which makes the deviation from the actual capital structure and the target capital structure smaller. Further research shows that the above relationship between non-state shareholder governance and the optimization and adjustment of the capital structure only exists in local SOEs and competitive SOEs. In addition, the path test found that non-state shareholder governance affects the dynamic adjustment of capital structure by reducing opportunism behavior of management rather than by financing constraints.

Role of risk characteristics on capital structure adjustments: evidence from India

Role of risk characteristics on capital structure adjustments: evidence from India

Technology firms and capital structure adjustment: Application of two-step system generalised method of moments

The study asks whether technology firms adjust their capital structures towards predetermined targets, and if so, at what speed? Also, is there an intra‐industry leverage‐level effect? The study empirically evaluates the listed technology firms in South Africa’s Johannesburg Stock Exchange (JSE). Methodologically, a generalised method of moments (GMM) is em‐ ployed on 34 firms over 21 years (1999–2019), resulting in a sample size of 714 observations. The results show that technology firms adjust their debt‐equity ratios towards target levels with speed above other industries at 45 to 57%. A comparison with prior research shows that this adjustment pace is consistent with the experience of technology firms in Asian emerging markets but differs markedly from that of developed economies. These results support the literature observation that technology is characterised differently in less developed economies, yet research on technology firms’ capital structure dynamics is scant. The results of this study should enlighten industrialists, investors, and policymakers involved with technology industries. Intuitively, the partial capital adjustment process should play an essential role in project financing decisions. Maintaining optimal capital adjustment speeds should lead to better industrial activity like maximised innovation and technology diffusion.

Role of risk characteristics on capital structure adjustments: evidence from India

Role of risk characteristics on capital structure adjustments: evidence from India

Speed of Adjustment of Capital Structure (Empirical Study on the Aviation Industry in Indonesia and Malaysia)

The purpose of this study is to prove how much SOA capital structure, what factors affect the optimal leverage and what factors affect the SOA capital structure in the airline industry in Indonesia and Malaysia. Hypothesis testing in this study was conducted using panel data regression. The sample used is 10 aviation industry companies in Indonesia and Malaysia with 100 observations from 2010-2019. The regression model is determined based on the results of the Chow and Hausman tests. Empirical findings from 100 observations of panel data variables of company size, short-term debt and non-debt tax shield have a positive and significant effect on optimal leverage. Profitability, asset growth, and business risk variables have a negative and significant effect on optimal leverage. Partial adjustment model (PAM) to measure the speed of firm adjustment to optimal leverage. From the partial adjustment model estimation results, the significant leverage lag indicates that airline industry companies in Indonesia and Malaysia adjust their capital structure towards optimal leverage with SOA of 46.20% per year. Generalized methods of moments (GMM) to estimate the speed of capital structure adjustment. The results show that macroeconomic variables, namely GPD growth, have a negative and significant influence on the speed of capital structure adjustment. In conclusion, it is evident that the funding behavior in the airline industry in Indonesia and Malaysia tends to follow the dynamic trade off theory.

Employment protection and leverage adjustment speed: Evidence from China

Stricter employment protection may affect capital structure adjustment speed in two ways. First, it may increase the cost of capital and decrease the leverage adjustment speed. Second, it increases financing needs and capital adjustment speed. Using China's 2008 Labor Contract Law as a natural experiment and the PSM-DID methodology, we find that the latter effect dominates the former. Specifically, stricter employment protection increases leverage adjustment speed, and this effect is more pronounced for non-state-owned firms and firms with larger leverage deviations. Furthermore, transmission channel tests show that employment protection increases firms’ substitution of labor with capital, driving up investment and financing needs. Finally, the increased leverage adjustment speed induced by enhanced employment protection is beneficial to firm performance.

Capital Structure Adjustment Speed in Indonesia: Does Sharia Compliance Matter?

Leverage Speed of Adjustment (henceforth SOA) has previously been studied by researchers; however, the examination of its connection with sharia law has been overlooked. The majority of the literature currently in circulation comes from the Middle East and North Africa (MENA) region and Malaysian markets, so its implications for businesses in Indonesia may not be applicable given local regulations and cultural norms. This study investigates the distinction in the debt levels and the SOA of firms in Indonesia based on compliance to sharia law. The Two-step Generalized Method of Moment (GMM) model was used to calculate the SOA in the leverage model. We discover that sharia compliance plays a role in stimulating the Indonesian firm’s level of debt and leverage SOA. To put it more precisely, sharia firms use less debt and have a slower SOA than conventional firms. Overall, Indonesian firms implement the dynamic trade-off theory in their leverage framework. Instead of relying on conventional debt, which is only available at certain levels, sharia firms must issue Islamic debt instruments to accelerate the speed of adjustment. Even after a robustness test using various sharia compliance approaches, our results remained consistent.