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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 conduct a comprehensive methodological review, exploring the strategies used to address endogeneity within the realms of corporate governance and financial reporting.

This research reviews the application of various methods to deal with endogeneity issue published in the 10 journals covering the corporate governance discipline included in the Web of Science’s Social Sciences Citation Index.

With a focus on empirical studies published in leading journals, the author scrutinizes the prevalence of endogeneity and the methodologies applied to mitigate its effects. The analysis reveals a predominant reliance on the two-stage least squares (2SLS) technique, a widely adopted instrumental variable (IV) approach. However, a notable observation emerges concerning the inconsistent utilization of clear exogenous IVs in some studies, highlighting a potential limitation in the application of 2SLS. Recognizing the challenges in identifying exogenous variables, the author proposes the generalized method of moments (GMM) as a viable alternative. GMM offers flexibility by not imposing the same exogeneity requirement on IVs but necessitates a larger sample size and an extended sample period.

The paper sensitizes researchers to the critical concern of endogeneity bias in governance research. It provides an outline for diagnosing and correcting potential bias, contributing to the awareness among researchers and encouraging a more critical approach to methodological choices, recognizing the prevalence of endogeneity in empirical studies, particularly focusing on the widely adopted 2SLS technique.

Practitioners, including corporate executives and managers, can benefit from the study’s insights by recognizing the importance of rigorous empirical research. Understanding the limitations and strengths of methodologies like 2SLS and GMM can inform evidence-based decision-making in the corporate governance realm.

This study aims to measure the impact of information and communication technology (ICT) infrastructure on divorce for a sample of developed countries for the period (2012-2021).

This paper uses fixed effect and generalized method of moments (GMM) estimation to delve into the impact of eight ICT infrastructure factors on divorce. The analyses are based on data collected from the World Bank Development Indicators.

The fixed effect analysis revealed that an increase in both fixed-telephone subscriptions and population covered by at least a 4G led to an increase in divorce. However, an increase in mobile cellular subscriptions and active mobile broadband subscriptions lead to a decrease in divorce. The results of the GMM estimator showed that fixed broadband internet prices, mobile broadband internet prices, the percentage of the population covered by the 4 G mobile network and fixed-telephone subscriptions had a substantial effect on divorce. While fixed broadband subscriptions, active mobile broadband subscriptions and mobile cellular basket were found to hinder divorce.

The findings of this study contribute to the existing literature by highlighting the impact of ICT on divorce in a sample of developed countries. Furthermore, it helps decision-makers and families to understand the causes of divorce related to ICT infrastructure in these societies, so they can understand this phenomenon and provide proactive policies.

This study used multiple factors to measure ICT infrastructure as well as the GMM estimator to delve into the impact of ICT on divorce.

This study examines the linear and non-linear effects of enterprise risk management (ERM) and corporate governance (CG) on insurers’ risk-taking behaviour.

The study employed panel data of 63 insurers from South Africa over the period 2015 and 2019. The study used the generalised method of moments (GMM) to determine the direct relationship, while the dynamic panel threshold technique was utilised to discover whether there is non-linearity in the relationship and the threshold level at which ERM and CG stimulate insurance risk-taking.

The result from the GMM elicits a positive relationship between ERM and risk-taking, implying that insurers with a robust ERM system are more likely to pursue higher risks. The empirical evidence also suggests that board size and board independence improve insurers’ risk-taking. Contrarily, gender diversity shows an inverse relationship with risk-taking. The dynamic panel threshold regression confirms non-linearities between ERM, CG and risk-taking. The empirical evidence indicates a U-shaped relationship between ERM and risk-taking, implying that a robust ERM system increases insurers’ risk-taking and vice-versa. Further, board size and independence reveal an inverted U-shaped relationship, suggesting that larger boards and a higher proportion of independent directors exhibit lower risk-taking. However, gender diversity presents a negative relationship, demonstrating a strong impact at higher threshold levels. This tells that the presence of females on the board reduces insurers’ risk-taking preferences.

Due to the risk-bearing nature of the insurance business, it is required that they ensure a robust ERM system for prudent risk-taking decisions. This demands strict adherence to ERM principles and allocating sufficient resources for effective implementation. Also, there is a need for strong CG structures that pay more attention to diversity when selecting board members due to their influence in ensuring improved risk-taking choices.

This study contributes to the existing literature by providing insights into the under-researched role of ERM and CG in insurers’ risk-taking behaviour. The study further extends the literature by providing evidence on the non-linearity and threshold levels at which ERM and CG influence insurers’ risk-taking choices. The findings are unique and contribute to the growing body of literature documenting the need for strong ERM and CG systems in insurance companies.

The purpose of this paper was to examine the nexus between conditional exchange rate volatility and economic growth in BRICS countries. Further, the dynamic causation between economic growth and exchange rate volatility is also examined.

We employed three techniques, namely, dynamic panel models, static panel models and Dumitrescu and Hurlin (DH) panel causality test to examine the economic growth–conditional exchange rate volatility nexus in BRICS countries.

The overall results showed that conditional exchange rate volatility has a negative and significant effect on economic growth. Interestingly, the results showed that whenever the exchange rate volatility exceeds the 0–1.54 range, the economic growth of BRICS is reduced, on average, by 5%. Further, the results of the causality test reconciled with that of ARDL wherein unidirectional causality from exchange rate volatility, exports, labour force and gross capital formation to economic growth was found.

The urgent recommendation is to develop and align fiscal, monetary, trade and exchange rate policies, either through creating a common currency region or through coordinated measures to offset volatility and trade risks in the long run. Further, to offset the impact of excessive exchange rate changes, BRICS economies can set up currency hedging systems, implement temporary capital controls during periods of extreme volatility or create currency swap agreements with other nations or regions. Last, but not least, investment and labour policies that are coherent and well-coordinated can support market stabilisation, promote investment and increase worker productivity and job prospects.

Researchers hold contrasting views regarding the effect of exchange rate volatility on economic growth. Some researchers claim that exchange rate volatility reduces growth, and several shreds of empirical evidence claim that lower exchange rate volatility is linked with an increase in economic growth, at least in the short run. However, the challenge lies in establishing the optimal range beyond which exchange rate volatility becomes detrimental to economic growth. The present study contributes to this aspect by seeking to identify the optimal spectrum beyond which excessive shifts in exchange rate volatility negatively affect economic growth, or endeavors to define the acceptable spectrum within which these fluctuations actually boost growth. To the best of our knowledge, this study is the first to analyse the given research area. The present study used a dummy variable technique to capture the impact of permissible exchange rate band on the economic growth.

The purpose of this study is to investigate and compare the dynamic leverage policies of Islamic and conventional banks within selected Organization of Islamic Cooperation (OIC) countries. The study specifically focuses on the concepts of leverage procyclicality and prospect theory.

To achieve the research objectives, the study uses data from three distinct periods: Crisis I (2007–2009), Crisis II (2011–2012) and Crisis III (2020). The analysis uses dynamic panel-data regression, using the generalized method of moments (GMM) technique.

The research findings indicate that both Islamic and conventional banks demonstrate leverage procyclicality. Interestingly, Islamic banks exhibit weaker leverage procyclicality during normal conditions but display stronger procyclicality during crises compared to their conventional counterparts. The application of prospect theory reveals that both bank types exhibit risk-taking or risk-averse behavior through leverage under certain financial and market performance measures as the first-level domain of the gain-vs-loss condition. Furthermore, during crises (as the second-level domain of the normal-vs-crisis condition), both Islamic and conventional banks experience heightened leverage. Notably, Islamic banks, owing to their lower risk exposure and greater shock resilience, demonstrate lesser risk-taking behavior through leverage than conventional banks, both during periods of underperformance and worsening conditions amid crises. These findings validate the extension of prospect theory's applicability in a two-level domain perspective. The dynamic nature of leverage policy, being procyclical and adhering to prospect theory, also varies following different crises specifically.

The study's limitations include the unequal crisis periods (Crises I, II and III), leading to an imbalanced examination of their effects, certain financial and market performance metrics that fail to corroborate the expected hypotheses and the limited generalizability of findings beyond the selected OIC countries.

Understanding the intricate dynamics and behavioral aspects of leverage policy for both Islamic and conventional banks, particularly during crisis scenarios, proves crucial for reviewing banking regulations, making informed financial decisions and managing risks effectively.

This study enriches the current knowledge by presenting two key points. First, it highlights the dynamic nature of leverage procyclicality in Islamic banks, showing a change from weaker procyclicality in normal conditions to stronger procyclicality during crises compared to conventional banks. Second, it expands the application of prospect theory by introducing a dual-level domain context. Examining the comparative leverage policies of Islamic and conventional banks during different crises within OIC countries provides novel insights into leverage procyclicality and behavioral responses.

This study aims to quantify the influence of urbanization on housing prices at the district-based level, while also investigating the heterogeneous impacts across different quantiles of housing prices.

The study uses remote-sensed spectral images from the Landsat 7 ETM+ satellite to measure urbanization, replacing prior reliance solely on urban population metrics. Subsequently, the two-step system generalized method of moments is used to evaluate how urbanization influences district-based housing prices through three spectrometries: Urban Index (UI), Normalized Difference Built-up Index (NDBI) and Built-Up Index (BUI). Finally, this study examines the heterogeneous impacts across various housing price quantiles through Dynamic Panel Quantile Regression with non-additive fixed effects under Markov Chain Monte Carlo simulation.

The study demonstrates that urbanization leads to an increase in regional housing prices. However, these impact magnitudes vary across housing price quantiles. Specifically, the impact exhibits an inverse V-shaped curve, with urbanization exerting a more pronounced influence on the 60th percentile of housing prices, while its effect on the 10th and 90th percentiles is comparatively weaker.

This study uses a novel method of remote sensing to measure urbanization and investigates its effects on housing prices. Furthermore, it provides an empirical application of non-additive fixed effect quantile regression for analyzing heterogeneity.

This study aims to investigate the institutional, macroeconomic and firm-specific determinants of financial leverage in Vietnam and provides new evidence from the dynamic panel fractional estimator.

This study uses a panel dataset of 859 Vietnamese firms from 2008 to 2022 and employs three estimators: Feasible Generalized Least Squares (FGLS), System Generalized Method of Moments (SysGMM) and Dynamic Panel Fractional (DPF), with DPF being particularly suitable for handling fractional dependent variables and the dynamic nature of financial leverage.

The results confirm the dynamic nature of the financial leverage model, with firm-specific factors, institutional factors and macroeconomic factors playing significant roles in shaping firms' financing decisions. The DPF estimator highlights the positive impact of stock market development on leverage. This study contributes to the literature by providing new evidence on the determinants of leverage in Vietnam, using the DPF estimator for more accurate estimation and revealing the significant impact of the size of the banking sector, the size of the stock market, the stock market development index, the financial development index and the corruption perception index on leverage.

This study contributes to the literature by providing new evidence on the dynamic nature of the financial leverage model and the impact of institutional, macroeconomic and firm-specific factors on financial leverage in the context of Vietnam. The use of the DPF estimator allows for a more accurate and reliable estimation of the determinants of leverage, considering the fractional nature of the dependent variable and the persistence of capital structure decisions over time.

This study explores the moderating effect of board gender diversity (BGD) between a firm's Environmental, Social, and Governance (ESG) performance and Economic value added (EVA) using NSE-listed 331 companies' data from 2015 to 2020, forming 1986 firm-year observations.

Our study is based on panel data; hence, we use a system GMM panel regression model to confirm whether the BGD moderates ESG and EVA. We also address the endogeneity issues.

Overall, our study reported a positive moderating effect of BGD between ESG and EVA. Similar results were observed across the chemical and financial services industries. However, in the case of the healthcare and consumer goods industries, we did not find support for the moderating effect.

The implications of our results are considerable and relevant for regulators, governing bodies, and corporate managers. It helps them understand how BGD plays a vital role in influencing the effect of ESG on a firm's EVA.

No existing research has explored the moderating effect of BGD between ESG and EVA, to the authors' best knowledge. Therefore, our study extends the existing literature and further supports resource dependency, agency, and stakeholder theories of corporate governance.

This study aims to respond to the latest research calls to precisely revisit the nexus between corporate green innovation (CGI) and financial decisions through deeply investigating the mediating effect of corporate environmental performance measured by the effectiveness of emission reduction.

This study analyzes nonfinancial-listed firms on the Australian Securities Exchange from 2002 to 2019 using multiple regression analysis on a panel data set. Initially, different static panel data approaches were used. To account for the potential endogeneity issue and generate robust outcomes, the authors apply the one-step system generalized method of moment, two-stage least squares and lagged model approaches.

The results provide a clear indication that the practices of green innovation can favorably contribute to the level of environmental performance, which in turn affect the firm’s ability in opening the new financial doors and shape solid capital structure. In this context, the effective environmental performance fully mediates the nexus between CGI and capital structure of a firm. More importantly, the outcomes are robust and coherent across different estimation techniques.

The originality of this study lies in its utilization of mediation analysis to explore the relationship between CGI and a firm's financial structure. This approach distinguishes it from previous research by offering a thorough and nuanced understanding of how green innovation practices influence the financing decisions of a firm.