Ioannis Dokas

After the global financial crisis, central banks used unconventional monetary policies, including quantitative easing (QE), to restore financial stability. Although several studies have analyzed the effects of these measures on financial markets, limited attention has been given to how central bank transparency influences the stability of commercial banks operating under these conditions. This study examines the impact of central bank transparency on national banking system vulnerability during periods of QE across eight economies from 2013 to 2019. Using a dynamic two-step generalized method of moments model based on bank-level data, the analysis includes bank-specific variables, monetary policy indicators, macroeconomic determinants, central bank characteristics, and structural factors of the banking sector and applies a fixed-effects panel regression model. The findings show that transparency moderates the effect of QE on bank vulnerability and strengthens banking system resilience. By emphasizing the role of central bank transparency as a key element of monetary policy, this research provides useful evidence for policymakers seeking to improve the effectiveness and credibility of unconventional monetary measures in different banking environments.

Purpose: This study investigates the effect of accrual-based and real earnings management practices on the likelihood of M&A deal withdrawal, highlighting the role of financial reporting quality in the acquirer’s decision-making. Design/methodology/approach: Using a dataset of 1,611 listed nonfinancial EU target firms involved in completed or withdrawn M&A, we implement a logistic regression model to investigate the relationship between earnings manipulation and deal outcomes. Findings: Our findings indicate that target firms engaging in aggressive manipulation practices through accruals, production cost and sales in the period preceding the deal announcement are significantly associated with increased deal withdrawal risk. This demonstrates acquirers’ ability to detect earnings management and incorporate this information into their decision-making process. Furthermore, the influence of earnings management on withdrawal probability remains consistent in conditions of high information asymmetry deriving from the national and industry differences, suggesting that acquirers can effectively evaluate target firms’ financial quality despite limited information. An additional analysis revealed that when target firms operate in common-law countries and regulated sectors, the impact of earnings management on deal withdrawal becomes insignificant. This finding is likely related to the limited opportunities for misleading practices in such business environments. Research limitations/implications: This research focuses on publicly listed target firms, and its findings may not fully reflect the dynamics present in private firms. Furthermore, while it analyzes information asymmetry at the national level, it does not specifically address how these effects might be more pronounced in M&As between developed and emerging countries, particularly using quantifiable measures of information asymmetry. Practical implications: This study emphasizes the need for acquirers to implement thorough due diligence procedures, considering both accrual and real earnings management, especially under conditions of high information asymmetry. It highlights the central role of financial reporting quality in the success of critical corporate events, such as M&As. Originality/value: In contrast to previous research that primarily focused on accrual-based models, this study innovates using both accrual and real earnings management, offering a comprehensive perspective on target firms’ manipulation tactics. This aspect, combined with the selected sample, establishes an innovative approach to the topic of M&As, contributing to enhancing the current literature and providing new research avenues.

Corporate failure prediction remains a major topic in the literature. Numerous methodologies have been established for its assessment, while data envelopment analysis (DEA) has received particular attention. This study contributes to the literature, establishing a new approach in the construction process of prediction models based on the combination of logistic LASSO and an advanced version of data envelopment analysis (DEA). We adopt the modified slacks-based super-efficiency measure (modified super-SBM-DEA), following the “Worst practice frontier” approach, and focus on the selection process of predictive variables, implementing the logistic LASSO regression. A balanced sample with one-to-one matching between forty-five firms that filed for reorganization under U.S. bankruptcy law during the period 2014–2020 and forty-five non-failed firms of a similar size from the U.S. energy economic sector has been used for the empirical analysis. The proposed methodology offers superior results in terms of corporate failure prediction accuracy. For the dynamic assessment of failure, Malmquist DEA has been implemented during the five fiscal years prior to the event of failure, offering insights into financial distress before the event of a default. The model outperforms alternatives by achieving higher overall prediction accuracy (85.6%), the better identification of failed firms (91.1%), and the improved classification of non-failed firms (80%). Compared to prior DEA-based models, it demonstrates superior predictive performance with lower Type I and Type II errors and higher sensitivity as well as specificity. These results highlight the model’s effectiveness as a reliable early warning tool for bankruptcy prediction.

Purpose: This study investigates the dynamic interactions between the financing of entrepreneurship through Private Equity and several factors, such as stock market valuations, gross domestic product and consumer prices, and the effect of monetary policy in the decision for investments. Design/methodology/approach: Our methodology consists in applying a panel vector autoregression approach that allows testing the causality of the variables of interest without assuming any specific direction. We disaggregate private equity to venture capital investments and later stage private equity and we uncover their asymmetric response to the examined factors. All types of investments are shown to be affected by GDP, stock prices, consumer prices and interest rates. However, the effect of the latter three variables are evidently more pronounced in later stage private equity compared to venture capital. Findings: Our findings contribute to the understanding of the motives behind Venture Capital and Private Equity financings and uncover novel paths of the transmission of monetary policy to entrepreneurial finance. Originality/value: The novelty of this research concerns the investigation of the monetary policy impact on investment decisions, including venture capital and private equity. This article provides significant highlights for the first time in the relative literature, offering new knowledge in the investment decision-making process in a dynamic framework.

This study investigates how target firms’ accrual-based earnings management affects the likelihood of cross-border mergers and acquisitions completion failure, emphasizing the roles of corruption, legal efficiency, and geographic distance. Using a sample of 496 European target firms involved in cross-border mergers and acquisitions, the analysis reveals a positive association between earnings management and deal withdrawal. While corruption and legal-system efficiency differences alone show no direct impact, their interaction with earnings management increases the likelihood of deal failure, particularly when target firms operate in more corrupt and less legally efficient countries than their acquirers. Geographic distance demonstrates weak evidence of a negative effect on deal completion when combined with increased earnings management levels. These findings underscore the critical role of earnings management in cross-border mergers and acquisitions outcomes, especially under high information asymmetry stemming from institutional differences.

This study investigates the effect of the characteristics of the board of directors on the accrual and real earnings management level, focusing on the role of the corruption level. The employed dataset consists of 469 European-listed firms from 2011 to 2019. Using a fixed-effect panel data regression model, the results documented that larger boards lack coordination and communication in less corrupt economies, facilitating earnings manipulation through accruals and sales. In highly corrupt countries, oversized boards are associated with increased manipulation of production costs and discretionary expenses. Board meetings are positively related to accrual and sales manipulation in low-corruption countries, and board independence leads to reducing discretionary expenses regardless of corruption level. Board tenure negatively affects accruals and discretionary expenses but tends to increase manipulation through production costs in low-corruption contexts. Additionally, when the CEO serves as the board chairman, it encourages the manipulation of discretionary expenses while reducing real earnings manipulation through sales and production costs. In aggregate, the level of corruption can influence a board’s effectiveness under specific conditions.

Central bank characteristics are important determinants of stock market returns and their volatility. While the literature has examined the effects of transparency and independence, no research has been conducted so far on the effect of central bank credibility on stock market returns’ volatility. A panel regression using financial and macroeconomic data from 45 OECD member countries over the period of 1998–2022 tested the hypothesis that central bank credibility determines stock exchange returns’ volatility. The results indicated that credibility reduces stock returns’ volatility, remaining robust and statistically significant across models. Economic growth also decreases stock market volatility, while money-market interest rates’ volatility, the stock market’s turnover ratio, and economic/financial crises act as amplifying factors of stock market volatility. All variables, except for economic growth, exhibit unidirectional causality, leading to changes in stock market volatility.

Purpose: This study focuses on the banking systems evaluation in Portugal, Italy, Ireland, Greece and Spain (known as the PIIGS) during the financial and post-financial crisis period from 2009 to 2018.Design/methodology/approach: A conditional robust nonparametric frontier analysis (order-m estimators) is used to measure banking efficiency combined with variables highlighting the effects of Non-Performing Loans. Next, a truncated regression is used to examine if institutional, macroeconomic, and financial variables affect bank performance differently. Unlike earlier studies, we use the Corruption Perception Index (CPI) as an institutional variable that affects banking sector efficiency.Findings: This research shows that the PIIGS crisis affects each bank/country differently due to their various efficiency levels. Most of the study variables — CPI, government debt to GDP ratio, inflation, bank size — significantly affect banking efficiency measures.Originality/value: The contribution of this article to the relevant banking literature is two-fold. First, it analyses the efficiency of the PIIGS banking system from 2009 to 2018, focusing on NPLs. Second, this is the first empirical study to use probabilistic frontier analysis (order-m estimators) to evaluate PIIGS banking systems.

Purpose: The scope of this research is to investigate performing loan efficiency for fifty European banks during the period 2008–2017.Design/methodology/approach: The study is structured as a two-stage analysis of performing loan efficiency and its driving factors. In the first stage of the proposed methodology “Data Envelopment Analysis” is used to estimate performing loan efficiency for each bank included in the sample. A bootstrap statistical procedure enhances the findings. In the second stage, the impact of other factors on the efficiency scores of loan performance using tobit regression is investigated.Findings: The results are consistent with the findings of the individual banks' financial analyses. According to the findings of DEA implementation, the evaluated banks may enhance their cost efficiency by 39% on average. In addition, the results indicate that loan efficiency performance improves after 2015, coinciding with the business cycle's upward trend. The tobit regression is employed in the second stage to examine the influence of bank-related and macroeconomic factors on banks' loan management efficiency. According to the findings of the tobit regression, three factors, namely the capital adequacy ratio, GDP per capita and managerial inefficiency, have a substantial influence on performing loan efficiency.Originality/value: This research investigates the effectiveness of European economic policy in protecting the European banking system from the consequences of the sovereign debt crisis in several euro area members. The results highlight the distance of the Eurozone from the level of the ‘optimal currency area’.

GDP, monetary variables, corruption, and uncertainty are crucial to energy policy decisions in today’s interrelated world. The global energy crisis, aggravated by rising energy prices, has sparked a thorough analysis of its causes. We demonstrate the significance of categorizing research by influence channels while focusing on their implications for energy policy decisions. We investigate the growing number of studies that use GDP, inflation, central banks’ characteristics, corruption, and uncertainty as critical factors in determining energy policies. Energy prices fluctuate because energy policies shift the supply–demand equilibrium. We categorise the effects and show that GDP, economic policy uncertainty, and, most notably, specific economic conditions and extreme events play a significant role in determining energy prices. We observed that energy consumption, GDP growth, and energy prices have a bidirectional, causal relationship. Still, the literature has not established which causative direction is the most significant. Taxes, interest rates, and corruption also significantly determine energy prices, although the origins of corruption have not been adequately examined. Lastly, uncertainty generally increases energy costs, but this relationship requires additional research in terms of the features of countries, conditions, and, most importantly, the theoretical backgrounds used.