Milos Tumpach

This study aims to conduct a bibliometric analysis on the topic of public policy and financial regulation in preventing and combating financial fraud using a variety of bibliometric methods and tools, including the in-built tools of Scopus by Elsevier (SciVal) and Web of Science by Clarivate Analytics, as well as VOSviewer software. The most relevant publications related to the search terms were identified. Based on the results, a map illustrating the interrelationships of concepts such as “financial fraud,” “public policy,” and “financial regulation” with other categories was created, allowing for the identification of five clusters, each of which was characterized in detail. The results of the evolutionary and temporal analysis of scientific research showed that before 2000, scholars focused on the legislative aspects of combating financial fraud; from 2000 to 2015, on risk management and the impact of financial fraud on economic growth; from 2016 to the present, on the search for methods and tools to detect and combat financial fraud. The spatial analysis confirmed a predominantly intercontinental connection between researchers. The comparison of subject areas demonstrated the interdisciplinary nature of the study, with a predominant focus on the fields of “computer science” and “economics, econometrics, and finance,” which is logical considering the economic nature and the ongoing technological transformation of financial fraud. The results can be utilized to develop new strategies, policies, and legislative initiatives to ensure financial integrity and increase confidence in financial systems.

Acknowledgment
This study is funded by the Ministry of Education and Science of Ukraine and contains the results of the projects No. 0123U101945 “National security of Ukraine through prevention of financial fraud and money laundering: War and post-war challenges”, 0121U109559 “National security through the convergence of financial monitoring systems and cyber security: Intelligent modelling of financial market regulation mechanisms” and by the Vega Agency No. 1/0638/23.

Local and global financial crises are caused by a wide range of geopolitical, macro-financial, and socio-economic determinants. The purpose of this study is to assess the role of central bank independence in preventing financial crises and mitigating their consequences. Two hypotheses were tested. A measure of the banking regulator independence is the CWN index of the central bank independence. The hypotheses were tested on data from 53 countries suffering from financial crises over the last 40 years (the sample includes both developed and developing countries from different continents). The tools of nonlinear logit regression (modeling the probability of loss of financial stability due to a financial crisis, considering different levels of the banking regulator independence) and panel regression with random effects (modeling the influence of the banking regulator independence on banking activities during crisis periods) were used for calculations. The study did not confirm that a high level of central bank independence is a necessary condition for preventing the occurrence of financial crises in the national economy. On the contrary, the likelihood of financial instability was found to be higher in countries with more independent central banks. Thus, during crisis periods, an increase in the CWN index by 1 ensures an increase in the regulatory capital adequacy parameter by an average of 0.28%, a decrease in return on assets by 0.59%, and an increase in the share of non-performing loans by 1.69%.

In the context of mergers and acquisitions (M&A), management decisions regarding asset allocation play a key role in determining the strategic value of intangible assets. This study investigates the allocation of such assets, particularly goodwill, in relation to enterprise value on balance sheets across global M&A transactions within the B2C sector from 2000 to 2021. Utilizing data from the Markables database, which includes 543 transactions, this study presents robust and quantile regression analyses to effectively address challenges arising from non-normally distributed data. The findings underscore a significant correlation between the strategic allocation of intangible assets, especially goodwill, and enterprise value, highlighting their essential role in reflecting future earning potential and growth prospects. Additionally, the study reveals specific factors, including transaction type (asset vs. share deals) and timing (transaction year), that influence these asset allocation decisions. These insights are critical for enhancing management decisions in valuation and strategic financial planning during M&A. By elucidating these dynamics, this paper significantly contributes to the literature on management accounting and corporate finance, offering a granular understanding of the valuation of intangible assets in business combinations.

Acknowledgment
This study emerged from a cooperative project between the University of Applied Sciences Kufstein (Austria) and the University of Economics in Bratislava (Slovakia) 2023-05-15-003 “Enhancing long-term business value towards environmentally and socially sustainable economy,” which was funded by the performance committee of the Austria-Slovakia Action initiative.

Type of the article: Research Article

Abstract
Despite the central role of the World Bank’s annual Country Policy and Institutional Assessment (CPIA) – specifically its Quality of Budgetary and Financial Management rating – in determining concessional lending allocations under the International Development Association (IDA) Performance-Based Allocation system, the within-country growth effect of this governance dimension remains empirically underexplored. This paper aims to quantify the within-country association between public financial management quality and economic growth across 66 IDA-eligible developing economies over 2006–2021, testing whether governance upgrades yield measurable short-run effects on GDP per capita growth. The analysis employs an unbalanced panel of 876 country-year observations, two-way fixed effects, Driscoll–Kraay inference to accommodate cross-sectional dependence and serial correlation, and instrumental-variable two-stage least squares (IV-2SLS) estimation using the second lag of the CPIA score as an instrument. The baseline within-country estimate is negative and statistically insignificant (β = −0.843, p = 0.140); a one-standard-deviation improvement in the CPIA score (0.58 points) is associated with approximately −0.49 percentage points of growth, or roughly 22 per cent of the sample mean. The negative direction is consistent across all three income groups, all six World Bank regions, and seven robustness specifications, with Sub-Saharan Africa being the only sub-sample to reach conventional significance (β = −1.223, p = 0.046). Standard growth controls – convergence, investment, trade openness, inflation, and government consumption – perform robustly across all specifications and align with established findings. These results suggest that the growth payoff from public financial management reform operates through slower institutional channels rather than a direct output effect detectable in the immediate post-reform horizon.

Acknowledgments
This study was supported by the International Visegrad Fund: Visegrad Grant No. 22420285, Title of the project: “Distress prediction models in V4 countries and their audit applicability”.

Type of the article: Research Article

Although financial reporting and auditing standards are substantially harmonized across the European Union, important differences remain in national accounting regulations, audit thresholds, and the practical application of the going concern principle. These differences are particularly relevant for small and medium-sized enterprises (SMEs), which constitute the dominant segment of the Visegrad Four (V4) economies. This paper examines differences in financial reporting and auditing frameworks among the Czech Republic, Hungary, Poland, and Slovakia and develops sector-specific distress prediction models to support going-concern assessments in SME auditing.

The empirical analysis is based on financial statement data for 66,988 active firms obtained from the Orbis database. After data cleaning and consistency checks, a modelling sample of approximately 41,000 SMEs was constructed. Financial distress is defined as a persistent inability to cover interest obligations, represented by two consecutive years in which earnings before interest and taxes (EBIT) are lower than interest expenses. Distress status is modelled using financial ratios, firm-size indicators, industry characteristics, and selected variables inspired by ISA 570. Separate binomial logistic regression models are estimated for country–industry groups derived from NACE classifications and evaluated using hold-out samples.

The results confirm that country- and sector-specific models achieve satisfactory predictive performance and provide useful support for assessing going-concern risks. The results also show that the most informative predictors differ across countries and industries, reflecting differences in regulatory environments and economic structures. The study highlights the importance of local calibration when developing distress prediction models and demonstrates that a universal approach may lead to reduced predictive accuracy. The proposed models provide a practical screening tool for auditors, lenders, and SME managers, complementing professional judgement and broader audit procedures.

Acknowledgments

This study is co-financed by the governments of Czechia, Hungary, Poland, and Slovakia through Visegrad Grants from the International Visegrad Fund. Visegrad Grant No. 22420285, Title of the project: “Distress prediction models in V4 countries and their audit applicability”. The mission of the Fund is to advance ideas for sustainable regional cooperation in Central Europe. The authors gratefully acknowledge the support of their home institutions and thank the anonymous reviewers for their insightful comments and suggestions.

Type of the article: Research Article

Abstract
With five years remaining to the 2030 deadline of the United Nations Sustainable Development Goals, the relationship between monetary policy and SDG progress remains largely unexplored. This paper aims to quantify the association between short-term policy rates and SDG 1, SDG 8, and SDG 10 achievement across high-income, upper-middle-income, and low- and lower-middle-income economies. The analysis draws on a panel of 129 economies over 2000–2023, combining SDSN SDR2025 goal scores, IMF interest-rate series, World Bank WDI controls, and WGI 2.0 indicators (2,563 country-year observations), estimated using two-way fixed-effects regressions with country-clustered standard errors and eight robustness blocks. First, higher policy rates show a modest and consistent positive association with SDG 8 across income groups (β ≈ +0.045, all p < 0.10), robust to two-period lags and a dynamic LSDV re-specification. Second, the pooled association with SDG 1 is null, but interaction estimates reveal significant income-group heterogeneity: within-HIC β = +0.412 (p = 0.006) and a significantly weaker UMC association (interaction β = −0.590, p = 0.002), with a negative but insignificant net UMC estimate (−0.178, p = 0.20). Third, the aggregate SDG Index is negatively associated with the policy rate only in the UMC sub-sample (β = −0.048, p = 0.027), and the SDG 8 association disappears when real or lending rates replace the policy rate – consistent with a signaling interpretation rather than an identified mechanism. Assessments of monetary policy in the SDG context should distinguish between goals with consistent associations and goals whose association varies significantly with income group.