Background - Financial market interactions often combine rivalry with interdependence: counterparties compete for margins, order flow, and informational advantage while relying on shared infrastructure, standards, clearing, and liquidity conventions. This creates a co- opetitive setting in which cooperation expands feasible outcomes and competition or convention selects a surplus division. Aim - This paper formalizes co-opetition in financial markets as a two-layer bargaining structure in which cooperation expands the feasible bargaining set S (through infrastructure, standards, clearing, and admissible information-sharing), while competition or convention selects an agreement on the Pareto frontier P(S). Methods - Two axiomatic bargaining solutions—the Nash solution (NS) and the Kalai–Smorodinsky solution (K–S)—are used as replicable rational benchmarks. Convex bargaining environments are compared with regime-type nonconvex environments, and the behavioral layer is expressed through an implementability criterion based on proportional asymmetry. Results - In convex settings, NS and K–S provide alternative benchmark selections that differ in product efficiency and proportionality. In regime-nonconvex settings, Pareto efficiency alone does not determine the branch on which coordination should occur; the K–S ray-intersection is therefore interpreted as a publicly readable focal candidate for regime selection. Conclusions - The paper does not claim an empirical proof of market-wide behavioral stability. Instead, it formulates behavioral implementability as a testable coordination condition - under regime nonconvexity and repeated or reputational interaction, observed agreements are expected to be closer to proportional K–S-like selections than to product- efficient extremes. A minimal observational, structural, and experimental verification strategy is outlined.
Background - Central Bank Digital Currencies (CBDCs) represent a structural transformation of monetary architecture. Every major monetary innovation has reconfigured rather than eliminated systemic risk, and CBDCs follow this pattern introducing design-contingent liquidity risk, novel operational and cybersecurity vulnerabilities, and regulatory governance gaps at sovereign scale. Aim - This paper examines CBDCs through an integrated risk-based framework, analysing liquidity risk, monetary transmission effects, operational and cyber risks, and user adoption dynamics as interconnected rather than independent dimensions. Methods - A comparative analytical review synthesizes monetary economics models, macro-network simulations, institutional reports (BIS, IMF, ECB), and an Austrian user survey (n = 2,006) across three analytical expectations. Results - Liquidity and transmission effects are design-contingent; operational and cyber risks are qualitatively distinct from those of prior financial technologies due to sovereign- scale concentration; adoption dynamics interact with the risk architecture: crisis-driven conversion to CBDC poses greater systemic risk than voluntary gradual adoption. Conclusions - CBDCs do not remove systemic fragility; they redistribute it across liquidity, operational, privacy, and governance channels. The evidence suggests that policy outcomes depend primarily on design choices and rollout conditions, which makes cautious, cash-like, privacy-sensitive implementation the most prudent baseline.
Background - Assessing fiscal discipline is often based on observed outcomes such as debt and deficit levels. However, these indicators reflect policy results rather than the underlying institutional design of fiscal rules. Existing datasets primarily capture the presence of rules but fail to evaluate their functional strictness. Aim - This paper develops a multidimensional index to systematically quantify the institutional strictness of fiscal rules and applies it to a comparative analysis of Germany, the United States, and the Czech Republic over the period 2000–2024. Methods - The study introduces the Fiscal Rule Strictness Index (FRSI), which aggregates six institutional dimensions: legal bindingness, numerical tightness, coverage, enforcement, escape clauses, and monitoring. The index is constructed using qualitative legal analysis and standardized coding of de-jure fiscal frameworks based on primary legislation and international datasets. Results - The findings reveal substantial cross-country differences in institutional strictness. Germany exhibits a highly restrictive framework due to constitutional anchoring and tight numerical constraints. The Czech Republic shows a significant increase in strictness following the 2017 reform but remains vulnerable to crisis-induced relaxations. In contrast, the United States scores lowest due to the absence of binding federal fiscal rules, despite strong subnational constraints. Recommendations - Future fiscal frameworks should strengthen coverage, limit circumvention through off-budget instruments, and ensure credible return paths after the activation of escape clauses. Practical relevance/social implications - The FRSI provides policymakers with a transparent tool to assess the credibility of fiscal commitments and improve communication with financial markets, particularly in high-debt environments. Originality/value: The study contributes to the literature by introducing a theoretically grounded and empirically applicable index that moves beyond outcome-based measures and captures the multidimensional nature of institutional fiscal strictness.
Background: Digitalization has become one of the most important trends in modern tax administration and public sector management. Tax authorities increasingly rely on digital technologies to improve administrative efficiency, enhance taxpayer services, and strengthen tax compliance. Despite significant investments in digital tools, the extent to which digitalization contributes to reducing tax arrears remains an open question. Aim: The aim of the article is to analyse the factors influencing the amount of personal income tax arrears in the Czech Republic during the period 2013–2024, with particular emphasis on digitalization and selected tax administration instruments. Methods: The study is based on annual data obtained from the reports of the Czech Financial Administration. The analysis includes indicators related to the number of tax entities, tax audits, electronically filed tax returns, assessed taxes, procedures for clearing doubts, tax arrears and arrears recovered through enforcement actions. Monetary variables were adjusted for inflation using the Consumer Price Index published by the Czech Statistical Office. Pearson correlation analysis and multiple linear regression analysis were employed to examine the relationships among the selected variables. Results: The results revealed a strong positive relationship between the number of tax audits and tax arrears. The regression model explained 95.4% of the variability in tax arrears and identified tax audits as the most significant predictor. The number of tax entities exhibited a statistically significant negative effect on tax arrears, suggesting that a broader taxpayer base may contribute to lower levels of unpaid tax liabilities. Although electronically filed tax returns showed a significant negative correlation with tax arrears, their effect was not statistically significant in the multivariate regression model. This finding suggests that digitalization may influence tax arrears indirectly through broader improvements in tax administration efficiency rather than through a direct effect. Conclusions: The findings indicate that effective tax administration cannot rely solely on digitalization. While digital tools contribute to administrative modernization and may support tax compliance, the reduction of tax arrears appears to depend primarily on effective control mechanisms and the overall functioning of tax administration. The study contributes to the ongoing discussion on the role of digital transformation in tax administration and provides empirical evidence on factors associated with tax arrears in the Czech Republic.
Objective: Algorithmic and high-frequency trading have become a permanent fixture of modern financial markets over the past two decades — and regulators on both sides of the Atlantic have been trying to keep up, with mixed results. This paper asks how well current regulatory frameworks, specifically the EU's MiFID II and the SEC's supervisory approach, hold up against the challenges that autonomous trading algorithms create. These are not purely technical issues — market manipulation, flash crashes, and the technological gap between different market participants all have real consequences for how the financial system functions. The paper works through three questions: what empirical research tells us about HFT's effects on liquidity, price formation, and market stability; how MiFID II and the SEC each try to get these risks under control; and where exactly current regulation breaks down — whether in the rules themselves or in how they're enforced. Methodology: The paper draws on a structured literature review. This covered peer reviewed empirical studies in market microstructure, reports from regulatory and international bodies (ESMA, SEC, BIS, IOSCO, FSB, FCA), and legal-policy analyses of the EU AI Act. Sources were pulled from five academic databases — IEEE Xplore, SpringerLink, ScienceDirect, SSRN, and Google Scholar — and each was assessed against four criteria: breadth of regulatory coverage, real-world enforceability, how well regulation adapts to technological change, and documented effects on market stability and integrity. Findings: The central finding is that regulatory effectiveness has less to do with whether formal rules exist and more to do with whether those rules can actually be applied in real time. The EU's preventive ex-ante model and the U.S. ex-post traceability approach both have blind spots — and technologically sophisticated trading firms know how to use them. The paper also argues that the ethical problems associated with algorithmic trading — manipulation, the information gap between institutional and retail participants, opaque AI models — are not really independent moral concerns. They are more like the visible surface of a deeper regulatory and technological failure. Part of the analysis maps how the EU AI Act interacts with MiFID II, tracing how requirements around high-risk system classification, transparency, human oversight, and post-deployment monitoring connect with existing RTS 6 obligations. From this, a four-pillar evaluation framework is proposed — fairness, accountability, transparency, and robustness — as a working tool for assessing algorithmic trading systems on ethical grounds. Practical relevance: The paper's conclusions have concrete implications for regulators, compliance teams, and trading firms alike. Supervisory authorities need to invest in real time monitoring infrastructure, push for greater cross-border enforcement consistency, and bring AI Act conformity assessment into MiFID II compliance processes. Trading firms, meanwhile, should stop treating algorithmic impact assessments, independent model validation, and explainable AI as optional extras — these should be standard practice. The proposed framework is intended as a starting point for ethics audits in automated trading, and to help narrow the gap between what regulation promises on paper and what actually happens in the market.
The interconnection among sustainability reporting, foreign ownership and value of firms remains an unresolved issue in developing economies, especially for the Nigerian manufacturing sector, where sustainability practices and foreign investment are important. This study examined the interactive effect of sustainability reporting and foreign ownership on the value of manufacturing firms listed on the Nigerian Exchange Group. Ex-post facto research design was employed and the study utilized 46 listed manufacturing firms using purposive sampling technique from 2015 to 2024. “Least Square Dummy Variable” regression method was applied in analyzing the panel data, with Tobin’s Q and Market-to-Book Value (Mtbv) as proxies for firm value. Explanatory variables were environmental reporting, social reporting and governance reporting, with foreign ownership as the moderating variable. The findings revealed that the interaction between environmental reporting and foreign ownership significantly enhance firm value (Tobin’s Q) while the interaction effect was insignificant for Mtbv. The interactive effect of social reporting and foreign ownership had an adverse effect on firm value when measured as Mtbv and did not have significant influence on Tobin’s Q. Furthermore, the interactive effect of governance reporting and foreign ownership showed no significant impact on firm value when measured as Tobin’s Q and Mtbv. Thus, managers are advised to align sustainability strategies with global reporting standards, while policymakers should strengthen regulatory frameworks to enhance transparency and investor confidence.
Background: Nigeria, Africa’s largest oil producer, paradoxically experiences persistent macroeconomic instability due to volatile domestic energy prices. Energy costs have a direct bearing on inflationary pressures, making it vital to examine their role in price dynamics. Objective: This study investigates the dynamic impact of energy price fluctuations on inflation in Nigeria between 1990 and 2023, focusing on major energy components, petrol, diesel, and electricity tariffs. Methods: The Autoregressive Distributed Lag (ARDL) bounds testing approach to cointegration was employed to capture both the short-run and long-run relationships. Control variables such as exchange rate and broad money supply were included to strengthen the robustness of the model. The Error Correction Model (ECM) was further applied to assess the speed of adjustment toward long-run equilibrium. Results: Findings reveal a significant and positive long-run relationship between energy prices and inflation, with petrol prices exerting the strongest impact. The ECM results indicate a moderate speed of adjustment following external shocks, underscoring the sensitivity of the Consumer Price Index (CPI) to energy price volatility. Conclusion: Energy price volatility is a major driver of inflation in Nigeria. A multi-pronged policy strategy is recommended, including stabilizing domestic supply chains, diversifying the energy mix, and implementing targeted social safety nets to cushion vulnerable households against adverse impacts of energy price adjustments.
Background: Artificial intelligence (AI), automation, and robotization are transforming financial business centers globally, but research on their implementation in Slovakia remains limited. Aim: This study investigates how AI, automation, and robotization are implemented in Slovak financial business centers and evaluates their impact on competitiveness. Methods: A qualitative multiple case study was conducted, including interviews with representatives from four Slovak financial business centers and detailed case analyses. Results: All centers have integrated AI, automation, and robotization into various business processes, with differing levels of maturity. These technologies enhance operational efficiency and competitive performance. Recommendations: Organizations should accelerate technology adoption, invest in employee upskilling, and strengthen collaboration with academic institutions to address implementation challenges. Further research could expand the study to additional centers in the CEE region. Practical relevance/Social implications: Findings support strategic decision-making in Slovak and Central European financial centers, promoting competitiveness, efficiency, and sustainable development. Originality/Value: This is the first in-depth study of AI, automation, and robotization implementation in Slovak financial business centers, filling a regional research gap and providing actionable guidance for managers and policymakers.
Background: This study investigates the conditional pricing of environmental, social, governance (ESG)-related risk exposures – specifically ESG, carbon intensity, and controversy – using portfolio-level data from firms in the Morgan Stanley Capital International Europe ESG Leaders Index (2018–2024). The sample comprises nine sector-neutral portfolios, double-sorted by ESG and Controversy scores, ensuring balanced exposure across Europe’s leading ESG-rated firms. Aim: This study evaluates how factor decomposition, macro-regime sensitivity, and time-varying risk exposure affect ESG integration in multifactor pricing models. It also assesses the effectiveness of Kalman filtering in stabilizing ESG beta estimates under data limitations. Methodology: A two-stage Fama-MacBeth approach estimates ESG, carbon, and controversy betas using rolling regressions and Kalman filtering. These betas are then incorporated into fixed-effect panel regressions with macroeconomic volatility controls and regime interaction terms for the 2020–2021 regulatory and financial stress periods. Results: Disaggregated E, S, and G exposures exhibit significant positive return premia, particularly under stress. Carbon and controversy factors display conditional pricing effects that intensify under transition regimes. Kalman filtering yields smoother, more interpretable beta estimates than rolling regression, enhancing model robustness. Recommendation: ESG pricing models should incorporate factor decomposition, regime dynamics, and dynamic beta estimation, particularly Kalman filters – when working with quarterly or constrained datasets. Replicating this approach using data from multiple professional ESG providers would be valuable to assess the robustness of the pricing effects under rating divergence and disclosure heterogeneity. Practical relevance/social implications: This study offers a replicable framework for ESG researchers and investment practitioners seeking to identify time-varying, regime-sensitive, sustainable premiums for asset pricing. Originality/value: This study is among the first to combine ESG factor decomposition with Kalman-filtered beta estimation in a regime-augmented panel model using European portfolio data. Unlike the dominant United States-focused literature, it applies double-sorted, sector-neutral portfolios based on ESG and controversy scores. The findings demonstrate that robust ESG pricing signals can be uncovered even in small, high-quality European samples when the models are specified dynamically and contextually.
Background: The relationship between public debt and private sector profitability has long been emphasized in economic theory in the context of sectoral balances. According to Post-Keynesian economics, private debt accumulation, under certain conditions, may be a source of private sector profits. Moreover, public debt dynamics may have a strong relationship to the evolution of firms’ sector debt. Aim: This paper develops a monetary financial model of a small open economy using the stock-flow consistent and system dynamics frameworks, focusing on the interplay between the public and the private sector debts, and public debt and private sector profitability. The aim is to test – using the model – the hypothesis that public debt as an injection of net financial assets into the economy may positively influence private sector profits. Additionally, the model assesses the relationship between the public debt and the firms’ debt sector dynamics. Methodology: Stock-flow consistent approach together with nonlinear differential equations and non-equilibrium approach are used to build the model. System dynamics is used for model simulations. The model works with quarterly time periods, six sectors – central bank, government, banks, households, firms and the rest of the world, consolidated sector balance sheet items acting as stocks, and inflows and outflows changing the value of those items - as flows. Behavioral equations define the model behavior, and interest rate mechanism is used as the global feedback loop. The model tracks how monetary flows across consolidated sectors change the accumulation of stocks and a variety of real and nominal macroeconomic variables. Baseline, boom and negative shock scenarios are used to simulate the outcome of the model on simulated data. Results: According to the simulation results, public debt accumulation may contribute to private sector profitability. Public debt may also have an inverse relationship with the dynamics of firms’ sector debt. However, the introduction of export shocks can trigger a systemic decline. The model highlights a strong link between public debt and private sector debt dynamics, as well as high sensitivity of real macroeconomic variables to external flows for a small open economy. Recommendations: This paper underscores critical influence of the foreign sector, policy rule design and endogenous debt dynamics across different sectors on a small open economy and variety of its macroeconomic variables. Although it is highly recommended to apply SFC framework and system dynamics with a high level of parametrization and a variety of feedback loops – the model provides aluable insights into the discussions of public debt evolution and its implications. Relevance: This paper addresses a key topic in practical economic policy: the dynamics of public debt, its potential drivers and causes. It develops a mathematical model based on complex nonlinear relationships with a useful simulation framework. This framework might help economists and policymakers better understand the causes, implications, and intersectoral relationships associated with the public debt. Originality: This paper is original, based on the ideas of Wynn Godley, Randall Wray, Steve Keen, Marc Lavoie and Thomas Palley, providing an originally developed consolidated balance sheet of foreign sector (rest of the world), and dynamic interest rate and inflation mechanisms. Additionally, original dependencies are introduced to the model – banks’ CAR ratio, advanced interest rate feedback loop mechanism and advanced logic of sectoral flows.
Background: Carbon neutrality and the entire energy transformation, especially of electricity supplies, lead to a change in the current energy paradigms. The past modelling approaches can lead to errors if not modified properly. Aim: In this article we estimate the lower-bound of direct macroeconomic costs of the proposed electric energy mix change in the Czech Republic. Methods: We augment the physical electric energy balance model with seasonally (monthly adjusted) estimated hourly average electric prices to show the economic difference between the yearly energy balance and import costs due to seasonal price patterns. This simple economic model is then applied on proposed future energy mix stemming from State Energy Policy (SEK) that does not consider the seasonal price patterns at all, and the paper goal is to provide the approximate magnitude of such an error. Our backward simulation imposing past prices and seasonal patterns on future energy mix is conservative, i.e., provides lower-bound estimate of the economic effect but also allows us to avoid future price and future consumption prediction errors. Results: We show that the envisaged change in production mix leads to a direct increase in net imports that are comparable to the value above 0.5% GDP. When considering the fiscal multiplier, the total negative impact shall be around 1% GDP, annually. As the Czech economic growth is not stellar, the implied GDP decrease can further worse economic prospects. Practical relevance/social implications: Models used by the state underestimate total costs and potential social impact of economic shrinkage. Value: State energy policy shall be revised considering substantial effect of seasonal price variations leading to fiscal imbalances.
Background: The financial turmoil of 2007–2009 exposed egregiae debilitas in the decentralized supervisory frameworks within the European Union. Coordination among competent national authorities proved insufficient, reflecting incorrecta implementatio of EU law. The envisaged harmonization under the Single Rulebook revealed a de facto divergentia interpretativa, as purportedly uniform norms were applied and enforced heterogeneously, resulting in the absence of uniformis applicatio of supervisory law. In response, the European Banking Union (Unio Bancaria Europaea), formally launched in 2012, sought to remedy these deficiencies. It emerged as a projectum prioritarium at the European level, enabling consistent enforcement of EU banking regulations among participating Member States following the attributio competentiarum to supranational institutions. Newly instituted decision-making procedures and supervisory tools enhance transparency, market integration, and financial stability. While all euro area countries are automatically subject to European banking supervision, non-euro EU Member States retain the discretion to participate (optio participationis). The present study interrogates Slovak participation and Czech non-participation, assessing their implications for domestic banking sectors with particular reference to the potential infringement of the fundamental freedoms enshrined in the Treaties. Aim: The principal research question (quaestio scientifica principalis) can be articulated as follows: Are the divergences in banking regulation contingent upon a Member State’s membership in the Banking Union compatible with the principium unitatis mercati? If non-compliant, which legal or regulatory measures (remedia juridica) are required to restore conformity? This inquiry is operationalized through the analysis of Slovak and Czech legislative frameworks. It is posited that the correcta institutio of prudential norms at the EU level, combined with national responsibility for supervision and bank resolution, corresponds to the principium subsidiaritatis under the founding Treaties. Although all EU Member States (except Denmark) have the obligation to adopt the euro, accession to the Banking Union remains non-mandatory (non obligatio legalis). Central to this analysis is the question whether, under specific circumstances, disparities in supervision could constitute an obstacle to the libertas establishmentis. Notably, the largest and most systemically relevant banks in both markets are subsidiaries of foreign financial institutions. To address this, the study undertakes a comparative examination of the legal and institutional frameworks governing banking supervision and resolution in the Czech Republic, a non-Banking Union Member State, and Slovakia, a Banking Union participant with a structurally analogous banking sector. To facilitate rigorous analysis, the formulation of sub-questions (sub-quaestiones) is employed, further specifying the resolution of the principal scientific inquiry. Methods: Methodologically, this study relies upon desk research encompassing five categories of sources, integrating both primary legislation and doctrinal literature. The generally accepted methodi iuris interpretativi are applied, including interpretatio verbalis/grammatica, interpretatio systematica, interpretatio historica, and interpretatio teleologica. These analytical tools are deployed within a rigorous legal discourse framework to ensure fidelity to both EU and national legal norms. Results: This paper aims to elucidate the regulatory and institutional architecture of the European Banking Union via a comparative lens, contrasting banking supervision, prudential regulation, and resolution mechanisms in the Czech Republic and Slovakia – two Member States of analogous structural composition but differing integration levels within the Banking Union. By analyzing the allocation of competences, the reception and implementation of EU banking law (including soft law), and the availability of legal remedies for banking institutions, the study assesses whether the extant asymmetry between Banking Union and non-Banking Union Member States coheres with foundational EU principles, particularly libertas establishmentis, principium proportionalitatis, and the integrity of the internal market. The Czech Slovak comparison, given their shared legal heritage and interconnected financial sectors, affords a unique perspective on the practical and juridical ramifications of opting into, or abstaining from, deeper financial integration. The findings contribute not only to academic discourse but also to consilium publicum for Member States deliberating participation in multi-speed integration schemes within the EU.
Background: The post-conflict reconstruction of Ukraine, especially in the housing and construction sector, has become a strategic priority for the European Union and its member states. Despite declared support, the real participation of Central European businesses, including those from the Czech Republic, remains limited due to multiple legal, security and financial barriers. Aim: The paper aims to identify the conditions, instruments and risks influencing the potential engagement of Czech enterprises in the reconstruction of Ukraine's housing and construction sector after 2022, with emphasis on investment frameworks, scenario modelling, and institutional capacities. Methods: The study combines a qualitative case study (cooperation between the University of Finance and Administration and V. N. Karazin University in Kharkiv), stakeholder analysis based on coded interviews with Czech entrepreneurs, and quantitative investment scenario modelling (2024–2033). Data triangulation was applied to ensure internal validity. Results: Findings confirm that while institutional and financial instruments (e.g., Ukraine Facility) are in place, their uptake is limited by high perceived risk and a lack of implementation facilitators. Investment scenarios range from 65 to 95 billion USD depending on security and absorption conditions. Czech SMEs face specific constraints such as insufficient legal safeguards and capacity limits yet remain strategically positioned to benefit from targeted support schemes. Recommendations: Policy actors should prioritise the development of national coordination platforms, risk insurance schemes (e.g., via EGAP), and pilot cooperation models with Ukrainian institutions. Stronger links between academia, public sector and private firms are essential to de-risk market entry and build long-term resilience. Practical relevance/social implications: The research provides applicable insights for government agencies, export organisations and business associations aiming to support Czech firms in entering high-risk post-conflict markets. Moreover, it demonstrates the role of academic institutions as platforms for international capacity building and post-war recovery. Originality/value: This is the first study focusing on the Czech context of post-war investment in Ukraine, combining scenario modelling with a grounded case study. The integration of qualitative and quantitative methods provides a comprehensive Framework for further research and policy development.
Background: The Czech real estate market has experienced rapid growth in recent years, driven by macroeconomic trends and limited housing supply. Retail investors face increasing barriers to direct property ownership, prompting a shift toward real estate investment funds (REIFs). However, the lack of a standardized performance benchmark hinders market transparency and comparability. Objective: This study aims to design a dual-index framework to benchmark the performance of Czech real estate investment funds. It investigates how fund structure, size, and investor segmentation affect index behaviour and evaluates the implications of different methodological approaches. Methods: Two types of indices, arithmetic and NAV-weighted, were constructed separately for retail and qualified investor funds. Data were collected quarterly from 39 real estate funds, with inclusion based on data availability and reporting consistency. Indices were computed using Python-based time-series processing, with quarterly rebalancing and weight capping to reduce concentration risk. Results: Qualified investor funds achieved higher average returns and exhibited lower performance dispersion. In contrast, retail funds displayed greater heterogeneity, and the weighted index was strongly influenced by a single large, underperforming fund. The arithmetic index proved sensitive to outliers, while the weighted index highlighted capital concentration effects. Recommendation: Investors and analysts should use both index types for a comprehensive performance view. Policymakers should encourage broader data disclosure and consider the systemic impact of dominant funds on retail benchmarks. Practical relevance: The indices provide a transparent benchmarking tool for market participants, enabling better performance evaluation and investment decision-making. The framework also supports regulatory efforts to enhance market maturity. Originality/value: This study is the first to introduce a dual real estate fund index for the Czech market. It provides an analytically sound and practically applicable model for benchmarking performance across investor segments, with methodological insights relevant to other emerging real estate markets.
Background: Between 2015 and 2023, young adults in Germany faced significant financial challenges due to escalating inflation, peaking at 10.6% between 2021 and 2023. Aim: This study aims to investigate the financial impacts of inflation on the household assets of young adults in Germany compared to other age groups. Methods: Employing a structured literature review of studies, reports, and statistical data from institutions like the European Central Bank and the Deutsche Bundesbank. Results: The findings reveal that high inflation eroded net asset returns for young households, delayed wealth accumulation, and exacerbated generational wealth disparities. Recommendations: The study recommends targeted policy actions to enhance financial resilience among young adults, such as financial education and support for wealthbuilding initiatives. Practical Relevance/Social Implications: Addressing the unique financial vulnerabilities of young adults during inflationary periods is essential for reducing wealth inequality and promoting economic stability. Originality/Value: This research contributes originality by focusing on an underexplored demographic, shedding light on how recent inflation has specifically impacted the wealth development of young German households.
Background: Traditional econometric models like ARIMA, while foundational for time series forecasting, often rely on assumptions of linearity and stationarity. These models can fall short in capturing the complex, nonlinear dynamics frequently present in financial markets. This has led to the adoption of machine learning methods like Long Short-Term Memory (LSTM) networks, which are specifically designed to recognize long-term dependencies in sequential data, offering a potential advantage in modeling volatile financial time series. Aim: This study compares the predictive performance of a classical econometric model (ARIMA) with a deep learning approach (LSTM) in the context of stock index forecasting using the DAX 50 ESG index from 2020 to 2024. Methods: An autoregressive integrated moving average (ARIMA) model is compared against a long short-term memory (LSTM) neural network. The models are evaluated using both a static train-test split and a more rigorous expanding window forecast scheme. Predictive accuracy is measured by standard error metrics (MAE, RMSE, MAPE) and the Diebold-Mariano test. Results: The empirical results show that the LSTM model achieves lower forecast errors than the best-fitting ARIMA model in both evaluation frameworks. In the expanding window scenario (repeated retraining), the LSTM maintains a statistically significant, though modest, forecasting advantage over the ARIMA model. Originality/Value: The findings suggest that while the LSTM's ability to capture nonlinear patterns offers a forecasting edge, the improvement is incremental in a highly liquid and efficient market. This case study highlights the potential of deep learning methods in finance but also reinforces he notion that strong market efficiency can limit the forecasting benefits of such complex models.
Background: The countries of the Visegrad Group (Czech Republic, Slovakia, Poland and Hungary) apply different personal income tax systems that reflect their different economic and social policies. Taking into account the fact that often every year changes are made in the tax legislation, there are changes in tax systems. Aim: The article is focused on measuring the progressivity of the tax on dependent activity in the Czech Republic, Slovakia, Poland and Hungary. Methods: Interval and global progression methods were used. Specifically, these are the progressivity of the average rate, the progressivity of the tax liability, the Lorenz curve, the Gini coefficient and the Musgrave and Thin index. Results: The resulting values are calculated according to model examples based on the tax laws of individual countries. Based on the results of interval progressivity, similar but also different features can be observed in individual countries. In the case of the Czech Republic, Slovakia and Poland, it can be observed that the tax on income from dependent activity is progressive. In the case of taxpayers with low incomes and in the case where a child lives with the taxpayer, the tax in some cases even has a regressive effect. On the other hand, in Hungary, a proportional tax applies throughout. Based on indicators of global progressivity, they show that the tax on income from dependent activities is the most progressive in Poland.
The tax burden affects a number of areas, including the economic and financial behavior of both legal entities and individuals. The aim of the article is to classify EU countries into groups based on selected tax burden indicators. The sample consists of 27 states of the European Union and the indicators used include direct taxes, indirect taxes, social contributions, taxes on consumption, on labor, on capital and implicit tax rate. In addition, the aim of the article is achieved through correlation and cluster analysis. Through cluster analysis, a total of 4 clusters were created for the period 2009-2021. The countries that joined the EU at the latest belong to the group of countries characterized by a lower tax burden. In contrast, most of the states that joined the EU earlier belong to the group of countries with a higher tax burden. In general, it can be said that countries also cluster on the basis of geographical or political characteristics. Through the cluster analysis, it was proven that there are significant differences between the states in the tax area and harmonization is not taking place, and there is thus further scope for tax harmonization. The contribution of the article is in the current assessment of the tax burden in EU countries and their classification according to similar tax systems for their discussion.
Background: Healthcare and pension expenditures represent significant budgetary commitments in OECD countries, with considerable variation in spending levels influenced by factors such as demographic structures, healthcare system models, and the role of private insurance. Germany, Austria, and Czechia exemplify diverse approaches to universal healthcare, reflecting unique socio-economic and policy contexts. Objective: This study aims to compare the financial flows and spending efficiencies of healthcare systems in Germany, Austria and Czechia to identify opportunities for savings and policy innovations. Methods: A comparative analysis of secondary data from OECD reports and academic literature was conducted, examining key metrics such as public and private expenditure, health insurance contributions, and administrative costs. Results: The analysis reveals that while Germany’s dual public-private insurance system ensures comprehensive coverage, it faces challenges in integrating care services. Austria’s regionally managed system benefits from robust public funding but struggles with administrative complexity. Czechia’s centralised financing model supports equitable access but requires improved resource allocation and efficiency. Across all systems, health insurance contributions exhibit tax-like characteristics, with significant implications for public policy and perception. Recommendations: Policymakers should consider measures such as integrating care services in Germany, streamlining administrative processes in Austria, and refining fund redistribution mechanisms in Czechia. Leveraging digital health technologies and fostering transparency in healthcare financing are critical for achieving systemic savings and equity. Practical relevance/social implications: This study highlights the importance of tailored financial reforms to address demographic shifts and rising healthcare costs. Its findings provide actionable insights for policymakers aiming to balance equity and efficiency in healthcare financing while ensuring public trust and sustainability. Originality/value: By dissecting the healthcare financial flows in Germany, Austria, and Czechia, this study offers a nuanced understanding of their systems' dynamics and identifies opportunities for cross-border learning to inform global healthcare policy reform.
Background: The real estate market in the Czech Republic exhibits significant differences among regions, especially in terms of the influence of economic factors such as wages on property prices. Wages are one of the key determinants of house prices, but their influence may vary across regions and over time. It is important to further understand the dynamics between wages and house prices at the regional level. Objective: This study seeks to investigate whether and how the impact of wages on house prices varies among regions and how it changes over time. Methods: The fixed effects panel regression with interaction terms was used to account for regional and time effects. The model includes lagged house price values to better capture market dynamics over time. Interaction terms between wages and regions allow for the detection of region-specific effects. The Newey-West correction was used to control for heteroskedasticity and autocorrelation. Results: In some regions, such as Prague, factors other than wages (e.g. lack of supply and high demand) may play a more significant role. The analysis also confirmed that house prices exhibit time inertia, which means that past price developments have an impact on the current market. Recommendation: It is recommended to focus on promoting affordable housing in regions with high prices and on investment opportunities in emerging regions where wages and house prices are growing more steadily. Practical relevance: This study provides insights into regional differences in the Czech Republic's housing market. These insights are valuable for regional housing and economic development strategies Policymakers can use this knowledge to better respond to affordable housing challenges. Originality/value: This study provides an original analysis of the impact of wages on house prices, with an emphasis on regional specificities and time trends, allowing for a deeper understanding of regional dynamics in the housing market in the Czech Republic. This analysis provides useful insights for future research and for practical applications in real estate market and regional policy decision-making.
