Template-Type: ReDIF-Article 1.0 Author-Name: Luis Dumlao Author-Name-First: Luis Author-Name-Last: Dumlao Author-Email: ldumlao@ateneo.edu Author-Workplace-Name: Ateneo de Manila University Title: The Principle of Cost-Based Supervision in Practice Abstract: A key response of financial regulators around the world to the financial and economic crises of ten years ago has been the formation of supervisory committees. Such committees now exist in several countries worldwide. Consequently, many regulators fund their supervisory function by charging their supervisees. The objective of this paper is to compare how these regulators charge fees, identify common practices, draw conclusion from observations, and provide relevant recommendations. This paper especially focuses on the Federal Reserve, the European Central Bank and the Bank of England that charge fees just enough to recover the cost of supervisory function, or those that follow what this paper refers to as the “principle of cost-based supervision.” A discussion on how selected examples of regulators practice the principle of cost-based supervision follows. Simulations of fees using selected procedures to supervisees in the Czech Republic and Greece follow. Then this paper introduces the asset elasticity of cost notated as n and simulates the hypothetical supervisory fee if n is constant. Classification-JEL: E50, E58, E59 Keywords: Bank Supervision, Supervisory Fee, Cost-Based Supervision Journal: International Journal of Economic Sciences Pages: 1-19 Volume: 13 Issue: 2 Year: 2024 Month: December File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117106 File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117106?download=1 Handle: RePEc:aop:jijoes:v:13:y:2024:i:2:p:1-19 Template-Type: ReDIF-Article 1.0 Author-Name: Tomáš Karel Author-Name-First: Tomáš Author-Name-Last: Karel Author-Email: tomas.karel@vse.cz Author-Workplace-Name: Prague University of Economics and Business Author-Name: Miroslav Plašil Author-Name-First: Miroslav Author-Name-Last: Plašil Author-Email: miroslav.plasil@vse.cz Author-Workplace-Name: Prague University of Economics and Business Title: Application of Hierarchical Bayesian Models for Modeling Economic Costs in the Implementation of New Diagnostic Tests Abstract: The COVID-19 pandemic has highlighted the need for reliable and rapid diagnostic tests to control the spread of infection. The introduction of new rapid antigen tests often goes in tandem with the limited data availability, making it challenging to assess their performance at the initial phase of the pandemic. Sensitivity and specificity, the key performance characteristics provided by manufacturers, are typically derived under laboratory conditions and may not accurately reflect the tests' performance in field settings. We use the hierarchical Bayesian model to obtain their realistic estimates in real world conditions and show how it may be used in situations in which new tests with limited history are presented on the market. Proposed methodology allows for the efficient information pooling, thereby improving on the accuracy of parameter estimates for new tests. The results suggest that the application of hierarchical model on the Czech data led to a considerabile reduction in uncertainty associated with the parameter estimates as well as with potential economic cost implied by false positive test results. The model can thus assist in better informed decision-making and financial planning of both the government and corporations. Classification-JEL: C11, C10, C19 Keywords: Bayesian statistics, Hierarchical Bayesian Model, COVID-19, Antigen tests, False Positivity Journal: International Journal of Economic Sciences Pages: 20-37 Volume: 13 Issue: 2 Year: 2024 Month: December File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117121 File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117121?download=2 Handle: RePEc:aop:jijoes:v:13:y:2024:i:2:p:20-37 Template-Type: ReDIF-Article 1.0 Author-Name: Daniel Macek Author-Name-First: Daniel Author-Name-Last: Macek Author-Email: daniel.macek@fsv.cvut.cz Author-Workplace-Name: Czech Technical University in Prague Faculty of Civil Engineering Author-Name: Stanislav Vitásek Author-Name-First: Stanislav Author-Name-Last: Vitásek Author-Email: stanislav.vitasek@fsv.cvut.cz Author-Workplace-Name: Czech Technical University in Prague Faculty of Civil Engineering Title: ESG risk analysis and preparedness of companies in the Czech Republic Abstract: This study examines the integration of Environmental, Social, and Governance (ESG) principles into the strategies of companies in the Czech Republic, a region where ESG considerations are increasingly influencing investment decisions and corporate governance. As global sustainability concerns gain momentum, Czech companies face growing scrutiny from investors, regulators, and stakeholders. This research aims to assess the current state of ESG risk analysis and evaluate the readiness of these companies to address the challenges posed by environmental stewardship, social responsibility, and governance effectiveness. To achieve this, the study employs a mixed-methods approach, combining qualitative data from semi-structured interviews with industry experts, corporate leaders, and regulatory authorities, and quantitative data from a survey distributed to a representative sample of companies across various sectors in the Czech Republic. The qualitative interviews provide in-depth insights into the challenges and strategies surrounding ESG integration, while the quantitative survey assesses the extent of ESG adoption, identifies key risk areas, and evaluates companies’ preparedness to tackle these issues. Data analysis includes thematic analysis of interview transcripts and statistical analysis of survey responses, offering a comprehensive view of ESG practices in the Czech business landscape. The findings reveal both best practices and areas needing improvement, providing valuable insights for stakeholders committed to enhancing corporate sustainability. This study contributes to the broader discourse on ESG by highlighting the evolving role of these factors in shaping corporate resilience, innovation, and long-term value creation in the Czech Republic, ultimately promoting a more sustainable and responsible business environment. Classification-JEL: M14, L21, Q01 Keywords: environmental; ESG; governance; social; risk analysis Journal: International Journal of Economic Sciences Pages: 38-54 Volume: 13 Issue: 2 Year: 2024 Month: December File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117113 File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117113?download=3 Handle: RePEc:aop:jijoes:v:13:y:2024:i:2:p:38-54 Template-Type: ReDIF-Article 1.0 Author-Name: Alina I. Popescu Author-Name-First: Alina I. Author-Name-Last: Popescu Author-Email: alina.popescu@rei.ase.ro Author-Workplace-Name: Bucharest University of Economic Studies, Romania Title: The Evolution of On-Demand Platforms: Conceptual Framework, Regulatory Challenges, and Policy Implications in the Digital Economy Abstract: Digital platforms currently form the cornerstone of what is referred to as 'platform economics,' progressively assuming a central role in the city's economy, experiential landscape, and governance. On-demand platforms play a pivotal role in elevating the level of digital sophistication among citizens. This article extends the current research on on-demand service markets, aiming to cultivate an understanding of this nascent domain of digital platform business within the broader framework of the smart city. In the first section, we delve into various concepts related to on-demand service markets, outlining their distinctive features in comparison to traditional service markets, and elucidating the principal components of the on-demand digital platform economy. The second part of this paper employs bibliometric analysis to unveil, among other insights, emerging areas of interest, key works, and influential researchers in the field, as well as the countries and institutions where research on on-demand service markets is most advanced. This research endeavour may lay the foundation for the development of a theory pertaining to the provision of on-demand services within the context of the platform economy. Finally, the research extensively discusses regulatory challenges and public policy implications in the context of on-demand platforms, with a focus on worker protection, algorithmic transparency, and data security. Classification-JEL: O30, O38 Keywords: on-demand services, digital platforms, mobility on-demand (MoD), video on-demand (VoD), bibliometrics, on-demand markets, smart mobility, regulatory issues Journal: International Journal of Economic Sciences Pages: 55-86 Volume: 13 Issue: 2 Year: 2024 Month: December File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117124 File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117124?download=4 Handle: RePEc:aop:jijoes:v:13:y:2024:i:2:p:55-86 Template-Type: ReDIF-Article 1.0 Author-Name: Michal Mec Author-Name-First: Michal Author-Name-Last: Mec Author-Email: michalmec@gmail.com Author-Workplace-Name: Prague University of Economics and Business, Prague Author-Name: Mikulas Zeman Author-Name-First: Mikulas Author-Name-Last: Zeman Author-Email: mikulas.zeman@vse.cz Author-Workplace-Name: Prague University of Economics and Business, Prague Author-Name: Klara Cermakova Author-Name-First: Klara Author-Name-Last: Cermakova Author-Email: klara.cermakova@vse.cz Author-Workplace-Name: Prague University of Economics and Business, Prague Title: Stock market prediction using Generative Adversarial Network (GAN) – Study case Germany stock market Abstract: Using neural networks in economics time series data is a new unexplored field. Lot of companies and economics research use mostly logistic regression or statistical approach when they try to predict the movement of stock market. Neural networks became a frequent tool for prediction in recent years and this approach has been confirmed to provide more reliable and better solutions when it comes to prediction and accuracy power. Within a wider context of current debate on neural networks employment in stock market predictions, we suggest an innovative methodology based on the combination of neural networks. In our analysis we use Wasserstein Generative Adversarial Network (WGAN) on Germany stock market as an example. We present how the trading strategy could be established on the prediction of the model and how it can be compared with other models in terms of returns. Overall, the WGAN monthly prediction outperformed Random Forest by 36%, benchmark by 32% and LSTM by 26% in the testing period. Our results also suggest that the WGAN model has on average higher returns than pure investment into index. Furthermore, WGAN is less volatile, which is always the preferred option for investors. Using neural networks for stock index prediction and confirming that WGAN investment strategy brings higher returns compared to generally used models is our main contribution to the current debate. Classification-JEL: G11, G17, C45 Keywords: Generative adversial network; Germany stock market; neural network; stock prediction Journal: International Journal of Economic Sciences Pages: 87-103 Volume: 13 Issue: 2 Year: 2024 Month: December File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117126 File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117126?download=5 Handle: RePEc:aop:jijoes:v:13:y:2024:i:2:p:87-103 Template-Type: ReDIF-Article 1.0 Author-Name: Martin Slaný Author-Name-First: Martin Author-Name-Last: Slaný Author-Email: martin.slany@cevro.cz Author-Workplace-Name: CEVRO University Author-Name: Filip Emmer Author-Name-First: Filip Author-Name-Last: Emmer Author-Email: filip.emmer@mail.muni.cz Author-Workplace-Name: Masaryk University, Faculty of Economics and Administration, Department of Regional Economics, Title: Evidence of the ripple effect across the Czech housing market Abstract: Czech regional housing markets have exhibited significant price co-movements over the last two decades. While part of this dynamic may be explained by traditional housing market fundamentals, some regions appear to be influenced by other variables. One possible explanation lies in the ripple effect, a phenomenon where house price shocks in one region influence prices in others. This study examines possible occurrence of the ripple effect using Toda-Yamamoto Granger causality. Results indicate statistically significant occurrence of lead-lag effect in eight out of 13 regions. Such price interconnectivity might be important factor for policymakers as study suggests that regional submarkets are not isolated and should be approached on macro level. Classification-JEL: R15, R30, R31 Keywords: House price spillovers, Regional housing market, Granger causality Journal: International Journal of Economic Sciences Pages: 104-115 Volume: 13 Issue: 2 Year: 2024 Month: December File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117127 File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117127?download=6 Handle: RePEc:aop:jijoes:v:13:y:2024:i:2:p:104-115 Template-Type: ReDIF-Article 1.0 Author-Name: C?HAN ÇALIKO?LU Author-Name-First: C?HAN Author-Name-Last: ÇALIKO?LU Author-Email: cihan.calikoglu@up.poznan.pl Author-Workplace-Name: Pozna? University of Life Sciences, Faculty of Economics Author-Name: ALEKSANDRA ?UCZAK Author-Name-First: ALEKSANDRA Author-Name-Last: ?UCZAK Author-Email: aleksandra.luczak@up.poznan.pl Author-Workplace-Name: Pozna? University of Life Sciences, Faculty of Economics Title: Multidimensional assessment of sdi and hdi using topsis and bilinear ordering Abstract: This study investigates how the Human Development Index (HDI) influences Sustainable Development (SD) in European Union (EU) countries by analyzing the relationship between the United Nations’ HDI and a newly constructed Sustainable Development Index (SDI) by the authors. The dataset comprises 18 indicators retrieved from Eurostat for 2021. The study employs the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) approach to calculate the SDI and utilizes bilinear ordering to visualize countries in a coordinate system based on their SDI and HDI scores. Spearman’s rank correlation reveals a strong positive relationship between SDI and HDI. The study identifies disparities, with countries like Denmark and Sweden showing high SDI and HDI, while Romania and Bulgaria have lower scores. Northern and Western EU countries generally perform better, whereas Eastern and Southern countries face more challenges, highlighting the need for targeted development strategies. The results emphasize the importance of considering both human and sustainable development in policy design, offering insights for enhancing development outcomes for the EU. Classification-JEL: Q01, O15, R11 Keywords: sustainable development, human development, TOPSIS, bilinear ordering, EU, MCDM Journal: International Journal of Economic Sciences Pages: 116-128 Volume: 13 Issue: 2 Year: 2024 Month: December File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117129 File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117129?download=7 Handle: RePEc:aop:jijoes:v:13:y:2024:i:2:p:116-128 Template-Type: ReDIF-Article 1.0 Author-Name: Jiri Rotschedl Author-Name-First: Jiri Author-Name-Last: Rotschedl Author-Email: jiri@rotschedl.com Author-Workplace-Name: Prague University of Economics and Business, Faculty of Economics, Department of Economics Author-Name: Jan Neugebauer Author-Name-First: Jan Author-Name-Last: Neugebauer Author-Email: st102396@students.ujep.cz Author-Workplace-Name: Jan Evangelista Purkyn? University in Ústí nad Labem, Faculty of Social and Economic Studies Author-Name: Marek Vokoun Author-Name-First: Marek Author-Name-Last: Vokoun Author-Email: marek.vokoun@ujep.cz Author-Workplace-Name: Jan Evangelista Purkyn? University in Ústí nad Labem, Faculty of Social and Economic Studies Author-Name: Vladimír Barák Author-Name-First: Vladimír Author-Name-Last: Barák Author-Email: vladimir.barak@vse.cz Author-Workplace-Name: Prague University of Economics and Business, Faculty of Economics, Department of Economic and Social Policy Title: Neuroeconomics - a review of the influence of neurotransmitters on the behaviour and decision-making of individuals in economic matters Abstract: Neuroeconomics is a modern interdisciplinary approach that explores the interplay between economic theories and the biological and physiological processes that influence human decision-making. This article explores the differences between traditional economic concepts, such as the "homo economicus" model, and neuroeconomics approaches that emphasize the importance of biological mechanisms. A key part of the analysis is the study of the role of neurotransmitters such as dopamine, acetylcholine, noradrenaline, and serotonin and their influence on decision-making processes. Measurement and manipulation techniques are also considered to map these processes and provide new insights into the behavior of individuals in economic situations, particularly in the context of impulsivity and impatience. The behavioral dimension of neuroeconomic models is also discussed, linking biological and economic aspects of human behavior. In this context, the paper highlights the controversial nature of the general conclusions, especially given the multidimensionality of human heterogeneity and the limits of experimental research, often influenced by the unavailability of technical facilities. Attention is also paid to the ethical and practical challenges posed by neuroeconomics, including the potential negative consequences for health, decision-making, and manipulative practices. From an interdisciplinary perspective, the article explores the contributions of neuroeconomics to health economics and social policy. The authors conclude that this innovative approach contributes to a deeper understanding of human decision-making and confirms the importance of the complex interplay between biological, behavioral, and economic aspects of human existence. This work highlights that neuroeconomics has the potential to become a key tool for improving quality of life and enhancing scientific knowledge at the interface of different disciplines. Classification-JEL: D87, D81, D91 Keywords: neuroeconomics, dopamine, serotonin, acetylcholine, oxytocin, noradrenaline, intertemporal decision making, risk perception, social preferences, neuroleadership, motivation, reward, trust Journal: International Journal of Economic Sciences Pages: 129-149 Volume: 13 Issue: 2 Year: 2024 Month: December File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117130 File-URL: https://eurrec.org/RePec/aop/jijoes/0091ES.rdf117130?download=8 Handle: RePEc:aop:jijoes:v:13:y:2024:i:2:p:129-149