Journals Poznań University of Economics and Business
Not a member yet
866 research outputs found
Sort by
Trade liberalisation and tax revenue mobilisation in ECOWAS countries
No full textObjectif : L’objectif de cet article est d’analyser l’effet de la libéralisation commerciale sur les recettes fiscales des pays de la Communauté Économique Des États de l’Afrique de l’Ouest (CEDEAO).
Conception/méthodologie/approche : L’analyse économétrique s’est faite sur des données de panel estimée par la méthode à effets fixes et couvre la période 1990–2016.
Résultats : Les résultats révèlent que l’effet de la libéralisation des échanges commerciaux sur les recettes fiscales est sensible à l’indicateur de mesure utilisé. La libéralisation commerciale, lorsqu’elle est mesurée par les taux tarifaires moyens, influence positivement et significativement les recettes fiscales totales et les recettes fiscales domestiques tandisqu’une relation négative et statistiquement significative est trouvée entre baisse des tarifs et recettes fiscales issues des transactions internationales. Par ailleurs, lorsque la libéralisation commerciale est captée par le degré d’ouverture commerciale, l’effet est positif et significatif pour toutes les catégories de recettes fiscales.
Originalité/valeur : Les gouvernements des différents pays de la zone ont intérêt à encourager la baisse des tarifs douaniers et l’ouverture au commerce international afin de renforcer la mobilisation des recettes fiscales. Toutefois, cette libéralisation commerciale doit s’accompagner d’une politique macroéconomique appropriée permettant de garantir un environnement économique stable et d’une bonne gouvernance pour assurer la crédibilité de la politique mise en oeuvre.Purpose: The purpose of this article is to analyse the impact of trade liberalisation on tax revenues in the countries of the Economic Community of West African States (ECOWAS).
Design/methodology/approach: The econometric analysis is based on panel data estimated using the fixed effects method and covers the period from 1990 to 2016.
Findings: The findings show that the effect of trade liberalisation on tax revenues is sensitive to the measure used. Trade liberalisation measured by average tariff rates has a positive and significant effect on total tax revenue and domestic tax revenue, while a negative and statistically significant relationship is found between tariff reductions and tax revenue from international transactions. Furthermore, when trade liberalisation is captured by the degree of trade openness, the effect is positive and significant for all categories of tax revenue.
Originality/value: It is in the interest of the governments of the various countries in the zone to promote lower tariffs and greater openness to international trade in order to increase the mobilisation of tax revenues. However, this trade liberalisation must be accompanied by appropriate macroeconomic policies to guarantee a stable economic environment and good governance to ensure the credibility of the policies implemented
Proposal for a comprehensive retirement insurance solution (CRIS) to mitigate retirement risk based on theory of change
Full text linkThe aim of the paper is to propose a new comprehensive retirement insurance solution (CRIS) that, by offering appropriate modules, can be flexibly adapted to customers’ needs during the accumulation of funds and entitlements and during retirement. Technically, the product is life-insurance-based and includes insurance for sickness and incapacity, long-term care (LTC), work activation expenses, hospital stays, and tontine and Luxembourg policies. Due to consumers’ changing expectations and needs, the technical dimension of this solution is based on a three-layer insurance product in which individual parts of the protection are supplemented by several additional benefits (types of assistance) that improve the quality of life of insurance participants and allow the ongoing use of the product.
Taxation of public pensions in European Union countries
Full text linkThe aging of society is one of the most important trends shaping the social, economic and political life of the 21st century. However, with the increasing number of people of retirement age, the problem of ensuring adequate conditions for a longer life arises. The state influences these conditions through the pension security system, including taxation of pensions. The paper attempts to answer the question whether taxation of remunerations and public pension benefits may have a significant impact on making decisions about choosing a country of work in the common market. For this purpose, Member States have been ranked in terms of two dimensions—the conditions of taxation of wages and the conditions of taxation of retirement benefits.
Personal bankruptcy prediction using machine learning techniques
Full text linkIt has become crucial to have an early prediction model that provides accurate assurance for users about the financial situation of consumers. Recent studies have focused on predicting corporate bankruptcies and credit defaults, not personal bankruptcies. Due to this situation, the present study fills the literature gap by comparing different machine learning algorithms to predict personal bankruptcy. The main objective of the study is to examine the usefulness of machine learning models such as SVM, random forest, AdaBoost, XGBoost, LightGBM, and CatBoost in forecasting personal bankruptcy. The study relies on two samples of households (learning and testing) from the Survey of Consumer Finances, which was conducted in the United States. Among the models estimated, LightGBM, CatBoost, and XGBoost showed the highest effectiveness. The most important variables used in the models are income, refusal to grant credit, delays in the repayment of liabilities, the revolving debt ratio, and the housing debt ratio
Apport des modèles mathématiques et big data pour la prise de décisions de l\u27entreprise; le cas d\u27épidémies telles que le SARS-CoV-2 dans le secteur de la santé au Chili
No full textThe pandemic caused by the COVID-19 virus has given rise to numerous analyses and studies due to the implications and serious consequences it has had on all areas of human development worldwide. The data unquestionably reflect the degree of impact it has had, not only on the mortality rate, but also on the economic indices of nations. In analysing all these indicators, the question arises as to whether some key elements, such as the number of incidences, the variables of the effective reproductive factor of the disease could better reflect the predictability of the cases and, in turn, evaluate the mitigating measures to placate the incidence of new cases. This analysis is especially significant considering that the pandemic is not over, and that more and better resolutions are still needed to address this ongoing crisis. In this context, the present study aims to analyse, from the theoretical mathematical models, what has been the contribution of this area of science to find and predict possible solutions to quell the effects of this global pandemic. For this purpose, statistical analyses based on three models will be used : non-linear phenomenological models, data modeling and the generalised logistic model, which are expected to contribute to a better evaluation and understanding of the measures taken to face this health crisis and, in the future, the importance of understanding the use of data and the technological tools available to mankind today in the face of any new virus.(original abstract)The pandemic caused by the COVID-19 virus has given rise to numerous analyses and studies due to the implications and serious consequences it has had on all areas of human development worldwide. The data unquestionably reflect the degree of impact it has had, not only on the mortality rate, but also on the economic indices of nations. In analysing all these indicators, the question arises as to whether some key elements, such as the number of incidences, the variables of the effective reproductive factor of the disease could better reflect the predictability of the cases and, in turn, evaluate the mitigating measures to placate the incidence of new cases. This analysis is especially significant considering that the pandemic is not over, and that more and better resolutions are still needed to address this ongoing crisis. In this context, the present study aims to analyse, from the theoretical mathematical models, what has been the contribution of this area of science to find and predict possible solutions to quell the effects of this global pandemic. For this purpose, statistical analyses based on three models will be used : non-linear phenomenological models, data modeling and the generalised logistic model, which are expected to contribute to a better evaluation and understanding of the measures taken to face this health crisis and, in the future, the importance of understanding the use of data and the technological tools available to mankind today in the face of any new virus.La pandémie causée par le virus COVID-19 a fait l\u27objet de nombreuses analyses et études en raison de ses incidences et conséquences graves dans tous les secteurs du développement humain au niveau mondial. Les données rendent compte de son impact non seulement sur le taux de mortalité mais aussi sur les indices économiques des pays. Lorsque l\u27on analyse tous ces indicateurs, on se demande si certains d\u27entre eux, tels que le nombre d\u27incidences et les variables du facteur reproductif effectif de maladie, ne peuvent pas mieux refléter la prédictibilité des cas et ainsi évaluer les mesures permettant d\u27atténuer l\u27incidence de nouveaux cas. Cette analyse est particulièrement significative si l\u27on considère que la pandémie n\u27est pas terminée et que de plus importantes et meilleurs résolutions sont encore nécessaires pour faire face à la crise en cours. Dans ce contexte, notre étude se propose d\u27analyser, à partir des modèles théoriques mathématiques, l\u27apport de ce secteur de la science pour trouver et prévoir de possibles solutions afin de diminuer les effets de cette pandémie. Pour cela, nous utiliserons des analyses statistiques basées sur trois modèles, phénoménologiques non linéaires, configuration de données et modèle logistique généralisé, en espérant qu\u27ils contribueront à une meilleure évaluation et compréhension des mesures prises face à la crise sanitaire et qui seront adoptées à l\u27avenir pour faire face à de nouveaux virus, en utilisant mieux les données et les outils technologiques dont dispose l\u27humanité
Forecasting realized volatility through financial turbulence and neural networks
Full text linkThis paper introduces and examines a novel realized volatility forecasting model that makes use of Long Short-Term Memory (LSTM) neural networks and the risk metric Financial Turbulence (FT). The proposed model is compared to five alternative models, of which two incorporate LSTM neural networks and the remaining three include GARCH(1,1), EGARCH(1,1), and HAR models. The results of this paper demonstrate that the proposed model yields statistically significantly more accurate and robust forecasts than all other studied models when applied to stocks with middle-to-high volatility. Yet, considering low-volatility stocks, it can only be confidently affirmed that the proposed model yields statistically significantly more robust forecasts relative to all other models considered
Google Search intensity and stock returns in frontier markets: Evidence from the Vietnamese market
Full text linkThe study investigates investor attention\u27s impact on stock trading by modeling the relationship between Google search intensity and stock return with stocks listed in frontier markets in Vietnam from October 2016 to October 2021. The study has three findings. First, the study confirms the price pressure hypothesis and attention theory that Google search intensity positively affects stock returns. Second, this study indicates that the impact of Google search intensity on stock price is short. The positive effect is within the week of searching and reverses the following week, although the reverse force is not strong. Third, the relationship is more robust post than pre-COVID-19, suggesting that after a shock, more new individual investors enter the market, the impact of GSVI on stock return is stronger
Assessing the long-term asymmetric relationship between energy consumption and CO2 emissions: Evidence from the Visegrad Group countries
Full text linkThis study investigates the impact of renewable (REW) and non-renewable (NREW) energy usage, along with economic growth, on carbon dioxide emissions in the Visegrad countries, which rely heavily on traditional energy sources. Using data from 1991 to 2021, the analysis employs a panel asymmetric regression with Driscoll-Kraay and FGLS standard errors. The latent cointegration test reveals long-term relationships with asymmetry among the variables. Real GDP fluctuations exhibit a negative impact on CO2emissions for both positive and negative shocks. A reduction in conventional energy source consumption leads to a greater CO2 emission reduction, confirming asymmetry. Conversely, an increase in consumption positively impacts CO2 reduction. However, non-conventional energy sources show no asymmetries. The OLS-based model proposed by Driscoll-Kraay showed reduced standard errors, but lower significance in the estimated parameters compared to the FGLS model. The findings recommend a sustainable energy transition for Visegrad countries by eliminating traditional sources and promoting renewable resources
Enhancing garbage fee compliance: Insights from a Slovak municipality
Full text linkTax avoidance and tax evasion remain critical challenges for central or local governments and municipalities. This non-compliance also represents an ethical issue since individuals who benefit from publicly provided services do not contribute to their financing as they are legally required. The study aimed to test whether the use of behavioural interventions would reduce the number of non-payers of the garbage collection fee in the city of Hlohovec, Slovakia. The experiment was carried out by distributing leaflets to households with permanent residence in Hlohovec. The subjects of the experiment were randomly divided into three groups. Households in the control group (number of households is 1,718) did not receive any leaflets, households in the first intervention group (number of households is 1,721) received a leaflet containing a social norm, and households in the second intervention group (number of households is 1,625) received a leaflet containing a deterrent message.
Role of subjective norms in shaping entrepreneurial intentions among students
Full text linkIn view of the inconsistency in prior research, the main goal of this analysis is to determine the influence of subjective norms on entrepreneurial intentions among Polish students. The secondary goal is to examine how these subjective norms are affected by entrepreneurial experiences among individuals close to students, the students’ self-employment history and work experiences, and their gender. Based on the framework of the theory of planned behaviour and data generated through surveys of students in a management programme (N = 255), structural equation modelling is applied. The results indicate that subjective norms indirectly influence students’ entrepreneurial intentions (through attitude towards entrepreneurship and perceived behavioural control). Regarding the antecedents of subjective norms, students’ prior entrepreneurial experience and work history are not significant, nor is gender.