https://journals.ue.poznan.pl/ebr/issue/feed Economics and Business Review 2024-06-05T10:28:54+02:00 Anna Bogajewska-Szymańska secretary@ebr.edu.pl Open Journal Systems <p>The Economics and Business Review (earlier as the Poznan University of Economics Review) has been published by Poznań University of Economics and Business Press since 2001. The EBR provides a platform for academicians all over the world to share, discuss and integrate state-of-the-art economics and finance thinking with a special focus on emerging market economies.</p> <p>The EBR invites submissions of original and unpublished articles. The journal is published in English only, with a frequency of four issues yearly. Texts are double-blind reviewed.</p> <p>EBR is an open access journal. To submit, process and publish an article in Economics and Business Review authors are not required to pay any charge.</p> <table style="height: 14px;"> <tbody> <tr style="height: 14px;"> <td style="width: 161px; height: 14px;"> <p><span style="text-decoration: underline;"><strong>Impact Factor 2022: </strong></span></p> </td> <td style="width: 38px; height: 14px;"> <p><span style="text-decoration: underline;"><strong>0.7</strong></span></p> </td> <td style="width: 132px; height: 14px;"> <p><strong> </strong></p> </td> <td style="width: 124px; height: 14px;"> <p><span style="text-decoration: underline;"><strong>CiteScore 2023: </strong></span></p> </td> <td style="width: 34px; height: 14px;"> <p><span style="text-decoration: underline;"><strong>1.4</strong></span></p> </td> </tr> </tbody> </table> <p> </p> <p><strong>Thematic issue: Large language models in economics and finance</strong><br /><em>Economics and Business Review</em> currently invites submissions for a thematic issue on large language models. Please check the <a href="https://journals.ue.poznan.pl/ebr/announcement/view/14">call for papers</a>.</p> <p><em>The Economics and Business Review journal received a grant within the Development of Scientific Journals programme of the Minister of Education and Science of Poland. Years 2022-2024, contract no. RCN/SP/0242/2021/1, financing 73 200 PLN. The project aims to maintain and improve editorial standards, increase the reach and impact of the journal, and modernize the journal website.</em></p> https://journals.ue.poznan.pl/ebr/article/view/1027 Determinants of labor productivity regional diversity in Italy 2024-06-05T10:28:54+02:00 Oleksij Kelebaj oleksij.kelebaj@doctoral.uj.edu.pl Katarzyna Filipowicz k.filipowicz@uj.edu.pl Tomasz Tokarski t.tokarski@uj.edu.pl <p>The aim of the paper is to assess the causes of spatial variations in labour productivity of Italian regions using the gravity model of economic growth. The model is an extension of Robert Solow’s economic growth model. The authors calibrate the model parameters using historical data and carry out numerical simulations of the long-run equilibrium states of the model. The scenarios considered in the paper vary in forecast investment rates, employment growth rates and urbanization rates. To achieve the full convergence in labour productivity, it is necessary to maintain higher investment rates in the south of the country than in Lombardy (by about 4-11%), and to keep investment rates in central and northern Italy at a similar level as in Lombardy. The fall in investment has affected the poorest regions, southern Italy, the most, followed by central Italy and the richest regions of the north of the country the least</p> 2024-06-04T00:00:00+02:00 Copyright (c) 2024 Oleksij Kelebaj, Katarzyna Filipowicz, Tomasz Tokarski https://journals.ue.poznan.pl/ebr/article/view/1149 Personal bankruptcy prediction using machine learning techniques 2024-02-12T13:29:22+01:00 Magdalena Brygała magdalena.brygala@pg.edu.pl Tomasz Korol tomasz.korol@zie.pg.gda.pl <p>It has become crucial to have an early prediction model that provides accurate assurance for users about the financial situation of consumers. Recent studies focused on predicting corporate bankruptcies and credit defaults, not personal bankruptcies. Due to that, this study fills the literature gap by comparing different machine learning algorithms to predict personal bankruptcy. The main objective of the study is to&nbsp;examine the usefulness of machine learning models such as random forest, XGBoost, LightGBM, AdaBoost, CatBoost, and support vector machines in forecasting personal bankruptcy. The research relies on two samples of households (learning and testing) from the Survey of Consumer Finances, which was conducted in the United States. Among the estimated models, CatBoost and XGBoost showed the highest effectiveness. Among 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.</p> 2024-06-12T00:00:00+02:00 Copyright (c) 2024 Magdalena Brygała, Tomasz Korol https://journals.ue.poznan.pl/ebr/article/view/1255 Growth prospects for the silver economy in the market segment of residential care services provided to dependent elderly people 2024-03-26T16:35:15+01:00 Rafał Iwański rafal.iwanski@usz.edu.pl <p>The aim of this study is to characterise the determinants of the development of the silver economy in the field of care services provided in a residential form for dependent elderly persons in Poland. The analysis was carried out on the basis of statistical and financial background data, including those from the Ministry of Family and Social Affairs, the Ministry of Health, OECD, etc. Although the demand for care services will continue to grow in the coming years, the following barriers to the development of this segment of the silver economy can be identified: lack of employees, unattractiveness of monetary gratification, inefficient financing mechanisms, lack of public investment in the development of care facilities, and increasing costs of providing services in all forms.</p> 2024-06-07T00:00:00+02:00 Copyright (c) 2024 Rafał Iwański