<abstract><title style='display:none'>Abstract</title> Recent developments in the field of information and communication technologies (ICTs) have created new opportunities for enhancing both the operations and competitiveness within the banking sector. The application of contemporary ICT-based solutions has resulted in significant changes in the traditional banking business, through the involvement of brand new approaches in the process of distribution of banking products and services to customers. As a part of the services offered by any modern bank, e-banking has become a synonym for an efficient system aimed at delivering traditional banking services through electronic communications channels, available to anybody, anywhere and anytime. The goal of the paper is to perform an empirical analysis of the current situation regarding the level of customer usage and satisfaction with e-banking services in the Republic of Macedonia. The study will enable us to determine which variables affect the level of adoption and satisfaction with е-banking services. The study is fully based on the statistical data analysis of the responses gathered from a representative sample of e-banking customers.</abstract>

An empirical study of customer usage and satisfaction with e-banking services in the Republic of Macedonia

<abstract><title style='display:none'>Abstract</title>The financial numbers game is unfortunately alive and doing well. One of the forensic accounting techniques is based on Benford’s Law and is used for the detection of unusual transactions, anomalies or trends. The aim of this paper is to test whether the financial statements of Croatian companies deviate from Benford’s Law distribution. The financial statements of 24 companies that are in the pre-bankruptcy settlement process and 24 companies that are not in the pre-bankruptcy settlement process were analysed using the Benford’s Law test of the first digit distribution for the period from 2015 to 2018. The data used to calculate the first digits of distribution were taken from the Zagreb Stock Exchange. The chi-square test has shown that the observed companies that are not in the process of pre-bankruptcy settlement do not have the first digit distribution which follows the Benford’s Law distribution. The Kolmogorov-Smirnov Z test has shown that the distribution of the first digits from the financial statements of companies listed on the Zagreb Stock Exchange fits to Benford’s Law distribution.</abstract>

The empirical analysis of financial reports of companies in Croatia: Benford distribution curve as a benchmark for first digits

<abstract><title style='display:none'>Abstract</title>Since the endogenous growth model appeared in the economic theory, taxation has been considered as one of the key determinants of the economic growth. In the public finance theory, taxation is considered to have a negative impact on economic growth, which is explained by implications of tax revenues distortions on the economic activity. This assumption has been investigated by many empirical studies. The aim of this paper is to analyse the impact of personal income taxation on economic conditions in Croatia in the long-run. After providing a brief insight into the economic and the public finance theory regarding taxation and economic growth, previous relevant research is presented. The empirical analysis of the impact of personal income taxation on economic conditions in Croatia is conducted using the Johansen cointegration approach. The existence of cointegration is examined and the error correction model is estimated using monthly data from January 2000 to March 2016. The results of the research show that personal income taxation in Croatia has a significant negative impact on the economic growth in the long-run, which is in line with the economic theory and relevant empirical research.</abstract>

The long-run impact of personal income taxation on economic development: Evidence from Croatia

<abstract><title style='display:none'>Abstract</title>In Herzegovina, different genotypes of grapevine are called the same, and the origin of these cultivars is mainly unexplored. Two groups of autochthonous cultivars are grown. The first group consists of more widespread Žilavka and Blatina, and accompanying Bena, Krkošija, Dobrogostina and Trnjak, and the second one of less common cultivars that should be preserved from extinction. Considering the small number of studies on the comparison of different methods used for analyses of similarities and relatedness of grapevine germplasm, it was interesting to assess the use of morphological characterization with molecular markers in identification of cultivars in Herzegovina. The results indicate that a similarity coefficient had a broad value range for both methods. Both methods successfully in different ways differentiated all analysed varieties, and for complete and comprehensive identification of grapevine varieties should be use.</abstract>

Morphological and genetic characterization of vine grape cultivars of Herzegovina

<abstract><title style='display:none'>Abstract</title> The paper assesses the existence of purchasing power parity (PPP) in ASEAN+3 economies taking into account EUR and USD as reference currencies. The research refers to the period from January 2000 to June 2017 and there are three points of view: we tested the period as a whole and then the pre-crisis period and the postcrisis period regarding the structural break due to the economic crisis. The evaluated economies include Brunei, Cambodia, China, Indonesia, Japan, Korea, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand and Vietnam. A range of panel unit root tests are applied, covering the Levin, Lin and Chu test, the Breitung test, the Im, Pesaran and Shin test, the ADF-Fisher test and the PP-Fisher test. In cases where the unit root is rejected, the validity of PPP is confirmed. However, our results are ambiguous and depend on the selection of the base currency, the time period observed and on the choice of the methodology.</abstract>

Purchasing power parity in ASEAN+3: an application of panel unit root tests

<abstract><title style='display:none'>Abstract</title> In this study, a housing wealth effect on personal consumption is assumed and tested on 16 selected European countries using an estimator developed for dynamic heterogeneous panel data analysis. Empirical estimates have shown that there is a long-run and a short-run housing wealth effect in analysed countries. The elasticity of real private consumption to changes in real disposable income has shown to be positive and statistically significant as well as the elasticity of consumption to changes in real housing wealth. Therefore, the research hypothesis of this paper of a statistically significant and positive long-term relationship between housing wealth and private consumption in the analysed countries was confirmed.</abstract>

Is there a housing wealth effect in European countries?

<abstract>
<title style='display:none'>Abstract</title>
The purpose of this study is to analyse the influence of exchange rate shocks on foreign trade (exports and imports) of fifteen economies within the ECOWAS sub-region. To accomplish the goal of this paper, Autoregressive Distributed Lag (ARDL) procedure was employed to investigate the impact volatility in the exchange rate market has on foreign trade in both long- and short-term with data between 1980 and 2020. To compute volatility, it relied on the GARCH (1, 1) model which predicted the conditional variances as proxy for volatility. Our empirical results are distinguished into export model and import model, and reveal that volatility in exchange rate influence foreign trade performance (exports and imports) negatively in the short-run, though statistically insignificant. The impact however becomes positive in the long run, and statistically significant for the two models. These results signpost that while the volatilities in foreign exchange market appear to deteriorate the international trade of these economies in the short-term, it substantially and significantly causes its improvement in the long-term. Hence, our results validate the J curve effect in the case of these ECOWAS economies. Policy implication from the findings suggests that to develop a robust international trade and ultimate economic growth, it is recommended that policymakers of these economies maintain a short-term stability in their foreign currency markets by way of adopting some intervention measures.
</abstract>

Dependence between foreign trade performance and exchange rate volatility: Panel ARDL approach

<abstract>
<title style='display:none'>Abstract</title>
This paper examines the relationship between family stressors and subsequent financial behavior of young individuals in Croatia. Previous research indicates that family stressors are associated with increased levels of financial stress, resulting in impulsive purchases, risky financial behavior, and increased debt. More specifically, family stressors during youth are shown to significantly affect an individual's financial behavior later in life. Research has shown that youth family stressors, such as poverty, parental divorce, and parental unemployment, can lead to financial stress and affect financial behavior in adulthood. This paper provides an illustrative review of the Family Stress Model (FSM) framework to understand how family stressors influence youngsters in the financial domain. Using regression modeling, we estimate that family stress significantly impacts the financial behavior of young individuals in Croatia. Specifically, the study finds that family stress is negatively associated with responsible financial behavior. These findings have important implications for policymakers and practitioners, particularly those involved in financial education and family support programs, highlighting the need to address family stress as a potential risk factor for poor financial outcomes among young individuals. It is important to recognize the relationship between youth family stressors and financial behavior and work on managing both to improve financial well-being in adulthood.
</abstract>

Exploring the impact of family stressors on financial behavior: A study of Croatian youth

<abstract>
<title style='display:none'>Abstract</title>
This study examines the role of digital business incubators, focusing specifically on the Qatar Digital Incubation Center (DIC), in fostering digital entrepreneurship. The methodology used is qualitative, employing content analysis to interpret textual and visual data from sources such as online databases, documents, reports, and academic research papers. International benchmark reports are used to assess Qatar's global ranking in research, development, innovation, and digital entrepreneurship. The findings highlight Qatar's commitment to digital transformation and its efforts to create a supportive ecosystem for entrepreneurship. They underscore Qatar's dedication to driving innovation through investments in telecommunications, information technology, education, and initiatives like the Qatar National Research Fund. Qatar's digital competitiveness is evident through its ICT infrastructure, extensive 5G implementation, and initiatives like the Smart Qatar Program. The DIC plays a pivotal role in supporting digital entrepreneurs by providing resources, mentorship, and a collaborative environment. By collaborating with government agencies, academic institutions, and industry partners, the DIC contributes to the growth and success of digital startups, fostering innovation, and positioning Qatar as a hub for digital entrepreneurship and technological innovation. This study provides valuable insights into the development of Qatar's digital entrepreneurship ecosystem and the significance of digital business incubators, including the DIC.
</abstract>

Digital Business Incubators and Digital Entrepreneurship: The case of Digital Incubation Center in Qatar

<abstract>
<title style='display:none'>Abstract</title>
The prediction of financial distress has emerged as a significant concern over a prolonged period spanning more than half a century. This subject has garnered considerable attention owing to the precise outcomes derived from its predictive models. The main objective of this study is to predict financial distress using two types of Artificial Neural Networks (ANN) compared to the Logistic Regression (LR), and this will be done by relying on the data of 12 Algerian companies for the period 2015-2019. The reason for choosing these two types of networks in particular, is attributed to the fact that Elman Neural Network (ENN) is commonly used network, in contrast to the Feed-forward Distributed Time Delay Neural Network (FFDTDNN). Regarding the choice of these companies as a study sample, can be attributed to the similarity in the temporal range covered by their financial statements, coupled with their approximate parity in terms of asset size. This study concluded that the ENN model outperformed the LR model in predicting financial distress with a classification accuracy of 100%. On the other hand, the LR model outperformed the FFDTDNN with a classification accuracy of 83.33%. Therefore, it can be asserted that ANNs cannot be regarded as superior to Logistic Regression (LR) in all statuses. Instead, it is accurate to affirm that specific types of ANNs exhibit greater efficacy than LR in predicting financial distress, while other types demonstrate relatively diminished effectiveness.
</abstract>

Unveiling the diverse efficacy of artificial neural networks and logistic regression: A comparative analysis in predicting financial distress

<abstract>
<title style='display:none'>Abstract</title>
This study examines the symmetric and asymmetric impact of public debt on economic growth in Côte d'Ivoire using time series data from 1972 to 2021. The analyses were performed using both linear and nonlinear autoregressive distributed lag (ARDL) models. The study also utilised the bounds F-test for cointegration, the Brock-Dechert-Scheinkman (BDS) nonlinearity test, and the Wald test for asymmetries. The findings of the bounds F-test provide support for both linear and nonlinear cointegration. The BDS test results indicate that the series are nonlinear, while Wald test results revealed an asymmetric relationship between public debt and economic growth in Côte d'Ivoire in the short run and symmetric relationship in the long run. Estimation results for the symmetric ARDL regression model provide no evidence of a statistically significant impact of public debt on economic growth, regardless of whether the analysis was conducted in the short run or long run. The NARDL findings indicate that, on average, positive changes to public debt lead to economic decline in the long run, while negative changes cause an economic upturn in the short run. The findings also show that GDP growth responds rapidly and strongly to negative changes in public debt. Therefore, the study encourages the government of Côte d'Ivoire to be cautious about public debt rise because it was established that they have a negative impact on economic growth. Negative changes in the public debt can serve to minimise the uncertainties in the business environment, thus promoting private, public, and foreign direct investments.
</abstract>

The impact of public debt on economic growth in Côte d'Ivoire: New evidence from linear and non-linear ARDL approaches

<abstract>
<title style='display:none'>Abstract</title>
According to the analyses published by the international organizations, the most developed countries are those from Group 8. The group of highly developed countries is in matter, which consists of: Japan, USA, Russia, Great Britain, Italy, Germany, France and Canada. The goal of the work is to determine the ranking list of the selected countries according to the level of development in 2021 based on a certain number of macroeconomic factors. For the purposes of realizing the formulated goal, the I distance method was applied. A decision for the I distance method comes from the fact that this model satisfies all the conditions characteristic for the nature of distance, that is, for the multidimensional phenomenon of development. Based on the ranking list of Group 8 countries, the United States of America is in the first place, followed by Germany, France, the United Kingdom, Italy, Canada, the Russian Federation and Japan. Speaking about the EU countries, the Netherlands has the highest level of development according to the selected indicators, followed by Ireland, Belgium, Spain, Poland, Sweden, Austria, Denmark, Czech Republic, Luxembourg etc. The coming future will probably bring changes when it comes to the ranking on the ranking list. Changes can be expected due to the war events, demographic trends, technological achievements, and generally the replacement of the leading positions when it comes to resources. Namely, it is certain that the countries that adapt faster to other energy sources as well as to more economical use of the existing ones, will have a leading role on a global scale.
</abstract>

I distance application in the ranking of Group 8 and European Union countries by level of development

<abstract>
<title style='display:none'>Abstract</title>
The problem of selecting an optimal set of investment stocks is of a huge interest for both individual and institutional investors. This paper compares the hybrid multiple criteria decision making (MCDM) approach to selecting the best stock to invest in, with the stock selection using modern portfolio theory (MPT). When selecting stocks, it is very important to thoroughly analyse stocks, according to multiple criteria, including their equity market indicators, as well as financial indicators. The objective of the research is to compare the stock selection using a hybrid MCDM approach and MPT, which includes only the equity market indicators. The analysed sample includes 18 stocks, which are CROBEX components on the Croatian capital market from January 2017 to January 2019. The rankings of stocks were calculated using five MCDM methods. These were then used to obtain the final hybrid stock ranking, which was compared to the MPT stock selection. The results show that there is a significant difference in the stock rankings. However, the stocks which have not entered any portfolio in MPT selection were ranked as lowest according to the hybrid MCDM approach, which confirms that those stocks are the worst to invest in. The research can serve as a guidance for investors to use all available stock information in their decision making process of investment.
</abstract>

Comparative analysis of stock selection using a hybrid MCDM approach and modern portfolio theory

<abstract><title style='display:none'>Abstract</title>Although energy efficiency is a hot topic in the context of global climate change, in the European Union directives and in national energy policies, methodology for estimating energy efficiency still relies on standard techniques defined by experts in the field. Recent research shows a potential of machine learning methods that can produce models to assess energy efficiency based on available previous data. In this paper, we analyse a real dataset of public buildings in Croatia, extract their most important features based on the correlation analysis and chi-square tests, cluster the buildings based on three selected features, and create a prediction model of energy efficiency for each cluster of buildings using the artificial neural network (ANN) methodology. The main objective of this research was to investigate whether a clustering procedure improves the accuracy of a neural network prediction model or not. For that purpose, the symmetric mean average percentage error (SMAPE) was used to compare the accuracy of the initial prediction model obtained on the whole dataset and the separate models obtained on each cluster. The results show that the clustering procedure has not increased the prediction accuracy of the models. Those preliminary findings can be used to set goals for future research, which can be focused on estimating clusters using more features, conducted more extensive variable reduction, and testing more machine learning algorithms to obtain more accurate models which will enable reducing costs in the public sector.</abstract>

Cluster analysis and artificial neural networks in predicting energy efficiency of public buildings as a cost-saving approach

<abstract><title style='display:none'>Abstract</title>The average expected duration of human life is rising because of different reasons. On the other hand, not only the duration, but the quality of life level is important, too. The higher the quality of life level, the citizens’ happiness and satisfaction levels are higher, which has positive impact on the development and operating of an economy. The goal of this paper is to identify groups of European countries, using statistical hierarchical cluster analysis, by using the quality of life indicators, and to recognise differences in quality of life levels. The quality of life is measured by using seven different indicators. The conducted statistical hierarchical cluster analysis is based on the Ward’s clustering method, and squared Euclidean distances. The results of conducted statistical hierarchical cluster analysis enabled recognizing of three different groups of European countries: old European Union member states, new European Union members, and non-European Union member states. The analysis has revealed that the old European Union member states seem to have in average higher quality of life level than the new European Union member states. Furthermore, the European Union member states have in average higher quality of live level than non-European Union members do. The results indicate that quality of life levels and economic development levels are connected.</abstract>

Quality of Life Indicators in Selected European Countries: Hierarchical Cluster Analysis Approach

<abstract><title style='display:none'>Abstract</title> Composite indexes have become a valuable asset for stakeholders as they provide ranks of entities and information upon which decisions are made. However, certain questions about their development procedure have been raised recently, especially regarding the weighting process. To tackle the observed issue, in this paper we propose a new multivariate approach for defining weights. Namely, the model based on the Data Envelopment Analysis (DEA), the Benefit-of-the-Doubt (BoD) model, has been used with significant success in the process of composite index development. On the other hand, the Composite I-distance Indicator (CIDI) methodology stands out as an impartial method for assigning weights to indicators. By combining these two approaches, some of the limitations of the original BoD model could be overcome. As a result, new entity-specific weights which maximize the value of the composite index can be proposed. As a case study, we analysed the Quacquarelli Symonds (QS) World University Rankings by Subject in the field of statistics and operational research. The obtained results, which are based on the data-driven weights, can provide new insights into the nature of the observed ranking. The approach presented here might provoke further research on the topic of composite index weights and on the university rankings by subject.</abstract>

Faculty of Organizational Sciences, University of Belgrade, Belgrade,

Multivariate approach to imposing additional constraints on the Benefit-of-the-Doubt model: The case of QS World University Rankings by Subject

<abstract><title style='display:none'>Abstract</title>The expansion of the Internet has radically changed the way in which citizens travel, book and organise travel arrangements. Since innovation and new information technologies have become crucial determinants to encourage competitiveness in the tourism sector in Europe, this article investigates how selected development indicators influence the Percentage of individuals that use Internet for travel and accommodation services. Eurostat data for 34 European, European Union (EU-28) and selected EU candidates, countries for 2017 were analysed. It has been presented that (1) Gross Domestic Product per capita in Purchasing Power Standards; (2) Percentage of population aged 15 to 64, by tertiary education; as well as (3) Percentage of individuals aged 16 to 74, who have basic or above basic overall digital skills, all correlate positively and strongly with the main variable under study. The conducted regression analysis has shown that variable digital skills has the greatest impact on the main variable under the study. The K-mean clustering of countries resulted with four clusters. The Western Balkan countries can be found in a cluster which has in average the lowest values of all four variables in compare to the averages of other three clusters.</abstract>

Online booking for travel and accommodation influenced by economic and digital development level: Position of the Western Balkan countries within Europe

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Croatian Review of Economic, Business and Social Statistics

 Croatian Review of Economic, Business and Social Statistics (CREBSS) is a scientific journal published by SCIENDO on behalf of the Croatian Statistical Society. It publishes...

 Croatian Review of Economic, Business and Social Statistics (CREBSS) is a scientific journal published by SCIENDO on behalf of the Croatian...