I investigated the effects of adolescents' attitudes toward risk on their choice of employment sector in adulthood. I employed a joint model of employment sector choice and three-dimensional background characteristics to demonstrate that employment preference is an inverse function of the degree of relative risk aversion. Empirical data was obtained from longitudinal data, and a logit model was applied to estimate the effects of the three-dimensional background characteristics on the risk-taking attitudes and employment choices. I observed that individuals with a higher tendency to engage in risky experiences exhibit low risk aversion, and thus, tend to choose a riskier employment sector.
Payment systems make a significant contribution to the flow of transactions and financial stability. In this paper, we start by applying the principles of the gravity model to explain the TARGET flows of banking transactions between Portugal and other eurozone countries. The main explanatory variables tested are a composite indicator of economic and financial activities, distance, membership of the Eurozone (EZ), and country risk measured by treasury bond yields. The results indicate that Portugal has a high level of integration in the European banking market as distance is not statistically significant, and that the membership of the EZ facilitates the financing of the economy. The economic size of the partner country becomes non-significant after controlling for country fixed effects. The increase in the Portuguese country risk during the European sovereign debt crisis led to a marked decline in external financing, indicating that this is an important channel of transmission of crises.
Exports play a significant role in the economic catching-up transition in Central and Eastern Europe (CEE). The East Asian market has emerged for CEE’s exports not only because of its dynamic economy, but also because of the European debt crisis, the political tension between Ukraine and Russia, and the recent threat of terrorism. This study utilises panel ARDL models to estimate the long-run and short-run relationships between export instability and commodity concentration and geographic concentration. The datasets cover the 2004–2014 period for the trade of all the CEE countries with 10 East Asian marketplaces. The results of the causal relationships show significance in the long-run, but not in the short-run. This study suggests that the CEE export policy toward East Asia is likely to consider the impact of trade concentrations on export instability.
Authors:Lena Malešević Perović, Silvia Golem and Maja Mihaljević Kosor
This paper analyses spatial impact of government expenditures on education on economic growth in the EU28 countries during the period 2004–2013. Employing a novel econometric technique that allows for the estimation of spatial spillovers, our results indicate that government expenditures on education significantly and positively infl uence GDP growth. Moreover, the indirect i.e. the spillover effects are quite large suggesting that the growth models should account for spatial interdependencies. Precisely, we find that education expenditures in one country affect GDP growth in the neighbouring countries, meaning that these spillovers are geographical in nature. Moreover, we find that the degree of interdependence among countries varies according to the average GDP per capita even if their geographical distances are identical. Additionally, immigration is found to be an important channel of spatial transmission.
Authors:Radmila Dragutinović-Mitrović and Predrag Bjelić
This paper aims at investigating the role of different trade regimes in determining the bilateral trade of Western Balkan countries and the enlarged European Union between 2001—2010. Special focus is laid on the intra-regional trade of Western Balkan countries and complementarities of this sub-regional trade integration and the EU accession process. Using panel data, we estimated the gravity model of bilateral exports from Western Balkan and Central Eastern European countries to the core EU members in the 2001–2010 period. The results confirm the importance of EU membership for the development of acceding countries’ trade and shed light on asymmetrical trade regimes as important factors of boosting the bilateral trade flows. Additionally, CEFTA 2006 has a significant contribution to intra-regional Western Balkans trade.
This article investigates the efficiency of the matching process by panel stochastic frontier estimation of the matching function in Croatia. The empirical analysis is conducted on a regional level using regional office-level monthly data obtained from the Croatian Employment Service for 2000–2011. The results suggest that the efficiency of the matching process is rising over time, although with significant regional variations. In order to explore these variations, structural characteristics of the labour market together with some policy variables are included in the second-stage estimation. Various structural variables have different impact on the matching efficiency, while policy variables are mostly positively correlated with it. For instance, both active labour market programs and the number of high-skilled employees in regional employment offices positively affect matching efficiency. Additionally, when regional income per capita is included in the model, it shows positive impact on the matching efficiency, indicating that demand fluctuations predominantly affect the matching process. Finally, in order to get consistent estimates, panel stochastic frontier model transformation is applied. The obtained results show that there is no major difference in estimated mean technical efficiency coefficients in comparison to the original estimation.
This paper deals with the possible existence of political budget cycles (PBCs) within the European Union (EU). I use panel data for 28 EU countries from 1995 to 2016 and provide estimates based on dynamic panel regressions. I employ a system-GMM estimator complemented by the Principal Component Analysis (PCA) to limit the number of instruments. The specifications include structural budget balances related to the potential GDP, thereby limiting the initial endogeneity. These measures capture the true motivation behind fiscal policies. The results suggest that the EU member states exhibit PBCs: (i) the intervention occurs in the year before elections and (ii) the structural budget balance to the potential GDP ratio is lower by −0.41 percentage points a year before elections. In addition, I have investigated the EU fragmentation in terms of the PBCs and selected 8 countries’ characteristics correlating to the existence of these cycles. These include lower GDP per capita, post-communist background, low tax burden, high perceived corruption, low levels of media freedom and internet usage, lower number of directly voted-in legislative officials, and a low parliamentary voter turnout.
Authors:Mirjana Gligorić Matić, Biljana Jovanović Gavrilović and Nenad Stanišić
After Second World War (WWII) a true evolution in understanding of economic development happened, which affected the ways of measuring prosperity, i.e. perceiving changes in people’s welfare. Numerous indicators have been created, which go ‘beyond GDP’ and cover different aspects of development and well-being. The aim of this paper is to analyse prosperity convergence in 32 European countries with a composite indicator – Legatum Prosperity Index (LPI). LPI is more complete than other indicators used in convergence analysis and reflects multidimensional nature of modern development and prosperity. Our research of absolute beta convergence is based on cross-sectional and panel data. Results indicate the existence of convergence in the overall index and its constitutive parts – dimensions and pillars, with different convergence speed regarding LPI and its segments for the total sample of countries, as well as for the countries of Eastern and Western Europe.
In our work, we compare the predictive power of different bankruptcy prediction models built on financial indicators calculable from businesses’ accounting data on the database of the first Hungarian bankruptcy model. For modelling, we use data-mining methods often applied in bankruptcy prediction: neural networks (NN), support vector machines (SVM) and the rough set theory (RST) capable of rule-based classification. The point of departure for our comparative analysis is the practical finding that black-box-type data-mining methods typically show better classification performance than models whose results are easy to interpret, i.e. there seems to be a kind of trade-off between the interpretability and predictive power of bankruptcy models. Empirical results lead us to conclude that the RST approach can be a competitive alternative to black-box-type SVM and NN models. In our research, we did not find any major trade-off between the interpretability and predictive performance of bankruptcy models on the database of the first Hungarian bankruptcy model.
Discussion on methodological problems of corporate survival and solvency prediction is enjoying a renaissance in the era of financial and economic crisis. Within the framework of this article, the most frequently applied bankruptcy prediction methods are competed on a Hungarian corporate database. Model reliability is evaluated by Receiver Operating Characteristic (ROC) curve analysis. The article attempts to answer the question of whether the simultaneous application of data reduction and univariate splitting (or just one of them) improves model performance, and for which methods it is worth applying such transformations.