Corporate governance and business performance: Evidence for the Romanian economy

Our finding contributes towards the understanding of movements regarding the adoption of corporate governance practice in emerging countries such as Romania and its impact on business performances of a company. We have developed two econometric models to assess the business performances of the companies listed on Bucharest Stock Exchange, in order to point out the impact of corporate governance on business performances. Our results are inconsistent for the period 2001–2011, but if we consider only 2011, the results document a positive correlation between corporate governance quality and market value of companies, such it is reflected by Tobin’s Q. Therefore, our results contribute to the studies relating corporate governance and business performances, as it confirms a positive relationship between the two variables which appears once the Romanian emerging economy has began to adopt the best corporate governance practices. Firstly, our research has important implications for managers in order to know that the adoption of the best corporate governance practices could contribute to the financial success of the firm. Secondly, the results are useful for any investor who needs to consider the quality of corporate governance as a good predictor for the best rate of return of theirs investments. Moreover, our findings have also implications on policy-makers and regulatory authorities in European developing countries and offer them a barometer of adopting the best corporate governance practices in European space. First published online: 17 Mar 201

Institutional, Sociological and Spatial Factors Influencing Consumer Protection Perceptions in the European Union

<p>The present study assesses through quantitative methods the problems specific to consumer protection. We focused on the factors that influence the number of complaints at national level and the perception of consumers that they are protected by public authorities. Data used for the 27 countries of the European Union were collected by official institutions, such as Heritage Foundations, United Nations Development Programme and the European Commission. Two types of econometric tools were employed: Ordinary Least Squares Multiple Regression and Spatial Econometric methods, such as map analysis, Moran’s I test for spatial autocorrelation and spatial regression. The results are convincing in what regards the institutional factors. Other types of behavior, such as social factors and spatial neighborhood effects, could not be highlighted.</p

Consumer protection through prices: an analysis of the energetic sector in European Union countries

Services of general economic interest (SGEI) are usually offered on markets characterized by monopoly, oligopoly, governmental or local authorities control or other forms of market imperfection. Consequently, issues related to consumer protection also present some particularities. In the energetic sector, the product offered (electricity) is absolutely homogeneous, allowing only consumer protection through price. Our study analyzed the presence of this phenomenon in the 27 countries of the European Union. Data was collected from official institutions, such as the World Bank, Europe's Energy Portal and the National Institutes of Statistics of the member states. Based on OLS regressions we demonstrated the existence of price-based protection for domestic consumers at EU level. Prices are regulated in such a way as to be correlated with the average wage. As an additional argument, we demonstrated that the energy price for industrial consumers follows a different formation mechanism, with main influence factor the energy import dependence

Machine Learning Models for Predicting Romanian Farmers’ Purchase of Crop Insurance

Considering the large size of the agricultural sector in Romania, increasing the crop insurance adoption rate and identifying the factors that drive adoption can present a real interest in the Romanian market. The main objective of this research was to identify the performance of machine learning (ML) models in predicting Romanian farmers’ purchase of crop insurance based on crop-level and farmer-level characteristics. The data set used contains 721 responses to a survey administered to Romanian farmers in September 2021, and includes both characteristics related to the crop as well as farmer-level socio-demographic attributes, perception about risk, perception about insurers and knowledge about agricultural insurance. Various ML algorithms have been implemented, and among the approaches developed, the Multi-Layer Perceptron Classifier (MLP) and the Linear Support Vector Classifier (SVC) outperform the other algorithms in terms of overall accuracy. Tree-based ensembles were used to identify the most prominent features, which included the farmer’s general perception of risk, their likelihood of engaging in risky behaviour, as well as their level of knowledge about crop insurance. The models implemented in this study could be a useful tool for insurers and policymakers for predicting potential crop insurance ownership