Modeling exchange rate volatility became an important topic for research debate starting with 1973, when many countries switched to floating exchange rate system. In this paper, we focus on the EUR/RON exchange rate both as an economic measure and present the implied economic links, and also as a financial investment and analyze its movements and fluctuations through two volatility stochastic processes: the Standard Generalized Autoregressive Conditionally Heteroscedastic Model (GARCH) and the Exponential Generalized Autoregressive Conditionally Heteroscedastic Model (EGARCH). The objective of the conditional variance processes is to capture dependency in the return series of the EUR/RON exchange rate. On this account, analyzing exchange rates could be seen as the input for economic decisions regarding Romanian macroeconomics - the exchange rates being influenced by many factors such as: interest rates, inflation, trading relationships with other countries (imports and exports), or investments - portfolio optimization, risk management, asset pricing. Therefore, we talk about political stability and economic performance of a country that represents a link between the two types of inputs mentioned above and influences both the macroeconomics and the investments. Based on time-varying volatility, we examine implied volatility of daily returns of EUR/RON exchange rate using the standard GARCH model and the asymmetric EGARCH model, whose parameters are estimated through the maximum likelihood method and the error terms follow two distributions (Normal and Student’s t). The empirical results show EGARCH(2,1) with Asymmetric order 2 and Student’s t error terms distribution performs better than all the estimated standard GARCH models (GARCH(1,1), GARCH(1,2), GARCH(2,1) and GARCH(2,2)). This conclusion is supported by the major advantage of the EGARCH model compared to the GARCH model which consists in allowing good and bad news having different impact on the volatility. The EGARCH model is able to model volatility clustering, persistence, as well as the leverage effect.
The main purpose of this paper is to provide an objective analysis of the economic development level of countries. This is done by measuring it through a new index and by classifying the countries in an optimal number of clusters, each group characterizing different levels of economic development. The proposed methodology is based on three steps: creating a composite index (by applying the principal component analysis), establishing the optimal number of development groups (based on the number of principal components and on the hierarchical clustering) and clustering countries into them (with the help of k-means analysis). Therefore, this approach solves the difficulty of classifying the countries, complication that is mentioned in the specialized literature. Also, the paper creates a better understanding on the economic development level of countries, as, usually, the papers examine the economic growth level of countries. The analysis is conducted at the level of 60 countries for year 2015, using 12 indicators from categories that influence economic development (income, inequality, health, education and living conditions). The empirical results revealed that the countries can be grouped in two groups: economical developed countries (approximatively 2/3) and economic developing countries (approximatively 1/3). The countries that are most developed from an economic point of view are: Singapore, Luxemburg and Finland.
The paper analyzes the relationship between value added tax revenue and intermediate consumption in the case of Romania in the period January 2007 – September 2018 (quarterly data), using an unrestricted Vector Autoregression Model based on the rate of dynamic taxation’s level (in terms of value added tax revenue) and the rate of dynamic intermediate consumption. In literature, is questioned only the relationship between tax revenue and gross domestic product. Our study emphasizes the link between tax revenue and parts of the own tax base. The relationship is questioned in both directions, namely with respect to the manner in which value added tax affect intermediate consumption and in terms of the influence of intermediate consumption on value added tax revenue in the case of Romania. Given that a significant part of the corporate taxpayers have left the value added tax regime, intermediate consumption is considered instead of final consumption. The analysis is focused on a specific relationship in order to assess the general impact of indirect taxation on production capacity of the undertakings. Our findings reveal that there is not a direct relationship between intermediate consumption and value added tax revenue at the level of Romania despite a such relationship at the EU-28 level. Moreover, in the case of Romania a high volatility of intermediate consumption was found. Both the breakage between tax revenue and his tax base, and volatility of the tax base suggest an influence of hidden economy. For future concerns about tax policy development, a specific model for estimating and forecasting value added tax revenue should be developed for Romania. On the other hand, based on the findings of this study, a model can be developed to assess the impact of the hidden economy on the value added tax revenue.
The telecommunication industry is growing every day, increasing its competitiveness. In almost all European countries, the market penetration of mobile network users exceeded 100% (for example in Croatia it is over 130%). Acquiring new users is virtually impossible because there are no new users. There are only users of rival companies who are exposed to numerous marketing campaigns carefully designed to try to win them. That’s why customer retention activity and churn prevention is a necessity. The purpose of this paper is to predict customers who are willing to migrate to another Romanian mobile telecommunications company and to determine the strongest factors of influence in the consumer’s decision to leave their current service provider for another provider. Migration behavior analysis is developed for customers with postpaid subscriptions. We applied the ROSE package for re-sampling and decision trees on the dataset to identify decision makers in the migration process. The combination of the two techniques in our study did not significantly improve the performance of the classifier measured by the AUC (Area Under the Curve). After balancing the sample, however, we obtain the optimal value of the AUC coefficient (0.724) for the second cluster, making the correct prediction of the churn phenomenon on the analyzed data set. The study is an addition of Churn Analysis in Romanian Telecommunications Company, M. M. Matei Maer and A. Dumitrache (2018), where ROSE and logistic regression was applied to the same dataset for the same purpose: balancing the sample and churn prediction, but the value of the AUC coefficient was really low, making it difficult to accurately predict the churn phenomenon. Therefore, another purpose of the current paper is to compare the performance of the two techniques used in combination with ROSE on the same set of data.
Tobacco consumption is a problem of both health and economic interest nowadays. According to recent studies conducted by the European Commission approximate 700,000 deaths per year are caused by smoking. For this reason, the European Commission frequently conducts a survey in order to monitor the attitude towards tobacco addiction. Smoking addiction changes due to different factors such as budget, time or entourage. The evolution in time of these factors and the consumers’ preferences is studied using behavioral economics based on a small group of respondents. Through a survey, over 500 persons were asked to choose their preference for cigarettes characteristics. We employ correspondence analysis using combinations of age, type of cigarette, number of cigarettes smoked per day and nicotine concertation to see the type of responses the consumers’ have according to their habit. Moreover, we made a 5 persons selection from the initial group and we observed their behavior for 9 months period of time. The consumers were asked to classify a set of packages according to their preferences and we applied conjoint analysis in order to determine how or if the initial preferences change. Furthermore, we explain the changes in behavior by taking into account the nowadays global impetus towards a healthier lifestyle. The results provided allow to emphasize the role of a strong analysis for each single target consumer’s behavior as this is one of the main roles of Behavioral Economics.