This paper basically completes a project to enumerate permutations avoiding a triple T of 4-letter patterns, in the sense of classical pattern avoidance, for every T. There are 317 symmetry classes of such triples T and previous papers have enumerated avoiders for all but 14 of them. One of these 14 is conjectured not to have an algebraic generating function. Here, we find the generating function for each of the remaining 13, and it is algebraic in each case.
De Finetti theorem establishes the conceptual basis of Bayesian inference replacing the independent and identically distributed sampling hypothesis prevalent in frequentist statistics with the much easier to justify in practical settings hypothesis of exchangeability. In this paper we make use of the extension of the concept of exchangeability from sequences to arrays arguing that the invariance to ordering is a much more tenable assumption than independent and identically distributed sampling in the financial modeling problems. Making use of the celebrated Aldous-Hoover representation theorem of exchangeable matrix we construct a Bayesian non-parametric model of the financial returns correlation matrices arguing that a Bayesian approach can mitigate many of the known shortcomings of the usual Pearson correlation coefficient. We posit the correlation matrix to be an exchangeable matrix and construct a Bayesian neural network to estimate the functions from the Aldous-Hoover representation theorem. The correlation matrix model is coupled with a Student-t likelihood (accounting for the heavy tails of financial returns). The model is estimated with a Hamiltonian Monte Carlo sampler. The samples are used to construct an ensemble of networks where each edge is weighted by the size of the correlation between two financial instruments. Various centrality measures are being calculated (betweenness, eigenvector) for each network of the ensemble allowing us to obtain a probabilistic view of each financial instrument’s importance. We also construct a minimum spanning tree associated with the mean correlation matrix allowing us to visualize the most important financial instruments from the universe selected.
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.
The paper aims to identify the main characteristics of the financial cycle for Romania using both the classical and growth cycle approaches. The turning point methodology represents the classical approach, while a band-pass filter is applied to capture the growth cycle. First, the paper assesses the significance of the medium-term cyclical component and finds that its importance increased since 2000s. The second purpose is to identify the relevant variables for the construction of a composite measure of the financial cycle. The results reveal that total credit and real estate prices are the best candidates. Regarding cycles’ characteristics, the classical approach shows that credit cycles tend last around 10 years, while the real estate cycles are longer and exhibit higher corrections during downturns.
We consider a generalization of the problem of counting ternary words of a given length which was recently investigated by Koshy and Grimaldi . In particular, we use finite automata and ordinary generating functions in deriving a k-ary generalization. This approach allows us to obtain a general setting in which to study this problem over a k-ary language. The corresponding class of n-letter k-ary words is seen to be equinumerous with the closed walks of length n − 1 on the complete graph for k vertices as well as a restricted subset of colored square-and-domino tilings of the same length. A further polynomial extension of the k-ary case is introduced and its basic properties deduced. As a consequence, one obtains some apparently new binomial-type identities via a combinatorial argument.
The paper attempts to present a comprehensive picture of the main characteristics of Romanian university-educated youths in their journey to employment. The persisting demographic decline and significant labor shortages point out to the importance of having an effective transition from school to work (as reflected in several Europe 2020 policy targets) so that youth and young adult cohorts are able to contribute to the Romanian economy to the full extent of their abilities. Analysis of the latest data available reveals that Romanian university graduates’ path to employment often involves a complete switch from study to work. Despite a lack of previous work experience, they enjoy high employment rates, relatively long job tenure that starts on, or shortly after, graduation, and have jobs that match their education. They also tend to be proactive in their job search and over 90% are not willing to change residence in order to start employment. Inactivity patterns that consider both work and education, and early leavers from education show significant fluctuations during the economic cycle. Results indicate the strong and weak areas with respect to labor market integration of youths and young adults, and can provide a starting point for policies to optimize their successful integration. It also points out to potential research areas to address key aspects of transitions from school to work that may clarify unsolved issues and guide effective policy interventions.
This paper investigates the influence of education and human capital on economic growth in European Union countries before Brexit, for a time span of 14 years in the period 2003 - 2016. A panel data regression model was applied taking into account the impact of human capital on the economic growth from the perspective of education levels and human capital movement. Therefore human capital is described by the variables number of researchers, youth not in education, employment or training, the migration changing rates and the labor force for three different education levels (basic, intermediate and advanced). The dependent variable used in the paper as a measurement of economic growth was considered annual growth rate of Gross Domestic Product. The results show that the hypothesis of the importance and impact of human capital on economic growth is supported.
The world economy has been developing at a very fast pace for the past few decades, growth which is commonly linked to the development of technology. Innovative ideas become successful when certain individuals decide to face the multiple risks that appear when transforming these ideas in to reality. The vast literature on entrepreneurship has shown that startups are important players in driving the economy on an ascending path. It is no surprise that highly developed countries, such as USA, Israel or Singapore have governmental programs which stimulate startup creation. More recently, the Romanian government has also joined in on spending money to offer entrepreneurs the chance to create successful businesses. Using spatial panel data on the 41 counties of Romania and the capital, Bucharest, on the period 2011-2016, this study highlights some significant dependencies between the survival of startups (for a period of 3 years) and other factors – both internal and external. The analysis shows that the aforementioned survival is clearly and positively impacted by Foreign Direct Investment, the share of fresh businesses in the total business environment and the number of immigrants with a permanent residence in the respective counties. Moreover, there are significant spatial effects occurring between neighboring counties. These results suggest that foreign investors could benefit from bringing their capital in Romania, as startups greatly contribute to the specialization of markets, and moreover, spillover effects present suggest that a smaller number of investment centers can be highly effective in their regions.
Migration plays an important role in almost all objectives of sustainable development. In the ‘80s and ‘90s, many authors debated the non-deterministic character of the impact of migration on the development of primarily the countries of origin. Migration as a complex process in globalization has amplified relations between states but there have been very rare reductions in development gaps between them that in turn discourage labour migration. In spite of the increase in well-being based on theory, practice has always revealed an asymmetric development that causes an increase in the differences between emigration and immigration countries.
The global strategy for poverty eradication adopted by world leaders in 2000 did not include migration-related targets, probably because the link between migration and development had not yet been properly perceived. Since then, studies, policy analyzes, international forums and migration recommendations have focused on policy-making in practice, including efforts to support migration concerns in the post-2015 development agenda. Various ideas and recommendations were presented during that data on the most appropriate way to use the migration-development link to maximize its positive effects. In 2015 was adopted the 17 Sustainable Development Goals (SDGs) of the 2030 Agenda for Sustainable Development. Starting with these documents, the contribution of migration to sustainable development was officially recognized for the first time.
From the beginning remittances have played an important role in setting migration as the most important development factor. We sustained that this view, on which allmost all national policies are based, distorts the notion of development and hide the main causes of current labor migration. In this context, this study also attempts to analyze the two-way relation between the factors that determine human development (income, education and health) and international migration.
Managing migration is one of the most important issues of global cooperation.
This paper presents the perceptions of social science students about the use of official statistical data, in the context of active learning of Statistics, and other topics related to Applied Statistics. In order to make these courses more attractive, and to challenge and stimulate statistical education, our students work on projects in which they use official statistical data to explore practical, real-life issues. Their attitudes and perceptions regarding official statistical data sources are very important, both for acquisition of statistical analysis skills, essential for their future professional life, and for improvement of the official data sources. Therefore, we conducted a custom-made survey among students from Romanian higher education institutions (HEIs) and gathered a database with 334 responses, which allowed us to identify the main characteristics, problems and solutions concerning the use of statistical official data sources by university students.