This article presents results of research conducted among financial intermediaries who work in insurance companies in the Podkarpackie region. The main issue is to compare actual data on the influence of the financial crisis on insurance sales and financial intermediary opinions. On the basis of the data, the authors observe that a recession in the insurance market is perceptible. Sales of insurance as well as other products and services is currently more difficult. However, some financial intermediaries also say that the crisis had a positive impact on some insurance sales.
This article’s aim is to examine a dependency between local government administration at a municipal level and the level of local entrepreneurship. This paper attempts to answer the question of whether the size of the local government administration has features of stimulant or de-stimulant in the process of setting up a business. In other words, does the size of public administration at a local level (municipal level) have a positive or negative impact on creating new business entities? This is important due to at least a couple of reasons. First of all, the current research achievements are not extensive, when it comes to the publications that link entrepreneurship and the size of local government administration. Secondly, the problem of entrepreneurship determinants constitutes still topical and not fully investigated (or explained) aspects of local economy development. Thirdly and finally, the authors of this article have proposed and copyrighted an approach to the quantification of the size of local government administration, modifying commonly used measures of local public administration. Thus, this article fits not only into the explanation of the entrepreneurship phenomenon and its determinants, but also contributes to the development of knowledge about dependencies between the size of local self-government and the entrepreneurship level. It expands the knowledge resource on analyzed dependencies and re-orients current approaches to similar research.
This article is dedicated to a study of the relations between the economy and the size of the general government sector. The main aim of the article is an identification of the most important variables that are used to determine relations between the economy and size of the sector, as well as to identify frequency of their occurrences in relations to pairs of variables which describe an economy and the size of the sector. In order to explore these relations, the authors used Bayes networks. The economies of EU member states and their public finance systems were the object of analyses in this article. The period that was selected for the research covered the years 2000-2013 (inclusive). In order to describe economies, the authors selected 18 variables, whereas to describe the general government sector - 15 variables. These variables were sourced from databases of Eurostat, OECD and the World Bank. Among an economy’s measures and general government sector measures, there were also some benchmarks found (standard and classic) as well as measures proposed by the authors, which had not been used in the scientific descriptions that were dedicated to research on size of the general government sector. Ipso facto, this article fits in the discussion on not only the size of the general government sector, but also attempts to answer the question of whether the economy determines the size of the sector. To date, the research questions on the impact of the size of the general government sector on the economy of a particular country have been common. This article inverts the investigated dependence and its content concentrates on the attempt to determine if the size of the sector in a particular country is a function of its economy expressed by ratios adopted in conducted the research.
The main objective of this article is proving how the regional diversification in the size of general government sector influences the economies of EU countries. To achieve this, presenting both the size of the general government sector and of the economy, using variables which enable comparison in time and space, is essential. Bearing this in mind, the general government sector has been depicted by nine variables and the economy has been described by thirteen explanatory variables. The complexity of the phenomenon imposes the implementation of an unconventional approach in this field of exploration. Our approach is based on Intelligent Data Analysis (IDA) - a methodology that includes a set of techniques that can be applied for extracting useful knowledge from large amounts of data. In order to indicate the impact of regional diversification in the size of the general government sector on the EU countries’ economies, probabilistic techniques were applied – Bayesian Networks. Analysis made in the study showed that the largest impact of the GGS size on the economy was identified in Portugal and Slovakia. The results of the studies show that the most "responsive" to the size of the GGS variable describing the economy was gross domestic product per inhabitant. The research proved that the economies of some countries showed similarities in the effect of the size of the general government sector on the parameters of the economy. We have identified five groups of such countries.
PL
Głównym celem artykułu jest ukazanie wpływu regionalnego zróżnicowania rozmiaru sektora finansów publicznych na gospodarki państw Unii Europejskiej. Do osiągnięcia tego celu konieczne jest zobrazowanie rozmiaru zarówno sektora finansów publicznych, jak i gospodarki – za pośrednictwem zmiennych umożliwiających ich porównanie w czasie i w przestrzeni. Mając to na uwadze, sektor finansów publicznych zobrazowano za pośrednictwem dziewięciu zmiennych, a gospodarka została opisana za pomocą trzynastu zmiennych wyjaśniających. Złożoność tego zjawiska wymaga realizacji niekonwencjonalnego podejścia w tej dziedzinie badań. Podejście autorów opiera się na inteligentnej analizie danych (IDA) – metodologii obejmującej zestaw technik, które można zastosować do wydobywania użytecznej wiedzy z dużej ilości danych. W celu wskazania opisanych związków w artykule zastosowało techniki probabilistyczne – sieci Bayesa.
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