This thesis studies the effect of generosity of unemployment insurance on economic growth. More generous unemployment insurance is argued to cause an increase in unemployment on the one hand and better job match quality on the other. Our model shows that in the developed countries, there may be some level of unemployment insurance which ensures that the productivity gain offsets the loss due to higher unemployment. On the contrary, in the developing countries, any level of unemployment insurance was revealed to harm economic growth. Moreover, we present strong evidence in favour of a positive effect of unemployment insurance on the aggregate productivity growth. Key words: Unemployment Insurance, Distance to Frontier, Endogenous Growth Model, Technology Growth, Economic Growth

THE ABSTRACT In the new global economy majority of the developed countries use imposition of sanctions in the case of some offences. I have applied the synthetic control methods on this particular case of political pressure to quantify the real costs of anti-Russian sanctions to the economy. Based on the results of this study it was identified, that real GDP growth rate of Russia was continuously reducing by about -1,19% per quarter on average. Reaching the highest value of sanction's effect of -2,8% in real GDP growth rate at the end of 2015. It was also revealed that sanctions had positive effect on current account balance of Russia, that indicator was increasing during the whole studied after sanction's period by about 3,15% per quarter on average. This thesis is presented as a research of interconnection the imposition of 2014 sanctions against Russia and indicators of economic development (GDP, inflation) using synthetic control methods. It was revealed that former economic and social mechanisms aren't capable to provide further development of economy of Russia, its self-sufficiency and safety. JEL Classification F12, F21, F23, H25, H71, H87 Keywords sanctions, synthetic control method, Russia, GDP growth rate, current account balance Author's e-mail 51375259@fsv.cuni.cz Supervisor's e-mail...

Spain is one of the founding countries of the European Monetary Union, that adopted the single currency in 1999. The aim of this thesis is to evaluate the overall impact of the Euro on the Spanish economy. The first part briefly introduces Spain's economy. The second part is about the European Central Bank's monetary policy. This part analyses the suitability of the single monetary policy and then examines its specific implications on the Spanish economy. The third part deals with the fiscal policy and the Stability and Growth Pact. This part analyses the impact of the Euro on the public finances.

This diploma thesis analyzes the evolution of regional disparities in terms of unemployment in Czech Republic in the period from 2005 to 2015. The theoretical part focuses on labor market issues and unemployment. In practical part of diploma thesis, there is examined unemployment according to the share of unemployed persons in the respective regions, then also unemployment according to the share of unemployed men and women, prediction of the future development of the share of unemployed persons for the year 2016, the number of registered job seekers, vacancies and the number of registered persons per vacancy. Subsequently all regions are examined in the mutual comparison of registered job-seekers in categories according to age and registration length. Analysis of the evolution of unemployment is illustrated by tables and graphs expressing time series. For statistical examination is used arithmetic average and especially indices in time series as a chain index, growth rate, the average ratio of growth and the average growth rate. There is the overall analysis of the regions according to selected criteria in the conclusion of the thesis. The results characterize regions, which appears to be the worst from the perspective of unemployment and belong amongst endangered or regions achieving the most favourable values.

Genetic and Hormonal Regulation of Children's Growth MUDr. Jan Vosáhlo Abstract Growth in childhood is a complex process of changing the body, which can be disrupted by various illnesses including endocrine disorders, particularly growth hormone deficiency. Tumors or other processes affecting hypothalamic-pituitary area can be a postnatal cause of GHD; prenatal causes include 1) developmental disorders of the pituitary as part of complex syndromes, 2) developmental disorders of the pituitary due to defects in regulatory genes and 3) defects in genes involved in the synthesis and secretion of GH. The first topic of the thesis was septo-optic dysplasia - a complex syndrome involving optic nerve hypoplasia, structural brain abnormalities and pituitary dysfunctions. We extensively described phenotype in 11 Czech patients; we observed both complete SOD and incomplete forms variously combining two of the three main components of the syndrome. The cohort then became a part of an international study of 68 patients, in which we studied the phenotype in dependence on the brain morphology. We found correlation between the severity of clinical symptoms and the degree of septum pellucidum abnormities and also a correlation between hippocampus and falx abnormities and neurological symptoms. As the second topic we studied...

This thesis concerns fiscal rules which represent a possible solution of excessive deficits of public budgets. The chosen topic is very relevant as most developed countries are now facing the problem of fiscal imbalance. The aim of the thesis is to analyze existing rules in the Czech Republic and to formulate recommendations for its public budgets with regard to the specifics of the economic and political environment. The main hypothesis is that fiscal rules in the Czech Republic are not well designed and do not contribute to the stabilization of public finances. This hypothesis was partially proved true. Proposal to strengthen the fiscal framework by implementation of the reform of medium-term expenditure frameworks and by adopting debt rule at the constitutional level results from the realized findings. Further recommendation is to establish independent fiscal institution that would oversee the fiscal policy in the Czech Republic.

The most discussed topics in economics is the relationship between economic growth and taxes. The aim of this study is to evaluate the influence of different types of taxes on economic growth of Organisation for Economic Co-operation and Development (OECD) member countries after World War II. The thesis is based on extended neoclassi-cal growth theory from 1992 by Mankiw - Romer - Weil. Regression Analysis of Panel Da-ta is used as technique for verification of the correlation of economic growth and taxation. The impact of taxation is integrated to the model through its effect on accumulation of physical capital, development of human capital and technology. The source of panel data used in the analyses is statistical databases of OECD, World Bank, Maddison historical data and Penn World Table. For better comparison of the results more different methods of measuring tax burden were used. It was share of tax income on GDP, share of income from different types of taxes on total tax revenue, labor tax and compound tax quota. Results than differ by measurement of tax incidence. It is too complex to set clear recommendation for growth, nevertheless it is obvious, that the goal of economic and political authorities is to shift the tax burden from direct to indirect taxes.

The objective of my final thesis was to choose, based upon findings and profitability assessments of each type of financing, a suitable financing of growth of the W.A.G, mineral fuels, Inc., the society which operates the project of unmanned filling-stations Tank & Go. In my thesis, I describe types of financing, the ways of gaining financial sources, the changes in legal form of entrepreneurship, the forms of cooperation as well as the state assistance to the entrepreneurs. Consequently, in the practical research, I evaluate the suitability of these types of financing to the project Tank & Go in accordance with the criteria given by the owner of the society as well as with its financial structure.

According to AK and R&D models, permanent rise in investment rates and the growing number or researchers should have permanent effects on growth rate. Charles Jones (1995a) used the lack of long-term movements in GDP and productivity growth to challenge the validity of these models. The aim of this paper is to empirically re-test these models of endogenous growth. The author follows the methods proposed by Ch. Jones (1995a) and extends the analysis for variables that could offset the movements in growth rates. The results show no support for the tested models.

The thesis deals with the analysis of the clustering and mapping techniques derived from the principles of the neural and statistical learning and growth theory. The selected branch of the unsupervised bio-inspired prototype-based models is described in terms of the proposed logical framework, which highlights the continuity of these methods with the classical "pure" statistical methods. Moreover, as those methods are broadly understood as the "black boxes" with the unpredictable, unclear and especially hidden behavior, the examples of the spatial computational and organizational patterns in two-dimensional space are provided. Additionally, this thesis presents the novel concept based on the non-linear, non-Gaussian Gompertzian function, which has been widely used as the universal law in dynamic growth models, but has not yet been applied in the field of computational intelligence. The essence of Gompertzian dynamics is mathematically analyzed and a novel simple version of the Gompertzian normalized function is introduced. Furthermore, the function was modified for use in the field of artificial intelligence and neural implications were discussed. Additionally, the novel neural networks were proposed and derived from the topological principles of Kohonen's self-organizing maps and neural gas algorithm. The Gompertzian networks were evaluated using several indicators for various generated and real datasets. Gompertzian neural networks with fixed grid and integrated neighborhood ranking principle generally show lower mean squared errors than the original SOM algorithms. Likewise, the unconstrained Gompertzian networks have demonstrated overall low error rates comparable to neural gas algorithm, more stable and lower error solutions than the k- means sequential procedure. In conclusion, the Gompertzian function has been shown to be a viable concept and an effective computational tool for multidimensional data analysis.