National Repository of Grey Literature 2 records found  Search took 0.02 seconds. 
Faktory ovplyvňujúce ekonomickú úroveň krajiny
Bobošová, Terézia
This thesis deals with the identification of factors influencing the level of economic performance of the countries. A theoretical platform presents the total population, the technological level and the economic freedom as possible factors of influence. Groups of countries, which have the similar character of the level of economic performance, are sorted out by cluster analysis. To describe the common factors influencing the level of economic performance among every created group of countries the panel data models are used. The results prove the influence of total population, technological level and economic freedom in the most developed, moderately developed and in developing countries around the world. Each of these indicators shows the positive effect on the level of economic performance, thereby creating an opportunity for the improvements.
Faktory ovlivňující příjmovou nerovnost
Koukalová, Pavla
This diploma thesis deals with the identification of factors that affect income inequality in the world. The literary overview describes the issue of income inequality, possible methods of measurement, projected factors of influence and the possibility of addressing income inequality. Statistical methods, in particular cluster, regression and panel analysis, are used to quantify and define the significance of the selected factors. The economic and technological level of the country, the education and the state of health of the population are key economic and demographic indicators. Each of these indicators, according to the results of the regression analysis, has a weak negative effect on income inequality, reducing it. The results of the panel analysis demonstrate that an indicator of the level of technology, education and the state of health of the population can be included among the major factors affecting income inequality in the world. The indicator of the economic level measured using per capita gross domestic product has proved insignificant, which means that while GDP has an impact on Gini’s coefficient, the other variables describe the relationship better.

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