Home > Search Results: Migová, Patrícia
Search:
Search Tips :: Advanced Search
Search collections:
Sort by: Display results: Output format:
National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Leasing Financing and Debt Financing - Determinants and the Linkages with the Economy
 Migová, Patrícia ; Pečená, Magda (advisor) ; Jakubík, Petr (referee)
This study examines the macroeconomic and legal determinants of leasing fi- nancing. The dataset used in this thesis is an unbalanced panel. It includes 30 countries and covers the period between 2012 and 2020. The leasing to GDP ratio represents the dependent variable. The key determinants are examined by the dynamic System Generalized method of moments. The results indicate that statistically significant macroeconomic variables are in line with the economic theory. The borrowing interest rate and value-added tax show the most robust results. Moreover, the value-added tax is the most important tax variable that negatively impacts leasing, and it was the only statistically significant regulatory variable. Furthermore, the analysis for the leasing to credit ratio is provided. The results support the existing literature that the corporate tax rate is an important determinant for leasing to credit ratio from the macroeconomic point of view and not only from the firms' perspective. Keywords Leasing financing, Debt financing, panel data models, System GMM estimator
Detailed record
Wage Discrimination in Top European Soccer Leagues
 Migová, Patrícia ; Janhuba, Radek (advisor) ; Matoušek, Jindřich (referee)
This thesis deals with the analysis of wage discrimination in top European soccer leagues. Number of papers written about this problem in the past examined either each European league separately or did not examine particular leagues at all. Our thesis investigates discrimination between White, Black, Hispanic and Mediterranean players. We created two unique datasets, including one with game statistics from season 2018/2019 and one with average game statistics from seasons 2016/2017, 2017/2018 and 2018/2019. In addition to analysis of discrimination, we were able to investigate with two different datasets, whether player's wages are determined by statistics from the last season or by average statistics from the last three seasons. The data are examined by applying the Ordinary Least Squares method. The results of our regressions show that there does seem to exist some discrepancy in wage gap between some racial groups represented in our datasets. Our results also show that wages are better determined by the average statistics from the last three seasons.
Detailed record

Interested in being notified about new results for this query?
Subscribe to the RSS feed.
Digital Repository :: Search :: Submit :: Personalize :: Help
Powered by Invenio v1.1.2
Maintained by admin.invenio@techlib.cz
This site is also available in the following languages:
Česky  English