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A Panel Data Analysis of Sub-Saharan Africa's Economic Growth
Hostačný, Jakub ; Cahlík, Tomáš (advisor) ; Bobková, Božena (referee)
This thesis examines the relationship between real GDP per capita growth rate of Sub-Saharan Africa countries and various variables suggested by theoretical literature related to Solow model or endogenous growth theories. The set of most commonly used variables is further extended by additional variables which have not been given an ample attention in the context of analysis of SSA countries' economic growth so far. The econometric analysis uses unbalanced panel data set comprising annual observations on 45 SSA countries between 1980 and 2011 applying a simple pooled OLS and FE estimation. We also touch IV estimation to address endogeneity problem. Moreover, we test the sensitivity of parameter estimates. Along with the analysis of total set of SSA countries, we subgroup countries into 4 groups - oil exporters, middle-income countries, non-fragile low-income countries and fragile countries. We present results for each group. The results support the findings of earlier empirical studies related to most commonly variables associated with economic growth, except the negative effect of population growth rate and conditional convergence hypothesis. The analysis of additional factors reveals the strong relevance of latitude, colonial heritage and landlockedness, while no systematic effect of neither...
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Non-Linear Classification as a Tool for Predicting Tennis Matches
Hostačný, Jakub ; Baniar, Matúš (advisor) ; Krištoufek, Ladislav (referee)
Charles University Faculty of Social Sciences Institute of Economic Studies MASTER'S THESIS Non-Linear Classification as a Tool for Predicting Tennis Matches Author: Be. Jakub Hostacny Supervisor: RNDr. Matus Baniar Academic Year: 2017/2018 Abstract In this thesis, we examine the prediction accuracy and the betting performance of four machine learning algorithms applied to men tennis matches - penalized logistic regression, random forest, boosted trees, and artificial neural networks. To do so, we employ 40 310 ATP matches played during 1/2001-10/2016 and 342 input features. As for the prediction accuracy, our models outperform current state-of-art models for both non-grand-slam (69%) and grand slam matches (79%). Concerning the overall accuracy rate, all model specifications beat backing a better-ranked player, while the majority also surpasses backing a bookmaker's favourite. As far as the betting performance is concerned, we develop six profitable betting strategies for betting on favourites applied to non-grand-slam with ROI ranging from 0.8% to 6.5%. Also, we identify ten profitable betting strategies for betting on favourites applied to grand slam matches with ROI fluctuating between 0.7% and 9.3%. We beat both bench mark rules - backing a better-ranked player as well as backing a bookmaker's...
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Non-Linear Classification as a Tool for Predicting Tennis Matches
Hostačný, Jakub ; Baniar, Matúš (advisor) ; Krištoufek, Ladislav (referee)
Charles University Faculty of Social Sciences Institute of Economic Studies MASTER'S THESIS Non-Linear Classification as a Tool for Predicting Tennis Matches Author: Be. Jakub Hostacny Supervisor: RNDr. Matus Baniar Academic Year: 2017/2018 Abstract In this thesis, we examine the prediction accuracy and the betting performance of four machine learning algorithms applied to men tennis matches - penalized logistic regression, random forest, boosted trees, and artificial neural networks. To do so, we employ 40 310 ATP matches played during 1/2001-10/2016 and 342 input features. As for the prediction accuracy, our models outperform current state-of-art models for both non-grand-slam (69%) and grand slam matches (79%). Concerning the overall accuracy rate, all model specifications beat backing a better-ranked player, while the majority also surpasses backing a bookmaker's favourite. As far as the betting performance is concerned, we develop six profitable betting strategies for betting on favourites applied to non-grand-slam with ROI ranging from 0.8% to 6.5%. Also, we identify ten profitable betting strategies for betting on favourites applied to grand slam matches with ROI fluctuating between 0.7% and 9.3%. We beat both bench mark rules - backing a better-ranked player as well as backing a bookmaker's...
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A Panel Data Analysis of Sub-Saharan Africa's Economic Growth
Hostačný, Jakub ; Cahlík, Tomáš (advisor) ; Bobková, Božena (referee)
This thesis examines the relationship between real GDP per capita growth rate of Sub-Saharan Africa countries and various variables suggested by theoretical literature related to Solow model or endogenous growth theories. The set of most commonly used variables is further extended by additional variables which have not been given an ample attention in the context of analysis of SSA countries' economic growth so far. The econometric analysis uses unbalanced panel data set comprising annual observations on 45 SSA countries between 1980 and 2011 applying a simple pooled OLS and FE estimation. We also touch IV estimation to address endogeneity problem. Moreover, we test the sensitivity of parameter estimates. Along with the analysis of total set of SSA countries, we subgroup countries into 4 groups - oil exporters, middle-income countries, non-fragile low-income countries and fragile countries. We present results for each group. The results support the findings of earlier empirical studies related to most commonly variables associated with economic growth, except the negative effect of population growth rate and conditional convergence hypothesis. The analysis of additional factors reveals the strong relevance of latitude, colonial heritage and landlockedness, while no systematic effect of neither...
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