Alternative approach to measuring development progress of countries.
Alternativní způsob měření rozvoje zemí.
diplomová práce (OBHÁJENO)
Zobrazit/ otevřít
Trvalý odkaz
http://hdl.handle.net/20.500.11956/94877Identifikátory
SIS: 193942
Kolekce
- Kvalifikační práce [17123]
Autor
Vedoucí práce
Oponent práce
Šťastná, Lenka
Fakulta / součást
Fakulta sociálních věd
Obor
Ekonomie a finance
Katedra / ústav / klinika
Institut ekonomických studií
Datum obhajoby
31. 1. 2018
Nakladatel
Univerzita Karlova, Fakulta sociálních vědJazyk
Angličtina
Známka
Dobře
Klíčová slova (česky)
Gross Domestic Product, Social Progress Index, K-means clustering, Bayesian Model AveragingKlíčová slova (anglicky)
Gross Domestic Product, Social Progress Index, K-means clustering, Bayesian Model AveragingThis thesis studies the relationship between GDP and Social Progress Index, components of social progress model and their dimensions. Using the dataset of 49 countries and Bayesian Model Averaging (BMA) and clustering analysis we found that there is not straight relationship between GDP and SPI. By testing 15 different models for each of 3 dimension (Basic Human Needs, Foundations of Wellbeing and Opportunity) of SPI we have found that the best variation of components would be to include all of them for each dimension. By using BMA approach we have found that the best model of SPI out of 12 components includes only intercept, tolerance and inclusion variables. The rest of components show quite low probability of inclusion, however, none of them showed 0 posterior probability. JEL Classification A13, C11, E01, I30, Keywords Kuznets, progress, SPI, GDP, BMA Author's e-mail valeria.e.efimenko@gmail.com Supervisor's e-mail daniel.vach@gmail.com
This thesis studies the relationship between GDP and Social Progress Index, components of social progress model and their dimensions. Using the dataset of 49 countries and Bayesian Model Averaging (BMA) and clustering analysis we found that there is not straight relationship between GDP and SPI. By testing 15 different models for each of 3 dimension (Basic Human Needs, Foundations of Wellbeing and Opportunity) of SPI we have found that the best variation of components would be to include all of them for each dimension. By using BMA approach we have found that the best model of SPI out of 12 components includes only intercept, tolerance and inclusion variables. The rest of components show quite low probability of inclusion, however, none of them showed 0 posterior probability. JEL Classification A13, C11, E01, I30, Keywords Kuznets, progress, SPI, GDP, BMA Author's e-mail valeria.e.efimenko@gmail.com Supervisor's e-mail daniel.vach@gmail.com