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Marginal Abatement Costs of Greenhouse Gas Emissions: A Meta-Analysis
Křížková, Alžběta ; Havránek, Tomáš (advisor) ; Ščasný, Milan (referee)
This thesis uses up-to-date meta-analysis methods to produce a systematic summary of the literature on marginal abatement costs (MAC) of greenhouse gas emissions. It collects 242 MAC estimates for 2030 and 2050 from 59 studies. Besides the usual tests for publication bias, the study employs several modern non-linear tests, such as the TOP 10, the Kink method, the Stem method, and others. Subsequently, Bayesian model averaging is performed for the first time in MAC literature to reveal a mild negative publication bias for the MAC in 2050. The thesis reveals that newer studies provide higher estimates of MAC. Other factors influencing MAC estimation are the size of stabilisation targets, emissions baseline, utilising the LEAP model, the inclusion of other greenhouse gases besides carbon dioxide, and considering the long-run decision making. Several robustness checks are conducted along the way to confirm the selection of the dataset and the robustness of the BMA analysis (using weighted BMA, FMA, OLS). The true value of MAC in 2030 corrected for publication bias is around 32 EUR/tCO2-eq, while for 2050, it is 59 EUR/tCO2-eq. 1
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Is Czech Spotify Gender-Biased?
Křížková, Alžběta ; Hroch, Miloš (advisor) ; Lütke Notarp, Ulrike (referee)
Is Czech Spotify gender-biased? Alžběta Křížková Abstract This thesis analyses the gender inequality of music streaming platform Spotify. It focuses on Czech Spotify, ergo, on the Czech music industry between May 2020 and March 2021. The interdisciplinary study covers crucial theoretical concepts from the theory of platforms, popular music, and gender studies. It verifies whether the theory built on Anglo-Saxon tradition can be applied to the local setting. The dataset comprises of songs placed in the "TOP 200" chart and select editorial playlists. The chart illustrates song popularity based on listeners (organic listening), and chosen editorial playlists indicate the platform's promotion of songs (suggested listening). The gender gap analysis is based on a comparison of three gender ratios of songs entering the platform in total, in the playlists, and songs that make it to the chart. The empirical research utilises fundamental statistics and presents various song aspects (genre, record label, band formation, and others) in relation to artists' gender on Spotify, but also in the Czech music industry. The results show a low representation of female artists in the whole industry, while the platform actively promotes female artists via suggested listening. Organic listening endorses gender stereotypes and...
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Sustainable Development Goal 7: Affordable and Clean Energy Panel Data Analysis
Křížková, Alžběta ; Cahlík, Tomáš (advisor) ; Moravcová, Michala (referee)
This thesis analyses the seventh Sustainable Development Goal: Affordable and Clean Energy. Four empirical models are built, each for one indicator. They are then evaluated using panel data analysis for all member states of the UN. The research question it seeks to answer is: "What characteristics have major impact on providing electric energy and other energy related benefits?" We found that in most of the cases, the proportion of urban population and the Human Development Index have a major impact on the indicators. Unlike any previous study dealing with similar topics, this paper analyses the whole goal with its four indicators, not just one particular energy aspect. That allows us to look for interconnection and common features between indicators and their influences.
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