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Spillover effect on crime during the COVID-19 lockdowns in the Czech Republic
Vondrášek, Martin ; Mišák, Vojtěch (advisor) ; Schwarz, Jiří (referee)
This thesis seeks to assess the impact of COVID-19 restrictions on crime spill- overs within the context of the Czech Republic. To examine this effect, daily panel data are utilized, revealing that the implementation of COVID-19 mea- sures, such as restriction of free movement, has a significant negative effect on all crime categories, including Violent crimes, Property crimes, Offenses - BESIP, and Other offenses. The Ordinary least squares regression with fixed effects is used as a baseline model. However, due to the presence of spatially lagged dependent variable, a Spatial lag model with fixed effects is adopted to address this issue. Moreover, the analysis includes a z-test, which surprisingly demonstrates a statistically significant increase in the spillover effect in Offenses - BESIP during the COVID-19 period in the Czech Republic.
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Data Analysis of Heatmap of Brno
Kozubek, Jakub ; Hurta, Martin (referee) ; Mrázek, Vojtěch (advisor)
The thesis deals with the analysis of temperature data for the area of the city of Brno. It is focused on the design and verification of hypotheses for warming and cooling parts of the city. The result of the work are methods for statistical testing and for regression analysis implemented in the Python programming language, the results obtained using these methods and their subsequent interpretation in relation to the originally proposed hypotheses.
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The Electoral Success of Far-right in Slovakia: An Empirical Analysis
Osuský, Peter ; Zouhar, Jan (advisor) ; Formánek, Tomáš (referee)
The aim of the thesis is to find factors that were catalysts or inhibitors of the unexpected electoral success of the far-right Slovak party People's Party - Our Slovakia and to create a model that describes its electoral gains elections across districts in the latest 2016 Slovak parliamentary election. For this purpose, methods of linear regression and spatial regression analysis are applied. The thesis concludes that using specific demographic, socioeconomic and in the case of spatial regression as well geographic characteristics of individual electoral districts such as share of population with higher education, share of male population, substantial presence of Roma or Hungarian minority etc., the electoral gains of the party across them can be relatively accurately estimated.
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