Investigating the relationship between economic preferences and attitudes towards vaccination against COVID-19.

University essay from Göteborgs universitet/Institutionen för nationalekonomi med statistik

Abstract: The purpose of this study is to investigate the relationship between economic preferences and attitudes towards vaccination against COVID-19. These relationships are important to explore in order to design correct and effective vaccination policies that can increase vaccination willingness and decrease vaccination hesitancy. This study is specifically looking at risk preferences, ambiguity preferences and other regarding preferences. Vaccination is arguably a decision between two risky options. The risk of vaccination and the risk of non-vaccination. It is also possible to argue that vaccination is a decision between a perceived unknown risk of vaccination and a known risk of non-vaccination. This introduces the concept of ambiguity aversion where ambiguity averse people arguably prefer the known risk of non-vaccination over the unknown risk of vaccination. It is also possible to argue that vaccination is one form of prosocial behaviour and people have various preferences for the wellbeing of others, i.e., other regarding preferences. Data on economic preferences and vaccination attitudes was gathered with an online survey and measured with validated survey questions. The survey was distributed to students at the School of Business, Economics and Law at the University of Gothenburg. The data was analysed with multiple different data analysis methods, most notably ordered probit regression and probit regression. A significant positive relationship is found between risk preferences and willingness to vaccinate against COVID-19. Ambiguity averse people are significantly more likely to vaccinate against COVID-19. Perfect altruists are significantly less likely to vaccinate against COVID-19 compared to free riders. Future research is encouraged to investigate whether these findings hold true for a larger and more representative sample.

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