I study the impact of corona populism -- politics aimed at denying or downplaying the danger posed by COVID-19 for strategic reasons -- on the evolution of the pandemic using regional data from Austria. The right-wing FPOE first vocalized strong support for strict lockdown measures, but made a corona populist turn at the end of the first wave of infections. Using  regression analysis, I show that the vote share of the FPOE at the last national parliamentary elections is a strong predictor for the number of COVID-19 deaths  after the FPOE switched their policy stance, while there is no or even a negative correlation before the policy switch. These results are robust under simple as well as sophisticated specifications of the model controlling for demographic and socioeconomic conditions. Interestingly, I do not find a statistically significant correlation between the FPOE vote share and the reported number of infections. I hypothesize that this can be traced back to a self-selection bias in testing. To explore this hypothesis, I extend the classical SIRD model to incorporate conditional quarantine and two groups of agents: the majority and the corona sceptics, where the latter are less inclined to get tested and engage in social distancing. Such a model can explain the nontrivial empirics: if mixing is sufficiently homophilic, an increase in the share of corona sceptics can cause an increase in the number of deaths without increasing the number of reported infections. I finally discuss the implications for both groups .
I study the impact of corona populism -- politics aimed at denying or downplaying the danger posed by COVID-19 for strategic reasons -- on the evolution of the pandemic using regional data from Austria. The right-wing FPOE first vocalized strong support for strict lockdown measures, but made a corona populist turn at the end of the first wave of infections. Using panel regression analysis, I show that the vote share of the FPOE at the last national parliamentary elections is a strong predictor for the number of COVID-19 deaths per capita after the FPOE switched their policy stance, while there is no correlation before the policy switch. Interestingly, I do not find a statistically significant correlation between the FPOE vote share and the reported number of infections. I hypothesize that this can be traced back to a self-selection bias in testing. To explore this hypothesis, I extend the classical SIRD model to incorporate conditional quarantine and two groups of agents: the majority and the corona sceptics, where the latter are less inclined to get tested and engage in social distancing. Such a model can explain the puzzling empirics: if mixing is sufficiently homophilic, an increase in the share of corona sceptics can cause an increase in the number of deaths without increasing the number of reported infections. I finally discuss the partly non-trivial implications of the interplay between group sizes, behavioral differences and the degree of homophily on public health outcomes within the theoretical model .
A
panel
A
per capita
D
or even a negative
D
These results are robust under simple as well as sophisticated specifications of the model controlling for demographic and socioeconomic conditions.
R
nontrivial
puzzling
R
implications for both groups
partly non-trivial implications of the interplay between group sizes, behavioral differences and the degree of homophily on public health outcomes within the theoretical model