Since the onset of the Covid-19 pandemic, parameterised epidemiological models (‘SIR’ models, for S usceptible, I nfected, and R ecovered) have been a popular tool to analyse the diseases dynamics (Anderson et al. 2020, Atkeson et al. 2020).
These models can be used to shed light on the impact of physical distancing and other public health measures in containing waves of infections (Aschwanden 2020, Ferguson et al. 2020, Davies et al. 2020).
SIR models rely on several parameters (for instance, to quantify the impact of physical distancing on the reproduction rate of the virus, or R), so their insights are only as good as the accuracy of their parameters.
By contrast, our study (Égert et al. 2020) contributes to a burgeoning literature that seeks to quantify the impact of government interventions on disease progression and mobility, employing reduced-form econometric estimates for the Covid-19 pandemic.
This literature has already shown that stricter lockdown policies go in tandem with a reduction in Covid-19-related deaths (Conyon et al. 2020). It has found strong evidence in favour of banning mass gatherings as one of the most effective ways of taming the spread of the virus (Ahammer et al. 2020).
Similarly, air travel restrictions […]