Economic modeling in support of public choice in the COVID-19 pandemic emergency
Bastidon Gilles, Cécile
Economic modeling in support of public choice in the COVID-19 pandemic emergency - 2022.
3
The Covid-19 pandemic prompted the development of multiple disciplinary approaches. However, the formalization of epidemiological and economic transmission mechanisms reveals biases that may affect the optimal choices of public policies. First, the macroeconomic approach does not systematically take into account the different channels through which the shock is amplified, such as the amplification of demand shocks and the persistence of asset price shocks. Secondly, the macroeconomic and epidemiological statistical data developed during a pandemic raise difficulties. For example, the parameters of the viral propagation model are not known in the early stages, in particular the case-fatality rate. Finally, the epidemiological models themselves may be biased, especially in the case of viruses whose spread is not characterised by a standard Markov process, and in the case where the different levels of heterogeneity of contact networks (human, transport, etc.) are not taken into account. These biases are reinforced, for most advanced economies, by the inexperience of public authorities in the context of major pandemics.
Economic modeling in support of public choice in the COVID-19 pandemic emergency - 2022.
3
The Covid-19 pandemic prompted the development of multiple disciplinary approaches. However, the formalization of epidemiological and economic transmission mechanisms reveals biases that may affect the optimal choices of public policies. First, the macroeconomic approach does not systematically take into account the different channels through which the shock is amplified, such as the amplification of demand shocks and the persistence of asset price shocks. Secondly, the macroeconomic and epidemiological statistical data developed during a pandemic raise difficulties. For example, the parameters of the viral propagation model are not known in the early stages, in particular the case-fatality rate. Finally, the epidemiological models themselves may be biased, especially in the case of viruses whose spread is not characterised by a standard Markov process, and in the case where the different levels of heterogeneity of contact networks (human, transport, etc.) are not taken into account. These biases are reinforced, for most advanced economies, by the inexperience of public authorities in the context of major pandemics.
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