We present an econometric model which can be employed to monitor the evolution of the COVID-19 contagion curve. The model is a Poisson autoregression of the daily new observed cases, and can dynamically show the evolution of contagion in different time periods and locations, allowing for the comparative evaluation of policy approaches. We present timely results for nine European countries currently hit by the virus. From the findings, we draw four main conclusions. First, countries experiencing an explosive process (currently France, Italy and Spain), combined with high persistence of contagion shocks (observed in most countries under investigation), require swift policy measures such as quarantine, diffuse testing and even complete lockdown. Second, in countries with high persistence but lower contagion growth (currently Germany) careful monitoring should be coupled with at least “mild” restrictions such as physical distancing or isolation of specific areas. Third, in some countries, such as Norway and Denmark, where trends seem to be relatively under control and depend on daily contingencies, with low persistence, the approach to restrictive measures should be more cautious since there is a risk that social costs outweigh the benefits. Fourth, countries with a limited set of preventive actions in place (such as the Netherlands, Switzerland, and the United Kingdom) may revise their positions if high values of contagion remain.
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Keywords: Contagion models, Covid-19, European countries, Poisson Autoregressive models, Reproduction number.
JEL classification: C21, C58, E44, G21.