Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/307261 
Autor:innen: 
Erscheinungsjahr: 
2022
Quellenangabe: 
[Journal:] Journal of Spatial Econometrics [ISSN:] 2662-298X [Volume:] 3 [Article No.:] 9 [Publisher:] Springer International Publishing [Place:] Cham [Year:] 2022
Verlag: 
Springer International Publishing, Cham
Zusammenfassung: 
The Covid-19 pandemic requires a continuous evaluation of whether current policies and measures taken are sufficient to protect vulnerable populations. One quantitative indicator of policy effectiveness and pandemic severity is the case fatality ratio, which relies on the lagged number of infections relative to current deaths. The appropriate length of the time lag to be used, however, is heavily debated. In this article, I contribute to this debate by determining the temporal lag between the number of infections and deaths using daily panel data from Germany's 16 federal states. To account for the dynamic spatial spread of the virus, I rely on different spatial econometric models that allow not only to consider the infections in a given state but also spillover effects through infections in neighboring federal states. My results suggest that a wave of infections within a given state is followed by increasing death rates 12 days later. Yet, if the number of infections in other states rises, the number of death cases within that given state subsequently decreases. The results of this article contribute to the better understanding of the dynamic spatio-temporal spread of the virus in Germany, which is indispensable for the design of effective policy responses.
Schlagwörter: 
Covid-19
Spatio-temporal models
Time lag effects
Spatial spillovers
Spatial Durbin model
Germany
JEL: 
C21
C23
I10
I18
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Dokumentart: 
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Dokumentversion: 
Published Version

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