Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data

被引:58
作者
Fezzi, Carlo [1 ,2 ]
Fanghella, Valeria [1 ]
机构
[1] Univ Trento, Dept Econ & Management, Via Vigilio Inama 5, I-38122 Trento, Italy
[2] Univ Exeter, Sch Business, Dept Econ, Land Environm Econ & Policy Inst LEEP, Exeter, Devon, England
关键词
COVID-19; Coronavirus; Economic impacts; Lockdown; GDP; Electricity quantity; Wholesale electricity markets; Pandemic; Fixed-effect regression; High-frequency estimates; Real-time monitoring; DEMAND; ENERGY;
D O I
10.1007/s10640-020-00467-4
中图分类号
F [经济];
学科分类号
02 ;
摘要
In response to the COVID-19 emergency, many countries have introduced a series of social-distancing measures including lockdowns and businesses' shutdowns, in an attempt to curb the spread of the infection. Accordingly, the pandemic has been generating unprecedented disruption on practically every aspect of society. This paper demonstrates that high-frequency electricity market data can be used to estimate the causal, short-run impacts of COVID-19 on the economy, providing information that is essential for shaping future lockdown policy. Unlike official statistics, which are published with a delay of a few months, our approach permits almost real-time monitoring of the economic impact of the containment policies and the financial stimuli introduced to address the crisis. We illustrate our methodology using daily data for the Italian day-ahead power market. We estimate that the 3 weeks of most severe lockdown reduced the corresponding Italian Gross Domestic Product (GDP) by roughly 30%. Such negative impacts are now progressively declining but, at the end of June 2020, GDP is still about 8.5% lower than it would have been without the outbreak.
引用
收藏
页码:885 / 900
页数:16
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