Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data.
Identifieur interne : 001A96 ( Main/Curation ); précédent : 001A95; suivant : 001A97Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data.
Auteurs : Carlo Fezzi [Italie, Royaume-Uni] ; Valeria Fanghella [Italie]Source :
- Environmental & resource economics [ 0924-6460 ] ; 2020.
Abstract
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.
DOI: 10.1007/s10640-020-00467-4
PubMed: 32836850
PubMed Central: PMC7399598
Links toward previous steps (curation, corpus...)
- to stream Main, to step Corpus: Pour aller vers cette notice dans l'étape Curation :001A96
Links to Exploration step
pubmed:32836850Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data.</title><author><name sortKey="Fezzi, Carlo" sort="Fezzi, Carlo" uniqKey="Fezzi C" first="Carlo" last="Fezzi">Carlo Fezzi</name><affiliation wicri:level="1"><nlm:affiliation>Department of Economics and Management, University of Trento, Via Vigilio Inama 5, 38122 Trento, Italy.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Economics and Management, University of Trento, Via Vigilio Inama 5, 38122 Trento</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:affiliation>Land, Environment, Economics and Policy Institute (LEEP), Department of Economics, University of Exeter Business School, Exeter, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Land, Environment, Economics and Policy Institute (LEEP), Department of Economics, University of Exeter Business School, Exeter</wicri:regionArea></affiliation></author><author><name sortKey="Fanghella, Valeria" sort="Fanghella, Valeria" uniqKey="Fanghella V" first="Valeria" last="Fanghella">Valeria Fanghella</name><affiliation wicri:level="1"><nlm:affiliation>Department of Economics and Management, University of Trento, Via Vigilio Inama 5, 38122 Trento, Italy.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Economics and Management, University of Trento, Via Vigilio Inama 5, 38122 Trento</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:32836850</idno><idno type="pmid">32836850</idno><idno type="doi">10.1007/s10640-020-00467-4</idno><idno type="pmc">PMC7399598</idno><idno type="wicri:Area/Main/Corpus">001A96</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">001A96</idno><idno type="wicri:Area/Main/Curation">001A96</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">001A96</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data.</title><author><name sortKey="Fezzi, Carlo" sort="Fezzi, Carlo" uniqKey="Fezzi C" first="Carlo" last="Fezzi">Carlo Fezzi</name><affiliation wicri:level="1"><nlm:affiliation>Department of Economics and Management, University of Trento, Via Vigilio Inama 5, 38122 Trento, Italy.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Economics and Management, University of Trento, Via Vigilio Inama 5, 38122 Trento</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:affiliation>Land, Environment, Economics and Policy Institute (LEEP), Department of Economics, University of Exeter Business School, Exeter, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Land, Environment, Economics and Policy Institute (LEEP), Department of Economics, University of Exeter Business School, Exeter</wicri:regionArea></affiliation></author><author><name sortKey="Fanghella, Valeria" sort="Fanghella, Valeria" uniqKey="Fanghella V" first="Valeria" last="Fanghella">Valeria Fanghella</name><affiliation wicri:level="1"><nlm:affiliation>Department of Economics and Management, University of Trento, Via Vigilio Inama 5, 38122 Trento, Italy.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Economics and Management, University of Trento, Via Vigilio Inama 5, 38122 Trento</wicri:regionArea></affiliation></author></analytic><series><title level="j">Environmental & resource economics</title><idno type="ISSN">0924-6460</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32836850</PMID><DateRevised><Year>2020</Year><Month>09</Month><Day>28</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Print">0924-6460</ISSN><JournalIssue CitedMedium="Print"><PubDate><Year>2020</Year><Month>Aug</Month><Day>04</Day></PubDate></JournalIssue><Title>Environmental & resource economics</Title><ISOAbbreviation>Environ Resour Econ (Dordr)</ISOAbbreviation></Journal><ArticleTitle>Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data.</ArticleTitle><Pagination><MedlinePgn>1-16</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1007/s10640-020-00467-4</ELocationID><Abstract><AbstractText>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.</AbstractText><CopyrightInformation>© The Author(s) 2020.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Fezzi</LastName><ForeName>Carlo</ForeName><Initials>C</Initials><Identifier Source="ORCID">0000-0002-4860-9128</Identifier><AffiliationInfo><Affiliation>Department of Economics and Management, University of Trento, Via Vigilio Inama 5, 38122 Trento, Italy.</Affiliation><Identifier Source="GRID">grid.11696.39</Identifier><Identifier Source="ISNI">0000 0004 1937 0351</Identifier></AffiliationInfo><AffiliationInfo><Affiliation>Land, Environment, Economics and Policy Institute (LEEP), Department of Economics, University of Exeter Business School, Exeter, UK.</Affiliation><Identifier Source="GRID">grid.8391.3</Identifier><Identifier Source="ISNI">0000 0004 1936 8024</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Fanghella</LastName><ForeName>Valeria</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>Department of Economics and Management, University of Trento, Via Vigilio Inama 5, 38122 Trento, Italy.</Affiliation><Identifier Source="GRID">grid.11696.39</Identifier><Identifier Source="ISNI">0000 0004 1937 0351</Identifier></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>08</Month><Day>04</Day></ArticleDate></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Environ Resour Econ (Dordr)</MedlineTA><NlmUniqueID>101620056</NlmUniqueID><ISSNLinking>0924-6460</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">COVID-19</Keyword><Keyword MajorTopicYN="N">Coronavirus</Keyword><Keyword MajorTopicYN="N">Economic impacts</Keyword><Keyword MajorTopicYN="N">Electricity quantity</Keyword><Keyword MajorTopicYN="N">Fixed-effect regression</Keyword><Keyword MajorTopicYN="N">GDP</Keyword><Keyword MajorTopicYN="N">High-frequency estimates</Keyword><Keyword MajorTopicYN="N">Lockdown</Keyword><Keyword MajorTopicYN="N">Pandemic</Keyword><Keyword MajorTopicYN="N">Real-time monitoring</Keyword><Keyword MajorTopicYN="N">Wholesale electricity markets</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>07</Month><Day>09</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>8</Month><Day>25</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>8</Month><Day>25</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>8</Month><Day>25</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32836850</ArticleId><ArticleId IdType="doi">10.1007/s10640-020-00467-4</ArticleId><ArticleId IdType="pii">467</ArticleId><ArticleId IdType="pmc">PMC7399598</ArticleId></ArticleIdList><pmc-dir>pmcsd</pmc-dir>
<ReferenceList><Reference><Citation>Am Econ Rev. 2012 Apr;102(2):994-1028</Citation><ArticleIdList><ArticleId IdType="pubmed">25067841</ArticleId></ArticleIdList></Reference><Reference><Citation>N Engl J Med. 2020 Feb 20;382(8):727-733</Citation><ArticleIdList><ArticleId IdType="pubmed">31978945</ArticleId></ArticleIdList></Reference><Reference><Citation>Lancet. 2020 Mar 21;395(10228):931-934</Citation><ArticleIdList><ArticleId IdType="pubmed">32164834</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Sante/explor/LockdownV1/Data/Main/Curation
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 001A96 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Curation/biblio.hfd -nk 001A96 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Sante
|area= LockdownV1
|flux= Main
|étape= Curation
|type= RBID
|clé= pubmed:32836850
|texte= Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Curation/RBID.i -Sk "pubmed:32836850" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Main/Curation/biblio.hfd \
| NlmPubMed2Wicri -a LockdownV1
| This area was generated with Dilib version V0.6.38. |  |