COVID-19 and Cognitive Biases: What Lessons Can Be Learned to Fight Against Global Warming

Michelle Mongo ()
Additional contact information
Michelle Mongo: Mines Saint-Etienne, Institut Henri Fayol, Coactis (EA 4161), 158, cours Fauriel

A chapter in Energy Transition, Climate Change, and COVID-19, 2021, pp 119-133 from Springer

Abstract: Abstract The world economy is facing an unprecedented health crisis linked to the COVID-19 virus. Despite numerous alerts from WHO during the early stages of the epidemic, public authorities were slow to implement strict health measures and individuals to apply barrier gestures. At the same time, many IPCC reports warn of the consequences of our human activities on the planet (IPCC, https://report.ipcc.ch/sr15/pdf/sr15_spm_final.pdf , 2018), but CO2 emissions continue to increase. For Meyer and Howard Kunreuther (The Ostrich Paradox : Why we underprepare for disaster, 2017), this rather paradoxical behavior is attributable to cognitive biases which push individuals to deny obvious risky situations. However, it should be recognized that the exceptional economic and health measures put in place by governments to limit the spread of the COVID-19 virus (Herrero and Thornton, The Lancet Planetary Health, 4(5), e174, 2020) and stimulate economies as many constituents of increasing examples as they are large-scale action is possible, in particular, to fight against global warming. Containment and its consequences on consumption and production patterns have shown us that more sustainable economic development is possible. Although the latter is not based on profound structural changes in world economies (Le Quéré et al., Nature Climate Change, 10(7), 647–653, 2020), it has the merit of asking us about the conditions necessary for more sustainable development.

Keywords: Covid-19; Climate change; Cognitive biases; Sustainable development; Circular economy (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-79713-3_7

Ordering information: This item can be ordered from
http://www.springer.com/9783030797133

DOI: 10.1007/978-3-030-79713-3_7

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().