Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/315609 
Year of Publication: 
2024
Citation: 
[Journal:] Journal of Risk and Uncertainty [ISSN:] 1573-0476 [Volume:] 68 [Issue:] 1 [Publisher:] Springer US [Place:] New York, NY [Year:] 2024 [Pages:] 1-23
Publisher: 
Springer US, New York, NY
Abstract: 
As climate variability is increasing, extreme events such as temperature fluctuations are expected to become more frequent. Low- and middle-income countries (LMICs) are especially vulnerable to heat-related variability and its ensuing impacts on mortality. Therefore, there is an urgent need to understand how citizens in LMICs trade-off climate-related mortality risks with other risks such as traffic accidents, and what values they place on reducing such risks. As populations in LMICs are income-constrained, we adopt a non-monetary, risk-risk trade-off (RRTO) valuation method instead of the standard willingness-to-pay stated preference-based approach. We estimate the resulting risk premium for heatwave-related mortality risks through an adapted double-bounded, dichotomous choice approach to establish whether, on average, people value avoiding these risks more compared to reducing traffic risks. Using a sample of over 2,300 individuals from across seven states in India, a country with one of the highest heat-related mortality globally, we estimate the heatwave risk mortality premium to be between 2.2–2.9, indicating that on average, individuals weigh reducing heatwave-related mortality risks more than two times that of reducing traffic accident mortality risks. Based on a standard benefit transfer methodology for LMICs, this premium translates to a Value of Statistical Life (VSL) of USD 0.37–2.61 million for India.
Subjects: 
Climate change
Heatwaves
Context premium
Risk-risk trade-off
Value of statistical life
India
JEL: 
I12
Q51
Q54
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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