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Climate change, large risks, small risks, and the value per statistical life

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Abstract

We conduct a contingent valuation survey in Spain and the UK to elicit information about the Willingness to Pay (WTP) for heat wave watch and response programs. We find that people are willing to pay for such programs, and that the WTP (€ 50 for each of 10 years; 2019 PPP euro) is virtually the same across the two countries and across respondents that received two alternate presentations of the mortality risks with and without the programs. The responses to the WTP questions are internally consistent. Persons who re-assessed their own risks as “very high” after reading the questionnaire’s information about the health effects of excessive heat are prepared to pay more for these programs. These persons are in poor health and less highly educated, and thus an important priority for outreach and education efforts by heat wave watch and response programs. That people value saving lives during heat waves as important is confirmed by the results of person tradeoffs, which show that avoiding a fatality during heat waves is comparable to avoiding a cancer fatality, is slightly more valuable than an avoiding a cardiovascular fatality, and definitely more valuable than an avoided road traffic fatality. The Value per Statistical Life implied by the WTP for the programs is € 1.1 million to € 4.7 million (2019 PPP euro), depending on the size of the mortality risk reduction valued by the respondent, for an average of € 1.6 million.

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Notes

  1. Choice tasks where respondents must choose between life-saving programs are a simple example of person tradeoffs (also termed “equivalence of numbers”)—one way of eliciting the value of health states to society or groups in the population that may or may not include the respondent (Pinto Prades, 1997). The goal is to find out how many cases cured of illness B or lives saved by program B are equivalent to one case cured from illness A or one life saved by program A. This rate of equivalence can be elicited directly by asking respondents to engage in matching tasks, or can be inferred from the responses to choice questions. Dalafave and Viscusi (2021) contrast prevented fatalities in shooting attacks with prevented fatalities in terrorist attacks. In examples from medical decisionmaking and public health, the programs may target patients with disease of different severity (Nord 1994), different age groups (Cropper et al. 1994), or be implemented at different point in time in the future (Cropper et al. 1994). More complex variants of person tradeoff questions may incorporate probabilistic descriptions of the accomplishments of the programs, allowing the analyst to study whether risk aversion applies to health states (Kemel and Paraschiv 2018).

  2. Dichotomous choice contingent valuation questions are often cast as a vote in a hypothetical referendum. If a majority of the voters were in favor, survey participants are told, the program would be adopted and the taxpayers would be obliged to pay the stated amount in the form of a tax. This phrasing ensures incentive compatibility (Carson and Groves 2007; Johnston et al. 2017), which may be compromised when the initial vote is followed by another vote with a revised cost amount (Watson and Ryan 2007). We chose to avoid any reference to a referendum on the ballot in our survey, since in both the UK and Spain referenda are generally reserved to serious constitutional matters and laws—and clearly heat wave adaptation programs do not qualify as such. (For example, in 2017 a referendum was held in Catalonia to decide on whether the region should become independent. The referendum, which was accompanied by severe disruptions, was ruled unconstitutional. In 2016, a referendum was held in the UK to decide whether the country should remain in the European Union or leave it.).

  3. This array is { 10, 20, 50, 100} Euro for Spain and its 2019 PPP equivalent for the UK, namely { 10, 25, 55, 110} GBP. These values were selected because they cover a broad range of implied VSL figures—from 200,000 to 10 million euro. When converted to 2019 PPP euro, both arrays are equivalent to 10, 25, 53, and 106 2019 PPP euro.

  4. These questions can be compared with the risk–risk tradeoffs in Mussio et al. (2023), where respondents are asked at which out of two locations they would prefer to live. The two locations differ in terms of traffic accidents and extreme weather events mortality risks, and can be compared with the risk in the area where the respondent lives.

  5. Although persons older than 65 are considered a vulnerable group during excessive heat episodes, the survey company could not guarantee representativeness among their panelists aged 66 and older.

  6. For comparison, Alberini and Ščasný (2018, 2021a) find that cancer is “highly dreaded” by 50–60% of the subjects in several countries of the European Union.

  7. In other words, they opted for the “indifferent” response in the very first question about the programs.

  8. These results are based on assuming that the underlying WTP is normally distributed. We also use the combined responses to the first and follow-up WTP question to construct a non-parametric, Kaplan–Meier estimator of the survival function of the WTP in each country. Figure 6 in the Appendix shows that the two countries’ survival functions (the percentage of the sample willing to pay any given amount) are well-behaved and for the most part overlapping. A log-rank test of the null that the distributions in the two countries are identical however rejects the null at the 1% significance level (log-rank statistic 65.97, for a p value of less than 0.001). This finding essentially confirms that, when we do not control for covariates, the WTP tends to be different across the samples from the countries.

  9. Further adding age and age squared to the probit regressions results in insignificant coefficients on these variables. We likewise obtain insignificant coefficients on age and age squared if we strip the model of most regressors, only keeping the Spain dummy, the risk “rates” version of the questionnaire dummy, age and age squared.

  10. The risk presentation treatment came later in the survey questionnaire, so it shouldn’t have had an effect on the risk “upgrade” decisions—and it didn’t.

  11. The exact estimate is 1.4866 (s.e. 0.0852). The Wald test of the null that this coefficient is equal to one is 32.59, for a p-value less than 0.001.

  12. The exact estimate is 0.9191 (s.e. 0.0705), and the Wald statistic is 1.63 (p-value 0.2033).

  13. Using labor market data, Martinez Perez and Mendez Martinez arrive at a VSL for Spain between €2.8 and €8.3 million (Martinez Perez and Mendez Martinez 2009). For the UK, Arabsheibani and Marin (2000) report a VSL of several million, whereas Hintermann et al. (2010), using panel data, find no evidence that compensating wage differentials even exist. This discrepancy may be due to the fact that it is extremely difficult to disentangle econometrically the determinants of workers’ wages (Alberini 2019).

  14. See https://data.worldbank.org/indicator/NY.GDP.PCAP.CD.

  15. Forzieri et al (2017) predict the fatalities due to heat waves in Europe a year at 103,000 during the 2050s and 151,500 during the 2080s. These fatalities correspond to € 202 billion, and € 297 billion, respectively (2019 PPP euro, using an income elasticity at 0.7). See Alberini and Ščasný (2021b) for more details.

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  1. University of Maryland, College Park, MD, 20742, USA

    Anna Alberini

  2. Institute of Economic Studies at Faculty of Social Sciences and The Environment Center, Charles University, José Martího 407/2, 162 00, Prague 6, Czech Republic

    Milan Ščasný

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Correspondence to Anna Alberini.

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This research was supported by the Horizon 2020 EU project COACCH under grant agreement no. 776479. Secondment was supported from the European Union’s Horizon 2020 Research and Innovation Staff Exchange program under the Marie Sklodowska-Curie grant agreement No. 870245 (GEOCEP).

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Appendix

Appendix

Figure 6

Fig. 6
figure 6

Non-parametric estimates of the survival function of WTP, namely 1-F(WTP), where F() denotes the cumulative distribution function of WTP. The survival function depicts a non-parametric estimates of the percentage of respondents willing to pay any given amount for the Spain and the UK samples

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The Kaplan–Meier estimator is a non-parametric estimator of the survival function of the WTP, namely 1-F(x), where F() is the cdf of the WTP and x is a specified value. It is an estimate of the probability that the WTP exceeds value x and is obtained as\(\widehat{S}\left(x\right)=\prod_{i:{x}_{i}\le x}\left(1-\frac{{d}_{i}}{{n}_{i}}\right)\), where \({d}_{i}\) is the count of respondents whose WTP must be comprised between \({x}_{i-1}\) and\({x}_{i}\), and \({n}_{i}\) is the number of respondents whose WTP exceeds\({x}_{i}\).

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Alberini, A., Ščasný, M. Climate change, large risks, small risks, and the value per statistical life. Climatic Change 177, 62 (2024). https://doi.org/10.1007/s10584-024-03721-6

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