Valuing mortality risk reductions in the time of COVID-19: A stated-preference analysis

Lack of high-quality value per statistical life (VSL) studies in low- and middle-income countries have been recognized by scholars and analysts in the benefit-cost analysis field for decades. However, progress has been slow in addressing it. We estimated VSL in China using a stated-preference survey in the context of reducing mortality risks associated with COVID-19. The survey was administered in seven cities across China in 2022 with a purposive sampling approach, and consistency checks at different levels of stringency regarding willingness to pay (WTP) for mortality risk reductions of different magnitudes were used to screen respondents. The estimated VSL ranges from 8.0 million to 10.3 million Chinese Yuan, which is higher than previous estimates. Also previous studies found much higher VSL estimates from a subsample obtained with more stringent consistency check requiring that WTP be approximately proportional to the magnitude of mortality risk reduction, we did not find such a difference with our dataset. In addition, based on our anlaysis, respondents in first-tier cities such as Beijing, Shanghai and Guangzhou have higher VSL than those in second-tier cities such as Changchun, Chengdu, Wuhan and Xi’an; the VSL-age relationship shows a U-shaped pattern; and the collective experience of city lockdown has a negative impact on VSL. Other factors which were found to influence VSL include education, sector of work, health status, risk perception, behaviors (physical exercises, wearing face masks, getting vaccinated), knowledge, political identity, and trust in government. I12, I18