Does a strict COVID-19 lockdown policy change risk attitudes? Evidence from a bordering town, Gengma, in Yunnan Province, China

Understanding how lockdown, a strict epidemic prevention policy, affects people’s risk attitudes is an interesting and fundamental issue. Behavioural experiments constitute one of the mainstream methods for measuring such microscopic effects. However, since epidemics are emergent events, their occurrence time is almost unpredictable; thus, obtaining comparative data before and after the implementation of a lockdown is difficult. Fortunately, in this study, we obtained a pair of controlled experimental data before and after the lockdown policy was implemented from the bordering town of Gengma in Yunnan Province, China. In 2018, we conducted risk preference behaviour experiments in various regions of Yunnan Province, including one experiment involving 65 residents of Gengma County, which became our first round of experiments. In November 2020, Gengma was locked down because of the COVID-19 pandemic. Immediately after the lockdown was lifted, we conducted another risk preference experiment, recruiting 55 residents, 39 of whom also participated in the first round of experiments, and this became our second round of experiments. Thus, we can better analyse how strict epidemic prevention policies change people’s risk attitudes. We found that before the COVID-19 lockdown policy was implemented, the participants’ risk attitudes fit well with the fourfold risk attitudes predicted by the Prospect Theory (PT). However, after a 14-day lockdown, Gengma residents’ risk attitudes significantly changed. They became more risk seeking for moderate-probability gains and risk averse for moderate-probability losses, which is contrary to PT’s prediction and contrary to their risk attitudes before the lockdown. These findings may serve as important references for policies related to epidemic prevention, community management, social security, and more in the post-COVID-19 era.