Affiliations: College of Engineering, Northeast Agricultural University, Harbin, Heilongjiang, China
Correspondence:
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Corresponding author: Changlin Ao, College of Engineering, Northeast Agricultural University, Harbin, Heilongjiang 150030, China. E-mail: [email protected].
Abstract: Effectively assessing public preferences for air quality improvement policies is extremely important to environmental policy formulation, but developing policies that cater to public tastes is a great challenge. Although the random parameters logit (RPL) model in the choice experiment is widely used in relevant studies, it remains limited in revealing additional preference heterogeneity. Given this, the study applies two extended models in exploring public preference heterogeneity for air quality policies. An RPL model with heterogeneity in means and variances (RPL-HMV) and an RPL model with correlated random parameters (RPL-CRP) are used to provide more beneficial insights for policy analysis. The study shows that better-educated groups are more willing to pay for increasing urban green coverage, and income increases the randomness of such preferences’ distribution among groups. From the perspective of preferences, reducing heavy pollution days is positively associated with decreasing morbidity of respiratory diseases caused by outdoor air pollution and negatively correlated with improving urban green coverage. In addition, compared to the RPL-CRP model, the willingness to pay in the RPL model is overestimated by 14.72%. The study further clarifies public preferences for air quality policies, and the extra information revealed by extended models provides more valuable references for policy-making.
Keywords: Choice experiment, air quality, random parameters logit model, preference heterogeneity, correlated random parameters, willingness to pay
