Over the past few years, there has been a significant focus on air pollution due to its various detrimental effects on human health. However, its influence on people's tendency to have children remains uncertain, as only a few studies have examined the correlation between public perception of air pollution and the desire to start a family. This article introduces a theoretical framework utilizing a two-stage interval iteration model to explore the connection between children's relative utility and the perception of air pollution. Data for this study were gathered from the "Chinese General Social Survey" (CGSS 2013). The CGSS 2013 project employed a four-stage stratified random sampling technique and conducted household interviews using questionnaires. The sample covered 28 provincial-level cities across China. The hypothesis was tested using a Probit regression model. The findings indicate that individuals considering air pollution a significant issue are 8.62% less likely to have more than one child. The variation in fertility desire sensitivity to air pollution points to heterogeneity among residents, such as registered residents and those living in various residential areas, as well as individuals with different characteristics like education levels. The study concludes that air quality significantly influences human fertility desire, highlighting the urgent necessity to raise awareness of environmental protection issues among both the public and authorities. In particular, there are two key steps to address this issue. Firstly, the government should establish clear air pollution control objectives and refine policies to enhance governance efficiency. Secondly, there is a need to encourage environmentally friendly behaviours among the public, promote more significant involvement in public environmental matters, and ensure effective oversight of the government's responsibilities in managing air pollution.
Keywords: China; Fertility desire; Perception of air pollution; Probit regression; Relative utility of children; Two-stage interval iterative model.
© 2023. The Author(s) under exclusive licence to International Society of Biometeorology.