Abstract
We investigate the effect of haze-related sentiment on urban–rural income inequality of prefecture-level cities in China. Income inequality is captured by the Theil index, the ratio and the difference between urban–rural income. We use GPT-3.5 models to conduct the sentiment analysis on the haze-related posts retrieved from the Weibo platform from 2018 to 2021. The generated emotion score and the number of posts are used to construct the haze-related sentiment measure. We find that haze-related unhappiness exacerbates urban–rural income inequality. The net population flow is investigated as the mechanism, indicating that negative sentiment reduces the net flows of both the floating population and resident population and consequently increases income inequality. The heterogeneity analysis finds that the effects of haze-related unhappiness on income inequality are smaller in cities with more hospital beds, doctors, and green spaces. Furthermore, the effects of the sentiment measure on income inequality vary significantly across cities in different geographic locations.
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