Air pollution has received increasing attention in recent years, particularly in China, due to the rapid industrialisation that has wrought intense levels of air pollution. A number of studies, therefore, have been devoted to quantifying the impacts of air pollution on property value in China. However, the empirical results are somewhat mixed. This naturally raises questions of whether there is a significant relationship between air quality and housing prices and the plausible reasons for the mixed results in previous studies. This study aims to fill this gap by explaining the variations in the findings by a meta-regression analysis. To control for heterogeneity, a weighted least square model was used to explore the factors influencing the magnitude and significance of the air quality effect based on empirical estimates from 117 observations. This study confirms that air quality does have a discernible impact on housing prices beyond the publication bias. Besides, the types of air quality indicator and the air data source do significantly influence estimates through affecting both the magnitude of the elasticity and the partial correlation coefficient (PCC). Further, the selections of control variables and estimation approaches also have significant impacts on estimates. This study also finds that published papers tend to be biased towards more economically significant estimates. The implications of the findings have also been discussed.
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