Ambient particulate air pollution and daily stock market returns and volatility in 47 cities worldwide

Abstract

Abstract We studied globally representative data to quantify how daily fine particulate matter (PM2.5) concentrations influence both daily stock market returns and volatility. Time-series analysis was applied on 47 city-level environmental and economic datasets and meta-analysis of the city-specific estimates was used to generate a global summary effect estimate. We found that, on average, a 10 μg/m3 increase in PM2.5 reduces same day returns by 1.2% (regression coefficient: − 0.012, 95% confidence interval: − 0.021, − 0.003) Based on a meta-regression, these associations are stronger in areas where the average PM2.5 concentrations are lower, the mean returns are higher, and where the local stock market capitalization is low. Our results suggest that a 10 μg/m3 increase in PM2.5 exposure increases stock market volatility by 0.2% (regression coefficient 0.002, 95% CI 0.000, 0.004), but the city-specific estimates were heterogeneous. Meta-regression analysis did not explain much of the between-city heterogeneity. Our results provide global evidence that short-term exposure to air pollution both reduces daily stock market returns and increases volatility.