This study investigates the relationship between corporate greenhouse gas (GHG) emissions and corporate social responsibility (CSR). Using GHG emissions data and the CSR index announced by the Korea Economic Justice Institute, we find that companies emitting more GHG are highly rated in the CSR index. This relationship becomes stronger as the firm size increases. This result indicates that reducing GHG, especially for big firms, may not be an effective way to raise the firm's CSR index as expected. We interpret this result as suggesting that other social contribution behaviours may be valued more than GHG reduction, despite its actual environmental influence. We therefore argue that the current CSR index possibly underestimates the importance of environmental factors, such as GHG reduction, and thus, the index needs to be improved.

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While monetary easing and increasing participation of financial institutions in commodity trading have enhanced the financialization of commodity markets, this paper investigates empirically whether the impact of global liquidity on commodity prices has grown since the crisis. For each commodity group, this paper uses a structural vector autoregression (SVAR) model to address the short‐run relationship between global liquidity and commodity prices. The key finding is that the effect of global liquidity on commodity prices becomes more salient since the global financial crisis. This paper also suggests a price‐based liquidity indicator has a greater explanatory power for the commodity price dynamics than monetary aggregates.

Using monthly regional panel data on air quality and large retail store sales in Korea, we empirically examine the effect of air pollution on retail sales. We account for regional heterogeneity in air pollution and control for various macroeconomic and climatic factors that can affect retail sales. We also use the air quality indicator in the west coastal islands (affected by trans‐border pollution but uncorrelated with the economic activity in the mainland) as an instrumental variable. The estimation results show that, in general, 1 additional day of PM10 level higher than 80 μg/m3 reduces monthly retail sales by approximately 0.1 percent. Nonetheless, an adaptive pattern emerges over time, particularly when the level of air pollution in the previous month was severe.

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