Abstract
We examine the relationship between climate policy uncertainty (CPU) and stock market volatility using the GARCH-MIDAS framework to accommodate the variables in their available frequencies thereby circumventing information loss associated with data aggregation or splicing. We find that stock market volatility significantly responds to CPU and we further document improved forecast and economic gains of observing CPU relative to ignoring it.
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