We introduce a method that identifies firm-level climate change exposure from conversations in the earnings conference calls of more than 10,000 firms from 34 countries between 2002 and 2019. The method adapts a machine learning keyword discovery algorithm and captures exposures related to...

We propose an empirical measure of firms' metering problems. We build on the notion that metering problems are reflected in the intensity with which firms apply Generally Accepted Accounting Principles (GAAP) to map economic transactions onto financial statements. We develop an algorithm to...

We estimate the risk premium for firm-level climate change exposure from 2003 to 2019. Exposure is constructed from discussions of climate-related risks and opportunities in earnings calls. When extracted from realized returns, the unconditional risk premium is zero. This insignificant overall...