On the use of machine learning for causal inference in climate economics

In the new CAMP working paper 05/2019, Hovdahl develops a procedure that enables the use of machine learning for estimating the causal temperature-mortality relationship. The paper demonstrates how machine learning can be used for causal inference in the presence of high-frequency panel data. Hovdahl further compares the developed machine-learning model to a traditional OLS model and finds that the models deliver different predictions of the effect of climate change on mortality. The procedure developed in the paper is applicable to other fields beyond climate economics.

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