Machine Learning about Treatment Effect Heterogeneity: The Case of Household Energy Use
<jats:p> We use causal forests to evaluate the heterogeneous treatment effects (TEs) of repeated behavioral nudges toward household energy conservation. The average response to treatment is a monthly electricity reduction of 9 kilowatt-hours (kWh), but the full distribution of responses ranges...
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| Format: | Article |
| Language: | English |
| Published: |
American Economic Association
2022
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| Online Access: | https://hdl.handle.net/1721.1/144195 |