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In this paper we study methods for estimating causal effects in settings with panel data, where a subset of units are exposed to a treatment during a subset of periods, and the goal is estimating counterfactual (untreated) outcomes for the treated unit/period combinations. We develop a class of...
Persistent link: https://www.econbiz.de/10012909860
In many prediction problems researchers have found that combinations of prediction methods (“ensembles”) perform better than individual methods. A simple example is random forests, which combines predictions from many regression trees.A striking, and substantially more complex, example is...
Persistent link: https://www.econbiz.de/10012889977
In many prediction problems researchers have found that combinations of prediction methods ("ensembles") perform better than individual methods. A simple example is random forests, which combines predictions from many regression trees
Persistent link: https://www.econbiz.de/10012479627
In this paper we study methods for estimating causal effects in settings with panel data, where a subset of units are exposed to a treatment during a subset of periods, and the goal is estimating counterfactual (untreated) outcomes for the treated unit/period combinations. We develop a class of...
Persistent link: https://www.econbiz.de/10012480784
Persistent link: https://www.econbiz.de/10012395697
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