Forward selection of control units in the panel data approach yields valid normal inference for average treatment effects even when the number of controls grows much faster than the time dimension and the true model is dense.
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Forward-Selected Panel Data Approach for Program Evaluation
Forward selection of control units in the panel data approach yields valid normal inference for average treatment effects even when the number of controls grows much faster than the time dimension and the true model is dense.