(When) Should You Adjust Inference for Multiple Hypothesis Testing

Davide Viviano (Harvard University)

Paper joint with Kaspar Wuthrich and Paul Niehaus

Abstract: Multiple hypothesis testing practices vary widely, without consensus on which are appropriate when. We provide an economic foundation for these practices. In studies of multiple interventions or sub-populations, adjustments may be appropriate depending on scale economies in the research production function, with control of classical notions of compound errors emerging in some but not all cases. Studies with multiple outcomes motivate testing using a single index, or adjusted tests of several indices when the intended audience is heterogeneous. Data on actual research costs in two applications suggest both that some adjustment is warranted and that standard procedures are overly conservative.

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