A Causal Interpretation of Extensive and Intensive Margin Effects in Generalized Tobit Models
Kevin E. Staub
Abstract
Kevin E. Staub
Abstract
This note proposes a new decomposition of average treatment effects on nonnegative outcomes. It represents the total effect as a population-weighted sum of the effects for two groups: those induced to participate by the treatment and those participating regardless of it. The usual decomposition into extensive and intensive margins used in the literature is generally incompatible with such a causal interpretation. The difference between decompositions can be substantial and yield diametrically opposed results.
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This note proposes a new decomposition of average treatment effects on nonnegative outcomes. It represents the total effect as a population-weighted sum of the effects for two groups: those induced to participate by the treatment and those participating regardless of it. The usual decomposition into extensive and intensive margins used in the literature is generally incompatible with such a causal interpretation. The difference between decompositions can be substantial and yield diametrically opposed results.
Key concepts: Interpretation (philosophy), Tobit model, Econometrics, Margin (machine learning), Mathematics, Decomposition, Population, Statistics