
handle: 10197/12777 , 10419/256821
Many interesting and important economic questions relate to the effects of binary treatments such as starting a college degree or participating in a job training program. The causal effects of these treatments are likely to be heterogeneous and recent research has emphasized the estimation of heterogeneous treatment effects, with a particular focus on Marginal Treatment Effects (MTEs). In this note, I describe why common methods of estimating MTEs of binary treatments can be very sensitive to omitted higher powers of covariates and demonstrate this using simple Monte Carlo simulations. I conclude by discussing approaches that may be useful for researchers to address this problem in practice.
Research Council of Norway
ddc:330, Monte-Carlo-Simulation, Kausalanalyse, Schätztheorie, Instrumental variables, C26, Marginal treatment effects, C01
ddc:330, Monte-Carlo-Simulation, Kausalanalyse, Schätztheorie, Instrumental variables, C26, Marginal treatment effects, C01
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