In the generalized Roy model, the marginal treatment effect (MTE) can be used as a building block for constructing conventional causal parameters such as the average treatment effect (ATE) and the average treatment effect on the treated (ATT). Given a treatment selection equation and an outcome equation, the function mte() estimates the MTE via the semiparametric local instrumental variables method or the normal selection model. The function mte_at() evaluates MTE at different values of the latent resistance u with a given X = x, and the function mte_tilde_at() evaluates MTE projected onto the estimated propensity score. The function ace() estimates population-level average causal effects such as ATE, ATT, or the marginal policy relevant treatment effect.
Package details |
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Author | Xiang Zhou [aut, cre] |
Maintainer | Xiang Zhou <xiang_zhou@fas.harvard.edu> |
License | GPL (>= 3) |
Version | 0.3.1 |
URL | https://github.com/xiangzhou09/localIV |
Package repository | View on CRAN |
Installation |
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