toydata

<p>A dataset containing 4 columns: <code>y</code> for a continuous outcome,
<code>d</code> for a binary treatment, <code>x</code> for a pretreatment covariate,
and <code>z</code> for an excluded instrument.</p>

datasets

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) (Heckman, Urzua, and Vytlacil 2006
<doi:10.1162/rest.88.3.389>). Given a treatment selection model and an outcome model, the function mte()
estimates the MTE via a semiparametric local instrumental variables method (or via a normal selection model).
The function eval_mte() evaluates MTE at any combination of covariates x and latent resistance u, and the
function eval_mte_tilde() evaluates MTE projected onto the estimated propensity score (Zhou and Xie 2019
<https://www.journals.uchicago.edu/doi/abs/10.1086/702172>). The object returned by mte() can be used to
estimate conventional parameters such as ATE and ATT (via average()) or marginal policy-relevant
treatment effects (via mprte()).

Xiang Zhou

localIV

Estimation of Marginal Treatment Effects using Local
Instrumental Variables

toydata function

<p>An object of class <code>data.frame</code> with 10000 rows and 4 columns.</p>

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toydata: A Hypothetical Dataset for Illustrative Purpose

Description

Usage

Arguments

Format