DRDID

DRDID-package

<img src="figures/logo.png?package=DRDID&version=1.2.0" style="float: right" alt="logo" width="120">
Implements the locally efficient doubly robust difference-in-differences (DiD) estimators for the average treatment effect proposed by Sant'Anna and Zhao (2020) tools:::Rd_expr_doi("10.1016/j.jeconom.2020.06.003"). The estimator combines inverse probability weighting and outcome regression estimators (also implemented in the package) to form estimators with more attractive statistical properties. Two different estimation methods can be used to estimate the nuisance functions.

internal

Implements the locally efficient doubly robust difference-in-differences (DiD)
estimators for the average treatment effect proposed by Sant'Anna and Zhao (2020)
<doi:10.1016/j.jeconom.2020.06.003>. The estimator combines inverse probability weighting and outcome
regression estimators (also implemented in the package) to form estimators with
more attractive statistical properties. Two different estimation methods can be used
to estimate the nuisance functions.

Pedro H. C. Sant'Anna

Doubly Robust Difference-in-Differences Estimators

Jun Zhao

DRDID-package function

Maintainer: Pedro H. C. Sant'Anna <a href="/link/pedrosantanna%40causal-solutions.com?package=DRDID&version=1.2.0" data-mini-rdoc="DRDID::pedrosantanna@causal-solutions.com">pedrosantanna@causal-solutions.com</a> [copyright holder]
Authors:<ul>
<li>Jun Zhao <a href="/link/beanzhaojun11%40gmail.com?package=DRDID&version=1.2.0" data-mini-rdoc="DRDID::beanzhaojun11@gmail.com">beanzhaojun11@gmail.com</a></li>
</ul>

Author

<img src='figures/logo.png' style='float: right' alt='logo' width='120' />
Implements the locally efficient doubly robust difference-in-differences (DiD) estimators for the average treatment effect proposed by Sant'Anna and Zhao (2020) tools:::Rd_expr_doi("10.1016/j.jeconom.2020.06.003"). The estimator combines inverse probability weighting and outcome regression estimators (also implemented in the package) to form estimators with more attractive statistical properties. Two different estimation methods can be used to estimate the nuisance functions.

DRDID: Doubly Robust Difference-in-Differences Estimators — DRDID-package

Maintainer: Pedro H. C. Sant'Anna <a href='mailto:pedrosantanna@causal-solutions.com'>pedrosantanna@causal-solutions.com</a> [copyright holder]
Authors:<ul>
<li>Jun Zhao <a href='mailto:beanzhaojun11@gmail.com'>beanzhaojun11@gmail.com</a></li>
</ul>

DRDID-package: DRDID: Doubly Robust Difference-in-Differences Estimators

Description

Arguments

Author

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