gs2020

<p>A simulated dataset for demonstration and testing.</p>

datasets

Provides tools for estimating causal effects in panel data using counterfactual methods, as well as other modern DID estimators. It is designed for causal panel analysis with binary treatments under the parallel trends assumption. The package supports scenarios where treatments can switch on and off and allows for limited carryover effects. It includes several imputation estimators, such as Gsynth (Xu 2017), linear factor models, and the matrix completion method. Detailed methodology is described in Liu, Wang, and Xu (2024) <doi:10.48550/arXiv.2107.00856> and Chiu et al. (2025) <doi:10.48550/arXiv.2309.15983>. Optionally integrates with the "HonestDiDFEct" package for sensitivity analyses compatible with imputation estimators. "HonestDiDFEct" is not on CRAN but can be obtained from <https://github.com/lzy318/HonestDiDFEct>.

Yiqing Xu

fect

Fixed Effects Counterfactual Estimators

Licheng Liu

Ziyi Liu

Ye Wang

Tianzhu Qin

Shiyun Hu

Rivka Lipkovitz

gs2020 function

Format

Simulated Gsynth-like Panel Data (No Reversal) — gs2020

Simulated Gsynth-like Panel Data (No Reversal)

gs2020: Simulated Gsynth-like Panel Data (No Reversal)

Description

Arguments

Format