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fect - Fixed Effects Counterfactual Estimators

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>.

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openblascpp

8.45 score 85 stars 1 dependents 201 scripts 2.2k downloads

gsynth - Generalized Synthetic Control Method

Conducts causal inference with interactive fixed-effect models. It imputes counterfactuals for each treated unit using control group information based on a linear interactive fixed effects model that incorporates unit-specific intercepts interacted with time-varying coefficients. This method generalizes the synthetic control method to the case of multiple treated units and variable treatment periods, and improves efficiency and interpretability. See Xu (2017) <doi:10.1017/pan.2016.2> for details.

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7.53 score 155 stars 312 scripts 1.6k downloads

panelView - Visualizing Panel Data

Visualizes panel data. It has four main functionalities: (1) it plots the treatment status and missing values in a panel dataset; (2) it visualizes the temporal dynamics of a main variable of interest; (3) it depicts the bivariate relationships between a treatment variable and an outcome variable either by unit or in aggregate; (4) it displays the network structure of multi-way fixed effects as a k-partite graph, identifying connected components, singletons, and duplicate observations. For details, see <doi:10.18637/jss.v107.i07>.

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7.45 score 52 stars 1 dependents 332 scripts 1.8k downloads

interflex - Estimation, Diagnostics and Visualization of Conditional Marginal Effects

Performs estimation, diagnostics, and visualization of conditional marginal effects and group average treatment effects of a treatment on an outcome across different values of a moderator. Optionally integrates with the 'mlr3extralearners' package for additional machine learning backends compatible with the double machine learning estimators. 'mlr3extralearners' is not on CRAN but can be obtained from <https://github.com/mlr-org/mlr3extralearners>.

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6.43 score 39 stars 77 scripts 915 downloads

hbal - Hierarchically Regularized Entropy Balancing

Implements hierarchically regularized entropy balancing proposed by Xu and Yang (2022) <doi:10.1017/pan.2022.12>. The method adjusts the covariate distributions of the control group to match those of the treatment group. 'hbal' automatically expands the covariate space to include higher order terms and uses cross-validation to select variable penalties for the balancing conditions.

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cpp

4.66 score 12 stars 19 scripts 614 downloads

fdid - Factorial Difference-in-Differences

Implements the factorial difference-in-differences (FDID) framework for panel data settings where all units are exposed to a universal event but vary in a baseline factor G. Provides support for various estimators; supports robust, bootstrap, and jackknife variance; returns dynamic, pre/event/post aggregates and raw means; and includes helpers for data preparation and plotting. Methodology follows Xu, Zhao and Ding (2026) <doi:10.1080/01621459.2026.2628343>.

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4.28 score 16 scripts 275 downloads