Regression Discontinuity Designs.

Python, R and Stata implementations: website.
Package rdrobust: Estimation, inference, falsification and RD Plots.
Package rddensity: Manipulation testing.
Package rdlocrand: Local randomization methods.
Package rdmulti: RD plots, estimation, inference, and extrapolation with multiple cutoffs and multiple scores.
Package rdpower: Power and sample size calculations.


Python, R and Stata implementations: website.
Package binsreg: Binscatter methods.

Synthetic Controls.

Python, R and Stata implementations: website.
Package scpi: Estimation and Inference for Synthetic Control methods.

Nonparametric Smoothing.

Python, R and/or Stata implementations: website.
Package nprobust: Kernel density and local polynomial regression methods.
Package lpdensity: Local polynomial distribution/density regression methods.
Package lpcde: Local polynomial conditional distribution/density regression methods.
Package lspartition: Partitioning-based least squares regression methods.

Treatment Effects under Ignorability.

R and Stata implementations: website (coming soon).
Data-driven semiparametric inference methods for multi-valued treatment effects.
Background paper: Cattaneo (2010).
2013 Stata implementation:

For installation/update type in Stata: findit poparms
Software paper: Cattaneo, Drukker and Holland (2013) | Replication.
Official Stata version features results from these papers: reference manual.

Random Attention Model.

R implementation (package ramchoice): CRAN | Manual.
Nonparametric estimation, inference and specification testing in random limited attention settings.
Background paper: Cattaneo, Ma, Masatlioglu and Suleymanov (2020) | Replication.
Background paper: Cattaneo, Cheung, Ma and Masatlioglu (2021) | Replication.