Software

MY STATA programs for Program Evaluation Econometrics


R_ML_STATA: Stata module to implement machine learning regression in Stata


C_ML_STATA: Stata module to implement machine learning classification in Stata


CUB: Stata module to estimate ordinal outcome model estimated by a mixture of a uniform and a shifted binomial


TFDIFF: Stata module to compute pre- and post-treatment estimation of the Average Treatment Effect (ATE) with fixed binary treatment


SUBSET: Stata module to implement best covariates and stepwise subset selection


SCTREE: module to implement classification trees via optimal pruning, bagging, random forests, and boosting methods


SRTREE: Stata module to implement regression trees via optimal pruning, bagging, random forests, and boosting methods


SENSIMATCH: Stata module to provide data-driven sensitivity analysis for Matching estimator


TVDIFF: Stata module to compute pre- and post-treatment estimation of the Average Treatment Effect (ATE) with binary time-varying treatment


MKERN: Stata module to perform multivariate nonparametric kernel regression


NPSYNTH: Stata module to implement Nonparametric Synthetic Control Method


NTREATREG: Stata module for estimation of treatment effects in the presence of neighbourhood interactions


TED: Stata module to test Stability of Regression Discontinuity Models


RSCORE: Stata module for estimation of responsiveness scores


DATANET: Stata module to facilitate dataset organization for network analysis purposes


CTREATREG: Stata module for estimating dose-response models under exogenous and endogenous treatment


IVTREATREG: Stata module to estimate binary treatment models with idiosyncratic average effect


TREATREW: Stata module to estimate Average Treatment Effects by reweighting on propensity score


It goes without saying that different software are useful tools according to specific purposes. In this section I provide a very short description of the most used packages both for economic-statistical analysis and for more general scientific purposes with an hyperlink to their website.


STATA: for statistical analysis

PYTHON: for machine learning and data science

R: for statistical analysis

MATLAB: for computational purposes

SIMLAB: for sensiyivity analysis

LATEX: for editing scientific papers

HTML: for building websites