Additional linear models including instrumental variable and panel data models that are missing from statsmodels.

Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction

Package for heterogeneous causal effects in the presence of imperfect compliance (e.g., instrumental variables, fuzzy regression discontinuity designs)

R package of useful functions for one-sample Mendelian randomization and instrumental variable analyses

Master Degree Coursework: Econometrics I

A Stata module for an instrumental variables correlated random coefficients estimator.

IV diagnostics package accompanying Lal, Lockhart, Xu, and Zu (2023).

PDSLASSO: Stata module for post-selection and post-regularization OLS or IV estimation and inference

Test for weak IV instruments in R.

Estimation and inference of a directed acyclic graph with unspecified interventions.

R functions for g-estimation of structural nested cumulative failure models using (1) confounding adjustment or (2) instrumental variable analysis

Code/Data/Figure for "Nonparametric Instrumental Variable Estimator for Survival Outcomes"

Starter Pack About Mendelian Randomization. My Feedback about MR traning followed in 2020.

Master Degree Coursework: Econometrics II

Code for ForestIV

IV technique. Replication & critique of N. Nunn paper using R

Graphical Instrumental Variable Estimation and Testing

This is an R package I developed to estimate the causal effect of an exposure on an outcome when there's invalid instruments and large proportions of contamination.

Econometrics courses (Coursera and HSE)

COVID-19 mortality rate (Python). Original empirical study submitted for the Applied Predictive Modeling course during my second semester at HKBU - Master of Science in Data Analytics and Business Economics.