Fast Estimation of Linear Models with IV and High Dimensional Categorical Variables
-
Updated
Apr 3, 2024 - Julia
Fast Estimation of Linear Models with IV and High Dimensional Categorical Variables
2SLS Regression with Diagnostics in R
R package of useful functions for one-sample Mendelian randomization and instrumental variable analyses
CRAN Task View: Causal Inference
nl-causal: nonlinear causal inference based on IV regression in Python
Inference in SVMA models identified by external instruments/proxies
A Stata module for an instrumental variables correlated random coefficients estimator.
This is the website repository for the Stata packages lassopack & pdslasso. Please visit:
Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions
Lecture slides, video recordings, and coding exercises from the 2024 Northwestern University Causal Inference Workshop. This repository is not affiliated with Northwestern University or the workshop.
2SLS IV regression with Python
R code to reproduce results of data examples in 'Selecting invalid instruments to improve MR with two-sample summary data''
Stata package for one-sample Mendelian randomization / instrumental variable analyses
Code for an R package to implement instrumental variables procedures that are robust to many & weak instruments.
R Code That Makes up the Bulk of my Master's Paper
This assignment relates to my 8th assignment in Econ 323 - Econometrics Analysis 2. I generate new demand and supply data and use this to test different casualty methods such as TSLS, IV, and Diff-In-Diff.
This repository shows some coding my colleagues and I made for our Advanced Econometrics course for the Diploma of Specialization in Data Science for Social Sciences and Public Management - PUCP
A brief workshop on two-stage least-squares regression for instrumental variable analysis
Two-sample two-stage least squares estimation
Add a description, image, and links to the instrumental-variables topic page so that developers can more easily learn about it.
To associate your repository with the instrumental-variables topic, visit your repo's landing page and select "manage topics."