program-evaluation

A Python package for causal inference using Synthetic Controls

Robust Local Polynomial Methods for RD Designs

Synthetic difference in differences for Python

📊 🌐 🧑‍🏫 Website for graduate-level course on program evaluation and causal inference using R, built with Quarto

📊 🌐 🧑‍🏫 Website for graduate-level course on program evaluation and causal inference using R, built with Quarto

Regression Discontinuity Design Software Packages

Manipulation Testing Using Local Polynomial Density Methods

📊 🌐 🧑‍🏫 Website for graduate-level course on program evaluation and causal inference using R, built with Quarto

Local Randomization Methods for RD Designs

Robust Local Polynomial Methods for RD designs with Multiple Cutoffs or Multiple Scores

Nonparametric and Semiparametric Software Packages

Power and Sample Size Calculations for RD designs

Curso de Econometría con un aplicaciones en Python

Implementation of Van Dijcke, David. "Regression Discontinuity Design with Distribution-Valued Outcomes." Manuscript.

Streamline policy evaluation workflows with AI-driven analysis and evaluation framework-agnostic processing

A PyTorch implementation of the "robust" synthetic control model

syntCF is an R package that provides a set of tools to estimate the effect of a program or a policy using a robust time series synthetic counterfactual approach coupled with the double difference estimator within a Machine Learning framework.

Open Course on Program Evaluation

Home for Anthony D'Agostino's professional webpage

Claude skill and Claude Code plugin for designing, prioritising and quality-assuring evaluation questions and evaluation matrices for development and humanitarian programmes. Applies OECD-DAC and UNEG standards and adapts them to EU, World Bank, UNICEF, FCDO and other donor frameworks.