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

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

정부 R&D 사업 논리모형·성과지표 설계 점검기 — YAML 설계서에서 끊긴 고리·지표 적합성·목표치 근거를 점검 / Logic-model and indicator design checker for government R&D programs

Enterprise impact-measurement and logic-model framework standardizing goals, activities, outputs, outcomes, and impacts across 38 community programs, with Dynamics 365 integration and Power BI analytics.

정부 R&D 사업 평가 Agent Skills 6종 — 사업 논리 점검·성과지표 감사·예산 추이·유사중복 스크린·성과 주장 점검·평가보고서 골격. 스킬마다 법 조문·지침 절 근거와 '지어내지 않는 것' 절 | Agent Skills for evaluating Korean government R&D programs, each grounded in statute and guideline sections