Python

The FWL Theorem: Making Multivariate Regressions Intuitive

Understanding the Frisch-Waugh-Lovell theorem to isolate causal relationships by partialling-out confounders in a simulated retail store dataset

Introduction to Partial Identification: Bounding Causal Effects Under Unmeasured Confounding

Computing causal bounds under unmeasured confounding using Manski and Tian-Pearl bounds with the CausalBoundingEngine package in Python

Introduction to Causal Inference: The DoWhy Approach with the Lalonde Dataset

Estimating the causal effect of a job training program on earnings using DoWhy's four-step causal inference framework with the Lalonde dataset

Introduction to Causal Inference: Double Machine Learning

Estimating the causal effect of a cash bonus on unemployment duration using Double Machine Learning with the Pennsylvania Bonus Experiment

Introduction to Machine Learning: Random Forest Regression

Predicting municipal development in Bolivia using Random Forest regression on satellite image embeddings

Exploratory Spatial Data Analysis (ESDA)

An interactive geocomputational notebook to study spatial clusters and outliers

Studying spatial heterogeneity

A geocomputational notebook to study spatial heterogeneity using the GWR and MGWR frameworks.

Construct and export spatial connectivity structures (W)

An introduction to how to construct, explore, and export spatial connectivity structures (W) using Python.

Monitoring subnational human development

A geocomputational notebook to monitor subnational human development using Python. Besides exploratory data analysis, the notebook introduces geospatial mapping, spatial dependence, and spatial inequality.

Spatial inequality dynamics

A geocomputational notebook to monitor spatial inequality dynamics.