Double Machine Learning and Causal Forests
How machine learning is used for causal questions: double ML to handle many controls, causal forests for effects that differ...
Econometrics
Unlock the power of econometrics with insights on key models and tools that help explain and forecast economic trends. Perfect for both beginners and advanced researchers.
Modern Difference-in-Differences Estimators
Two-way fixed effects is biased when treatment is staggered. What Callaway-Sant'Anna, Sun-Abraham and Goodman-Bacon do instead, and when to use...
Causal Inference in Economics: Three Methods
Causal inference in economics rests on three methods: difference in differences, regression discontinuity, and synthetic control. Here is how each...
Machine Learning in Econometrics
Machine learning handles high-dimensional data and nonlinearity. Econometrics answers causal questions. Here is where each wins and how they combine.
Quantile Regression Explained
Quantile regression estimates how a variable affects the whole distribution of an outcome, not just its mean. What it does,...
Structural Breaks in Time Series
A structural break is a change in the data-generating process itself. How to test for one with Chow and Bai-Perron,...
Bootstrap Methods in Econometrics
Resampling your own data to get standard errors and confidence intervals without assuming a distribution. How the bootstrap works and...
Nonparametric and Semiparametric Methods
For when you do not want to assume a functional form. What nonparametric and semiparametric estimators do, what they cost...
Simultaneous Equations Models
When variables determine each other, ordinary least squares is biased. What simultaneous equation bias is, and how two-stage least squares...
Structural Equation Models Explained
Structural equation models link observed indicators to latent variables you cannot measure directly, then estimate the paths between them in...