Lectures

Each lecture ships in three formats compiled from one source: web notes with glossary and footnote popovers, a LaTeX-compiled PDF, and reveal.js slides. Exercises appear in the notes with collapsible hints and worked solutions; the solutions companion prints them in full.

The course handbook binds the finished lectures into one PDF, followed by the course glossary and index. It grows as lectures are published.

#	Lecture	Materials	Status
1	From an Economic Question to a Local Projection	notes · solutions · slides · lab · practicum	live
2	Levels, Differences, Cumulative Responses, and Units	—	in development
3	Identification, Controls, and the Pre-Shock Information Set	—	in development
4	LP-IV and Cumulative Multipliers	—	in development
5	Pointwise Inference, Persistence, and Lag Augmentation	—	in development
6	Inference About the Response Path	—	in development
7	LPs versus VARs: Estimands, Bias, and Variance	—	in development
8	Smoothing and Restrictions Across Horizons	—	in development
9	State Dependence and Asymmetric Responses	—	in development
10	What Linear LPs Mean in Nonlinear Economies	—	in development
11	Panel LPs and Common Macroeconomic Shocks	—	in development
12	LP Difference-in-Differences	—	in development
13	Sensitivity Analysis and Policy Counterfactuals	—	in development
14	Research Synthesis, Replication Audit, and Defense	—	in development

The four parts

Part	Lectures	What you can do afterwards
I. Define and identify the dynamic effect	1–4	State an estimand, build the regression, argue identification, use an instrument
II. Evaluate estimation and uncertainty	5–8	Choose and defend an inference procedure, compare estimators, restrict responsibly
III. Heterogeneity, nonlinearity, and panels	9–12	Interpret interacted, nonlinear, panel, and staggered-treatment designs
IV. Use and defend LP evidence	13–14	Bound the conclusions, reproduce someone else’s work, survive an audit

Two references accompany the whole course: Jordà and Taylor’s Local Projections (Journal of Economic Literature, 2025) and Inoue, Jordà, and Kuersteiner’s Inference for Local Projections (Econometrics Journal, 2026). Each lecture’s reading guide names the sections that matter for that week.