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 will bind the finished lectures into one PDF, followed by the course glossary and index.

#	Lecture	Practicum	Status
1	From an Economic Question to a Local Projection	P01	in development
2	Levels, Differences, Cumulative Responses, and Units	P02	in development
3	Identification, Controls, and the Pre-Shock Information Set	P03	in development
4	LP-IV and Cumulative Multipliers	P04	in development
5	Pointwise Inference, Persistence, and Lag Augmentation	P05	in development
6	Inference About the Response Path	P06	in development
7	LPs versus VARs: Estimands, Bias, and Variance	P07	in development
8	Smoothing and Restrictions Across Horizons	P08	in development
9	State Dependence and Asymmetric Responses	P09	in development
10	What Linear LPs Mean in Nonlinear Economies	P10	in development
11	Panel LPs and Common Macroeconomic Shocks	P11	in development
12	LP Difference-in-Differences	P12	in development
13	Sensitivity Analysis and Policy Counterfactuals	P13	in development
14	Research Synthesis, Replication Audit, and Defense	P14	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.