PhD Modules: Causal Inference for Applied Microeconometrics

Short courses for PhD programmes, research institutes, and public bodies

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A set of short, self-contained modules on the core methods used in applied microeconometrics for credible causal inference. Each module can stand alone or be combined into a one- or two-week intensive PhD course.

Modules

  1. Potential outcomes framework. The Rubin causal model; treatment effects (ATE, ATT, LATE); selection bias and the fundamental problem of causal inference; identifying assumptions and what credible identification looks like in practice.

  2. Randomised experiments. Why randomisation solves the selection problem; sampling vs assignment; block, cluster, and stratified designs; analysis of RCTs; field-experiment practicalities and common threats (attrition, non-compliance, Hawthorne effects, spillovers).

  3. Regression discontinuity design (RDD). Sharp vs fuzzy designs; identification through local randomisation; bandwidth selection, local polynomials, and bias-corrected confidence intervals; validity checks (manipulation tests, covariate balance); applied examples in health and education.

  4. Difference-in-differences (DiD). The two-period 2×2 design; parallel trends as the identifying assumption; event-study and dynamic specifications; staggered adoption and the recent econometric literature (Callaway–Sant’Anna, de Chaisemartin–D’Haultfœuille, Sun–Abraham, Borusyak–Jaravel–Spiess); inference with few clusters.

Course logistics

  • Audience. PhD students, early-career researchers, and applied economists in research institutes, regulators, and policy units.
  • Format. Lectures plus worked examples in R and hands-on labs. Modular — each module is self-contained.
  • Length. Around 4-6 hours per module; the full set is typically delivered as a 16-24 hour intensive course.
  • Language of instruction. English or Spanish.
  • Software. R via RStudio. Stata code can be provided on request.
  • Materials. Slides, R scripts, replication datasets, and graded exercises.

Availability

These modules are available for delivery at other institutions and PhD programmes, as well as for research institutes, firms, and public bodies — in English or Spanish. Get in touch to discuss a fit for your programme.