Ph.D. coursework in econometrics and empirical industrial organization at Yale. The write-ups, notebooks and code linked below are my own; where a solution restates the problem it answers, that problem is the instructor's. Lecture slides, syllabi and official solutions are not hosted here — if you spot anything on this page that should not be, please let me know.
Yale University, 2025–26
- Empirical Industrial Organization (ECON 6600), Fall 2025 —
Profs. Philip Haile and Charles Hodgson. Honors.
Three replication-grade implementations:
[Repository]
Demand. Random-coefficients logit with optimal instruments, diversion ratios and merger counterfactuals, estimated with pyBLP [Notebook] [Code] [Write-up]
Single-agent dynamics. Value-function iteration and structural estimation of the optimal machine-replacement model, on Rust's original bus-engine data [Notebook]
Dynamic games. Bajari–Benkard–Levin forward simulation with conditional choice probabilities, recovering profit parameters from an entry/exit game [Code] [Write-up] - Econometrics of Dependent Data / Econometrics IV (ECON 5553), Spring 2026 —
Prof. Timothy Christensen. Honors.
Four write-ups, 25 pp.: matching estimators and treatment effects; martingales, uniform
integrability and tail sigma-algebras; pre-testing and the uniformity of inference; the Wold
decomposition; stable convergence and Bartik instruments; limit theory for dyadic data and
under two-way dependence
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Two longer course requirements: the oral examination, a presentation of Andrews, Barahona, Gentzkow, Rambachan and Shapiro, “Causal Interpretation of Structural IV Estimands” (QJE 140(3), 2025) [Presentation], and a referee report written to Econometrica guidelines on Borusyak, Chen, Hull and Lei, “Nonparametric Identification of Demand without Exogenous Product Characteristics” (NBER WP 34842) [Referee report] - Econometrics III (ECON 5552), Fall 2025 — Prof. Yuichi Kitamura. Audited, at full workload. Five write-ups, 31 pp.: parametric and nonparametric identification; asymptotic theory for nonlinear models; limited-dependent-variable models; quantile instrumental variables; Kolmogorov–Smirnov and related distributional tests; the bootstrap and subsampling, applied to Survey of Consumer Finances data [1] [2] [3] [4] [5]
Credit
The idea of publishing graduate coursework as a structured, readable page comes from Matteo Courthoud, whose PhD Econometrics and Empirical IO notes are a model for how much of a doctoral education can be made public and useful. This page is narrower: it collects my own solutions and implementations rather than a set of lecture notes.