AEM 6851

Monte Carlo Methods for Applied Econometrics

Course Description

Course information provided by the 2026-2027 Catalog.

AEM 6851 teaches Monte Carlo simulation as the tool researchers use to investigate their own estimators rather than defer to published recipes. The course is organized around the data-generating process: for each topic, we specify a DGP that describes a problem applied researchers commonly face, derive what an estimator should do under it, simulate, and compare outcomes against ground truth. The aim is to build the intuition and computational skill needed to diagnose when an estimator works, when it fails, and when the estimator you need has not been studied under the conditions you face. The goal is to be able to design a Monte Carlo experiment that produces an evidence-based answer.

Enrollment Information Recommended Prerequisites: AEM 6850.

Last 4 Terms Offered (None)

Learning Outcomes

• Specify a data-generating process and implement it as a reproducible R simulation.
• Use Monte Carlo evidence to evaluate the finite-sample properties of estimators and their inference procedures.
• Compare causal estimators (OLS, IV, DiD, ML-based) under realistic failure modes.
• Design and write up an original Monte Carlo study relevant to their research.

View Enrollment Information