An applied introduction to modern econometrics. We focus on causal inference and forecasting using linear regression, fixed/random effects, instrumental variables, difference-in-differences, limited dependent variable models, and model diagnostics. Real data labs develop reproducible research habits.
Statistics (random variables, expectation, variance, hypothesis testing).
Calculus and linear algebra (matrix notation).
You will be able to:
Specify, estimate, and interpret linear models with rigorous assumption checks.
Diagnose bias (omitted variables, selection, measurement error) and propose solutions.
Implement panel, IV, and DiD designs; understand their identifying assumptions.
Communicate empirical findings with clean tables/figures and plain-language summaries.
Build reproducible workflows (scripts, versioning, well-commented code).
Preferred: R (tidyverse, fixest, AER, modelsummary) or Python (pandas, linearmodels, statsmodels).
Alternatives: Stata.
All assignments must include code + README enabling full replication.
Week 01: Review of probability & sampling; causality vs. correlation
Week 02: Simple & multiple OLS; assumptions; Gauss–Markov
Week 03: Inference: heteroskedasticity, robust SEs, bootstrap
Week 04: Functional form, interactions, and nonlinearities
Week 05: Omitted variable bias, measurement error, and selection
Week 06: Panel data: FE/RE; clustered SEs
Week 07: Difference-in-Differences & event studies
Week 08: Instrumental Variables: relevance & exogeneity; 2SLS
Week 09: Limited dependent variables: logit/probit; count models
Week 10: Regression discontinuity (intro)
Week 11: Forecasting basics; cross-validation; out-of-sample tests
Week 12: Causal diagrams (DAGs) & identification strategies
Week 13: Replication and robustness practice
Week 14: Project presentations
Collaboration: Discuss ideas; submit your own work.
Late Work: 48-hour window with 10% per day penalty; after that by prior approval only.
Academic Integrity: University policy applies; violations receive a zero and are reported.
Accessibility: I’m committed to equitable learning—contact me early for accommodations.
MWF 10:00 - 11:00 AM
Economics Building, Room 201
45 Students
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