Welcome to Economics 421: Introduction to Econometrics (Winter 2022) at the University of Oregon (taught by Edward Rubin).

For information on the course specifics, please see the syllabus.

The slides below (linked by their topic) are .html files that will only work properly if you are connected to the internet. If you're going off grid, grab the PDFs (you'll miss out on gifs and interactive plots, but the equations will render correctly). I create the slides with xaringan in R. Thanks go to Grant McDermott for helping/pushing me to get going with xaringan.

1. The introduction to "Introduction to Econometrics"
   PDF | .Rmd

2. Review of key math/stat/metrics topics
   Density functions, deriving the OLS estimators, properties of estimators, statistical inference (standard errors, confidence intervals, hypothesis testing), simulation
   PDF | .Rmd

3. Review of key topics from EC320
   (the first course in our intro-to-metrics sequence)
   PDF | .Rmd

4. Heteroskedasticity: Tests and implications
   PDF | .Rmd

5. Heteroskedasticity: Living with it
   PDF | .Rmd

6. Consistency and OLS in asymptopia
   PDF | .Rmd

7. Introduction to time series
   PDF | .Rmd

8. Autocorrelated disturbances
   Implications, testing, and estimation. Also: introduction ggplot2 and user-defined functions.
   PDF | .Rmd

9. Nonstationarity
   Introduciton, implications for OLS, testing, and estimation. Also: in-class exercise for model selection.
   PDF | .Rmd

10. Causality
    Introduction to causality and the Neymam-Rubin causal model. Also: Recap of in-class model-selection exercise.
    PDF | .Rmd

11. Instrumental Variables
    Review the Neymam-Rubin causal model; introduction to instrumental variables (IV) and two-stage least squares (2SLS). Applications to causal inference and measurement error. Venn diagrams.
    PDF | .Rmd