Detailed course contents:

Lecture 1: Unbiasedness, consistency, and efficiency (Chapters 2 and 5)

Lecture 2,3,4: Time Series (Chapters 10 - 12)
Basic Regression analysis with time series data.
- Properties of OLS with time series data.
- Trends and seasonality.
- Stationarity, nonstatinarity and weak dependence.
- Serial correlation and heteroskedasticity in time series regressions.

Lecture 5,6: Panel Data (Chapters 13 - 14)
- Pooling cross sections across time: Simple panel data methods.
- Fixed effects estimation
- Random Effects Models

Lecture 7: Instrumental Variables & 2SLS (Chapter 15)
- Instrumental variables estimation.
- Two Stage Least Squares (2SLS).

Lecture 8: Midterm exam

Lecture 9: Simultaneous equations (Chapter 16)
- Simultaneous equations models (simultaneity bias in OLS, etc.).

Lecture 10, 11 Limited Dependent Variable models (Chapter 17)
- Binary response models (linear probability, logit, probit).
- Corner solution, censored and truncated data models.

Lecture 12: Repetition (Chapters 10-17)