2017-01-09~12 | Chungsang Tom Lam：Causal Inference and Model Selection in Econometrics
This course provides an introduction to causal inference and model selection using econometric analysis.
The class is roughly divided into two parts.
• The first part introduces the basics of
the linear regression model and its
• The second part applies the model
and discusses when and how can we
make causal inference using
• Sample Mean and the Concept of Averages
• Linear Regression Basics
• Omitted Variable Bias and Bad Control
• Instrumental Variables and Two-stage Least Squares
• Average Treatment Effects and Local Average Treatment
• Fixed Effects and Random Effects
• Generalised Least Squares and Feasible Generalised Least Squares
• Robust Standard Errors
• Difference in Differences
• Regression Discontinuity
Chungsang Tom Lam
The University of Chicago, Ph.D in Economics
Assistant Professor in the John E. Walker Department of Economics Clemson University
Fields of interest :
Economics of Network
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