Introduction to Econometrics
The course is a largely intuitive introduction to the linear regression model---the workhorse of applied
economics. The focus is on the ordinary least squares estimator, its interpretation, and the assumptions
underlying its statistical properties.
Successful completion of the course enables students to Understand how linear regression is used to estimate causal relationships from observational data. Derive solutions to structured and semi-structured problems related to the specification, estimation and testing of linear regression models. Argue for and against the use of specific control variables in linear regression models. Prove consistency or find asymptotic bias of linear estimators. Understand the logic of sampling variance and distribution of estimators. Carry out simple hypothesis tests in linear models. Estimate the models covered in the course using econometric software, and interpret their results.
Four weekly problem sets---32% (total); final exam---68%. The final course grade will be assigned on a
curve (i.e., on a relative scale). You are allowed to form study groups with 2 other students and turn in
one assignment per study group. Default group assignments will be posted in “working groups.xls” on
the course website.