Students who have successfully participated in this course are familiar with a wide range of standard techniques that are commonly used to analyze cross section data in the context of: 

• models for estimating causal effects;
• duration models;
• parametric models for dealing with discrete and limited dependent variables;
• non- and semiparametric estimation. 

Students are also able to identify the assumptions and limitations of the techniques, to perform empirical analysis using the discussed models, and to evaluate empirical work performed by others.

Specifics

The final grade is based on the exam (80%) and the problem sets (20%). In the problem sets, students are asked to perform empirical analyses using the software package STATA. The data will be provided on Canvas. No late submissions of the solutions to the problem sets will be accepted. Exam questions will be based on the material covered in class and in the problem sets.

Recommended Prerequisites

Main topics covered in the course: 

• social experiments;
• matching;
• differences-in-differences estimation;
• instrumental variables;
• regression discontinuity design;
• duration analysis;
• maximum likelihood estimation;
• kernel smoothing;
• binary-choice models;
• discrete-choice models;
• censored and truncated data.

Type of instructions

Type of exams

1. A. Colin Cameron and Pravin K. Trivedi, Microeconometrics: Methods and Applications, Cambridge University Press, 2005.
2. J.D. Angrist, S. Pischke, Mostly harmless econometrics, Princeton, 2009.
3. Papers announced on Blackboard