KOUT 2055 - Applied Econometrics with Stata - Advanced

The course provides theoretical tools in econometrics and empirical applications on Stata software. The course focuses on cross-sectional data analysis with a primary focus on linear regression, postestimation and interpretations. Binary dependent variable regression analyses are also part of the first part of the course. The second part of the course deals with ways to address estimator biases, including biases to causal interpretation. This part of the course focuses on impact evaluation methods (Randomized control trial, instrumental variables, difference in differences) and an introduction to panel data analysis. Each class should be divided in two unequal times, the theoretical part and the empirical application using data (from open access portals or from recently published economic papers). Both cross-sectional and panel data are used.

COURSE REQUIREMENT

• Run linear and non-linear regressions on Stata.
• Discuss the reliability of the results.
• Apply different estimation methods to different available database.
• Draft a research project.

Professionnal Skills

Reproduce applied research, interpret and present results to different audiences.

Undergraduate level in calculus and in probability and statistics.

Basic knowledge of Stata software.

Q&A once a week, with correction of previous problem set-up. Research group brief discussions are also possible.

The course requires a solid understanding of the theory of ordinary least squares regressions. Two individual take-home assignments will count for 30% of the grade. Students are also required to carry out a small research project in groups for which oral presentation (20% of the grade) and drafted article (50%) will be evaluated. Students' participation/implication will be taken into account for the final grade.

• In Class Presence: 2 hours a week / 24 hours a semester
• Online learning activities: 1 hours a week / 24 hours a semester
• Reading and Preparation for Class: 2 hours a week
• Research and Preparation for Group Work: 25 hours a week
• Research and Writing for Individual Assessments: 2 hours a week