FIN544 Stata Programming and Applications in Finance

• Topics

  The course focuses on econometric programming in Stata. The course introduces students to fundamental and advanced programming techniques using Stata. Applications to real datasets will be covered with the goal of identifying causal relations in empirical corporate finance. The course will cover panel data, diff-in-diff estimators, randomized inference as well as an introduction to machine learning among other things.

• Learning outcome

  After completing the course, students will be able to:

  Knowledge.

  - identify causal relations in empirical corporate finance

  Skills.

  - use Stata to implement modern technics to identify causal relations in empirical corporate finance

  - choose appropriate identification strategy

• Teaching

  The course takes place over six weeks and is taught via Zoom. Each week consists of a 30 minute pre-recorded video lecture and a 60-minute synchronous lecture.

• Restricted access

  The lecture will be open to all PhD students at NHH as well as PhD candidates from other Norwegian institutions

• Required prerequisites

  • Successful completion of PhD-level empirical corporate finance course;
  • Stata command language and programming fundamentals (data management commands, standard estimation commands, macro, programming constructs)

• Compulsory Activity

  Students are required to deliver weekly written individual assignments during the course.

• Assessment

  Students are required to deliver one individual, written homework assignment.

• Grading Scale

  Pass-fail

• Computer tools

  STATA

• Literature

  Christopher F. Baum, An Introduction to Stata Programming, Second Ed., Stata Press