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Principles of Programming in Econometrics

  • Teacher(s)
    Charles Bos
  • Research field
  • Dates
    Period 0 - Aug 28, 2023 to Sep 01, 2023
  • Course type
  • Program year
  • Credits

Course description

During four consecutive days, the basics of programming in Econometrics are explained. This course starts with a single day where we discuss the basic syntax of the programming language Python, with excursions to other languages like Matlab and/or Julia. Using Python as a workhorse, during the next three days general concepts of programming are discussed, including how to proceed from a set of equations via an algorithm to a valid program, robustness of programming, and other more practical topics related to Econometrics. Each of the topics is explained using Python code, exploring syntax and pitfalls as we go. The course is split between a theoretical and a practical part. The theoretical part assumes a matrix-oriented programming language. It is not immediately related to a specific programming environment, though examples will be given in Python, with some Matlab and Julia for comparison. The practical part of the course uses Python to implement several exercises, under the guidance of assistants.

Principles of Programming in Econometrics

Up-to-date information on the structure of the course is disseminated through the VU Canvas course page.

The course focusses at the thought process of a programmer, teaching you the tricks and trades that could help you out.

Before the start of the course, students are expected to have studied the initial exercise E0, also available through the website http://personal.vu.nl/c.s.bos/ppectr.html, and to have worked through the first set of video lectures on Canvas. They are welcomed to read through the full slide deck (see website/canvas) in advance.

Background material can be found at the websites of Kevin Sheppard, or Thomas Sargent & John Stachurski.

Course literature

Primary reading
- Slides (available through (http://personal.vu.nl/c.s.bos/ppectr.html))
- Python for Econometrics, Kevin Sheppard, https://www.kevinsheppard.com/Python_for_Econometrics
- Quantitative Economics, Thomas Sargent & John Stachurski, https://lectures.quantecon.org/py/ (Python) or https://lectures.quantecon.org/jl/ (Julia)