Dynamic optimization

Gives the theoretical background and tools for discrete dynamic programming.

• Vector spaces, norms, Banach spaces
• Contraction mappings, Blackwell's theorem
• Berge's optimization theorem,
• Discrete dynamic optimization under certainty,
• Algorithms to solve discrete dynamic optimization problems under certainty
  • Value function iteration,
  • Interpolation,
  • Howard improvement
  • Coding
• Discrete dynamic optimization under undertainty,
• Algorithms to solve discrete dynamic optimization problems under uncertainty.
• Finite horizon dynamic programming with applications to shortest path problems, currency exchange, knapsack problems, longest common subsequence, etc
  • analysis of problems, complexity analysis and coding

The aim of this course is to provide students with some the mathematical and practical tools to set up, analyze and simulate discrete time dynamic optimization problems. 

Required and Corequired knowledge and skills

In addition to the list of courses, some programming experience in either Matlab, Python or Julia would be useful.

Lectures, group work, For some parts of the course podcasts are available.
The relevant learning objectives for this course are:

• LO 1.3: Identify and analyse an issue using the relevant analytical tools and methods.
• LO 2.1: Adopt a scientific approach to data collection, research and analysis and communicate results with clear, structured, and sophisticated arguments.
• LO 3.1: Apply quantitative and qualitative techniques to support data analysis using standard office and statistical software.

References, bibliography, and recommended reading

• Stokey, Lucas with Prescot, 1989, Recursive methods in economic dynamics, Harvard University Press
• Ljunqvist and Sargent, 2000, Recursive macroeconomic theory, MIT press
• Daron Acemoglu, 2009, Introduction to modern economic growth, Princeton University Press
• Ferguson and Lim, 2003, Discrete time dynamic economic models, Routledge

Course notes

• Syllabus
• Université virtuelle

Contacts

Thomas Demuynck (thomas.demuynck@ulb.be)

Campus

Solbosch

Method(s) of evaluation

• Other

Other

Written open book exam, Group assignements (usually in the form of analysing a problem and coding)

Mark calculation method (including weighting of intermediary marks)

Written exam 80%, assignment 20%

Language(s) of evaluation

• english