• Main objectives:

This course reviews/introduces some important mathematical concepts and techniques commonly used in economic analysis and the core graduate theory courses. The main purpose is to brush up your math background so that you can focus on the economic intuition in your next classes.

The course will be taught on an intensive everyday basis in a two-week period from August 31st to September 11th. There will be both lectures emphasizing the theory and tutorials emphasizing problem solving.

Topics to be covered include:

Part 1. Notation, logic, methods of proof, basic set theory.
Part 2. Elements of analysis
Part 3. Linear algebra and matrices
Part 4. Unconstrained and constrained single and multiple variable optimization
Part 5. Probability theory and basic statistics
Part 6. Introduction to dynamic programming

• Grading: Pass or Fail

• Additional resources:
  The books listed below cover the majority of the material and could be used as a reference. Since the course will proceed rapidly, and a lot of its contents will hopefully be material you have covered before, you are encouraged to review what you can before the course begins.  
  • Hoy, Livernois, McKenna, Rees & Stengos, Mathematics for Economics – 2^nd Edition, MIT Press, 2001. ISBN: 0 262 08294-2 
  • Angel de la Fuente, Mathematical Methods and Models for Economists.  Cambridge University Press. 2000. ISBN 978-0521585293
  • Teresa Bradley, Essential Mathematics for Economics and Business 4^th edition, Wiley, 2013. 
  • Corbae, Stinchcombe and Zeman. An Introduction to Mathematical Analysis for Economic Theory and Econometrics.  Princeton University Press, 2009.  ISBN 978-0-691-11867-3.
    

• Daily study plan:

• Day 1 (08/31): Part 1 - Logic, proof and set theory
  
• Day 2 (09/01): Part 2 - Elements of analysis
• Day 3 (09/02): Part 3 [1/2] - Linear algebra and matrices, 1) and 2)
  
• Day 4 (09/03): Part 3 [2/2] - Linear algebra and matrices, 3) to 5)
  
• Day 5 (09/04): Part 4 - Optimization
• Day 6 (09/08): Part 5 - Probability theory and basic statistics
• Day 7 (09/09): Part 6 - Introduction to dynamic programming

• Practice exercises:
• Part 1
• Part 2
• Part 3
• Part 4
•