Mathematics for Economists
Academic year 2018 – 2019
For Mathematics for Economists in academic year 2018 – 2019 click here.
Lecturer
The lecturer is Claire Naiditch from USTL Lille in Lille (FR).
Contact
Bât. SH2, Cité scientifique
59655 Villeneuve d’Ascq Cedex
France
claire.naiditch@univ-lille.fr
Pre-requisites
Students are supposed to have knowledge on standard Mathematics:
- Analysis of functions
- Derivation and integration
- Matrix calculus
Lecture topics
Please read under Course contents.
Course contents
Concavity and Convexity
- Concave and convex functions of a single variable
- Quadratic forms
- Quadratic forms: definitions
- Quadratic forms: conditions for definiteness
- Quadratic forms: conditions for semidefiniteness
- Concave and convex functions of many variables
- Quasiconcavity and quasiconvexity
Static optimization
- Optimization: introduction
- Optimization: definitions
- Existence of an optimum
Interior optima
- Necessary conditions for an interior optimum
- Local optima
- Conditions under which a stationary point is a global optimum
Optimization: Equality constraints
- Two variables, one constraint
- Optimization with an equality constraint: Necessary conditions for an optimum for a function of two variables
- Optimization with an equality constraint: Interpretation of Lagrange multipliers
- Optimization with an equality constraint: Sufficient conditions for a local optimum for a function of two variables
- Optimization with an equality constraint: Conditions under which a stationary point is a global optimum
- Optimization with equality constraints: n variables, m constraints
- The envelope theorem
Optimization: The Kuhn-Tucker conditions for problems with inequality constraints
- Optimization with inequality constraints: The Kuhn-Tucker conditions
- Optimization with inequality constraints: The necessity of the Kuhn-Tucker conditions
- Optimization with inequality constraints: The sufficiency of the Kuhn-Tucker conditions
- Optimization with inequality constraints: Nonnegativity conditions
- Optimization: Summary of conditions under which first-order conditions are necessary and sufficient
Dynamic optimization
- Calculus of variations
- Optimal control and the Maximum Principle
Core reading
- Osborne, Matin J. 2016. Mathematical methods for economic theory (https://mjo.osborne.economics.utoronto.ca/index.php/tutorial/index/1/toc/c)
- Hoy, M., Livernois, J., McKenna, C., Rees, R. and Stengos, T. 2011; Mathematics for Economics. 3rd edition. The MIT Press, Cambridge, Massachussets, USA
- M.D. Intriligator (2002), Mathematical Optimisation and Economic Theory, SIAM, ISBN 978-0-898715-11-8
Learning outcomes
Upon successful completion of the course, students should be able:
- To formulate and solve a standard static optimization problem in micro- or macroeconomics
- To formulate and solve a standard dynamic optimizing problem in micro- or macroeconomics
- To understand the main properties of matrices that are used in economic analysis
Organisation
The course consists of six lectures of two hours each. All lectures are concentrated at the beginning of the term. The lectures mainly concentrate on exercises and problems directly related to economics.
Assessment
Students are evaluated through a written examination.