# Mathematical Economics

Course ID:
ECO_450
Semester:
Year of Study:
For Erasmus Students:
No

## Learning Outcomes

By the end of this course the student will be able to:

• Use efficiently the basic mathematical methods used in economic analysis and modeling.
• Model and analyze the most common research problems of economics and their dual i.e.: maximization of the utility function of the consumer and firm’s profits.
• Model the effect of time on the research problems in economics.
• Understand the connection between mathematical modeling and econometric modeling.

## Course Contents

(A) Introduction: Minima / maxima of functions, total differentials, quadratic forms, the Hessian matrix, the envelope theorem, comparative static analysis.

(B1) Classical programming: optimization subject to equality constraints. The Lagrange method: economic interpretation and comparative static analysis. Applications in economics: utility maximization, expenditure minimization, cost minimization.

(B2) Nonlinear programming: optimization subject to inequality constraints. Kuhn-Tucker (K-T) conditions. The K-T conditions as necessary and sufficient conditions. Applications in Economics: “corner” solutions in the utility maximization problem, generalized conditions for cost minimization and profit maximization.

(C) Dynamic Programming: differential equations, difference equations, the Phase-Diagram technique. Local stability analysis. Introduction to Dynamic Programming.

## Teaching Activities

Lectures (3 hours per week)

## Teaching Organization

 Activity Semester workload Lectures, 3 hours per week (3x13) 39 hours Study at home 111 hours Total number of hours for the Course (25 hours of work-load per ECTS credit) 150 hours (total student work-load)

## Assessment

Written examination at the end of the semester (100%)

## Use of ICT

Use of ICTs in teaching (PowerPoint) and communication with students (e-class).

### Course Info

Teaching Hours:
3 hours per week
ECTS Credits:
6.00
Teaching Credits:
3.00
Weight:
1.50
Language:
Teaching Method:
Indicative Prerequisites:

Instructor:

Teaching Fellow
E-mail: