Mathematical Economics

Mathematical Economics

Course ID:

ECO_450

Semester: 8th

Year of Study:

For Erasmus Students: Όχι

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

(3×13) 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).

Teaching Hours: 3

ECTS Credits: 6

Teaching Credits: 3

Weight: 1.5

Type:

Language: Ελληνική

Teaching Method: Πρόσωπο με πρόσωπο

General Competences: Λήψη αποφάσεων, Εργασία σε διεπιστημονικό περιβάλλον, Παράγωγή νέων ερευνητικών ιδεών, Προαγωγή της ελεύθερης, δημιουργικής και επαγωγικής σκέψης

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