First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Economics and Political Science
ECONOMICS AND FINANCE
Course unit
MATHEMATICS FOR ECONOMICS
EPP6077338, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2018/19

Information on the course unit
Degree course Second cycle degree in
ECONOMICS AND FINANCE
EP2422, Degree course structure A.Y. 2017/18, A.Y. 2018/19
N0
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Degree course track ECONOMICS [002PD]
Number of ECTS credits allocated 9.0
Type of assessment Mark
Course unit English denomination MATHEMATICS FOR ECONOMICS
Website of the academic structure http://www.economia.unipd.it
Department of reference Department of Economics and Management
E-Learning website https://elearning.unipd.it/economia/course/view.php?idnumber=2018-EP2422-002PD-2018-EPP6077338-N0
Mandatory attendance No
Language of instruction English
Branch PADOVA
Single Course unit The Course unit CANNOT be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge ALESSANDRA BURATTO SECS-S/06

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses SECS-S/06 Mathematics for Economics, Actuarial Studies and Finance 9.0

Course unit organization
Period First semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Lecture 9.0 63 162.0 No turn

Calendar
Start of activities 01/10/2018
End of activities 18/01/2019

Syllabus
Prerequisites: Basic calculus, Differential calculus, Integrals, Basic Linear Algebra
Target skills and knowledge: The objective of this course is to equip students with the basic mathematical techniques required for a rigorous study of Economics. Students are expected to acquire knowledge and understanding of advanced mathematical tools in order to use them with autonomy in Economics and Finance issues.
Examination methods: Exercises and problems related to the arguments just presented in class will be assigned through Moodle each week. Homework contribution to the final evaluation up to 3 points.
A final written test with exercises (max evaluation 28/30).
Assessment criteria: The evaluation will be based on the knowledge of the topics covered during the lessons. In addition to a good learning ability, it is expected the ability to apply the acquired knowledge in an autonomous and competent way.
Course unit contents: - Calculus of a Single Variable: differentiation and optimization of real-valued functions of a single variable, (a brief review)
- Vector Algebra: matrices and linear systems (review), eigenvalues and eigenvectors
- Multivariable Calculus: Differentiation of Real-Valued Functions of several variables, Concave and Quasiconcave functions. Implicit function theorem.
- Optimization (unconstrained and constrained): Equality constraints: Lagrange Method (review), Inequality constraints: Kuhn-Tucker conditions, Envelope theorem, Comparative statics
- Fixed Point Theorems and Applications: Brouwer’s and Kakutani’s theorems, Implicit function theorem
- Differential Equations: ODE systems, dynamic systems
- Optimal control: Pontryagin's Maximum Principle
- Dynamic Programming: Hamilton Jacobi Bellman equation
Planned learning activities and teaching methods: All the slides presented during the classes will be uploaded in Moodle together with the related audio records.
All "Mathematica" files created for the course will be uploaded in Moodle.
The homework assigned in Moodle will be evaluated and commented in class focussing on tricky concepts.
Additional notes about suggested reading: The lecture notes in pdf, the audio recording of the lessons (mp3 files) and other teaching material, together with specific communications from the lecturer can be found, inside the Moodle platform.
Textbooks (and optional supplementary readings)
  • Simon, Carl P. and Lawrence Blume, Mathematics for Economists - International student edition. New York - London: Norton, 2010.
  • Morton I. Kamien and Nancy L. Schwartz, Dynamic Optimization. Mineola New York: Dover Publications, Inc, 2012. 2nd. Ed Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Interactive lecturing
  • Working in group
  • Problem solving
  • Flipped classroom
  • Loading of files and pages (web pages, Moodle, ...)
  • Students peer review
  • recordered audios of lessons

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)
  • One Note (digital ink)
  • Latex
  • Mathematica

Sustainable Development Goals (SDGs)
Quality Education Gender Equality Affordable and Clean Energy Climate Action