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Numerical Methods for Economics

Code: 2ECON04     Acronym: MN

Keywords
Classification Keyword
CNAEF Mathematics

Instance: 2020/2021 - 1S Ícone do Moodle

Active? Yes
Responsible unit: Agrupamento Científico de Matemática e Sistemas de Informação
Course/CS Responsible: Master in Economics

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
ME 35 Bologna Syllabus 1 - 7,5 56 202,5
Mais informaçõesLast updated on 2020-05-02.

Fields changed: Lingua de trabalho

Teaching language

Portuguese and english

Objectives

This course deals with numerical methods for the solution of economic problems using a computer.

Emphasis will be on intuition and applicability conditions of methods and not on their deductibility and computer implementation.

The objectives of the course are:

  •  to provide students with the numerical and computational techniques necessary for the implementation and resolution of economic problems in a computer;
  •  to provide students with the tools required to run economical and financial simulations;
  •  for students to acquire awareness of the potential of this approach to solve large dimensional problems (or problems without a closed solution) as well as to point out the limitations of finite precision arithmetic.

Learning outcomes and competences


  • Solve economic models by using computational numerical methods.

  • Analyse economic models to identify the mathematical building blocks behind the model.

  • Test for the most adequate numerical methods to tackle the mathematical building blocks from the economic models.

  • Build algorithms to solve economic models.

  • Adapt existing computer codes to solve new problems.

  • Test computationally and discuss shock effects on the economic problems.

  • Develop critical capacities in the analysis of data and simulations results.

  • Summarize the advantages and limitations of finite precision arithmetic.

Working method

B-learning

Program


  1. Introduction to MATLAB /OCTAVE.

  2. Data analysis: economic data, finantial markets.

  3. Finite precision arithmetic.

  4. Linear Systems of equations: supply-demand models, IS-LM model, Mundell-Fleming model.

  5. Systems of nonlinear equations: AS-AD model.

  6. Eigenvalues and eigenvectors: dynamic IS-LM and AS-AD, duopoly, stability of dynamic systems.

  7. Interpolation and least squares: compound interest rate.

  8. Optimization: portfolio optimization.

  9. Difference and differential equations: discrete dynamics of supply and demand models, with and without rational expectations, Solow and Ramsey-Cass-Koopmans models.

  10. Stochastic simulation, Cramér–Lundberg (risk analysis).

Mandatory literature

Afonso, Óscar João Atanázio; Computational economics. ISBN: 978-1-138-85966-1
Moler, Cleve B.; Numerical computing with MATLAB. ISBN: 0-89871-560-1

Complementary Bibliography

Hendrick, David A.; Computational economics. ISBN: 0-691-12549-X
Judd, Kenneth L; Numerical methods in economics. ISBN: 0-262-10071-1

Teaching methods and learning activities

The course is organized in lab sessions, based on modules. The teaching methodology in each module is structured as follows:

  • description of the problem to solve;
  • identification with explanation of the appropriate numerical methods for their resolution;
  • examples of application in economics;
  • exercises and simulation (sedimentation and knowledge exploitation).

Software

Jupyter
OCTAVE
MATLAB

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation Weight (%)
Teste 30,00
Trabalho laboratorial 70,00
Total: 100,00

Amount of time allocated to each course unit

Designation Time (hours)
Estudo autónomo 72,00
Frequência das aulas 30,00
Trabalho laboratorial 12,00
Apresentação/discussão de um trabalho científico 6,00
Elaboração de relatório/dissertação/tese 40,50
Trabalho escrito 42,00
Total: 202,50

Eligibility for exams

Evaluation will be based on the achievement of:

  1. 2 projects held during the semester;
  2. 2 short assessments.

Calculation formula of final grade

35% P1 + 35% P2 + 15% SA1 + 15% SA2 where: P - Project and SA - Short-Assessment.

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