Numerical Methods for Economics

Code:

2ECON04

Acronym:

MN

Keywords
Classification	Keyword
CNAEF	Mathematics

Instance: 2018/2019 - 1S

Active?	Yes
Web Page:	https://moodle.up.pt/course/view.php?id=450
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	46	Bologna Syllabus	1	-	7,5	56	202,5

Teaching language

Português/English (horários/schedules ME1 Português; ME3 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: 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.

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

R
Jupyter
OCTAVE
MATLAB
Python

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	27,00
Frequência das aulas	39,00
Trabalho laboratorial	12,00
Total:	78,00

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.