COMPUTATIONAL ECONOMICS

Single discipline educational activity

Course Sheet

Course code:

ECCO22

Academic Year of enrolment:

2023

Year of supply:

2023/2024

Type of Course:

Characterising

Degree:

Course of 2nd Cycle Degree in ECONOMICS AND FINANCE OF FIRM AND ECOSYSTEMS

Disciplinary Sector:

Political Economy

Language:

Italian

Location:

PESCARA

Credits:

Programme Year:

Professor and Collaborators:

GIULIONI Gianfranco

Cycle:

First semester

Hours of classroom activity:

Individual study hours:

153

Prerequisites:

It is desirable that the student has a preliminary knowledge of microeconomics and macroeconomics.

Objectives

EDUCATIONAL OBJECTIVES

The course aims to improve students' knowledge of both macro and microeconomic static and dynamic economic models. The difficulties of analytical solution will be illustrated, subsequently addressing the possibilities of their numerical solution. The numerical methods required will be presented during the course ishowing how to efficiently solve the analyzed economic models and providing the necessary knowledge to tackle other problems with similar mathematical needs.
The ultimate goal is to enable students to independently undertake the analysis of complex economic models and/or to develop new research.
A further educational objective of the course concerns the acquisition and consolidation of the ability to use one of the scientific computing software reviewed during the course.
The course teachings constitute an important step in achieving the main objective of the entire course of study: to train experts in economic sciences who are fully aware of the functioning of economic and financial systems and are able to identify, plan and manage suitable strategies for dealing with rapidly changing and increasingly complex contexts.

EXPECTED LEARNING RESULTS

Knowledge

At the end of the course the student will have to know and understand the aspects related to micro and macroeconomic modeling both from a static and dynamic point of view.
In the static field, the models of market supply and demand, the simultaneous equilibrium model on the goods and money market, the aggregate supply and demand model and portfolio optimization will be addressed. In the dynamic field, the cobweb models, of dynamic duopoly, of aggregate demand and Phillips curve, of hexagonal and endogenous growth and those of diffusion of technological knowledge will be analyzed.
The student will also have to know the main techniques of scientific calculus that allow the numerical solution of the previously mentioned economic models: direct and iterative methods for the solution of systems of linear and non-linear equations, constrained maximization, the solution of systems of equations to differences and differential ones,

Ability to apply knowledge

The acquired knowledge can be applied in the solution of real problems through the ability to develop algorithms that allow to arrive at a solution of the problems posed. students must be able to implement these algorithms using one of the scientific calculation software illustrated during the course.

Autonomy of judgment

At the end of the course the student will have to be able to decide independently which is the most suitable tool to use for the solution of complex problems that will be faced.

Communication skills

At the end of the course the student must be able to use an appropriate language in the field of computational economics.

Ability to learn

At the end of the course the student must be able to autonomously learn advanced notions in specialized topics related to computational economics and scientific calculation.

Contents

The course aims to provide students with skills for using the computational approach in economic analysis by merging economics with the numerical techniques necessary for the solution of economic problems.
Economic models both of a microeconomic and macroeconomic nature and of a static and dynamic nature of increasing complexity will be presented. For each model the difficulties of solution through analytical techniques will be presente and the numerical techniques most suited to the solution will be gradually introduced. Students will be accompanied in the implementation of these techniques by experimenting with the main scientific computing software.

Extended Syllabus

I Static economic models

1 Supply and demand
2 IS-LM in a closed economy
3 IS-LM in an open economy
4 AD-AS
5 Portfolio

II Dynamic economic models

6 Supply and demand dynamics
7 Duopoly
8 SP-DG
9 Solow
10 Skill-biased technological change
11 Technological-knowledge diffusion
12 Ramsey-Cass-Koopmans

Recommended Bibliography

The teaching material will be made available by the teacher during the course.

The student will also be able to deepen the topics of the course by consulting the following references:
- Quaternoni, Saleri, Gervasio (2017) Scientific calculation, springer.
- Afosco, Vasconcelos (2016) Computational economics, a concise introduction, Routledge.

Methods of Provision

Conventional

Teaching Methods

The teaching activity will be provided through meetings lasting two hours for a total amount of 72 hours. The meetings will mainly consist of lectures by the teacher, discussions of individual or group work assigned by the teacher or laboratory experiences aimed at achieving the training objectives of the course.
If the legal-health framework and the University provisions provide for it, the teaching activities and the related receptions / exams can be carried out electronically (totally or partially). For any further information and updates, please refer to the University portal.

Evaluation methods

Verification of learning:

Students will be assessed with a written exam consisting of five open questions with predefined answer spaces and five multiple choice questions with only one correct alternative. The duration of the written test is one hour. The topics examined will reflect those covered during the teaching and present in the program. In addition to verifying the knowledge acquired, the property of language and the acquisition of communication skills will be evaluated. Each open question will be assigned one of the following qualitative judgments: no answer, insufficient, sufficient, fair, good, excellent and excellent. Each multiple choice question will be assigned one of the following attributes: no answer, wrong answer, correct answer.

The final evaluation will take into account the material produced by the students as a result of problems assigned by the teacher individually or in groups.
The solutions of the assigned problems must be accompanied by a short text in which the student illustrates the reasons for the choices made.
In the case of group work, students must indicate the contribution made by the individual member of the group.
The additional material presented by the students will be evaluated with the aim of establishing the ability to apply knowledge, independent judgment, communication skills and learning skills. The teacher will attribute to the material presented a judgment among the following: insufficient, sufficient, fair, good, excellent and excellent.

The teacher will formulate an overall assessment of the student's activity by taking into account the results of the written test and the material presented by formulating a final grade expressed out of thirty using the following conversion grid:

fail --> failure to pass the exam
pass --> from 18 to 20
fair --> from 21 to 24
good --> from 25 to 27
very good --> from 28 to 30
excellent --> 30 with honors

Contacts/More Information

For information and educational material
http://erre.unich.it/giulioni
The teacher carries out learning support activities both by receiving on-site and by teleconference by appointment.

Università degli Studi
"G. d'Annunzio"

Chieti - Pescara

Aree