00092R - COMPUTATIONAL ECONOMICS AND FINANCE.

The course aims to improve students' knowledge of static and dynamic economic models, both macroeconomic and microeconomic. The difficulties of analytical solutions will be illustrated, followed by the possibility of solving them numerically. The required numerical methods will be presented during the course, illustrating how to efficiently solve the analyzed economic models and providing the knowledge necessary to tackle other problems with similar mathematical requirements. The ultimate goal is to enable students to independently undertake the analysis of complex economic models and/or develop new research. Another educational objective of the course is the acquisition and consolidation of the ability to use one of the scientific computing software programs reviewed during the course. The course's teachings are an important step towards achieving the primary objective of the entire program: to train economics experts with a full understanding of the functioning of economic and financial systems and the ability to identify, plan, and manage strategies suited to rapidly changing and increasingly complex environments.
EXPECTED LEARNING OUTCOMES: KnowledgeBy the end of the course, students will be expected to know and understand the aspects of micro- and macroeconomic modeling from both a static and dynamic perspective. Static models will include market supply and demand models, the simultaneous equilibrium model in the goods and money markets, the aggregate supply and demand model, and portfolio optimization. Dynamic models will include analysis of the cobweb, dynamic duopoly, aggregate demand and Phillips curve, endogenous and exogenous growth, and the diffusion of technological knowledge. Students will also be familiar with the main scientific computing techniques that enable the numerical solution of the previously mentioned economic models: direct and iterative methods for solving systems of linear and nonlinear equations, constrained maximization, and the solution of systems of difference and differential equations.
Ability to Apply Knowledge:
The knowledge acquired can be applied to real-world problems through the ability to develop algorithms that allow for the solution of the problems posed. Students will be able to implement these algorithms using one of the scientific computing software programs illustrated during the course. Making Judgements: At the end of the course, students should be able to independently decide which tool is most appropriate for solving complex problems.
Communication Skills:At the end of the course, students should be able to use appropriate language in the field of computational economics.
Learning Skills:At the end of the course, students should be able to independently learn advanced concepts in specialized topics related to computational economics and scientific computing.