quantitative economics

Core Courses

This specialty aims to provide theoretical and practical knowledge combining economics with quantitative tools such as mathematics, statistics and programming.

The program emphasizes the scientific analysis of economic phenomena by using quantitative models and statistical methods, allowing the student to understand economic behaviour, formulate previsions by analysing data. This speciality permits students to work in public and private institutions, research centres, think tanks …

Students with in this program will benefit from a solid formation in mathematics and statistics along with acquisition of skills in econometrics and data science. In addition, an analytical approach to economic policies is the final aim.

This specialization prepares students toward scientific research and PhD programs in the economic fields.

Semester Five

1. Teaching Unit: Fundamental

• Econometrics 1
• Time Series Analysis 1
• Operations Research 1
• Data Analysis 1

Semester Six

1. Teaching Unit: Fundamental

• Econometrics 2
• Time Series Analysis 2
• Operations Research 2

Advanced Topics

Semester Five

1. Teaching Unit: Fundamental

1) Econometrics 1: Provides students with skills in simple and multiple linear modelling, as well as an introduction to the main estimation methods.

• Simple linear regression, ordinary least squares, and maximum plausibility methods.
• Multiple linear regression, ordinary least squares, and maximum plausibility methods.
• Extension of the multiple linear regression model.
• Partial correlation, multicollinearity, and methods for selecting explanatory variables

2) Time Series Analysis 1:The main understandings and use of statistical methods for forecasting various economic phenomena.

• General information about time series and estimating their components
• Stationarity, autocorrelation and partial correlation
• Exponential smoothing models for forecasting time series

3) Operations Research 1:Contribution to the development of mathematical models that reflect a component of the problems to be solved. In addition to the exposure of the model through a set of economic relationships while providing opportunities for alternative solutions for decision-making operation.

• Network analysis models
• Game theory
• Markov chains
• Dynamic programming

4) Data Analysis 1:Learning multidimensional statistical analysis tools to understand the characteristics of economic phenomena, their interactions and interdependencies.

·     Matrix Operations

·       Eigenvalues ​​and Linear Applications

·       Statistical Inference

·       Multiple Linear Regression and Canonical Correlation

·       Global Analysis

·       Analysis by Principal Components (ACP)

 

Semester Six

Teaching Unit: Fundamental

1) Econometrics 2:Diagnostic skills for various econometric estimation problems, their solutions to obtain an acceptable analysis and forecasting model, alongside with the employment of modelling using simultaneous equations.

·      Autocorrelation Problem

·        Heteroscedasticity Problem

·       Normality Problem

·       Model Miss Specification

·       Measurement Errors

·       Data Problems

·       Simultaneous Equations

·       Seemingly Unrelated Regression Equations (SURE)

·       Modeling Methodology

·       Computer Applications

2) Time Series Analysis 2:Knowledge of random time series, understanding of autoregressive and moving average models and therefore ARMA mixed models. In addition, models that study seasonality, forecasting with the Box-Jenkins method, AFRIMA and ARCH methods are used.

• Random time series models

Long memory models

• Nonstationary random processes and unit root tests

• Box-Jenkins methodology for short-term forecasting

·       

3) Operations Research 2:The rapprochement between the problem posed and reality through mathematical equations, which reflect the composition of the problem. In this context, an exposition of the evaluation model is elaborated by using mathematical equations. This allows alternative solutions to be provided for decision-making that explain the components of the problem and the influencing factors.

• Waiting Lines

..Inventory Management Models

• Simulation

4) Data analysis 2:This module allows students to complete the study of multidimensional statistical analysis tools to know the characteristics of economic phenomena.

• Factor analysis with ajustment (AFC)
• Multiple factor analysis with ajustment (MFA)
• Cluster analysis (CA)
• Discriminant analysis (AFD)
• Qualitative discriminant analysis (CART)
• Logistic analysis (LA)