The first year of the study cycle comprises of two compulsory curricular units, complemented by four optional curricular units.

**Research Methodologies**

After attending the seminar, the students are expected to:

- dominate the process of scientific research;

- learn the fundamental steps for building a PhD. thesis;

- dominate the process of preparing the project of a PhD. thesis

**Complements on Statistics**

After attending the curricular unit, students are expected to:

- understand the fundamental concepts in the Biplot Methods;

- distinguish the appropriateness of the applicability of each of the methods taught;

- use the software MultBiplot;

- analyse and interpret the outputs of the program MultBiplot;

- estimate and validate structural equation models with latent variables, specified as covariance based models or as PLS (Partial Least Squares) models;

- use specific software to estimate structural equation models with latent variables;

- understand the fundamental concepts and techniques in categorical analysis;

- understand the concept of optimal scale;

- realize the importance of conjoint analysis;

- recognize the importance of the different methods to analyse real data problems.

- understand the main concepts of the three-way methods for data analysis;

- recognize the importance of these methods to analyse real data problems;

- understand the STATIS procedure;

- recognize the limitations of the Linear Probabilistic Model, as well as the advantage of using the Logit Model or the Probit Model instead;

- recognize the differences and the similarities between the two models;;

- understand the advantage of using dummy variables in the logistic regression;

- estimate the logistic regression, either using disaggregated data, or aggregated data;

- conduct hypotheses tests in this framework and to interpret the results;

- specify Data Envelopment Analysis models and critically analyse their results.

**Complements on Econometrics**

After attending the curricular unit, students who passed the final exam are expected to:

- become familiar with the main features of econometrics;

- demonstrate understanding of econometric representation of economic ideas and analysis;

- select and apply appropriate techniques to solve specific research questions;

- understand the peculiarity of duration data as a basis for survival analysis and the problems attached to it;

- understand the relevant concepts of survival analysis and show ability to apply them to suitable data;

- know how to apply survival analysis to solve practical problems for which its use is appropriate.

- gain insight on estimation and testing on both time series and panel data models, either on theoretical grounds and on applications of econometric techniques designed to examine problems often encountered in economic and financial series.

**Complements on Mathematical Economics**

After attending the curricular unit, students are expected to:

- analyze the essential aspects underlying the theory of security markets in discrete time;

- understand and use mathematical techniques and models applied in financial derivatives analysis;

- master the basic concepts of game theory;

- understand the potential of game theory to describe and predict the behavior of decision makers under interaction;

- use game theory to model situations of strategic interaction.

**Complements on Operational Research**

After attending the seminar, the students are expected to:

- to carry out efficiency and productivity analyses using more complex models than the basic Data Envelopment Analysis model;

- to use the software Efficiency Measurement System to carry out those analyses;

- to use de Malmquist índice to perform productivity analyses;

- to use multicriteria methodologies in the context of decision analysis.

**Thesis Project**

After attending the curricular unit, students are expected to:

- deepen competences required to perform advanced research;

- know the main bibliographic sources and the search engines available in the internet ;

- have developed special skills such as analytical capacity required to enroll in a PhD program.