Statistics, Economics, and Social Sciences

Learning goals. The aim of the lectures is to provide an exhaustive discussion of the main topics concerning the linear model (OLS, MLE, IV, asymptotic theory and inference) for cross-section analysis and a brief introduction to the analysis of discrete data. Students must understand the analytical problems of these methods and be able to apply them to concrete situations. Knowledge and understanding. After attending the course the students know and understand the main problems related to the linear regression model (for example: absence of exogeneity) and the main methods to be used to solve such problems (for example: IV estimator). Applying knowledge and understanding. At the end of the course the students are able to formalize real problems in terms of linear regression models and to apply the methods specific to the discipline to solve them. They are also able to apply the methods to concrete situations and to interpret the results. Making judgements. Students develop a knowledge of the analytical properties of the presented methodologies and the ability to build programs for their implementation. They also learn to critically interpret the results obtained by applying the procedures to concrete situations. Communication skills. Students acquire the technical-scientific language of the discipline, which it must be used appropriately in both the intermediate and final written tests and in the oral tests. Communication skills are also developed through group activities. Learning skills. Students who pass the exam have learned a method of analysis that allows them to tackle the study of analytical properties in more complex modeling contexts in subsequent quantitative area teachings.