Number of ECTS:
1 - know and understand the fundamental concepts of econometrics.
2 - have the capacity to read, interpret and asses elementary econometric results.
3 - understand and apply the methods and techniques of linear regression analysis in the perspectives of estimation and inference.
4 - have the capacity to incorporate principles of economic theory in mathematical and statistical models.
5 - be familiar with computer programs used to produce econometric analyses.
6 - be able to recognize the limitations imposed by econometric models.
1 - The nature of econometrics and economic data.
2 - Tools for econometrics.
2.1 - Mathematics.
2.2 - Probabilities.
2.3 - Statistical inference.
3 - The simple regression model.
4 - Multiple Regression Analysis.
4.1 - Estimation.
4.2 - Inference.
4.3 - OLS asymptotic.
4.4 - Other topics.
D.N. Gujarati , Basic Econometrics , McGrawHill
D.N. Gujarati , Essentials of Econometrics , McGrawHill
M.M. Oliveira & al , Econometria, Exercícios , McGrawHill
R. Ramanathan , Introductory Econometrics with Applications , Harcourt Brace Jovanovich
Hill, C., William Griffiths and George Judge , Undergraduate Econometrics , John Wiley & Sons
Assesssment methods and criteria:
Classification Type: Quantitativa (0-20)
Is organized in lectures and tutorials. In the lectures, the teacher presents the fundamental concepts, the discipline methods and techniques using, when possible, examples and applications. In the tutorials, the students work with the econometric package STATA to solve exercises, allowing them to familiarize with the treatment, filtering and use of real databases and the estimation and interpretation of results. Method of evaluation: (i) 2 frequencies with a weight of 70% for the final grade and (ii) 1 practical work carried out during the semester, with a weight of 30% for the final grade. In the practical work, the students analyze an economic question proposed by the teacher, using the econometric package STATA. The teacher gives the database. The purpose is to evaluate the students skills on program use, writing the report and also their understanding and interpretation of the results. Reassessment period: final exame (100%) or recovery of the practical work weighting 50%