Learning Results
1. To transmit sensibility to statistical modeling of economic and social phenomena.
2. To study some quantitative forecasting methods applied to Management Sciences, its problems and
solutions.
3. To apply the learned methods to the analysis of economics data
4. To gain familiarity with econometric software (EViews)
5. To develop the capacity of oral and written communication within the scope of econometric analysis
Program
1. Simple Linear Regression Model and Multiple Linear Regression Model. Estimation of the parameters – the
method of Ordinary Least Squares. Classical hypothesis. Properties of the OLS estimator: the Gauss-Markov
Theorem.
2. Linear models and nonlinear models. Interpretation of the parameters.
3. Inference in Regression analysis: hypothesis testing and prediction.
4. Multiple Regression analysis with qualitative information: dummy variables.
5. Violation of the classical hypothesis.
6.Time Series models.
Curricular Unit Teachers
Internship(s)
NAO
Bibliography
(1) Wooldridge, J.M. (2000), “Introductory Econometrics: A Modern Approach”, South Western Publishers.
(2) Gujarati, D. (2003), “Basic Econometrics”, 4th ed., McGraw-Hill International Editions.
(3) Pindyck, R. S. and Rubinfeld, D. L. (1998), “Econometric Models and Economic Forecasts”, McGraw-Hill
International Editions.
(4) Murteira, B., Ribeiro, C.S., Silva, J.A. e Pimenta, C. (2007), “Introdução à Estatística”, 2.ª ed., McGraw-Hill de
Portugal.
(5) Sincich, T. (1996). “Business Statistics by Example”, 5th ed., Prentice-Hall International Editions.