Econometrics
Objectives
This course unit seeks to introduce statistical methods to estimate and test economic models. In the first part of the course, theory and application of multiple regression techniques are addressed with emphasis on the problems arising in the analysis of cross section data and in the second part emphasis is given to the modeling of time series data. By the end of the course, students should be able to analyze economic problems using rigorous econometric techniques. Students will be required to use real data in exercises and to discuss and analyze the results in the classroom.
General characterization
Code
2175
Credits
7
Responsible teacher
Paulo Manuel Marques Rodrigues
Hours
Weekly - Available soon
Total - Available soon
Teaching language
English
Prerequisites
n/a
Bibliography
1. A.C. Cameron and P.K. Trivedi (2005) MICROECONOMETRICS: Methods and Applications, Cambridge University Press, New York.
2. Heij, P. de Boer, P. H. Franses, T. Kloek and H. K. van Dijk (2004) Econometric Methods with Applications in Business and Economics, Oxford University Press (main reference).
3. W. H. Green (2008) Econometric Analysis (6th edition), Prentice Hall
4. J.H. Stock and M.W. Watson (2010) Introduction to Econometrics (3rd Ed.) AddisonWesley Series in Economics
5. M. Verbeek (2004) A Guide to Modern Econometrics (2nd edition), Wiley.
6. J.M. Wooldridge (2006), Introductory Econometrics (3rd edition), South-Western College Publishing
Teaching method
While lectures cover the core materials, it is important that students supplement classroom time with pre-class preparation, through independent
study. Background reading is expected.
Evaluation method
Continuous assessment elements and their weights: Students will have the following assessments: intermediate exam (30%), assignments (30%) and a final exam (40% - minimum grade required of 7).
The teaching methodologies adopted are intended to stimulate the students' ability to go from theory to practice, through the apprehension of concepts, tools and methodologies which are explained in the course. Thus, they contribute to the process of individual and group learning and develop critical analysis.
Subject matter
The proposed lecture programme consists of four separate topics: Review of Linear Regression Models Endogeneity, Instrumental Variables and GMM Econometric Analysis of Time Series Data Panel Data Methods