Macroeconometrics
Code
2168
Academic unit
null
Department
null
Credits
7
Teacher in charge
Luís Miguel Rainho Catela Nunes
Teaching language
English
Objectives
In this course, students will learn the most important concepts, models, and techniques used in the empirical econometric analysis of macroeconomic data. The focus of the course will be on dynamic models using econometric time series methods. During the course, students will also learn how to use specialized econometric software tools.
Prerequisites
N/A
Subject matter
The following topics will be covered during this course.
1. Basic concepts in time-series analysis:
-difference equations, stationarity and ARMA models, forecasting.
2. Models for unobserved components:
-state space models, the Kalman filter, structural time series models.
3. Modeling trends and cycles:
-HP and band-pass filters, unit-roots and cointegration, spectral analysis.
4. Structural VAR models:
-short run and long run restrictions, alternative identification methods.
5. Modeling volatility and correlation:
-univariate and multivariate ARCH-type models, contagion.
6. Structural changes and regime switching.
7. Non-linear models.
Bibliography
The main textbook used in this course is:
-Enders, W. (2009), Applied Econometric Time Series, 3rd ed., John Wiley & Sons, Inc. rovisional. Subject to changes.
An optional more advanced book is:
-Hamilton, J.D. (1994), Time Series Analysis, Princeton University Press. Additional readings from other books, articles, and reports will be announced during the course.
Teaching method
Students should attend weekly classes to understand and learn to use the main time series macroeconometric tools and the theoretical arguments used to derive the main results, and to get acquainted with the interpretation of the results for selected empirical examples. Students are expected to participate actively in the discussions of the examples covered in class. Reading of the required texts is essential since they provide detailed discussions of each topic and provide students with several additional examples illustrating the applicability of the general techniques.
Computer lab sessions will help students to use specialized econometric software tools. Group assignments are important to develop all the learning objectives.
Evaluation method
The final course grade is based on a midterm exam (20%), a final exam (40%), and several group assignments (40%). Groups should have 3 students (exceptionally 4). Grades for the assignments will specifically take into account the quality of the work done and the autonomy of the group. All important assessment dates will be posted at the course page on moodle.