The Econometrics course will be organized in three blocks. The first block (24 hours) will present an advanced treatment of econometric theory and principles of estimation and inference in linear regression models, focusing also on maximum likelihood estimation, generalized methods of moments, and heteroskedasticity. In the second block (17 hours), students will study the estimation of nonlinear regression models, notably limited dependent variable models. The third block (21 hours) will present models for time series data. Further 25 hours of computer tutorials will be aimed at developing analytical skills using Gretl (http://gretl.sourceforge.net ).
Students should have knowledge, at least at undergraduate level, of the following topics:
These topics are in chapters 1 to 9 and 15 of “Introductory Econometrics: A Modern Approach” (Wooldridge, 7th edition, 2015). Alternatively, they can be found in chapters 1-9 and 12 of “Introduction to Econometrics” (Stock and Watson, 3rd edition, 2015). These textbooks are for undergraduate economics students who have taken a course of introductory probability and statistics.
At the end of the course, students will be assigned a take-home exam on the second and the third blocks (60% of the final grade) with deadline on 6 January 2020 and there will be an open-book written exam on the first block (40% of the final grade) on Tuesday 14 January 2020. On Thursday 16 January, students will be asked to orally explain what they did in the take home exam and why.
Students that will not pass the exam will resit it later in the year: the resit will be an open-book written exams on all the blocks.
A detailed list of chapters of these textbooks will be provided during the course.
Software for computer tutorials: