The aggravation of C19-restrictions -- compared to semester start -- meanwhile has taken place. Therefore, the seminar is switched to pure distance learning (= no attendance on campus, all lecturing via MS-Teams video stream, also exams are online).

Brush-up of basic econometrics:
multivariate least squares regression, inference and asymptotics

IV and 2SLS, GMM

Estimation with panel data

Limited Dependent Variables

The goal of this course is to convey a solid understanding of econometric concepts and assumptions. Students will learn to make sense of the results of various tests and regression analysis methods. At the end of the semester, students will understand state-of-the-art econometric research methods and be able to assess their appropriateness in the context of current research papers.

Due to recent and foreseeable C19 development (as of Nov 18), there will be no lecturing in class rooms. Instead, the lecture will be streamed via MS-Teams (link will be provided soon). Likewise, exams will be held online.

Lecturing, assignments (home work), exams.  Course subject is mainly chapters 4-7 of Marno Verbeek's textbook, with some deepening based on other textbooks. Lectures will focus on implementation of concepts in programming language R, rather than presenting concepts in formally rigorous manner. Likewise, assignments will focus on such implementation. Exams, instead, will focus on interpretation of output of relevant statistical programs.

Assignments (homework):  40 points (5 x 8 points)

Exams: 60 points (2 x 30 points)

Exams in units 5 and 11 (planned: Dec 17 and Jan 21).

Substitute date for one of the above exams (chosen freely): unit 12 (planned: Jan 26)

Verbeek, chapters 1-3  and appendices A and B (or equivalent):

basic statistics, regression modelling, least squares (LS) estimation,
interpretation of LS estimators,  testing of restrictions,
finite sample vs. asymptotic properties of LS estimators

individual appointment