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16036-01 - Vorlesung: Microeconometrics: Nonlinear Models and Statistical Learning 3 KP

Semester Frühjahrsemester 2021
Angebotsmuster Jedes Frühjahrsem.
Dozierende Christian Kleiber (christian.kleiber@unibas.ch, BeurteilerIn)
Inhalt Introductory econometrics courses mainly cover the linear regression model, which is suitable for modelling response variables that may be considered as continuous. However, there are many practical situations where data are naturally discrete, e.g. binary or count data. The course will cover the classical nonlinear regression models for such data. It will use the framework of generalized linear models (GLMs), which provides a unified approach to models such as logit, probit and Poisson regression. Inference will be likelihood based.

In addition, there will be an introduction to the recent literature on statistical learning (aka machine learning), specifically to the notion of regularisation, with LASSO as the main example. If time permits there will also be a chapter on finite mixture models.

Empirical illustrations may include data from labor economics, health economics, or marketing, among further sources. The course will make use of the R language for statistical computing and graphics, hence basic knowledge of this software (including data import, running regressions) is expected.

All course materials are on OLAT.


(1) In order to make room for further (regression) models, there will at most be a brief review of likelihood methods. Participants are expected to be familiar with these methods at the level of the compulsory MSc level Econometrics course.

(2) The course was formerly offered under the title Microeconometrics I. Many topics from that course will still be covered, however, there will be new topics from statistical learning. In order to make room for these, multinomial response models will no longer be covered. These are now included in a restructured course offered by K. Schmidheiny that was formerly called Microeconometrics II.
Literatur Main references:

Cameron AC, Trivedi PK (2005). Microeconometrics, Cambridge Univ. Press.
Fahrmeir, L, Kneib T, Lang S, Marx B (2013). Regression -- Models, Methods and Applications, Springer. [available in electronic form via the university library!]
James G, Witten D, Hastie T, Tibshirani R (2013). An Introduction to Statistical Learning. New York: Springer. [available in electronic form via the university library!]
Winkelmann R, Boes S (2009). Analysis of Microdata, 2nd ed, Springer.

Further (topic-specific) references will be indicated in the relevant contexts.
Weblink Weblink


Teilnahmebedingungen Prerequisites:
Completed bachelor's degree (for students majoring in Business and Economics).
Introduction to Econometrics [BA] (for students from other departments: regression basics).
Econometrics [MSc] (for students from other departments: a second course in statistics, notably likelihood methods).
Anmeldung zur Lehrveranstaltung Registration: Please enrol in MOnA. EUCOR-Students and students of other Swiss Universities have to enrol at the students administration office (studseksupport1@unibas.ch) within the official enrolment period. Enrolment = Registration for the exam!
Unterrichtssprache Englisch
Einsatz digitaler Medien Online-Angebot obligatorisch


Intervall wöchentlich
Datum 03.03.2021 – 02.06.2021
Zeit Mittwoch, 10.15-12.00 - Online Präsenz -

The course will be taught digitally with some Q&A-Sessions in the timeslots you can see below:

Datum Zeit Raum
Mittwoch 03.03.2021 10.15-12.00 Uhr --, --
Mittwoch 10.03.2021 10.15-12.00 Uhr --, --
Mittwoch 17.03.2021 10.15-12.00 Uhr --, --
Mittwoch 24.03.2021 10.15-12.00 Uhr --, --
Mittwoch 31.03.2021 10.15-12.00 Uhr --, --
Mittwoch 07.04.2021 10.15-12.00 Uhr --, --
Mittwoch 14.04.2021 10.15-12.00 Uhr --, --
Mittwoch 21.04.2021 10.15-12.00 Uhr --, --
Mittwoch 28.04.2021 10.15-12.00 Uhr --, --
Mittwoch 05.05.2021 10.15-12.00 Uhr --, --
Mittwoch 12.05.2021 10.15-12.00 Uhr --, --
Mittwoch 19.05.2021 10.15-12.00 Uhr --, --
Mittwoch 26.05.2021 10.15-12.00 Uhr --, --
Mittwoch 02.06.2021 10.15-12.00 Uhr --, --
Module Modul: Kernbereich Wirtschaftswissenschaften (Masterstudium: Sustainable Development)
Modul: Schadenversicherung (Masterstudium: Actuarial Science)
Modul: Statistik und Computational Science (Masterstudium: Actuarial Science)
Spezialisierungsmodul: Areas of Specialization in International and/or Monetary Economics (Masterstudium: International and Monetary Economics)
Vertiefungsmodul: Marketing and Strategic Management (Masterstudium: Wirtschaftswissenschaften)
Vertiefungsmodul: Quantitative Methods (Masterstudium: Wirtschaftswissenschaften)
Leistungsüberprüfung Semesterendprüfung
Hinweise zur Leistungsüberprüfung Notes for the Assessment:
Written exam; date and time TBA.
In addition, there will be at least two assignments, for which students may work in groups of two. Overall, the assignments will account for 20% of the final grade.

An-/Abmeldung zur Leistungsüberprüfung Belegen via MOnA innerhalb der Belegfrist
Wiederholungsprüfung keine Wiederholungsprüfung
Skala 1-6 0,1
Wiederholtes Belegen beliebig wiederholbar
Zuständige Fakultät Wirtschaftswissenschaftliche Fakultät / WWZ, studiendekanat-wwz@unibas.ch
Anbietende Organisationseinheit Wirtschaftswissenschaftliche Fakultät / WWZ