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

Semester Frühjahrsemester 2020
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.

NB.

(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. They will be included in a restructured course offered by K. Schmidheiny that was formerly called Microeconometrics II.
Literatur Literature:
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.
Weblink Weblink

 

Teilnahmebedingungen Prerequisites:
Completed bachelor's degree (for students majoring in Business and Economics)
Introduction to Econometrics (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 kein spezifischer Einsatz

 

Intervall wöchentlich
Datum 18.02.2020 – 26.05.2020
Zeit Dienstag, 14.15-16.00 Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32

The lecture notes and exercises can be found in digital form on OLAT.

Datum Zeit Raum
Dienstag 18.02.2020 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 25.02.2020 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 03.03.2020 14.15-16.00 Uhr Fasnachtsferien
Dienstag 10.03.2020 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 17.03.2020 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, online
Dienstag 24.03.2020 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Lecture notes and exercises can be found in digital form on OLAT.
Dienstag 31.03.2020 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Lecture notes and exercises can be found in digital form on OLAT.
Dienstag 07.04.2020 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Lecture notes and exercises can be found in digital form on OLAT.
Dienstag 14.04.2020 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Lecture notes and exercises can be found in digital form on OLAT.
Dienstag 21.04.2020 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Lecture notes and exercises can be found in digital form on OLAT.
Dienstag 28.04.2020 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Lecture notes and exercises can be found in digital form on OLAT.
Dienstag 05.05.2020 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Lecture notes and exercises can be found in digital form on OLAT.
Dienstag 12.05.2020 14.15-16.00 Uhr Juristische Fakultät, Lecture notes and exercises can be found in digital form on OLAT.
Dienstag 19.05.2020 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Lecture notes and exercises can be found in digital form on OLAT.
Dienstag 26.05.2020 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Lecture notes and exercises can be found in digital form on OLAT.
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:
Oral exam; date and time by appointment with Prof. Kleiber.
In addition, there will be at least two assignments, for which students may work in groups of two. Each assignment will account for 10% of the final grade.

You can still withdraw from the examination by submitting a completed, signed form to our office from 17.03.20 until 27.03.20 / 12:00 o’clock. Withdrawals sent by email will not be accepted. You will find the examination withdrawal form on the Homepage of the Student Dean’s Office. Prior to 16.03.20, please only use MONA for withdrawing. The exam rooms will be published up to 20.05.20.
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

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