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

Semester Frühjahrsemester 2019
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.

 

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
Weblink Weblink
Einsatz digitaler Medien kein spezifischer Einsatz
HörerInnen willkommen

 

Intervall wöchentlich
Datum 19.02.2019 – 28.05.2019
Zeit Dienstag, 14.15-16.00 Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Datum Zeit Raum
Dienstag 19.02.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 26.02.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 05.03.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 12.03.2019 14.15-16.00 Uhr Fasnachtsferien
Dienstag 19.03.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 26.03.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 02.04.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 09.04.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 16.04.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 23.04.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 30.04.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 07.05.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 14.05.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31
Dienstag 21.05.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Dienstag 28.05.2019 14.15-16.00 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32
Module Modul Schadenversicherung (Masterstudium: Actuarial Science)
Modul Statistik und Computational Science (Masterstudium: Actuarial Science)
Modul: Kernbereich Wirtschaftswissenschaften (Masterstudium: Sustainable Development)
Spezialisierungsmodul: Areas of Specialization in International and/or Monetary Economics (Master International and Monetary Economics)
Vertiefungsmodul Marketing and Strategic Management (Master Wirtschaftswissenschaften)
Vertiefungsmodul Quantitative Methods (Master Wirtschaftswissenschaften)
Leistungsüberprüfung Semesterendprüfung
Hinweise zur Leistungsüberprüfung Notes for the Assessment:
Written exam (date and duration TBA). Participants may bring (1) a dictionary, (2) a calculator (subject to the usual constraints), two DIN A4 pages (not 2 x 2!) of their own, HANDWRITTEN notes.

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.

written exam: tba
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, studiendekanat-wwz@unibas.ch
Anbietende Organisationseinheit Wirtschaftswissenschaftliche Fakultät

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