040120 SE Topics in data-driven decision making (MA) (2020W)

Track in Data Analysis und Track in Behavioral Economics and Experiments and Track in Policy Evaluation

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften

Prüfungsimmanente Lehrveranstaltung

Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Anmeldung von Mo 14.09.2020 09:00 bis Mi 23.09.2020 12:00
Anmeldung von Mo 28.09.2020 09:00 bis Mi 30.09.2020 12:00
Abmeldung bis Sa 31.10.2020 12:00

Details

max. 25 Teilnehmer*innen

Sprache: Englisch

Lehrende

Alexander K. Wagner

Termine (iCal) - nächster Termin ist mit N markiert

For our meetings we use BB Collaborate (login through Moodle).

    
    Dienstag
    06.10.
    13:15 - 14:45
    Digital
    
    Dienstag
    13.10.
    13:15 - 14:45
    Digital
    
    Dienstag
    20.10.
    13:15 - 14:45
    Digital
    
    Dienstag
    27.10.
    13:15 - 14:45
    Digital
    
    Dienstag
    03.11.
    13:15 - 14:45
    Digital
    
    Dienstag
    10.11.
    13:15 - 14:45
    Digital
    
    Dienstag
    17.11.
    13:15 - 14:45
    Digital
    
    Dienstag
    24.11.
    13:15 - 14:45
    Digital
    
    Dienstag
    01.12.
    13:15 - 14:45
    Digital
    
    Dienstag
    15.12.
    13:15 - 14:45
    Digital
    
    Dienstag
    12.01.
    13:15 - 14:45
    Digital
    
    Dienstag
    19.01.
    13:15 - 14:45
    Digital
    
    Dienstag
    26.01.
    13:15 - 14:45
    Digital

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Aims, content, and methods: Digital services permeate almost every aspect of life, reshaping business transactions and social interactions alike. In this course, we investigate recent advances in data-driven approaches to decision making relevant to economics and management. The aim of this course is to introduce students to recent research trends and to learn and discuss critically how these tools can used for decision making in organizations.

The course consists of two parts. In part 1, we review theoretical concepts related to causal inference through randomized experiments as well as concepts of prediction. In part 2, we study how these concepts can be applied to a number of relevant questions in economics and management. The fields from which applications are selected include behavioral economics, game theory, organizational behavior and industrial organization.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Assessment: The assessment is based on presentations (of R exercises and research papers), and a paper ('Seminararbeit').
Note that it is imperative to participate in the first session. Students who cannot (for a good reason) participate in the first session should send me an e-mail one week before the first session.

Mindestanforderungen und Beurteilungsmaßstab

Participants should have taken an introductory course to the field of experimental economics, for example the MA course “Behavioral and Experimental Economics” (UK040832). Students with comparable backgrounds can also be admitted but need to provide evidence that their knowledge is comparable. In addition, a sound knowledge of microeconomics, microeconometrics and R (for exercises) is required. The course language is English.

Prüfungsstoff

Students solve R exercises and write a seminar paper; they also present their R exercises and and their seminar paper topic.

Exercises count 20%, the presentation counts 30% and the written work counts 50% of the grade. At total of >50% is required for a passing grade.

Literatur

handout/moodle

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Fr 12.05.2023 00:12