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    Chair of Labour Economics

    Master

    Summer Semester 2022

    Lecturer

    Dr. Judith Saurer

    Structure, content and objectives

    This course provides an overview of the field of modern labor economics. Its aim is to acquaint students with classical as well as modern topics in labor economics and to encourage the development of research interest in this field. As such, the course’s objective is to familiarize students with both the core theoretical models of labor economics as well as the main econometric methods used to provide empirical evidence.

    The course will cover the following topics:

    1. Labor supply
    2. Labor demand
    3. Human capital formation
    4. Compensating wage differentials
    5. Discrimination

    The course will consist of frontal teaching of the basic theoretical as well as empirical tools as well as a careful reading of some of the key scientific articles related to the outlined topics (a reading list will be provided at the beginning of the semester). Students are expected to read the scientific articles in advance and will be asked to discuss them in small groups. In addition, a discussion of the articles will help illustrating how established scholars approach the core questions in modern labor economics and giving students an understanding of high quality empirical research.

    At the end of the course, an introduction into empirical economic analysis will be provided (both theoretical and hands on at a PC).

    Literature

    Main reference for the lecture is Cahuc and Zylberberg. (2004): "Labor Economics", 1st edition, Massachusetts Institute of Technology. In addition, we will discuss well-published economic articles related to the single topics discussed in class (they will be made available via Wue Campus).

    Prerequisites

    Solid background in Microeconomics and Econometrics is required

    Examination

    Discussion of scientific articles in class (a list will be provided at the beginning of the semester): 25% Take home examination: 75%

    Online introductory meeting on Friday 29/04 from 10 to 11:30 am (Zoom-link will be provided on WueCampus)

    Organizational details

    Course times:

    • Friday 24/06 from 9 am to 5 pm in Hörsaal 124 (Neue Uni)
    • Saturday 25/06 from 10 am to 6 pm in Hörsaal 124 (Neue Uni)
    • Saturday 02/07 from 10 am to 6 pm in Hörsaal 124 (Neue Uni)

    Submission of the take-home exam: 09/07

    Lecturer

    Dr. Patrick Schneider

    Aim and outline of the course

    This course offers an introduction to the fundamentals of causal inference and to widely used research designs in the social sciences. In the first part a framework for understanding causality is introduced. Specifically, the epistemological differences between association, intervention and counterfactuals are explained. Then it is shown why experiments are paramount in generating causal knowledge and which assumptions are needed for which level of the causal hierarchy. Finally, we will discuss two widely used approaches to causality, i.e. potential outcomes and directed acyclic graphs.

    The second part is devoted to the research designs such as regressions analysis, difference-in-differences, instrumental variables, and regression discontinuity. The emphasis is how these research designs are for example applied to answer important questions in labor economics such as

    • how a minimum wage increase affects employment

    • the effect of medicaid expansion on health outcomes

    • how class size influences educational attainment

    • whether there is an effect of military service on earnings

    • the career costs of children

    • the effect of schooling/job training on wages

    • age discrimination

    • how punishment affects drunk driving

    The assumptions each research design requires in order to identify a causal effect will be at center stage of the lecture. Therefore the emphasis is to teach students what one needs to estimate in order to answer a given question. Further, the research designs are discussed such that students will be able to evaluate and apply these research designs to other questions and fields.

    After the course, students should be able to understand the basic concepts and methods of causal inference; should be able to read and interpret research and judge its credibility. This course furthermore serves as a basis for subsequent master courses on statistical inference and estimation, i.e. on how to estimate. 

     Literatur

    The course’s material is mainly based on the following books:

    Angrist, J. D. and J.-S. Pischke. (2009). Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton: Princeton University Press.

    Pearl, J. and D. Mackenzie. (2018). The Book of Why: The New Science of Cause and Effect. New York: Basic Books. Cunningham, S. (2021).

    Causal Inference: The Mixtape. New Haven: Yale University Press

    Prerequisites

    A introductory course in statistics will be helpful.

    Examination

    A term paper by 14.08.21

    Organizational details

    Start: Monday 02.05.2022

    Mondays 12:15 – 13:45 and Tuesdays 14:14 – 15:45 in SR 321

    Lecturer

    Prof. Christina Felfe de Ormeño, Ph.D.

    Bachelor/Master Seminar Labor Economics: «Nobel Prize 2021 – The credibility revolution»

    Less people die while riding a motorbike than people die while lying in bed. Does this imply that beds are dangerous? While in this case, it may be straight forward to understand the statistical fallacy, there are plenty of other interesting questions in which it is hard to disentangle cause and effect.  For instance, it is complex to understand the causal effect of education on wages, minimum wages on employment, or immigration on employment, just to name a few relevant questions.

    The Nobel prize winners, David Card, Joshua Angrist, and Guido Imbens have developed a statistical toolkit to answer these questions. These causal analysis methods require curiosity to find settings that resemble the experimental ideal – so called natural experiments – and creativity to find the appropriate data. With a natural experiment and the appropriate data at hand the methods to be employed to provide causal answers to interesting and relevant questions are straight forward.

    In this seminar, students shall be acquainted with the intuition and the theory of the state-of-the-art causal analysis methods and familiarize themselves with these methods by working hands-on. The seminar will consist of theoretical lectures (5 in total) and a series of case studies where students will replicate original work by the Nobel prize winners in their early years. Students are expected to hand in their code (either in Stata or in R) by May 31, 2022!

    The lectures will take place online (via Zoom) on Mondays from 10:30am – 12 pm on the following dates: April 25, May 2, May 9, May 16, and May 23, 2022.

    General information:

    The Chair of Labour Economics supervises Master's theses in the area of labour, education, and migration economics. Topics usually relate to actual policy concerns, examples are discrimination, early child development, education, integration of immigrants, labour supply, peer effects, just to name a few. Theses should be of empirical nature using either primary or secondary data. The thesis can be written either in German or English. For more information regarding the formal and content-related structure of the thesis, see: Thesis Guideline

    Former thesis‘ topics:

    • The impact of parental benefits on parental gender norms
    • Gender stereotypes and occupational decisions of adolescents
    • Intergenerational changes for migrants in Germany
    • Acceptance of a universal basic income
    • Incorporating social identity into economic analysis

    Procedure:

    It is highly recommended to attend the master seminar, where the students can discuss their ideas, elaborate a literature review and familiarize themselves with the appropriate empirical methodology. The thesis will build on these skills.

    There is no list with prespecified topics, but each students approaches the chair with his or her own idea. Following a written application including a short description of the idea and the motivation as well as a transcript of courses and grades, conversations with the members of the chair will help to finetune the exact topic. A close supervision is guaranteed and desired throughout the whole process of thesis writing.