Lehre - Aktuelle Kurse

Vorlesung mit Übung

Dr. Asmus Zoch, Dr. Marc Gillaizeau

spring term 2020

Elective course for M.Sc. Economics

English

Goals and contents of the module:

This course will focus on different micro-econometric models using actual empirical studies from the field of laboureconomics. Starting from the standard theory of competitive labour markets, we introduce the concept of human capital, toexplain wage differences between individuals, and explore the role of education. Exploring the Mincer earnings function,discrimination and unemployment, the students will learn how to analyse actual labour data sets using Stata. The first partof the course will deal with linear panel data models and instrumental regressions, the second part will focus on discretechoice models. This course will end with the introduction of non-parametric estimators.Expected competences acquired after completion of the module:Ability to use Stata to conduct independent micro-econometric analysis and apply advanced micro-economic models.Further information:Introductory literature:
• Wooldridge, Jeffrey M. (2002), Econometric Analysis of Cross Section and Panel Data, Cambridge, Mass.: MIT Press. Chapters 10-20.
• George J. Borjas, Labor Economics

Expected number of students in class: 25

Contact information:

Dr. Asmus Zoch; Phone: (0621) 181-1842;

email: zoch(at)uni-mannheim.de; Office 123

Vorlesung mit Übung

Dr. Nicholas Barton

spring term 2020

English

Goals and contents of the module:

In this course, we will study both theoretically and empirically how best to motivate public servants with a focus on developingcountries. We will start with the traditional theory of motivation, looking at how incentive contracts and selection can affectperformance in the public sector and examine the results of experiments that have changed the incentive structure of publicservants. We will also examine a newer literature that focusses on how identity is shaped in the work place and notes thatworkers who are intrinsically motivated to work may not respond well to explicit incentives. Again, we will look at experimentalevidence that examines to what extent these theories are important in the real world.Expected competences acquired after completion of the module:Students will gain an understanding of the theory of incentives as well as how these apply to the real world in developingcountries. The course also aims to give students a better understanding of the empirical methods used in applied work onthe subject of incentivising public-sector workers.

Further information: Recommended literature will be discussed in class.

Expected number of students in class: 15

Contact Information: Dr. Nicholas Barton, email: nibarton(at)mail.uni-mannheim.de

spring term 2020

English

Course content:

Research seminar where Ph.D. students, who have completed their course work, present theirown research and receive feedback. (Topics in empirical development economics with microeconometric methods.Development economics can be subdivided into three branches: Macro, micro theory and empirical with micro data. Weonly cover the last area. Macro and micro theory have been the driving forces of development economics initially, but withthe increasing availability of microdata for Africa, Asia and Latin America in the last two decades, the foundation of the J-PAL network and the Nobel Prize in 2019, empirical development economics has been gaining attention.)

Competences acquired:

Doctoral Students will know how to- identify a research question,- put a research question into context of the relevant literature,- present their current stage of research to their peers in a seminar environment.

Contact information:

Caroline Mohr, email: cdse(at)uni-mannheim.de

Seminar

Prof. Dr. Markus Frölich

spring term 2020

Deutsch

6

Ziele und Inhalte des Moduls:

Das Seminar umfasst aktuelle Themen bezogen auf Arbeitsmärkte in Entwicklungsländernmit einem empirischen mikroökonometrischen Fokus. Die Themen beinhalten unter anderem: Kinderarbeit,informelle Arbeitsmärkte, Unternehmertum, die Schaffung von Firmen, Arbeitsmarktregulierungen, Mikrokredite,Mikroversicherungen, etc. Die Seminartermine werden nach den Wünschen der Studierenden ausgewählt. DieStudierenden sollen aktuelle Probleme von Entwicklungsländern erörtern und erkennen sowie empirische Studien zudiesen Fragen bewerten und diskutieren. In diesem Sinne ist es eine Mischung zwischen einem reinen Seminar zuEntwicklungsländern und einem angewandten Ökonometrieseminar. Die Studierenden sollen also auch angewandteökonometrische Papiere verstehen, diskutieren und vorstellen, um die konkrete empirische Forschungsweise zuerlernen. Das Seminar ist insbesondere auch als eine Vorbereitung auf eine mögliche Bachelorarbeit im Bereich derangewandten empirischen Forschung gedacht, welche dann üblicherweise eine eigenständige ökonometrische Analysemit Sekundärdaten verlangt. Das Seminar stellt somit eine Brückenfunktion zwischen den Grundlagenvorlesungenzur Ökonometrie, welche eher das Methodenwissen vermitteln, und der eigenständigen empirischen Analyse in derwissenschaftlichen Forschung dar. Erwartete Kompetenzen nach Abschluss des Moduls: Die Studierenden haben gelernt, einen Aufsatz zu einem Themaaus der Entwicklungsökonomie zu schreiben und zu präsentieren, wobei sie den Bezug zu mikroökonomischenModellen und insbesondere empirisch-ökonometrischer Analyse herausgearbeitet haben. Dies umfasst somit auch einekritische Analyse und Begutachtung von empirischen Studien und deren Methodik, insbesondere der Ökonometrie, der Datengrundlage und der Umsetzung der empirischen Herangehensweise.

Weitere Informationen: Bitte beachten Sie den gemeinsamen Anmeldezeitraum für Seminare des Bachelorstudiengangs VWL.

Kontakt: Prof. Dr. Markus Frölich, Tel. 0621/181-1920 (Sekretariat: Anja Dostert),

E-Mail: dostert(a)uni-mannheim.de, L7,3-5, Raum 1.21/1.22.

Vorlesung mit Übung

Dr. Katharina Richert, Dr. Giulia Montresor

spring term 2020

English

Statistik I+II, Grundlagen der Ökonometrie, Ökonometrie

Grading: Grading will be based on the final exam (90 minutes) accounting for 80% of the final grade andon thepresentation (30 minutes plus discussion) grade accounting for 20%.

Goals and contents of the module:

The course is designed for introducing students to the main empirical strategies thataretypically used for impact evaluation: Randomized Control Trials, Identification on Observables, Instrumental Variables, Difference-in-Difference, Regression Discontinuity Design. Students will be both exposed to fundamental conceptsbehindthe estimation of causal effects and related applied applications. Students will be asked to actively participate andpreparea presentation once during the tutorial session.Course Structure: The lecture will take place every week. Lecturecontents will be practiced during bi-weekly Stataexercise sessions in the tutorial or deepened with discussions of thecurrent literature presented by students every secondweek. Every participating student will have to present one researcharticle once. The 30-minutes presentations (+/-10%)will contain a 20 minute summary of the paper and a 10 minutediscussion of positive and negative paper aspects,potentially including secondary literature. Additionally, the presentingstudent will have to prepare 2-3 questions suitable tomotivate a group discussion with all course participants. In order toparticipate in the group discussions, als students arerequired to read the suggested literature before the tutorial sessions.

Expected competences acquired after completion of the course:
• Understand what impact evaluation is and the different techniques used
• Understand the identifying assumptions underlying each impact evaluation technique
• Review the “parameters of interest”
• Make judgments about what specific impact evaluation technique is appropriate to use according to the context andtype of intervention
Further information: Main reading: Frölich, M.and Sperlich, S. (unpublished): Policy Evaluation – Econometric methods andapplications

Other useful material:
• Khandker S. et al. (2010): Handbook on Impact Evaluation: Quantitative Methods and Practices
• Angrist J. and Pischke, J. (2009): Mostly Harmless Econometrics
• Angrist J. and Pischke, J. (2015): Mastering Metrics
• Caliendo M. and Kopeinig S. (2005): Some Practical Guidance for the Implementation of Propensity Score Matching
• Angrist, J., Imbens, G., and Rubin, D. (1996): Identification of causal effects using instrumental variables. Journal ofthe American Statistical Association, 91(434), 444-455.
• Lee, D. and Lemieux, T. (2010): Regression discontinuity designs in economics. Journal of economic literature, 48(2),281-355.

Maximum number of students in class: 41

Contact Information: Dr. Giulia Montresor; Phone: (0621) 181-1941; E-mail: montresor(at)uni-mannheim.de;

Office: L7,3-5, room 131 Dr. Katharina Richert, E-mail: richert(at)uni-mannheim.de

Vorlesung mit Übung

spring term 2020

English

7

Goals and contents of the module:

The course gives an introduction into the data management in Stata. That includes how to set up do-files, the preparation of data for analysis, the generation of variables, the use of macros in Stata, andthemerging of data sets. Basic and advanced statistical procedures will be discussed in the course. For each model, therewill be an introduction to the statistical model and it will be shown how to analyze the corresponding data with Stata andhow to interpret the output of Stata. The models considered are some elementary statistical models, the linearregressionmodel with homoscedastic and heteroscedastic error terms, analysis of variance models, linear panel datamodels,nonlinear regression models and binary and multinomial models.

Expected competences acquired after completion of the module:

The students know basic probabilistic andstatisticalconcepts, e.g. the concept of a statistical test and how to compute and use p-values. The students can analyze data with Stata: The students are able to review a data set, generate summary statistics, and merge data sets. They know how to work with variables, matrices, and macros. They know how to perform elementary tests. The students cangenerateadvanced plots. They are able to set up a linear model with homoscedastic or heteroscedastic error terms and understand the results provided by Stata. They can do an analysis of variance and test for heteroscedasticity in a linear regression model. They understand the ideas of linear panel data regression and can analyze corresponding data. Thestudents areable to estimate the parameters, perform tests for the parameters, and analyze the results in nonlinear regression models and binary choice models.

Further information: Literature: Cameron/Trivedi (2009). Microeconometrics using Stata. Stata Press.

Expected number of students in class: depends on students’ choice (max. 41).

Contact Information:

Dr. Atika Pasha; E-mail: pasha(at)uni-mannheim.de,

Dr. Ingo Steinke; Phone: 0621 181 1940; E-mail:isteinke(at)rumms.uni-mannheim.de