Lehre – Aktuelle Kurse

Seminar

Prof. Dr. Markus Frölich

every term

Deutsch

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. Die Studierenden 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 mikroökonomischen Modellen 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 Bachelor­studien­gangs­VWL.

Kontakt:

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

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

fall term term 2021

English

Goals and contents of the module:

The course will introduce students to the main concepts of poverty and inequality measurements and the critical links between poverty and inequality and economic growth. Students will get an overview on theories of justice, methodological aspects of poverty & inequality measurement, gender inequalities, economic mobility, inequality and poverty in rich countries as well as development policy targeting poverty. The course will focus on low- and middle-income countries.

It is structured as follows:

1. Introduction

2. Long Run Determinants of Growth

3. Concepts and Measurements of Poverty I

4. Concepts and Measurements of Poverty II

5. Poverty Alleviation I: (Micro-)finance

6. Poverty Alleviation II: Cash transfers

7. Concepts and Measurements of Inequality

8. Does Inequality Cause Growth?

9. Pro-Poor Growth

10. Inequality and Gender

11. Poverty and Inequality in High-Income Countries

12. Economic Mobility

13. The Behavioral Economics of Poverty

14. Recap

Expected competences acquired after completion of the module: The students become acquainted with the topics in poverty and inequality and learn to critically review and discuss empirical studies in the field.

Expected number of students in class: 20

Contact Information:

Name: Dr. Marc Gillaizeau; Email: gillaizeau uni-mannheim.de; Office: L7, 3-5, room 1.19

Office hours: on request via email

Lecture

Prof. Dr. Markus Frölich

Each fall semester

English

Final exam (120 min)

Goals and contents of the module:

Topics will include co­unterfactual outcomes, heterogeneous treatment effects,(propensity) score matching, differences in differences, instrumental variables designs, randomized control trials, regression discontinuity design.

The course content in 2021 will depend on the Covid situation. In the (possible) scenario that limitations to physical presence on campus are still in place in fall, there would be no computer exercise sessions. In such situation, only econometric theory will be considered and all practical aspects such as computer exercises and machine learning would be dropped and resumed again in fall 2022. Given unpredictability, the detailed course planning can only be done in September.

Expected competences acquired after completion of the module: The students become acquainted with modernmethods in impact evaluation.

Further information:
• Impact Evaluation (Frölich, Sperlich, 2019, Cambridge University Press)

Expected number of students in class: 20

Contact Information:

Anja Dostert; Email: dostert uni-mannheim.de; Office: L7, 3-5, room 1.21/1.22

Vorlesung und Übung

fall term 2021

English

9.5

Goals and contents of the module:

Although Stata already offers a large number of econometric tools, novel approachesare often not available and have to be implemented by users. This course offers an introduction to advanced programmingin Stata. Since comparatively few people know how to do so, Stata programming skills can be a competitive advantage.The lecture will start with an introduction to efficiently written do-files (including data processing). We will look at anddiscuss different data types. In hands-on sessions students will be taught how to prepare the data for analysis. Variableswill be generated and their distributions explored; data will be merged; and regression results will be critically discussed.Moreover, in this course students will learn how to implement new commands for Stata and to conduct Monte Carlosimulations. These are important for verification of implementations and are used as a very important tool to analyse thesmall sample properties of estimators and to complement the theoretical properties of estimators making them an integralpart of econometric analyses. We will also touch upon Stata's matrix programming language Mata, non-linear optimization,e.g. ML estimation and bootstrap methods

Expected competences acquired after completion of the module:

Students will be able to program quantitativemethods using Stata independently. They are able to use Stata and Mata as programming languages and understandthe standard syntax and the grammar of the languages. They will also be able to understand commands in Stata andedit these accordingly. Knowledge won from this module can be applied to various records. Students are capable ofautomatizing analysis and working efficiently. In addition to that, they will be able to conduct Monte Carlo simulations andinterpret and use the results to estimate the quality of the estimation procedure. They can generate samples from a varietyof distributions. Through Monte Carlo simulations, students will have a better comprehension of the uncertainty and qualityof the estimation and test procedures.

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

Expected number of students in class: 21

Contact information:

Name: Dr. Nicholas Barton; Email: nibarton mail.uni-mannheim.de

Name: Dr. Ingo Steinke; Email: isteinke rumms.uni-mannheim.de

Lecture and Exercise

Prof. Dr. Markus Frölich

English

10

Goals and contents of the module:

The goal of the module is to offer advanced treatment of econometric theory and toserve as the gate way to further advanced theoretical and applied econometric modules offered in the economics graduateprogram at the Department of Economics in Mannheim.

The module offers a revision of undergraduate level econometrics before moving on to extensive coverage of large-sampletheory and some organizing estimation principles such as GMM estimators. Asymptotic properties of these estimators arealso the focus of the module as well as non-linear models and the treatment of serial correlation.

Expected competences acquired after completion of the module:

On successful completion of the module, studentsare expected to attain the following competences:

• Attain advanced theoretical knowledge in econometrics in the specific topics the module covers at a high technicaland mathematical level.
• Be familiar with current theories and recent developments in the specific topics of focus for the module.
• Attain a higher/advanced level of analytical capability.
• Be in a position to take on follow-up advanced theoretical and applied econometrics modules.
• Attain the level of competence that permits independent undertakings in search of new knowledge in the specialistareas the module covers.
• Attain the level of competence required to carry out (theoretical) research-oriented projects independently.
• To be in a position to exchange information, ideas, and solutions with experts of the field on a scientific level as wellas with laymen.
• To be able to communicate and to work effectively and efficiently with people and in groups.
• Graduates are able to communicate precisely in the English specialist language.

Further information: Recommended textbooks:
• Econometrics; Bruce E. Hansen; University of Wisconsin; www.ssc.wisc.edu/~bhansen/econometrics/
• Wooldridge (2010): Econometric Analysis of Cross Section and Panel Data. MIT Press.

Expected number of students in class: 65

Contact information:

Prof. Dr. Markus Frölich; Email: froelich uni-mannheim.de; Office: L7, 3-5, room 114;

Office hours: upon appointment

fall term 2021

English

Course content:

Research seminar where Ph.D. students, who have completed their course work, present their own research and receive feedback. This seminar is intended to discuss topics around theoretical as well as applied research in the area of causal inference as well as randomized experiments and experimental design. Students are encouraged to review literature on a topic within this field, and explore if such research field may reflect or support their development of their own PhD project. Seminar topics normally refer to either Econometric Theory, i.e. identification or design development as well as estimators and their properties, or the applicability of methods that are linked to causal identification.

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.

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