Lehre - Frühere Kurse

  • Spring semester 2017

    E5031 Applied Labour Economics (Master)

    Responsible teacher of the module: Dr. Asmus Zoch
    Course language: English
    Prerequisites: E601-E603 (or equivalent)
    Workload: 270 hours in total, containing 42 hours class time and 228 hours for independent studies,
    project and exam preparation
    ECTS-Credits: 9
    Course description: 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

     

    E820 Experimental Econometrics and RCTs in Development Economics

    Responsible teacher of the module: Prof. Dr. Markus Frölich
    Course language: English
    Prerequisites: E700 - E703, E801 - E806
    ECTS-Credits: 5
    Course description: The seminar prepares for own research in theoretical econometrics. This seminar covers recent developments inmicroeconometrics with a particular focus on identification and estimation strategies that deal with endogeneity issues.Preference will be given to articles in Econometrica, recently published or forthcoming.Expected Competences acquired after completion of the module:On successful completion of the module, students are expected to attain the following competences:- Attain advanced knowledge in econometric theory.- Attain a higher/advanced level of analytical capability.- To be in a position to exchange information, ideas, and solutions with experts of the field on a scientific level as well aswith laymen.- Ability to communicate precisely in the English specialist language.- Presentation skills.- Attain the level of competence that permits independent undertakings in search of new knowledge in microeconometric theory.

     

    Economics of Education

    Responsible teacher of the module: Dr. Adrien Bouguen

    Course language: English
    Prerequisites: Mikroökonomik A, Statistik I
    ECTS-Credits: 5
    Course description: What can economists possibly say about education? Dealing with the important economic issues linked to education, Iwill present an overview of the main theoretical and empirical knowledge available. The topics covered in this course willinclude: the impact of class size, the teacher quality, the returns to education, the link between health or criminal behaviourand education, the role of school choice and of tuition fees in higher education, and the measurement of peer effects.Throughout the semester, I will discuss empirical methodologies used to analyze education systems worldwide. Exampleswill be taken from both developing and developed countries.Goals of the course:Introducing students to the available literature on education and to the methodology used to analyze education systems worldwide. At the end of the semester, students will be acquainted to rigorous quantitative methods used to analyze education and will have been in contact with the most prominent results available in the economics of education.Requirements for the assignment of ECTS credits:Students will first be required to participate actively in class discussions (10%). They also should attend all sessions (10%).The rest of the grade will be composed of several assignments to be completed at home (80%). A total of 6 assignmentswill be given to students (one every second session). All assignments should be completed by students but only a subsetof them will be graded (between 2 and 4, randomly chosen).“ Literature that will be covered in class can be found in the details below (subject to modification).

     

    Entwicklungs­ökonomie

    Responsible teacher of the module: Prof. Dr. Markus Frölich

    Course language: Deutsch
    Prerequisites: Grundlagen der Ökonometrie
    ECTS-Credits: 6
    Course description: Benotung und Vergabe von ECTS-Punkten: schriftliche Seminararbeit, Vortrag, Koreferat, aktive Mitarbeit im SeminarZiele 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, derDatengrundlage und der Umsetzung der empirischen Herangehensweise.Weitere Informationen: Bitte beachten Sie den gemeinsamen Anmeldezeitraum für Seminare des Bachelor­studien­gangs­VWL: 18. November 2018 (22:00 Uhr) bis 23. November 2018 (24:00 Uhr)Erwartete Zahl der Teilnehmer/innen: max. 13

     

    Statistics and Stata

    Responsible teacher of the module: Dr. Alexandra Avdeenko, Dr. Ingo Steinke

    Course language: English
    Prerequisites: Statistik I+II, Grundlagen der Ökonometrie
    ECTS-Credits: 6
    Course description: Goals and contents of the module: The course gives an introduction into the data management in Stata. That includeshow to set up do-files, the preparation of data for analysis, the generation of variables, the use of macros in Stata, and themerging 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 linear regressionmodel with homoscedastic and heteroscedastic error terms, analysis of variance models, linear panel data models,nonlinear regression models and binary and multinomial models.
    Expected competences acquired after completion of the module: The students know basic probabilistic and statisticalconcepts, e.g. the concept of a statistical test and how to compute and use p-values. The students can analyze data withStata: The students are able to review a data set, generate summary statistics, and merge data sets. They know howto work with variables, matrices, and macros. They know how to perform elementary tests. The students can generateadvanced plots. They are able to set up a linear model with homoscedastic or heteroscedastic error terms and understandthe results provided by Stata. They can do an analysis of variance and test for heteroscedasticity in a linear regressionmodel. They understand the ideas of linear panel data regression and can analyze corresponding data. The students areable to estimate the parameters, perform tests for the parameters, and analyze the results in nonlinear regression modelsand 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).

  • Fall semester 2016

    E5026 Programming in Stata

    Responsible teachers of the module: Dr. Alexandra Avdeenko, Dr. Ingo Steinke

    Course language: English
    Prerequisites: E601-603 (or equivalent)
    ECTS-Credits: 7

    Course description: Although Stata already offers a large number of econometric tools, novel approaches are often not available and have tobe implemented by users. This course offers an introduction to advanced programming in Stata. Since comparatively few people know how to do so, Stata programming skills can be a competitive advantage. The lecturewill start with an introduction to efficiently written do-files (including data processing). We will look at and discuss differentdata types. In hands-on sessions students will be taught how to prepare the data for analysis. Variables will be generatedand their distributions explored; data will be merged; and regression results will be critically discussed. Moreover, in thiscourse students will learn how to implement new commands for Stata and to conduct Monte Carlo simulations. These areimportant for verification of implementations and are used as a very important tool to analyse the small sample propertiesof estimators and to complement the theoretical properties of estimators making them an integral part of econometricanalyses. We will also touch upon Stata's matrix programming language Mata, non-linear optimization, e.g. ML estimationand bootstrap methods.Expected competences acquired after completion of the module:Die Studierenden sind in der Lage, quantitative Methoden in Stata selbständig zu programmieren. Sie kennen Stata undMata als Programmiersprachen und verstehen die Standard­syntax bzw. die Grammatik der Sprachen. Dadurch habensie auch erlernt, Statas Kommandos besser zu verstehen und auch gegebenenfalls anzupassen. Ihr Wissen können die Studenten auf verschiedene Datensätze anwenden. Sie sind in der Lage, aufwändige Analysen zu automatisieren unddamit effizienter zu arbeiten. Darüber hinaus sind sie in der Lage, Monte Carlo Simulationen durchzuführen und deren Ergebnisse zu interpretieren und zu verwenden, um die Güte von Schätz­verfahren einzuschätzen. Sie können Stichprobenaus einer großen Auswahl von Verteilungen generieren. Mit Hilfe von Monte-Carlo-Simulationen erreichen die Studentenein besseres Verständnis für die Unsicherheit und Güte von Schätz- und Test­verfahren.Further information:Cameron/ Trivedi (2009). Mircoeconometrics using Stata. Stata Press.
    Expected number of students in class: 40

     

    E553 Development Economics: Experimental Approaches

    Responsible teachers of the module: Dr. Alexandra Avdeenko, Dr. Adrien Bouguen

    Course language: English
    Prerequisites: E601-603 (or equivalent)
    ECTS-Credits: 5

    Course description: Development economics deals with economic aspects of the development process in low-income countries. After anexamination of the long-run factors of economic development, this lecture focuses on interventions intended to promoteeconomic growth and welfare of the population in developing countries. In particular, it accumulates evidence to answerthe following questions: Which interventions improve the living conditions of the poor? Methodologically, this lecture comprises of econometric methods used for program evaluation. These methods identifycausal relations­hips between interventions and their intended outcomes (e.g. using instrumental variables, randomizedcontrol trials, regression discontinuity). The practical exercises include hands-on empirical work with STATA. Evaluationwill be based on replications of famous empirical articles in developing countries. Students will implement threereplications but only one will be graded (based on a random assignment at the end of the semester). Students will onlyhave a few days to perform the replications, typically from the Friday after the end of the block to the Sunday evening. Thisyear the course will mainly talked about institutions and education. In terms of learning outcomes for students the lecturepursues the following goals:
    • Introduce students to state-of-the-art research on institutions and education.
    • Give students insights on how to do empirical research employing econometric methods.
    • Enable students to make critical assessments of research work.
    • Enable students to independently great scientific articles using empirical tools learned in class.

     

    E603 Advanced Econometrics

    Responsible teachers of the module: Prof. Dr. Markus Frölich

    Course language: English
    Prerequisites: Undergraduate level of econometrics
    ECTS-Credits: 10

    Course description: The goal of the module is to offer advanced treatment to econometric theory and to serve as the gate way to furtheradvanced theoretical and applied econometric modules offered in the economics graduate program at the Department ofEconomics 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 and Extremum estimators. Asymptotic properties of theseestimators are also 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, students are expected to attain the following competences:
    • Attain advanced theoretical knowledge in econometrics in the specific topics the module covers at a hightechnical and 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 thespecialist areas 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 levelas well as 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:
    • Wooldridge (2010): Econometric Analysis of Cross Section and Panel Data. MIT Press.
    • Heij, De Boer, Franses, Kloek, and Van Dijk (2004): Econometric Methods with Applications in Business andEconomics. Oxford University Press.
    • Kirchgässner, Wolters (2007): Introduction to Modern Time Series Analysis.
    • Kirchgässner, Wolters (2006): Einführung in die moderne Zeitreihenanalyse.
    Expected number of students in class: 60

     

    E820 E820 Experimental Econometrics and RCTs in DevelopmentEconomics

    Responsible teachers of the module: Prof. Dr. Markus Frölich

    Course language: English
    Prerequisites: E700 - E703, E801 - E806
    ECTS-Credits: 5

    Course description: The seminar prepares for own research in theoretical econometrics. This seminar covers recent developments inmicroeconometrics with a particular focus on identification and estimation strategies that deal with endogeneity issues.Preference will be given to articles in Econometrica, recently published or forthcoming.Expected Competences acquired after completion of the module:On successful completion of the module, students are expected to attain the following competences:- Attain advanced knowledge in econometric theory.- Attain a higher/advanced level of analytical capability.- To be in a position to exchange information, ideas, and solutions with experts of the field on a scientific level as well aswith laymen.- Ability to communicate precisely in the English specialist language.- Presentation skills.- Attain the level of competence that permits independent undertakings in search of new knowledge in microeconometrictheory.

     

    Entwicklungs­ökonomie

    Responsible teachers of the module: Prof. Dr. Markus Frölich

    Course language: English
    Prerequisites: Grundlagen der Ökonometrie
    ECTS-Credits: 6

    Course description: Benotung und Vergabe von ECTS-Punkten: schriftliche Seminararbeit, Vortrag, Koreferat, aktive Mitarbeit im SeminarZiele 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, derDatengrundlage und der Umsetzung der empirischen Herangehensweise.Weitere Informationen: Bitte beachten Sie den gemeinsamen Anmeldezeitraum für Seminare des Bachelor­studien­gangs­VWL: 18. November 2018 (22:00 Uhr) bis 23. November 2018 (24:00 Uhr)Erwartete Zahl der Teilnehmer/innen: max. 13

  • Spring semester 2016

    E564 Impact evaluation, treatment effects, causal analysis

    Form and applicability of the module: Elective course for Master in Economics

    ECTS-Credits: 7

    Teaching method (hours per week): lecture (2), exercise (1)

    Cycle of offer: each spring semester

    Course language: English

    Goals and Contents of the module: Expected Competences acquired after completion of the module:Students will have a working knowledge of recent developments in robust impact evaluation methods and skills in theirapplication using Stata. In particular, they understand concepts of identification and causality and the different types oftreatment effects. They will understand the theoretical and practical implications of different sample scenarios (randomcontrol trials, selection on observables and unobservables) and can choose the appropriate estimation strategy (matchingestimator, propensity score, IV, regression discontinuity, difference in difference). They understand assumptions made andtheoretical properties of the related nonparametric estimators and the pitfalls of the classical parametric estimators.

    Requirements for the assignment of grade and ECTS credits: written exam, 120 minutes

     

    E820 Experimental Econometrics and RCTs in DevelopmentEconomics

    Instructor: Prof. Dr. Markus Frölich

    Offered term: each semester

    Method: seminar (2 SWS)

    Course level: PhD

    Course language: English

    Prerequisites: E700 - E703, E801 - E806

    Examination: presentation and seminar paperECTS: 5Descrption:The seminar prepares for own research in theoretical econometrics. This seminar covers recent developments inmicroeconometrics with a particular focus on identification and estimation strategies that deal with endogeneity issues.Preference will be given to articles in Econometrica, recently published or forthcoming.Expected Competences acquired after completion of the module:

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

    - Attain advanced knowledge in econometric theory.

    - Attain a higher/advanced level of analytical capability.

    - To be in a position to exchange information, ideas, and solutions with experts of the field on a scientific level as well aswith laymen.

    - Ability to communicate precisely in the English specialist language.

    - Presentation skills.

    - Attain the level of competence that permits independent undertakings in search of new knowledge in microeconometric theory.

     

    Empirical Economics of Education

    EducationInstructor: Dr. Adrien BouguenOffered: spring term 2016Method (hours per week): lecture (2)Course level: Bachelor­Course language: EnglishPrerequisites: Microeconomics I, Statistics IExamination: class participation (10%), homework (30%), and final exam (60%)ECTS: 5 Course description:What can economists possibly say about education? Dealing with the important economic issues linked to education, Iwill present an overview of the main theoretical and empirical knowledge available. The topics covered in this course willinclude: the impact of class size, the teacher quality, the returns to education, the link between health or criminal behaviourand education, the role of school choice and of tuition fees in higher education, and the measurement of peer effects.Throughout the semester, using terminology accessible to non-specialists, I will discuss the difference between correlationand causality, and study the intuition of the main “impact evaluation” methods used by economists to contribute to thesocial debate on education. Examples will be taken from both developing and developed countries. Goals of the course:Introducing students to the available literature on education and to the methodology used to analyse education systemsworldwide. At the end the semester, students will be acquainted to rigorous quantitative methods used to analyseeducation and will have been in contact with the most prominent results available in the economics of education. Requirements for the assignment of ECTS credits:Students will first be required to participate actively in class discussions (10% of the final grading). Secondly, a shortpiece of homework will be hand-in after each session to the class. At the beginning of each session, I will collect somepreparations randomly (30% of the final grade). Homework is not made to sanction or to increase unnecessarily yourworkload but to help you revising for the final exam. The final exam will form the rest of the mark (60%).

     

    Instructor: Dr. Adrien Bouguen

    Offered: spring term 2016

    Method (hours per week): lecture (2)

    Course level: Bachelor

    Course language: English

    Prerequisites: Microeconomics I, Statistics I

    Examination: class participation (10%), homework (30%), and final exam (60%)

    ECTS: 5

    Course description: What can economists possibly say about education? Dealing with the important economic issues linked to education, Iwill present an overview of the main theoretical and empirical knowledge available. The topics covered in this course willinclude: the impact of class size, the teacher quality, the returns to education, the link between health or criminal behaviourand education, the role of school choice and of tuition fees in higher education, and the measurement of peer effects.Throughout the semester, using terminology accessible to non-specialists, I will discuss the difference between correlationand causality, and study the intuition of the main “impact evaluation” methods used by economists to contribute to thesocial debate on education. Examples will be taken from both developing and developed countries. Goals of the course:Introducing students to the available literature on education and to the methodology used to analyse education systemsworldwide. At the end the semester, students will be acquainted to rigorous quantitative methods used to analyseeducation and will have been in contact with the most prominent results available in the economics of education. Requirements for the assignment of ECTS credits:Students will first be required to participate actively in class discussions (10% of the final grading). Secondly, a shortpiece of homework will be hand-in after each session to the class. At the beginning of each session, I will collect somepreparations randomly (30% of the final grade). Homework is not made to sanction or to increase unnecessarily yourworkload but to help you revising for the final exam. The final exam will form the rest of the mark (60%).

    Some literature that will be covered in class (subject to modification):
     
    Session 1 Introduction:  Human Capital Theory (1) (Mincer) – Multivariate Regressions
    Description of the first Human Capital Theory by Jacob Mincer + introduction to econometrics via multivariate regressions

    • Investment in Human Capital and Personal Income Distribution, Jacob Mincer, Journal of Political Economy, 1958
    • Human Capital and Earnings: British Evidence and a Critique, George Psacharopoulos and Richard Layard, 1979  Review of Economic Studies
    • Estimating the Returns to Schooling: Some Econometric Problems. Zvi Griliches, Econometrica 45 (1): pp. 1-22. (1977).

     
    Session 2 Human Capital theory (Becker)  - Difference in Differences
    Description of the Human Capital Theory by Gary Becker  + introduction to public policy evaluation via difference in differences strategy

    • Investing in Human Capital: A theoretical Analysis, Gary Becker ,Journal of Political Economy, 1962
    • Education and the Distribution of Earnings, Gary Becker, Chiswick, American Economic Review, 1966

     
    Session 3: Return To education – Instrumental Variables

    • Schooling and Labor Market Consequences of School Construction in Indonesia: Evidence from an Unusual Policy Experiment, Esther Duflo,  American Economic Review, 2001
    • Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems, David Card, 2001, Econometrica
    • Return to investment in Education: a further update, G.Psacharoupoulos, H.A.Patrinos, Education Economics , 2004
    • Does Compulsory School Attendance Affect Schooling and Earnings ?, Angrist, Krueger, The Quarterly Journal of Economics, Vol. 106, No. 4 (Nov., 1991), pp. 979-1014
    • Estimating the Return to Schooling: Progress on Some Econometric Problems, Zvi Griliches, Econometrica 1977
    • Using Geographic Variation in College Proximity To estimate the Return to Schooling, David Card, 1993, NBER

     
    Session 4: Externality and non monetary returns to schooling:

    • Understanding Differences in Health Behaviors by Education, Cutler, Lleras-Muney, 2009, Journal of Health Economics
    • Education, Work, and Crime: a human capital approach, Lance Lochner, International Economic Review, 2004
    • The Effect of Education on Crime: Evidence from Prison Inmates, Arrests, and Self-Reports, Lance Lochner, Enrico Moretti, The American Economic Review, 2004
    • How large re returns to schooling? Hint: money isn't everything, Oreopoulous, Salvanes, NBER Working Paper 2009

     
    Session 5:  Demand for Education: Are students credit constraints? What are the main impediment to schooling participation?

    • The Evidence of Credit Constraint in Post-secondary education, Carneiro, Heckman, The Economic Journal, 2002
    • College Cost and time to complete degree: Evidence from a Tuition discontinuity, Garibaldi, Giavazzi, Ichino, Rettore, 2012
    • School subsidies for the poor: evaluating the Mexican Progresa poverty program, Paul Schultz, The Journal of development economics, 2004

     
    Session 6: School Choice – Randomized Controlled Trial

    • School Vouchers: A Critical View, The Journal of Economic Perspectives, 2002, Vol. 16, No. 4, pp. 3-24
    • Vouchers for Private Schooling in Columbia: Evidence from a Randomized NaturalExperiment. J. Angrist, E. Bettinger, E. Bloom, E. King and M. Kremer, NBER WorkingPaper 8343, (2001)
    • School choice and school productivity (or could school choice be a tide that lifts allboats, C. Hoxby, NBER Working Paper 8873, (2002)
    • Would School Choice Change the Teaching Profession?. C. Hoxby, The Journal of Human Resources, Vol. 37, No. 4 (Autumn, 2002), pp. 846-891
    • Does Competition Among Public Schools Benefit Students and Taxpayers? C. Hoxby, American Economic Review, Vol. 90(5) (2000)
    • Good Principals or Good Peers? Parental Valuations of School Characteristics,Tiebout Equilibrium, and the Incentive Effects of Competition among Jurisdictions. J.Rothstein, American Economic Review, Vol. 96(4), (2006)

     
    Session 7 Improving School Supply: Alternative or complementary to school choice, one may policy question is how to improve schooling. We look at some successful examples. 

    • Using Maimonides' Rule to Estimate the Effect of Class Size on Scholastic Achievement. (1999) J. D. Angrist and V. Lavy, Quarterly Journal of Economics, Vol.114(2),
    • The French zones d’éducation prioritaire: Much ado about nothing? R. Bénabou, F. Kramarz and C. Prost, Economics of Education Review, Vol. 28 (2009)
    • Identifying Class Size Effects In Developing Countries: Evidence From Rural Bolivia. M. Urquiola, Review of Economics and Statistics, Vol. 88(1), (2006)
    • Class-Size Caps, Sorting, and the Regression-Discontinuity Design. M. Urquiola and E.Verhoogen, American Economic Review, Vol. 99(1), (2009)
    • Stephen Machin & Sandra McNally & Costas Meghir, 2010. "Resources and Standards in Urban Schools,“ Journal of Human Capital, University of Chicago Press, vol. 4(4), pages 365 - 393.
    • Improving Education in the developing world: What have we learned from Randomized Evaluations ? Kremer, Holla, Annual Review of Economics, 2009
    • The Effect of Attending a Small Class in the Early Grades on College-Test Taking and Middle School Test Results: Evidence from Project STAR,  A. Krueger,D. Whitmore, 2001    The economic Journal,
    • The Evaluation of Charter School Impacts 2010, IES Final Report, Philip Gleason, Melissa Clark, Christina Clark Tuttle, Emily Dwoyer,
    • Estimating the Returns to Urban Boarding Schools: Evidence from Seed, WP, Curto V , Fryers R, 2011,
    • Behaghel, Chaisemartin, Charpentier, Gurgand, 2013, Les effets de l'internat d'excellence de Sourdun sur les elèeves bénéficiaires, J-PAL, DEPP, IPP ? http://www.cnrs.fr/inshs/recherche/docs-vie-labos/sourdun-rapport.pdf

     
    Session 8: Teacher Quality: One central input in the education production function is the teacher: How can we improve their productivity? Is it desirable?

     
    Session 9:  Evaluating teacher effect - Fixed effect model: From a more empirical perspective, can we assess the size of the teacher effect?

    • Estimating Teacher Impacts on Student Achievement: An Experimental Evaluation, Kane and Staigler, 2008,Working Paper
    • Teachers, schools, and academic achievement, Steven G. Rivkin, Eric A. Hanushek, And John F. Kain, Econometrica 2005
    • Teacher Quality in EducationalProduction: Tracking, Decay, and Student Achievement, Jesse Rothstein,  The Quarterly Journal of Economics, 2010.  MIT Press, vol. 125(1), pages 175-214, February
    • "Teacher training, teacher quality and student achievement,“ Harris and Sass, Journal of Public Economics, Elsevier, vol. 95(7), pages 798-812
    • Does Teacher Training Affect Pupil Learning? Evidencefrom Matched Comparisons in Jerusalem Public Schools, Angrist and Lavy, Journal of Labor Economics, 2001

     
    Session 10: Peer Effect: Are peers important in education?

    • Peer Effects In Education: How Might They Work, How Big Are They And How Much Do We Know Thus Far? Handbook Of Economics Of Education Volume 3 2010, Sacerdote
    • Identification Of Endogenous Social Effects: The Reflection Problem, Manski 1993, The Review Of Economic Studies, Vol. 60, No. 3. (Jul., 1993), Pp. 531-542.
    • Peer Effects With Random Assignment: Results ForDartmouth Roommates, Sacerdote Quarterly Journal Of Economics, 2011
    • Peer Effects, Teacher Incentives, And The Impact Of Tracking: Evidence From A Randomized Evaluation In Kenya. Duflo, Esther, Pascaline Dupas, And Michael Kremer.  2011.  American Economic Review, 101(5): 1739-74
    • Getting Parents Involved: A Field Experiment In Deprived Schools Review Of Economic Studies, Avvisat, Guyon, Gurgand, Maurin, Review Of Economic Studies, 2014

     
    Session 11: Early Childcare development:What are the benefits of introducing early education program (preschool , kindergarten) ?What sort of stimulation should they receive? 

    • Personality Psychology and Economics, Handbook of Economics of Education, 2011, Almlund, Duckworth, Heckman, Kautz
    • The Economics and Psychology of Inequality and Human Development,“ Cunha, Heckman Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 320-364, 04-05
    • Schools, Skills, And Synapses, Heckman , Economic Inquiry, 2008
    • Cognitive and school outcomes for high risk African American at Middle Adolescence: Positive Effectsof Early Intervention, Frances A. Campbell and Craig T. Ramey  American Education Research Journal
    • Boys’ Cognitive Skill Formation And Physical Growth: Long-Term Experimental Evidence On Critical AgesFor Early Childhood Interventions, Tania Barham, Karen Macours, and John A. Maluccio

     

    Entwicklungs­ökonomie

    Modul­verantwortliche/r: Prof. Dr. Markus Frölich

    Turnus des Angebots: jedes Semester

    ECTS-Punkte: 6

    Lehr­methode (Umfang): Blockseminar (2 SWS)

    Arbeits­aufwand: Präsenzzeit Seminar: 21 Stunden; Zeit für die Anfertigung der Seminararbeit, für die Vorbereitung derReferate sowie für das Selbststudium 147 Stunden

    Unterrichtssprache: Deutsch

    Teilnahme­voraussetzungen: Grundlagen der ÖkonometrieBenotung und Vergabe von ECTS-Punkten: schriftliche Seminararbeit, Vortrag, Koreferat, aktive Mitarbeit im Seminar

    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.

     

    Ökonometrie und Programmieren / Programming in Stata

    Course title: Ökonometrie und Programmieren / Programming in Stata

    Instructor: Alexandra Avdeenko

    Offered: FSS 2016

    Method (hours per week): lecture (2)

    Course level: Bachelor

    Course language: English

    Prerequisites: Basic Stata skills of advantage

    Examination: Programming exam, 90 min

    ETCS-Credits: 5

    Course description:The main objective is to give students a practical introduction to econometrics. This course offers an introduction to advanced­programming in Stata. Although Stata already offers a large number of econometric tools, novel approaches are often notavailable and have to be implemented by users. Since comparatively few people know how to do so, Stata programmingskills can be a competitive advantage. The lecture will start with an introduction to efficiently written do-files (including dataprocessing). Different data types will then be presented, i.e. the German Socio-Economic Panel (SOEP). In hands-on sessionsstudents will be taught how to prepare the data for analysis. Variables will be generated and their distributions explored; datawill be merged; and regression results will be critically discussed. Moreover, in this course students will learn how to implementnew commands for Stata and to conduct Monte Carlo simulations. These are important for verification of implementations­and are used as a very important tool to analyse the small sample properties of estimators and to complement the theoreticalproperties of estimators making them an integral part of econometric analyses. We will also touch upon Stata's matrix­programming language Mata. Moreover, we will apply the programming techniques to implement selected cross-sectionmodels

     

     

  • Spring semester 2015

    E564 Impact evaluation, treatment effects, causal analysis

    Form and applicability of the module: Elective course for Master in Economics

    Duration of the module: 1 semester

    ECTS-Credits: 7

    Teaching method (hours per week): lecture (2), exercise (1)

    Cycle of offer: each spring semester

    Course language: English

    Expected Competences acquired after completion of the module: Students will have a working knowledge of recent developments in robust impact evaluation methods and skills in theirapplication using Stata. In particular, they understand concepts of identification and causality and the different types oftreatment effects. They will understand the theoretical and practical implications of different sample scenarios (randomcontrol trials, selection on observables and unobservables) and can choose the appropriate estimation strategy (matchingestimator, propensity score, IV, regression discontinuity, difference in difference). They understand assumptions made andtheoretical properties of the related nonparametric estimators and the pitfalls of the classical parametric estimators.

    Requirements for the assignment of grade and ECTS credits: written exam, 120 minutes

    E820 Experimental Econometrics and RCTs in Development Economics

    Instructor: Prof. Dr. Markus Frölich

    Offered term: each semester

    Method: seminar (2 SWS)

    Course level: PhD

    Course language: English

    Prerequisites: E700 - E703, E801 - E806

    Examination: presentation and seminar paper

    ECTS: 5

    Description: The seminar prepares for own research in theoretical econometrics. This seminar covers recent developments inmicroeconometrics with a particular focus on identification and estimation strategies that deal with endogeneity issues.Preference will be given to articles in Econometrica, recently published or forthcoming.Expected Competences acquired after completion of the module:On successful completion of the module, students are expected to attain the following competences:- Attain advanced knowledge in econometric theory.- Attain a higher/advanced level of analytical capability.- To be in a position to exchange information, ideas, and solutions with experts of the field on a scientific level as well aswith laymen.- Ability to communicate precisely in the English specialist language.- Presentation skills.- Attain the level of competence that permits independent undertakings in search of new knowledge in microeconometric theory.

     

    Entwicklungs­ökonomie

    Art und Verwendbarkeit des Moduls: Wahl­veranstaltung im Bachelor-Studien­gang Volkswirtschafts­lehre

    Modul­verantwortliche/r: Prof. Dr. Markus Frölich

    Turnus des Angebots: jedes Semester

    ECTS-Punkte: 6

    Lehr­methode (Umfang): Blockseminar (2 SWS)

    Arbeits­aufwand: Präsenzzeit Seminar: 21 Stunden; Zeit für die Anfertigung der Seminararbeit, für die Vorbereitung der Referate sowie für das Selbststudium 147 Stunden

    Unterrichtssprache: Deutsch

    Teilnahme­voraussetzungen: Grundlagen der Ökonometrie

    Benotung und Vergabe von ECTS-Punkten: schriftliche Seminararbeit, Vortrag, Koreferat, aktive Mitarbeit im Seminar

    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, derDatengrundlage und der Umsetzung der empirischen Herangehensweise.Weitere Informationen: Bitte beachten Sie den gemeinsamen Anmeldezeitraum für Seminare des Bachelor­studien­gangs­VWL: 18. November 2018 (22:00 Uhr) bis 23. November 2018 (24:00 Uhr)

    Erwartete Zahl der Teilnehmer/innen: max. 13

    Ökonometrie und Programmieren / Programming in Stata

    StataInstructor: Alexandra Avdeenko / Dr. Bettina Siflinger

    Offered: FSS 2015

    Method (hours per week): lecture (2)

    Course level: Bachelor

    Course language: English

    Prerequisites: Basic Stata skills of advantage

    Examination: Programming exam, 90 min

    ETCS-Credits: 5

    Course description: The main objective is to give students a practical introduction to econometrics. This course offers an introduction to advanced­programming in Stata. Although Stata already offers a large number of econometric tools, novel approaches are often notavailable and have to be implemented by users. Since comparatively few people know how to do so, Stata programmingskills can be a competitive advantage. The lecture will start with an introduction to efficiently written do-files (including dataprocessing). Different data types will then be presented, i.e. the German Socio-Economic Panel (SOEP). In hands-on sessionsstudents will be taught how to prepare the data for analysis. Variables will be generated and their distributions explored; datawill be merged; and regression results will be critically discussed. Moreover, in this course students will learn how to implementnew commands for Stata and to conduct Monte Carlo simulations. These are important for verification of implementations­and are used as a very important tool to analyse the small sample properties of estimators and to complement the theoreticalproperties of estimators making them an integral part of econometric analyses. We will also touch upon Stata's matrix­programming language Mata. Moreover, we will apply the programming techniques to implement selected cross-section models.