This mode is very flexible and the presence in the lecture room can vary between 0% - 100%.
Syllabus
Registration via LPIS
Research Seminar in Main Subject I - Economics
Research Seminar in Main Subject I - Empirical Business Research
Research Seminar in Main Subject II - Economics
Research Seminar in Main Subject II - Empirical Business Research
Research Seminar in Main Subject III - Economics
Research Seminar in Main Subject III - Empirical Business Research
Research Seminar in Main Subject IV - Economics
Research Seminar in Main Subject IV - Empirical Business Research
Dissertation-relevant theories - Economics
Dissertation-relevant theories - Empirical Business Research
Research Seminar - Economics
Research Seminar - Empirical Business Research
Research Seminar - Economics
Research Seminar - Empirical Business Research
Academic Writing
Methodology and Theory
Research Seminar - Participating in scientific discourse I
Research Seminar - Participating in scientific discourse II
Day | Date | Time | Room |
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Friday | 10/23/20 | 08:00 AM - 11:00 AM | TC.4.14 |
Friday | 10/30/20 | 08:00 AM - 11:00 AM | TC.4.14 |
Friday | 11/13/20 | 08:00 AM - 11:00 AM | TC.4.14 |
Friday | 11/20/20 | 08:00 AM - 11:00 AM | Online-Einheit |
Friday | 11/27/20 | 08:00 AM - 11:00 AM | Online-Einheit |
Friday | 12/04/20 | 08:00 AM - 11:00 AM | Online-Einheit |
Friday | 12/11/20 | 08:00 AM - 11:00 AM | Online-Einheit |
Friday | 12/18/20 | 08:00 AM - 11:00 AM | Online-Einheit |
On this page:
- Contact details
- Procedure for the course when limited activity on campus
- Contents
- Learning outcomes
- Attendance requirements
- Teaching/learning method(s)
- Assessment
- Prerequisites for participation and waiting lists
- Recommended previous knowledge and skills
- Availability of lecturer(s)
- Readings
- Unit details
In case of limited activity on campus we will switch to a rotation mode.
A microsoft teams access will be created before the first class, so that students can also participate online. Microsoft Teams is used flexibly, either at the lecturer's desk in the lecture room (or - if it is not allowed to enter the lecture rooms - in the home office). The screen of the lecturer's desk is shared between the students in the lecture room and those at home. For the students in the lecture room, the lecturer's PC projects onto the whiteboard; students at home need their own laptop (tablet), with which MS-Teams can share the screen. The sound is transmitted from the lecture room via a microphone to the students in the home office. (It is not intended / necessary to film the lecturer.)
This course examines econometric identification issues in empirical microeconomics and public policy analysis. It supplements topics covered in Econometrics with a focus on the sensible application of econometric methods to empirical problems. The course provides background on issues that arise when analyzing non-experimental social science data and a guide for tools that are useful for applied research and policy analysis. The course also emphasizes how a basic understanding of economic theory and institutions can help inform the analysis.
By the end of this course, students will:
- have a firm grasp of the types of research design that can lead to convincing analysis,
- understand threats to uncovering causal effects from economic data
- be able to apply a range of microeconometric tools and interpret results
- be encouraged to develop independent research interests and applied research projects.
Attendance in class is compulsory. Students who miss a class must send an excuse by email.
Readings for each week will be assigned one week in advance. Students are expected to read the material in advance and be prepared for class discussions.
Students give short presentations of papers assigned for reading
2-3 problem sets will be posted on the course website over the term.
Final grades are based on
- Problem sets: in total 20%
- Participation in class discussions: 15%
- Student presentations: 15%
- Final exam: 50%
Prerequisites are MA level courses in Econometrics and Microeconomics
Recommended knowledge of basic data handling skills and Stata (or similar programming package)
Knowledge in one or more fields of applied microeconomics, such as labor economics, public finance, development economics, industrial organization etc.
Unit | Date | Contents |
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1 | 10/23/20 | Introduction Decomposition Methods Reading (still preliminary): DiNardo, Fortin and Lemieux (1996) Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach, Econometrica, Vol 64, 1001-1044. Fortin, Nicole, Thomas Lemieux, and Sergio Firpo (2011) “Decomposition Methods in Economics”, Handbook of Labor Economics (Volume 4A) Bell, Brian, Michael Böhm, Nicole Fortin (2017) “Top Earnings Inequality and the Gender Pay Gap: Canada, Sweden, and the United Kingdom” working paper. Kline, Patrick, (2011) “Oaxaca-Blinder as a Reweighting Estimator”, American Economic Review: Papers and Proceedings, 101, pp. 532-537 |
2 | 10/30/20 | Linear Regression, Propensity Scores, Matching Reading (still preliminary): Mostly Harmless Econometrics, Chapter 3
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3 | 11/13/20 | Fixed Effects and Panel Data Methods, Differences-in-Differences, Event Study Designs Reading (still preliminary): Mostly Harmless Econometrics, Chapter 5
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4 | 11/20/20 | Synthetic Control Methods Clustering Standard Errors Reading (still preliminary): Abadie, A., M. M. Chingos, and M. R. West “Endogenous stratification in randomized experiments”. Working Paper 2017. A. Abadie, A. Diamond, J. Hainmueller “Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program, Journal of the American Statistical Association, Vol. 105, No. 490, June 2010. A. Abadie, A. Diamond, J. Hainmueller “Comparative Politics and the Synthetic Control Method”, American Journal of Political Science, Vol. 59, No. 2, April 2015, Pp. 495–510. G. Peri, V. Yasenov, “The Labor Market Effects of a Refugee Wave: Synthetic Control Method Meets the Mariel Boatlift”, IZA Discussion Paper 10605, 2017. Marianne Bertrand, Esther Duflo, and Sendhil Mullainathan. How much should we trust differences-in-differences estimates? The Quarterly Journal of Economics, 119(1):249–275, 2004. Abadie, Athey, Imbens, Wooldridge “When Should We Adjust Standard Errors for Clustering?”, Working paper, 2017. |
5 | 11/27/20 | Instrumental Variables Estimation, Control Functions, Local Average Treatment Effects, Marginal Treatment Effects Reading (still preliminary)
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6 | 12/04/20 | Regression Discontinuity Designs Imbens, Guido W. and Thomas Lemieux (2008) "Regression Discontinuity Designs: A Guide to Practice" Journal of Econometrics, 142, 615-635. David S. Lee and Thomas Lemieux (2010) "Regression Discontinuity Designs in Economics" Journal of Economic Literature, 48, 281-355. David Card, Raj Chetty, Andrea Weber, (2007), "Cash-on-Hand and Competing Models of Intertemporal Behavior: New Evidence from the Labor Market", Quarterly Journal of Economics, 122(4), 1511-1560 Thistlethwaite and Campbell (1960) “Regression-Discontinuity Analysis: An Alternative to the Ex-Post Facto Experiment” Van der Klaaw (2002) “Estimating the Effect of Financial Aid Offers on College Enrollment: A Regression-Discontinuity Approach” International Economic Review,Vol 43(4). Angrist, Joshua D. and Victor Lavy (1999) “Using Maimonides’ Rule to Estimate the Effect of Class Size on Scholastic Achievement” The Quarterly Journal of Economics, 114, 533-575. Miguel Urquiola and Eric Verhoogen (2009), “Class-Size Caps, Sorting, and the Regression-Discontinuity Design”, American Economic Review, 99:1, 179–215.
Alex Solis (2017) “Credit Access and College Enrollment”, Journal of Political Economy 125, no. 2: 562-622. McCrary, Justin (2008) “Manipulation of the running variable in the regression discontinuity design: A density test”, Journal of Econometrics, 142, 698–714. Card, David and David S. Lee (2005) “Regression Discontinuity Inference with Specification Error”, Journal of Econometrics, 142(2) 655-674. Calonico, S., Cattaneo, M. D., and Titiunik, R. (2014), “Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs”, Econometrica, 82, 2295 – 2326. Calonico, S., Cattaneo, M. D., and Titiunik, R. (2014), “Robust Data-Driven Inference in the Regression-Discontinuity Design?” Stata Journal, 14, 909 - 946. Calonico, S., Cattaneo, M. D., and Titiunik, R. (2015), “Optimal Data-Driven Regression Discontinuity Plots”, JASA, 110, 1753 - 1769 |
7 | 12/11/20 | Regression Kink Designs Reading (still preliminary):
Card, David, David Lee, Zhuan Pei and Andrea Weber (2017) “Regression Kink Design: Theory and Practice”, Advances in Econometrics, volume 38, 341 – 382. Card, David, Andrew Johnston, Pauline Leung, Alexandre Mas, and Zhuan Pei, (2015) “The Effect of Unemployment Benefits on the Duration of Unemployment Insurance Receipt: New Evidence from a Regression Kink Design in Missouri, 2003-2013,” American Economic Review: Papers and Proceedings, 105 (5), 126–130. NBER Working Paper 20869
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8 | 12/18/2020 | Final Exam |
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