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Předmět, akademický rok 2023/2024
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Applied Microeconometrics - JEM007
Anglický název: Applied Microeconometrics
Zajišťuje: Institut ekonomických studií (23-IES)
Fakulta: Fakulta sociálních věd
Platnost: od 2020
Semestr: letní
E-Kredity: 6
Způsob provedení zkoušky: letní s.:
Rozsah, examinace: letní s.:2/2, Zk [HT]
Počet míst: 40 / 40 (40)
Minimální obsazenost: neomezen
4EU+: ne
Virtuální mobilita / počet míst pro virtuální mobilitu: ne
Stav předmětu: vyučován
Jazyk výuky: angličtina
Způsob výuky: prezenční
Způsob výuky: prezenční
Poznámka: předmět je možno zapsat mimo plán
povolen pro zápis po webu
při zápisu přednost, je-li ve stud. plánu
Garant: Mgr. Barbara Pertold-Gebicka, M.A., Ph.D.
Vyučující: Mgr. Barbara Pertold-Gebicka, M.A., Ph.D.
MA Salim Turdaliev
Třída: Courses for incoming students
Anotace -
Poslední úprava: Mgr. Barbara Pertold-Gebicka, M.A., Ph.D. (13.02.2023)
- Are you writing or plan to write an applied Master's thesis using cross-sectional data?
- Do you know that correlation does not imply causation, but do not know how to identify causality?
- Do you like connecting Econometrics and economic theory?

During the Applied Microeconometrics course you will learn how to let the data talk and will get familiar with several econometric methods useful for estimating causal effects of individuals', firms' or states' decisions. For example:
"Did the marketing campaign increase firm's profits?... or was it just implemented at the time when firm's profits were rising?"
"What was the effect of introducing joint taxation of married couples?"
"Did limitation of cigarettes advertising lead to less smoking?... or would the incidence of smoking fall even without this policy?
"Do incumbent politicians have an advantage over runner-ups?... or voters chose them in previous elections and will choose them again simply because they are better?
"Does studying at a high quality college lead to higher earnings?... or is it just that students from richer families can afford better colleges?"

Podmínky zakončení předmětu -
Poslední úprava: Mgr. Barbara Pertold-Gebicka, M.A., Ph.D. (13.02.2023)

To pass the course students need to:

• Critically summarize one research topic (30 points)
   detailed setup will be announced in mid March, with deadline 14 days later
   generally, the task will be to write a review of a specific research paper 

• Complete a home assignment (30 points)
   detailed setup will be announced in mid April, with the deadline 14 days later
   generally, the task will be to replicate an empirical research using available data

• Complete an Econometric Game - a project-based final exam (40 points)
   This is a take-home exam designed in a form of a short research preject.
   The setup will be anounced early May and students will present the outcome of their analysis during the last week of classes.
   Final projects in written form will be due by the end of May.

Literatura -
Poslední úprava: Mgr. Barbara Pertold-Gebicka, M.A., Ph.D. (13.02.2023)

Main inspiration:

Abadie, A., & Cattaneo, M. D. (2018). Econometric methods for program evaluation. Annual Review of Economics10, 465-503.

Readings for individual lectures:

1. Lewis, R. A., & Reiley , D. H. (2014). Online ads and offline sales: measuring the effect of retail advertising via a controlled experiment on Yahoo!. Quantitative Marketing and Economics 12 (3), 235 266. field experiment, different methods of analyzing experimental data

2. Kalíšková, K. (2014). Labor supply consequences of family taxation: Evidence from the Czech Republic. Labour Economics30, 234-244.  difference-in-differences and triple difference analysis using a natural experiment

3. Bertrand, M., Duflo, E., & Mullainathan, S. (2004). How much should we trust differences-in-differences estimates?. The Quarterly journal of economics119(1), 249-275.   difference-in-differences estimation

4. Donald, S. G., & Lang, K. (2007). Inference with difference-in-differences and other panel data. The review of Economics and Statistics89(2), 221-233.  difference-in-differences estimation and other cases with multi-level data

5. Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program. Journal of the American statistical Association105(490), 493-505.  synthetic control method

6. Priebe, J. (2020). Quasi-experimental evidence for the causal link between fertility and subjective well-being. Journal of Population Economics33(3), 839-882.  instrument, estimating local average treatment effect (LATE)

7. Lee, D. S., & Lemieux, T. (2010). Regression discontinuity designs in economics. Journal of economic literature48(2), 281-355.  regression discontinuity designs

8. Lee, D. S. (2008). Randomized experiments from non-random selection in US House elections. Journal of Econometrics142(2), 675-697.  sharp regression discontinuity design (sharp RDD)

9. De Paola, M., & Scoppa, V. (2014). The effectiveness of remedial courses in Italy: a fuzzy regression discontinuity design. Journal of Population Economics27, 365-386.   fuzzy regression discontinuity design (fuzzy RDD)

10. Black, D. A., & Smith, J. A. (2004). How robust is the evidence on the effects of college quality? Evidence from matching. Journal of econometrics121(1-2), 99-124.  matching estimator and its comparison to OLS

Sylabus -
Poslední úprava: Mgr. Barbara Pertold-Gebicka, M.A., Ph.D. (13.02.2023)

Lecture 1 (Tuesday, February 14, 12:30) - Introduction to the course, example of an empirical analysis inspired by one research paper

Lecture 2 (Tuesday, February 21, 12:30) – Microeconometric analysis - data sources, usual empirical problems, introduction to identification strategies

       Seminar 1 (Thursday, February 22, 15:30) - Introduction to Stata

Lecture 3 (Tuesday, February 28, 12:30) - Controlled experiments

Lecture 4 (Tuesday, March 7, 15:30) - Natural experiments I - difference-in-differences estimation

       Seminar 2 (Thursday, March 9, 15:30) - Applying difference-in-differences in practice

Lecture 5 (Tuesday, March 14, 12:30) - Difference-in-differences continued - triple difference, robustness

Lecture 6 (Tuesday, March 21, 12:30) - Synthetic control function

       Seminar 3 (Thursday, March 23, 15:30) - Applying synthetic control function in practice
Lecture 7 (Tuesday, March 28, 12:30) - Natural experiments II - natural experiments as instruments

       Seminar 4 (Thursday, March 30, 15:30) - instrumental variable estimation in Stata, checking quality of instruments

Lecture 8 (Tuesday, April 4, 12:30) - Further issues with instrumental variable estimation

Lecture 9 (Tuesday, April 11, 12:30) - Regression discontinuity - sharp

Lecture 10 (Tuesday, April 18, 12:30) – Regression discontinuity - fuzzy

       Seminar 5 (Thursday, April 20, 15:30) - applying regression discontinuity in practice - randomization checks, method choice, etc.

Lecture 11 (Tuesday, April 25, 12:30) – Matching models 
Lecture 12 (Tuesday, May 2, 12:30) -  Matching models

        Seminar 6 (Thursday, May 4, 15:30) – matching models in practice

Lecture 13 (Tuesday, May 9, 12:30) – Student presentations: final projects

       Seminar7 (Thursday, May 11, 15:30) – Student presentations: final projects

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