# ESF:DXE_EMTR Econometrics - Course Information

## DXE_EMTR Econometrics

**Faculty of Economics and Administration**

Autumn 2024

**Extent and Intensity**- 0/24/0. 12 credit(s). Type of Completion: zk (examination).

Taught in person. **Teacher(s)**- Mgr. Lukáš Lafférs, PhD (lecturer)

doc. Ing. Daniel Němec, Ph.D. (lecturer)

doc. Ing. Štěpán Mikula, Ph.D. (assistant) **Guaranteed by**- doc. Ing. Daniel Němec, Ph.D.

Department of Economics – Faculty of Economics and Administration

Contact Person: Mgr. Lucie Přikrylová

Supplier department: Department of Economics – Faculty of Economics and Administration **Prerequisites**- Course participants should be familiar with linear algebra, probability theory, statistics and econometrics on a basic level.

Linear algebra: Simon, Carl P., and Lawrence Blume. Mathematics for economists. Vol. 7. New York: Norton, 1994. (chapters 8,9,10,11)

Probability theory and statistics: Wooldridge, Jeffrey M. Introductory econometrics: A modern approach. Cengage learning, 2015. (Appendix B, C)

Econometrics: Wooldridge, Jeffrey M. Introductory econometrics: A modern approach. Cengage learning, 2015. (Part I, Glossary) **Course Enrolment Limitations**- The course is only offered to the students of the study fields the course is directly associated with.

**fields of study / plans the course is directly associated with**- there are 26 fields of study the course is directly associated with, display
**Course objectives**- The purpose of this course is to make students familiar with the wide range of econometric topics that they may find relevant throughout their PhD studies. Special emphasis is given on identification and on exploring causal mechanisms from observational data.
**Learning outcomes**- Successful course participant will understand most of the basic tools in the modern econometric toolbox. Participant will be able to critically assess and discuss the validity of the identification setup and empirical estimation strategy.
**Syllabus**- Regression basics: assumptions of the regression model, geometry of linear squares, confidence intervals, purpose: prediction vs explanation, correlated variables, weighted regression, transformations and model selection: bias-variance trade-off
- Logistic regression:
- Statistical inference: Maximum Likelihood - idea, properties, connection to OLS, resampling methods - the Bootstrap
- Causality: potential outcomes, experiment/non-experiment, Directed Acyclic Graphs (DAGs), non-parametric identification via DAGs, quasi-experimental examples, Instrumental variables, source of exogenous variation, Matching, Difference-in-Differences, Regression Discontinuity

**Literature**- Angrist, Joshua D., Guido W. Imbens, and Donald B. Rubin. "Identification of causal effects using instrumental variables." Journal of the American statistical Association 91.434 (1996): 444-455.
- Pearl, Judea. "Causal diagrams for empirical research." Biometrika 82.4 (1995): 669-688.
- Adams, Christopher P. Learning Microeconometrics with R. CRC Press, 2020.
- Hansen, Bruce, Introduction to Econometrics, chapter 10, available at: https://www.ssc.wisc.edu/~bhansen/probability/, 2021
- Hansen, Bruce, Introduction to Econometrics, available at: https://www.ssc.wisc.edu/~bhansen/probability/, 2021
- Hansen, Bruce, Econometrics, available at: https://www.ssc.wisc.edu/~bhansen/probability/, 2021
- Lewbel, Arthur. "The identification zoo: Meanings of identification in econometrics." Journal of Economic Literature 57.4 (2019): 835-903.
- CUNNINGHAM, Scott. Causal inference: The mixtape. Yale University Press, 2021. URL info
- FARAWAY, Julian James.
*Linear models with R*. Second edition. Boca Raton, FL: CRC Press/Taylor & Francis Group, 2014, xii, 274. ISBN 9781439887332. info - WOOLDRIDGE, Jeffrey M.
*Introductory econometrics : a modern approach*. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info

*required literature*- ROSSI, Richard J.
*Mathematical statistics : an introduction to likelihood based inference*. First published. Hoboken, New Jersey: John Wiley & Sons, Inc., 2018, xvii, 422. ISBN 9781118771044. info - ANGRIST, Joshua David and Jörn-Steffen PISCHKE.
*Mostly harmless econometrics : an empiricist's companion*. Princeton: Princeton University Press, 2009, xiii, 373. ISBN 9780691120355. URL info - EFRON, Bradley and Robert TIBSHIRANI.
*An introduction to the bootstrap*. New York: Chapman & Hall, 1993, xvi, 436. ISBN 0412042312. URL info

*recommended literature***Teaching methods**- 12 2-hour lectures (i.e., 24 teaching hours, 45 minutes each)
**Assessment methods**- Three written group-assignments (3*20% = 60%) + Written final exam (40%)
**Language of instruction**- English
**Further Comments**- The course can also be completed outside the examination period.

The course is taught annually.

The course is taught: in blocks.

- Enrolment Statistics (Autumn 2024, recent)
- Permalink: https://is.muni.cz/course/econ/autumn2024/DXE_EMTR