Applied Econometrics: Policy Evaluation

Teachers

Included in study programs

Teaching results

Knowledge
Students will gain knowledge of modern methods of research design for estimating the causal effects of measures, programs and policies.
Students will master and understand the estimators for pooled cross-section data and panel data, as well as the estimator of instrumental variables.
Skills
Students will acquire advanced skills for the use of modern software (e.g. Stata) in empirical economic research, will be able to write scripts and program more advanced analyzes.
Competencies
Students will be able to formulate an economic problem and propose a research design for its examination through empirical analysis, formulate hypotheses and analytically confirm or reject them.
Students will be able to independently develop their knowledge in the field of econometrics and the use of modern software, will understand the empirical article on applied econometrics for policy evaluation and will be able to use them in new contexts.

Indicative content

1. Basic concepts, e.g. causality, bias, ceteris paribus.
2. Research design, identification strategies, estimator.
3. Randomized controlled trials.
4. Multiple linear regression.
5. Omitted-variable bias.
6. Instrumental variables.
7. IV estimator and two-Stage least squares (2SLS) regression analysis.
8. Regression discontinuity design.
9. Diff-in-Diff estimator.
10. Estimates using pooled cross-section and panel data for evaluating policy effects.
11. Synthetic Control Method.
12. Non-standard standard errors.

Support literature

Cunningham, S., 2021. Causal inference: The mixtape. Yale University Press.
Angrist, J.D. and Pischke, J.S., 2014. Mastering 'metrics: The path from cause to effect. Princeton University Press.
Wooldridge, J.M., 2016. Introductory econometrics: A modern approach. Nelson Education.
Angrist, J.D. and Pischke, J.S., 2008. Mostly harmless econometrics: An empiricist's companion. Princeton university press.

Requirements to complete the course

20 % - activity and tests during seminars
20 % - assignments
60 % - final exam

Student workload

156 (participation in lectures 26, participation in seminars 26, preparation for seminars 26, elaboration of assignments 26, preparation for the final exam 52)

Language whose command is required to complete the course

English

Date of approval: 12.03.2024

Date of the latest change: 11.02.2022