|Kod Erasmus / ISCED:||(brak danych) / (brak danych)|
|Jednostka:||Wydział Nauk Ekonomicznych|
Przedmioty WNE dla programu QPE w Międzydziedzinowej Szkole Doktorskiej (ZIP)
|Punkty ECTS i inne:||
The aim of this course is to familiarize students with the methods used in modern, applied empirical research involving microeconomic data. Topics such as model specification, estimation and inference will be covered for each data type. All lectures will take place in computer lab, and will involve description of the given method and analysis of the case studies to gain a better understanding. This course we will use an open source statistical software, R.
Grades will be based on home assignments and the final test.
1. Course outline, grading. Introduction to R software.
2. Ordinary Least Squares – advantages and disadvantages, limiting conditions
Generalization of the linear model:
3. Heteroskedasticity and quantile regression.
4. Endogeneity and two stage least square methods.
5. Generalized linear models.
Maximum likelihood estimation:
6. Binary models.
7. Inference with MLE: testing hypothesis, marginal effects, elasticities.
8. Random utility model and models for multinomial variables.
9. Models for ordinal variables and count data.
10. Truncation, censoring and sample selection.
11. Sample selection in non-linear models.
12. Endogeneity in non-linear models, control function approach and others.
Simulation and computational methods:
13. Monte Carlo, Bootstrap and Jacknife.
14. Programming and evaluating your own maximum likelihood model.
15. Treatment effect models, difference in differences.
16. Regression Discontinuity.
17. Propensity score matching.
Panel data models:
18. Random and fixed effects models. Random parameters models.
19. Simultaneous equations models.
20. Dynamic panel data models.
21. Unbalanced panel data models.
22. Survival analysis.
23. Factor analysis.
Other possible topics:
24. Bayesian analysis.
25. Semi-parametric, non-parametric methods.
Textbooks - baseline
− Greene, W. H., 2011. Econometric Analysis. 7 Ed., Prentice Hall.
− Cameron, A. C., and Trivedi, P. K., 2005. Microeconometrics: Methods and Applications. Cambridge University Press.
Textbooks – selected topics
− Train, K. E., 2009. Discrete Choice Methods with Simulation. 2 Ed., Cambridge University Press, New York.
− Hensher, D. A., Rose, J. M., and Greene, W. H., 2015. Applied Choice Analysis. 2 Ed., Cambridge University Press, Cambridge.
− Greene, W. H., and Hensher, D. A., 2010. Modeling Ordered Choices: A Primer. Cambridge University Press.
|Efekty uczenia się:||
Completing the course allows participants to familiarize with methods and tools of microeconometrics – both theoretically (rationale, assumptions, theory) and in practice (being able to use them for data analysis – building a model, estimation, interpretation of the results). (P8S_WG, P8S_UW)) The course provides a baseline for using the microeconometric analysis in practice and self-teaching the many extensions. (P8S_UU) The models covered are applied in various fields of microeconomics (analysis of markets, industries, consumers, social research, experimental economics etc.) in which the simple linear regression is inadequate or insufficient.
|Metody i kryteria oceniania:||
1. Completing the course is based on the results of the final written exam (70%) and home assignments (30%).
2. The final grade is calculated using the following formula:
according to the following grading scale:
result (%) grade
3. The final exam includes a theoretical (multiple choice test) and a practical component (problems requiring choosing the right model, building it, estimation and interpretation). The practical part of the exam is ‘open book’ and computer-based.
4. Home assignments consist of solving data analysis problems (individually or in groups, depending on the assignment). Solutions are verified and the most common mistakes are reviewed in class.
5. Attendance is not a requirement for completing the course.
6. All students are subject to the same exam schedule (final and retake). There are no other possibilities to take the exam and complete the course (unless by the Dean’s decision).
7. Missing any of the exams is equivalent of failing it (the ‘NK’ grade).
We enforce the department’s ‘Zero tolerance for cheating’ rules.
Właścicielem praw autorskich jest Uniwersytet Warszawski, Wydział Nauk Ekonomicznych.