Microeconometrics 2400-M1EPMIK

1. Outline, organization and grading. Introduction to Stata.
2. Classical Linear Regression Model assumptions – why do one usually needs some other econometric approach?
3. Accounting for heteroskedascity.
4. Quantile regression. Hedonic price method.
5. Accounting for non-linearities, interactions. Endogeneity and the Instrumental Variable method.
6. Simulation methods – Monte Carlo, Bootstraping, Jackknife.
7. Types of explained variables. Models for binary variables. Maximum Likelihood estimation.
8. Testing hypotheses for ML models.
9. Marginal effects, elasticities, Random Utility Model, non-market valuation methods.
10. Models for multinomial choice.
11. Models for ordered variables. Models for counts.
12. Panel data in microeconometric models. Random parameters models.
13. Models for censored or truncated data, sample selection and stratification.
14. Models for duration, factor analysis, evaluating treatment effects.
15. Overview of other microenometric analysis methods.

Type of course

obligatory courses

Prerequisites (description)

(in Polish) Zakłada się, że student zna i rozumie zagadnienia omawiane w ramach kursów: ekonometria, statystyka, rachunek prawdopodobieństwa, analiza matematyczna, mikroekonomia. Z uwagi na narzędziowy charakter kursu nie jest to niezbędne, ułatwia jednak zrozumienie omawianych zagadnień (i w przeciwnym przypadku wymaga uzupełniania braków na bieżąco

Course coordinators

Wiktor Budziński
Mikołaj Czajkowski

Learning outcomes

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). The course provides a baseline for using the microeconometric analysis in practice and self-teaching the many extensions. 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.
KW01, KW02, KW03, KW04, KW05, KU01, KU02, KU03, KU04, KU05, KU06, KU07, KK01, KK02, KK03

Bibliography

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.
 Cameron, A. C., and Trivedi, P. K., 2011. Microeconometrics Using Stata. 2 Ed., Stata Press.
Textbooks - manuals
 Stata documentation
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.
Textbooks - other
 Wooldridge, J. M., 2012. Introductory Econometrics: A Modern Approach. 5 Ed., Cengage Learning.
 Wooldridge, J. M., 2010. Econometric Analysis of Cross Section and Panel Data. 2 Ed., The MIT Press.
 Gujarati, D., and Porter, D., 2008. Basic Econometrics. 5 Ed., McGraw-Hill/Irwin.
 Gujarati, D., 2011. Econometrics by Example. Palgrave Macmillan.
 Durlauf, S. N., and Blume, L. E., 2009. Microeconometrics. Palgrave Macmillan.

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 2400-M1EPMIK in USOSweb