Microeconometrics

obligatory courses

(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

The aims at familiarizing participants with the methods of contemporary microeconometrics and developing the ability to use them in practice (the choice of a model and its specification, estimation, interpretation, inference). Tutorials take place in computer lab. They include the overview of the methods that are being introduced and practical exercises in their application – solving real-life econometric analysis problems. The statistical package used in this tutorial is Stata.

Completing the course is based on the final exam (70%) and homework assignments – econometric analysis problems requiring applying the methods introduced in class (30%).

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.

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.

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