Quantitative research methods in economy 2

Garant předmětu:

Lecturer:

Tutor:

Supervisor:

Department of Economics, Management and Humanities

Synopsis:

This course should be a sequel to the basic Econometrics (Basic statistical methods and Linear regression model). It assumes familiarity with the general linear model and knowledge how to deal with basic model and data deficiencies, simultaneous systems, and simple time-series processes. Advanced Econometrics is the next course in a sequence (MA course(s) in Statistics and on Regression) designed to introduce tools necessary to understand and implement empirical studies in (micro)economics. The main emphasis of the course is twofold: (i) to extend regression models in the context of cross section and panel data analysis, (ii) to focus on situations where linear regression models are not appropriate and to study alternative methods. The objective of the course is to expose the student to variety of basic applied microeconomic challenges with the ultimate goal of gaining a stronger appreciation of strengths and weaknesses of the econometric methodology. Examples from applied work will be used to illustrate the discussed methods. Selected topics from advanced econometrics will be covered as well.

Requirements:

Syllabus of lectures:

1. Review of basic linear regression model and introduction to maximum likelihood estimation and hypothesis testing

2. Generalised linear regression model – GLS and FGLS, Cholesky decomposition

3. Generalised linear regression model – SURE and example of a singular system

4. Generalised linear regression model – Panel data analysis, Fixed effects model, random effects model, Hausman test

5. Cases where residuals and regressors are correlated – Misspecification, Errors in variables

6. Cases where residuals and regressors are correlated – Unobserved fixed effect in panel data analysis, Simultaneity, Lagged dependent variables and serial correlation

7. Cases where linear regression models are not appropriate (nonlinear models) – Maximum likelihood estimation

8. Nonlinear models – estimation and testing

9. Nonlinear models – Qualitative response models, Tobit model

10. Self-selection models, Heckmann two-step estimation and MLE

11. Ordered Multinomial Models, Unordered Multinomial Models

12. Duration analysis

13. Various advanced topics – LAD estimation, Bootstrap

14. reserve

Syllabus of tutorials:

Study Objective:

Study materials:

Obligatory:

1. William Greene, Econometrics Analysis, NY, Macmillan Publishing Company, 5th edition or newer (8th).

2. J.M. Wooldridge, Econometric Analysis of Cross Section and Panel Data, MIT Press, 2002

Elective:

3. G.S. Maddala, Limited dependent and Qualitative Variables in Econometrics, Cambridge University Press, 1983 or newer edition

4. L. Matyas and P. Severstre, The Econometrics of Panel Data, Kluwer Academic Publishers, 1992, or 2008.

5. Jan Kmenta, Elements of Econometrics, Macmillan, NY, 1990.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Doctoral studies, daily studies (compulsory elective course)
• Doctoral studies, combined studies (compulsory elective course)