Modern econometric analysis 1

Subject description

Empirical regression and the algebra of least squares.
The classical linear regression model and its generalization.
The likelihood function, statistical distributions and testing principles.
Asymptotic analysis: Stochastic convergence and asymptotic properties of estimators.
Estimation and testing in the generalized regression model.

The subject is taught in programs

Objectives and competences

The students will obtain advance and competitive knowledge and skills for modern econometric analysis. They will be able to apply this knowledge to the investigation of various processes, and also understand the econometric methods, approaches, ideas, results and conclusions met in the most sophisticated books and articles. The course will focus on modern econometric methods. The students should get the skills for construction and development of complex econometric models. The considered methods and models will be mastered theoretically and illustrated practically on real data bases with modern econometric software.

Objectives and competences of the course are thus the following:

To improve and expand the knowledge of quantitative skills with advanced econometric methods.
To master the theoretical fundations of econometric methods.
To develop the skills for scientific research work in the field.
To obtain the skills necessary for the application of theoretical concepts.
To develop the capabilities to choose appropriate methodology for the analysis of the studied relationships.
To develop capabilities for interpretation of the results.

Teaching and learning methods

Lectures.
Seminars.
Computer labs.
Consultations.

Expected study results

The course expands and enriches the knowledge of contemporary quantitative methods for detection and analysis of developments in various fields. It is intended for comprehension of procedures for facing various theories with the data, i.e. for quantitative estimation and measurement of theoretical concepts. The expertise of modern advanced econometric methods and procedures enables testing of numerous hypotheses based on real data. Quantitatively measured concepts can thus directly facilitate decision-making and concucting of policies at all levels of the decision-making process.

The emphasis of the course will be given on generalizing the classical linear regression model, estimating regression models with various estimators, asymptotic analysis, and testing in the generalized regression model.

Comprehension of theoretical fundaments of the discussed methods and procedures develops critical thinking. First and foremost, a sufficient level of critical thinking should be developed for the interpretation of findings and suitability assessment of decision-making, based on such findings. A comprehensive knowledge of modern advanced econometric methods enables fast and efficient testing of various relationships. It can thus be used for application of the most efficient and effective decisions and mesures.

Basic sources and literature

Bierens, H. J.: Introduction to the Mathematical and Statistical Foundations of Econometrics. Cambridge: Cambridge University Press, 2005.
Davidson, R., MacKinnon, J. G.: Econometric Theory and Methods. Oxford: Oxford University Press, 2004.
Davidson, R., MacKinnon, J. G.: Estimation and Inference in Econometrics. Oxford: Oxford University Press, 1993.
Greene, W. H.: Econometric Analysis: Seventh Edition. New Jersey: Prentice Hall, 2012.
Hansen, B. E.: Econometrics. Madison, WI: University of Wisconsin, Department of Economics, 2014.
Hayashi, F.: Econometrics. Princeton, NJ: Princeton University Press, 2000.
Pindyck, R. S., Rubinfeld, D. L.: Econometric Models and Economic Forecasts: Fourth Edition. Boston, MA: Irwin/McGraw-Hill, 1998.
Ruud, P. A.: An Introduction to Classical Econometric Theory. Oxford: Oxford University Press, 2000.
Verbeek, M.: A Guide to Modern Econometrics: Third Edition. Chichester: John Wiley & Sons, 2008.