1. SylabUZ
2. Wydział Matematyki, Informatyki i Ekonometrii
3. semestr zimowy 2023/2024
4. Mathematics - drugiego stopnia z tyt. magistra
5. Econometrics

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Econometrics - opis przedmiotu

Cel przedmiotu

To familiarize the student with basic analysis methods in linear regression models.

Wymagania wstępne

Zapisz zmiany

The student is required to have knowledge of linear algebra, probability theory and mathematical statistics.

Zakres tematyczny

Lecture/Class/Laboratory

1. Recalling the definition of a classic linear model with many explanatory variables, its matrix form and model assumptions. The form of the least squares estimator of the vector of structural parameters and the unbiased estimator of the variance of the random component.
2. Generalized linear model. Linear equation with respect to parameters. Polynomial model.
3. Methods of selecting variables for the model based on the maximum likelihood method.
4. Generalized least squares method. Estimation of the vector of model structural parameters and the variance of the random component.
5. First order autocorrelation model.
6. Qualitative variables. Analysis of variance models. Taking into account the periodicity of the studied phenomenon.

Metody kształcenia

Conventional lecture. Exercises in which students solve tasks from a prepared list. During the laboratory, students become familiar with the functions enabling them to perform appropriate analyses, and then receive data for independent work.

Efekty uczenia się i metody weryfikacji osiągania efektów uczenia się

Opis efektu	Symbole efektów	Metody weryfikacji	Forma zajęć

Warunki zaliczenia

Lecture grade based on exam. The grade for the exercises is based on the results from the test and activity during classes. The laboratory grade is based on tests to determine the degree of mastery of statistical tools and the ability to draw correct conclusions based on the obtained analysis results.
The final grade for the course consists of the grade for the exercises (35%), the grade for the laboratory (35%) and the grade for the exam (30%). The condition for taking the exam is a positive grade from the exercises and a positive grade from the laboratory. The condition for passing the course is obtaining positive grades from exercises, laboratory and lecture.

Literatura podstawowa

1. A. S. Goldberger, Econometric Theory, Wiley, New York 1964.

2. J. Faraway, Linear Models with R, Chapman & Hall/CRC Texts in Statistical Science, Boca Raton Florida 2005. 

3. G. S. Maddala, Introduction to Econometrics. 2nd Edition, Macmillan Publishing Company, New York 1992.

4.. W. H. Greene  Econometric Analysis, Prentice Hall, Inc., New Jersey 2000.

5. G. A. F. Seber. Linear regression Analysis. John Wiley&Sons, New York 1977.

6.  G. A. F. Seber, Linear Regression Analysis, John Wiley & Sons,New York 1977. 

Literatura uzupełniająca

1. H. Varian, Macroeconometric Analysis, Norton, NewYorl-London 1992.

2.C. R. Rao, Linear Statistical Inference and its Applications, New York 1965.

Uwagi

Zmodyfikowane przez dr Ewa Sylwestrzak-Maślanka (ostatnia modyfikacja: 10-04-2024 16:07)