Econometrics 2600-DSFRz2EKON
1. The subject of econometrics. Economic theory and the econometric model.
2. Classical Least Squares estimation (LS) - fitting the linear model to the observation. Model with one explaining variable and many explaining variables.
3. Measures of model fit and interpretation of model parameters - linear relationship (including for transformed variables). Analysis of variance.
4. Statistical inference in LS. Assumptions about the distribution of the random error. The t and F statistical tests.
5. Methods of selecting explanatory variables for the econometric model. Initial analysis of statistical data. Binary variables in the model. Outliers - detection of their presence in the data set and methods of proceeding.
6. LS: assumptions, properties of the LS estimator, efficiency of the LS estimator: Gauss-Markov theorem.
7. Diagnostic tests - testing of the functional form, normality of distribution, stability of parameters, homoscedasticity, autocorrelation.
8. Basic problems of estimation using LS - omitted variables, insignificant variables, collinearity, simultaneity.
9. Nonlinear models. Methods of selecting the analytical form of the model. Methods of estimating nonlinear models.
Type of course
Prerequisites (description)
Course coordinators
Learning outcomes
in terms of knowledge:
• identifies methods of verifying econometric models, including diagnostic tests (normality of distribution, autocorrelation, homoscedasticity) (K_W01)
• explains the importance of model fit measures and model parameters for the analysis of economic and financial phenomena (K_W01)
• estimates econometric models using the classical least squares method (LSM), both for models with one and multiple explanatory variables (K_U02)
• interprets parameters of econometric models, (including applying model fit measures and analyzing variance and dependencies between variables (K_U02)
• applies diagnostic tests to verify the correctness of econometric model assumptions, such as tests of normality of distribution, autocorrelation, homoscedasticity (K_U02)
• selects explanatory variables for the econometric model (K_U02)
• uses econometric software, such as GRETL, for the construction and analysis of econometric models (K_U03)
in the scope of social competences:
• critically evaluates the quality and adequacy of econometric models used in the analysis of economic and financial phenomena (K_K01)
Assessment criteria
Final project
Points / grade
Above 50% points
Bibliography
Primary:
Borkowski B., Dudek H., Szczesny W., Ekonometria, wybrane zagadnienia. PWE, Warszawa 2003 i dalsze wydania.
Kufel T. Ekonometria Rozwiązywanie problemów z wykorzystaniem programu GRETL, PWN, Warszawa, wyd. 3, 2020.
Lipiec-Zajchowska M. Wspomaganie procesów decyzyjnych. Tom II. Ekonometria Beck 2003.
Complementary:
Gajda J., Ekonometria praktyczna, Absolwent, Łódź 1996.
Gruszczyński M. i In., Ekonometria i badania operacyjne, PWN, Warszawa, 2009.
Turyna B., Statystyka dla ekonomistów, Difin, Warszawa, 2011.
Greene W.H. Econometric Analysis, Prentice-Hall, 2006 (and next issues)
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: