ECONOMETRIC METHODS (bachelor studies)

CURRENT INFORMATION:

  • The lectures in Winter semester 2024/25: October 3, 10, 17, 24, 31; November 7, 14, 21, 28; December 5, 12, 19; January 9, 16.
# Topic Files Literature
1 OLS - derivations and assumptions R code
CSV data		 Greene
Chapter - The Classical Multiple Linear Regression Model
Chapter - Least Squares
Chapter - Statistical Properties of the Least Squares Estimator
2 Restrictions. Stability R code
CSV data		 Greene
Chapter - Inference and Prediction, Sections 3-5
Chapter - Functional Form and Structural Break
3-4 Maximum Likelihood Estimation R code
RData file		 Greene
Chapter - Maximum Likelihood Estimation
5-6 Serial correlation R code
CSV data
CSV data - exercise 1
CSV data - exercise 2		 Greene
Chapter - Serial Correlation
7 Heteroskedasticity R code
CSV data		 Greene
Chapter - Generalized Regression Model and Heteroscedasticity
8 COMFAC analysis R code
CSV data		 Greene
Chapter - Models With Lagged Variables
9 Nonstationarity. Error correction model R code
CSV data
 Greene
Chapter - Models With Lagged Variables
Chapter - Time-Series Models
Chapter - Nonstationary Data
10 Generalized method of moments R code
CSV data		 Greene
Chapter - Minimum Distance Estimation and the Generalized Method of Moments
Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, vol. 44(2), pages 195-222

GENERAL INFORMATION: