The slides used during classes, sketches of training sessions, exercises solutions and mock exams will be made available for download from Virtuale.
Argomenti del programma: This course is taught entirely in English. Requirements The course assumes familiarity with introductory calculus, linear algebra, probability, and statistics. Basic knowledge of microeconomics is recommended. All empirical applications are implemented using the statistical software R.
The material (articles, commented notes & slides, programs and data-sets) will be distributed during the lectures and make available on the platform Virtuale.
Argomenti del programma: Learning objectives: at the end of this course, students will be able to: 1. Understand the role and importance of econometrics in economic analysis. 2. Formulate and estimate linear regression models. 3. Perform hypothesis testing and interpret statistical significance. 4. Identify and correct common econometric problems such as multicollinearity, heteroskedasticity, and endogeneity. 5.
The slides used during classes, sketches of training sessions, exercises solutions and mock exams will be made available for download from Virtuale.
Argomenti del programma: This course is taught entirely in English. Requirements The course assumes familiarity with introductory calculus, linear algebra, probability, and statistics. Basic knowledge of microeconomics is recommended. All empirical applications are implemented using the statistical software R.
Additional material will be made available to enrolled students on the Virtuale Platform.
Argomenti del programma: IMPORTANT INFORMATION FOR INCOMING STUDENTS .The course requires prerequisite knowledge in descriptive statistics, probability and statistical inference (see the EPOS course Statistics and Programming as an example) 1. Introduction to the course: Economic questions and data 2. Review of probability and statistics 3. Linear regression model with one regressor 4. Linear regression model with multiple regressors 5.
Libri Universitari