The following material will be covered in the course:
1.Random variables, distributions of random variables, expected value and standard deviation of random variables.
2. Statistical tests of hypotheses.
3. Coding of qualitative information: dummy explanatory variables.
4 Interaction terms as explanatory variables.
5. Conditional expected values and probability distributions.
6Multiple linear regression models: OLS estimators.
7Spurious correlations and the role of "control variables".
8.I How to interpret coefficient estimates: case studies and outputs of statistical packages.
9Hypothesis testing on coefficient estimates: T tests
10. Multicollinearity issues.
Each material covered in the course will be illustrated using a number of case studies, highlighting which specific econometric model is best suited to produce empirical evidence capable of supporting decision making processes in the field of public policies.
PC Softwares for Econometrics:
The course is aimed at teaching students how to use the statistical package STATA to estimate econometrics models. Course outline: 1) STATA windows 2) STATA files: do files, log file and data files 3) STATA commands 4) Data formats 5) Estimation of multiple regression models