Y2 - Introduction to Econometrics

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1. Week 1:
2. L1: Methods and exercises
3. 1.1. What is scientific research?
4. 1.2. Exercise on scientific learning
5. 1.3 Association versus causal effect
6. 1.4. Types of data and unit of analysis
7. 1.5. Operationalization and conceptualization: methods and exercise.
8. L2: OLS-simple linear regression estimation and goodness of fit
9. 2.1. Simple linear regression model: brief introduction and some examples
10. 2.2. Finding out about relationships between varaibles: graphs covariance and correlation
11. 2.3. The linear regression model
12. 2.4. Estimation of coefficents of regression model: the OLS estimator
13. 2.5. Comparing correlation with linear regression model
14. 2.6. OLS practical example
15. 2.7. Goodness of fit measures: R^2 and SER
16. Exercises 2.1. Introduction to Stata
17. Exercises 2.2. First part of Emprical exercise 4.2 of the book
18. L3: OLS-simple linear regression assumptions and properties
19. 3.1. OLS: Introduction assumptions
20. 3.2. OLS assumption 1: Zero Conditional Mean
21. 3.3. OLS assumption 2: Independent and identically distributed observations
22. 3.4. OLS assumption 3: Large outliers in X and Y are unlikely
23. 3.5. Sampling distribution of OLS estimators (if assumptions hold)
24. 3.6. Property of OLS estimators: Mean of OLS estimator and unbiasedness
25. 3.7. Property of OLS estimators: variance of estimators and consistency
26. Exercises 3. 2nd part of the Empirical Exercise 4.2. of the book