G30 Econometrics I
| 1st | October | 3rd | Guidance, matrices | |
| 2nd | 16th | Matrices, OLS as an algebraic tool | ||
| 3rd | 23rd | Cancelled | ||
| 4th | 30th | The linear regression model, small sample properties of the OLS estimator | ||
| 5th | November | 6th | Small sample properties of the OLS estimator, goodness-of-fit, hypothesis testing | |
| 6th | 13th | Hypothesis testing, asymptotic properties of the OLS estimator | ||
| 7th | 20th | Multicollinearity, prediction, interpreting the linear model | ||
| 8th | 27th | Selecting the set of regressors, misspecifying the functional form, explainig house prices | ||
| 9th | December | 4th | Heteroskedasticity and autocorrelation, consequences for the OLS estimator, | |
| deriving an alernative estimator, heteroskedasticity | ||||
| 10th | 11th | Heteroskedasticity, testing for heteroskedasticity, illustration, autocorrelation | ||
| 11th | 18th | Autocorreltion, testing for first-order autocorrelation, illustration, | ||
| alternative autocorrelation patterns | ||||
| 12th | 25th | What to do when you find autocorrelation?, endogeneity, instrumental variables and GMM, | ||
| a review of the properties of the OLS estimator, cases when the OLS estimator cannot be saved | ||||
| 13th | January | 22th | Cases when the OLS estimator cannot be saved, the instrumental varibles estimator | |
| 14th | 29th | The instrumental variables estimator, an introduction to maximum likelihood | ||
| 15th | February | 5th | Cancelled |