1. 1 MADE STATA Introductory manual

2. 2 MADE QUIZ (for the last time) What are the main OLS assumptions? 1.On average right 2.Linear 3.Predicting variables and error term uncorrelated 4.No serial correlation in error term 5.Homoscedasticity + Normality of error term

3. 3 MADE Regression with STATA Refresh yourself how we did regressions ? –regress gdppc fdi trade inv school2 –regress gdppc fdi trade inv school2, nocons

4. 4 MADE Diagnostics with STATA Normality of the residual –predict e, residual [directly after regress] –sktest e [Jarque-Bery test] RESET test (so-called omitted variables or functional form test) –ovtest, rhs

5. 5 MADE First conclusions There is something wrong with the model specification: –residuals are not normal (although sample is not that small) –some variables seem to demonstrate nonlinearity We need to check if it causes problems for estimation…

6. 6 MADE Diagnostics with STATA Heteroscedasticity –hettest, rhs [Breush-Pagan test]

7. 7 MADE Diagnostics with STATA Heteroscedasticity –imtest, white [White test]

8. 8 MADE Diagnostics with STATA Autocorrelation (we would need time, not this dataset) –tsset t –dwstat [Durbin-Watson test] –bgodfrey, lags(1 2 3) [Breush-Godfrey test]

9. 9 MADE Conclusions Model specification is wrong –sample small and no normality –omitted variable problem –for sure heteroscedasticity (cannot trust standard errors) => There is something very wrong! Solutions –we can use robust estimators, but it will not solve the inconsistency problem –we need a new model specification

10. 10 MADE Diagnostics with STATA Structural stability [Chow test] –gen d=0 –gen dfdi=0 –gen dtrade=0 –gen dinv=0 –replace d=1 if lat<0 (why so????) –replace dfdi=fdi if lat<0 –replace dtrade=trade if lat<0 –replace dinv=inv if lat<0 –reg gdppc fdi trade inv school2 d dfdi dtrade dinv –test (d=0) (dfdi=0) (dtrade=0) (dinv=0)

11. 11 MADE Structure does not seem to be driving this

12. 12 MADE Job for you now S tart thinking –Maybe there are some variables we should include in specification? –Maybe we should start taking logs? –Maybe interactions? –Maybe model should be estimated on subsamples? Try draw ing things to prove your approach