| Weeks | Topics |
| 1 |
Dummy variable regression models
i) ANOVA models, ii) ANCOVA models, iii) The interpretation of dummy variables
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| 2 |
Multicollinearity
i) estimation in the presence of perfect muticollinearity, ii) estimation in the presence of high but imperfect muticollinearity iii) consequences of using OLS in the presence of multicollinearity, iv) detection of multicollinearity, v) remedial measures
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| 3 |
Heteroscedasticity
i) OLS estimation in the presence of heteroscedasticity, ii) consequences of using OLS in the presence of heteroscedasticity, iii) detection of heteroscedasticity, iv) remedial measures
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| 4 |
Autocorrelation
i) OLS estimation in the presence of autocorrelations, ii) consequences of using OLS in the presence of autocorrelations, iii) detections of autocorrelations, iv) remedial measures
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| 5 |
Autocorrelation
i) OLS estimation in the presence of autocorrelations, ii) consequences of using OLS in the presence of autocorrelations, iii) detections of autocorrelations, iv) remedial measures
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| 6 |
detection and solving econometric problems with Stata
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| 7 |
detection and solving econometric problems with Stata
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| 8 |
Mid-term Exam
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| 9 |
Econometric modelling
i) model selection criteria, ii) types of model specification errors, iii) consequences of model specification errors, iv) test of specification errors, v) errors of measurement
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| 10 |
Qualitative Response Regression Models
i) Tobit model ii)logit model iii)probit model
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| 11 |
Panel data regression models
i) why panel data, ii) fixed effects model, iii) random effects models
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| 12 |
Panel data regression models
i) why panel data, ii) fixed effects model, iii) random effects models
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| 13 |
sample exercise practice
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| 14 |
sample exercise practice
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