Sumários
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8 Outubro 2020, 16:00 • Rita Sousa
SUMMARY
The statistical inference in the MLRM, namely the F and the t tests, is dependent from the errors' normality. The students must be able to compute and interpret the Kolmogorov-Smirnov and Jarque-Bera tests. In terms of Multicollinearity the students must be able to compute and interpret the TOL, VIF and the Variance Proportions diagnostics. They must also know which are the consequences for the OLS coefficients standard errors.
STUDENTS AUTONOMOUS WORK
Students must read CLASS MATERIALS.
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8 Outubro 2020, 14:30 • Rita Sousa
SUMMARY
The statistical inference in the MLRM, namely the F and the t tests, is dependent from the errors' normality. The students must be able to compute and interpret the Kolmogorov-Smirnov and Jarque-Bera tests. In terms of Multicollinearity the students must be able to compute and interpret the TOL, VIF and the Variance Proportions diagnostics. They must also know which are the consequences for the OLS coefficients standard errors.
STUDENTS AUTONOMOUS WORK
Students must read CLASS MATERIALS.
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2 Outubro 2020, 14:30 • Rita Sousa
SUMMARY
Specification and stability tests are commonly used to detect the presence of specification errors in the Multiple Linear Regression Model (MLRM). In these lectures students must me able to compute and interpret the RESET, CHOW and WALD tests to conclude about the specification errors. They must also analyze the consequences for OLS estimators when some of the assumptions do not hold and to use alternative estimators and inference procedures that are statistically more appropriate.
STUDENTS AUTONOMOUS WORK
Students must read CLASS MATERIALS and the following information:
|
SUBJECT |
BOOK/CHAPTER |
|
Specification and stability tests |
Wooldridge, J. (2008), chapter 5, 6 and 9 |
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2 Outubro 2020, 13:00 • Rita Sousa
SUMMARY
Specification and stability tests are commonly used to detect the presence of specification errors in the Multiple Linear Regression Model (MLRM). In these lectures students must me able to compute and interpret the RESET, CHOW and WALD tests to conclude about the specification errors. They must also analyze the consequences for OLS estimators when some of the assumptions do not hold and to use alternative estimators and inference procedures that are statistically more appropriate.
STUDENTS AUTONOMOUS WORK
Students must read CLASS MATERIALS and the following information:
|
SUBJECT |
BOOK/CHAPTER |
|
Specification and stability tests |
Wooldridge, J. (2008), chapter 5, 6 and 9 |
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28 Setembro 2020, 16:00 • Rita Sousa
SUMMARY
Multiple linear regression is used to establish the linear relationship between a dependent and more than one explanatory variables; it is a generalization of the simple model. Students must be able to understand how the Ordinary Least Squares (OLS) method works, to compute and interpret the R^2, the adjusted R^2, the standard error of the regression, the F-test, the t-tests and confidence intervals for the parameters.
STUDENTS AUTONOMOUS WORK
Students must read CLASS MATERIALS and the following information:
|
SUBJECT |
BOOK/CHAPTER |
|
Multiple linear regression model |
Wooldridge, J. (2008), chapter 3 |