Sumários
SPECIFICATION AND STABILITY TESTS
27 Novembro 2020, 11:00 • Rita Sousa
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.
MULTIPLE LINEAR REGRESSION MODEL (MLRM)
27 Novembro 2020, 09:30 • Rita Sousa
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.
SPECIFICATION AND STABILITY TESTS
26 Novembro 2020, 11:00 • Rita Sousa
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.
SPECIFICATION AND STABILITY TESTS
26 Novembro 2020, 09:30 • Rita Sousa
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.
MULTIPLE LINEAR REGRESSION MODEL (MLRM)
24 Novembro 2020, 11:00 • Rita Sousa
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.