On the classic Linear regression y＝Xa+b y is dependent variable, x is the set of independent variables, and a is the parameter vector to be estimated. the error term. 1.What assumptions do the OLS need to become BLUE(best linear unbiased estimator)? List all assumptions 2.How is OLS turned into BLUE derived? 3.Discuss the direct relationship between OLS and hypothesis testing. What is waWhen ols conducts hypothesis testing? 4.the properties of linearity, efficiency and unbiasedness. What assumptions are needed to support these properties? List them.
On the classic Linear regression y＝Xa+b y is dependent variable, x is the set of independent variables, and a is the parameter vector to be estimated. the error term. 1.What assumptions do the OLS need to become BLUE(best linear unbiased estimator)? List all assumptions 2.How is OLS turned into BLUE derived? 3.Discuss the direct relationship between OLS and hypothesis testing. What is waWhen ols conducts hypothesis testing? 4.the properties of linearity, efficiency and unbiasedness. What assumptions are needed to support these properties? List them.
Chapter1: Making Economics Decisions
Section: Chapter Questions
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On the classic Linear regression
y＝Xa+b
y is dependent variable, x is the set of independent variables, and a is the parameter vector to be estimated. the error term.
1.What assumptions do the OLS need to become BLUE(best linear unbiased estimator)? List all assumptions
2.How is OLS turned into BLUE derived?
3.Discuss the direct relationship between OLS and hypothesis testing. What is waWhen ols conducts hypothesis testing?
4.the properties of linearity, efficiency and unbiasedness. What assumptions are needed to support these properties? List them.
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