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QNo2 - rewrite the estimator of the slope and intercept...

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QNo2. (a) Prove OR Solution: Assumption1 (Linearity) : The population model, the dependent variable y is a linear function of the explanatory variables x plus an error term u as Where and are the population intercept and slope parameters, respectively. Assumption2 (Random Sampling) : The sample we have is a random sample from the population. I.e. the sample is independent, identically distributed ( iid ); this suggests that Note that very few cross-sectional data files are random samples. Assumption3 (Zero conditional mean) : Assumption4 (Sample variation in explanatory variables) : We need this assumption so that the slope estimate will be well-defined. It will convenient to

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Unformatted text preview: rewrite the estimator of the slope and intercept such as Taking expectation on both side of eq. (1), we have Where the first equality comes from Assumption (1) and Assumption (4), and the second equality comes from Assumption (2) and Assumption (3). Finally, eq., (2) follows. Hence Proved; OR QNo2. (b) Given Model: Estimated Model: Here, OLS estimator of is best because in the absence of intercept ; we mean that dependent variable is more dependent on; As shows the value of in the absence of; so if will not present in the model it means that will dependent more on variable....
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QNo2 - rewrite the estimator of the slope and intercept...

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