3. Consider the following model log(yi) =B + B log(xi) + ui, where i =...

 

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3. Consider the following model log(yi) =B₁ + B₂ · log(xi) + ui, where i = 1, . . ., 60, ya is the food expenditure (in $) for the ith household, and x, is the income of the ith household. After running OLS regression, we get the following results. Standard errors: OLS (Intercept) income -- Est. 83.416 10.210 S.E. t val. 43.410 2.093 1.922 4.877 р 0.062 0.000 The Taxation Office conjectures the food expenditure ELASTICITY with respect to income is 10. (a). Conduct a proper hypothesis test to examine the argument of the Taxation Office. (8 points) 3. Consider the following model log(yi) =B₁ + B₂ · log(xi) + ui, where i = 1, . . ., 60, ya is the food expenditure (in $) for the ith household, and x, is the income of the ith household. After running OLS regression, we get the following results. Standard errors: OLS (Intercept) income -- Est. 83.416 10.210 S.E. t val. 43.410 2.093 1.922 4.877 р 0.062 0.000 The Taxation Office conjectures the food expenditure ELASTICITY with respect to income is 10. (a). Conduct a proper hypothesis test to examine the argument of the Taxation Office. (8 points)

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