Consider the following estimated regression equation, where both Rent and Earnings aremeasured in pounds (£) at the individual level (standard errors in parentheses):log(\Rent) = 6.9(0.69)+ 0.9(0.3)log(Earnings),(a) Interpret the coefficient on log(Earnings). (b) If we divided Earnings by 1000, so that it is measured in 1000s of pounds instead of pounds,how would (i) the slope, (ii) the intercept change in the above equation? Now suppose the variable London is added, which is equal to one if an individual iives inLondon, and zero otherwise. The estimated regression equation changes to:log(\Rent) = 6.22(0.622)+ 0.5(0.05)log(Earnings) + 2(0.5)London,(c) Interpret the coefficient on London. (d) Explain why the coefficient on log(Earnings) when London is included in the regression andthe coefficient on log(Earnings) when London is not included in the regression are not thesame.
Consider the following estimated regression equation, where both Rent and Earnings are
measured in pounds (£) at the individual level (standard errors in parentheses):
log(\Rent) = 6.9
(0.69)
+ 0.9
(0.3)
log(Earnings),
(a) Interpret the coefficient on log(Earnings).
(b) If we divided Earnings by 1000, so that it is measured in 1000s of pounds instead of pounds,
how would (i) the slope, (ii) the intercept change in the above equation?
Now suppose the variable London is added, which is equal to one if an individual iives in
London, and zero otherwise. The estimated regression equation changes to:
log(\Rent) = 6.22
(0.622)
+ 0.5
(0.05)
log(Earnings) + 2
(0.5)
London,
(c) Interpret the coefficient on London.
(d) Explain why the coefficient on log(Earnings) when London is included in the regression and
the coefficient on log(Earnings) when London is not included in the regression are not the
same.
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