In examining the determinants of income, data were collected regarding the characteristics of 45 adults, and the regression ln Y = β 0 + β 1 ln X 1 + β 2 ln X 2 + β 3 X 3 + ε was used, where Y is the annual income (in thousands of dollars), X 1 is the adult's age, X 2 is his/her years of education, and X 3 is a dummy
variable = 1 and is used if the adult is female. You run the regression and obtain the equation
ln = 6.3 + 0.91 ln x 1 + 1.3 ln x 2 - 0.05 x 3 .
How would you interpret the coefficient on years of education?

Question

In examining the determinants of income, data were collected regarding the characteristics of 45 adults, and the regression ln Y  =  β 0   +  β 1   ln X 1   +  β 2   ln X 2   +  β 3 X 3   + ε was used, where  Y  is the annual income (in thousands of dollars),  X 1   is the adult's age,  X 2   is his/her years of education, and  X 3   is a dummy  
 variable = 1 and is used if the adult is female. You run the regression and obtain the equation  
 ln    = 6.3 + 0.91 ln x 1   + 1.3 ln  x 2   - 0.05 x 3 . 
   How would you interpret the coefficient on years of education?

Answer

For every one percent increase in his/her years of education, we would expect the income to increase on average by 1.3 percent, assuming that all the other independent variables in the model are held constant.

100%

Answer

For every one percent increase in his/her years of education, we would expect the income to increase on average by 1.3 percent, assuming that all the other independent variables in the model are held constant.

100%

Answer

For every addition in his/her years of education, we would expect the income to increase on average by $1,310, assuming that all the other independent variables in the model are held constant.

Answer

For every 1.3 percent increase in his/her years of education, we would expect the income to increase approximately by $1,000, assuming that all the other independent variables in the model are held constant.

0%

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