Answer to Question #203235 in Economics of Enterprise for emiru amsalu

Question

Problem 3

In this question we look at the relation between the logarithm of weakly earnings and years of education. Using data from the national longitudinal study of youth, we find the following results for a regression of log weekly earnings and years of education, experience, experience squared and an intercept:

Log (earnings) = 4.016 + 0.092 . educi + 0.079 .expei + 0.002 . experi 2

( 0.222) ( 0.008) ( 0.025) (0.001)

c). Labour economist studying the relation between education and earnings are often concerned about what they call “ability bias”. Suppose that individuals differ in ability, and that the correct specification of the regression function is one that includes ability:

log ( earnings )I = β1 + β 2 ⋅ educI + β 3 ⋅ experI − β 4 ⋅ experI2 + β5 ⋅ abilityI + εI .

In this regression, what do you expect the sign of β5 (the coefficient on ability) to be?

Answer 1

The regression equation allows the researcher to find the relationship between dependent variable and the independent variables. It helps in determining which variable affects the dependent variable the most. 

This can be learnt by looking at the coefficient of the independent variable. Also, the sign of the coefficient can be let the researcher know whether the variables have a positive or negative relationship. 

The coefficient on ability will be positive. If an individual has a higher ability to do the work than the other individual, then that individual will earn more. The person with higher ability will be able to perform more complex tasks which would increase his/her earning potential. On the other hand, a person with lower ability would not be able to perform complex tasks which would reduce his/her earnings.