Suppose we are interested in examining the difference in wages between men and w

Question

Suppose we are interested in examining the difference in wages between men and women and run the following regression: Wage = beta_0 + beta_1 Gender + beta_2 Experience + epsilon where wage = wage rate per month (e.g. $2,000 month) gender = 1 if person is male, 0 otherwise experience = number of years at the company The output from this regression is represented below: Model 1: OLS estimates using the 49 observations 1-49 Dependent variable: WAGE Please answer the following questions given the information above: (a) On average, how much more do men make relative to women? (b) Does this difference represent employment discrimination based on gender? Use economic reasoning to explain why or why not this may be the case. c) Suppose that we define a new independent variable, Female, where this variable takes on the value "1" if the person is female and "0" otherwise, and we add this variable to the above specification. Are there any issues with the new specification? Using the formula for the OLS estimator, explain what happens when this regression is run

Explanation / Answer

solution: if mlel is coded as 1 then

a) Since the Experience predicter is not statictally significent removing it from the equation we get, wage=1366.27+525.632*1, thus wage for male=526998.27.

if female is coded as 0 then,

wage=1366.27+525.632*0=1366.525, so for every male earns 1366.27 extra for every female.

b) As stated in the example above here, Yes there is a difference which represents employment discrimination due to gender. Such case differers from the real world condition since there are polices which states there will be no judgement on cast gender and creed.

c)If the feamle value si coded as 1 and male as 0, then the equation also gets changed. thus here it very important to assign the values associated with the predicter.

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