00:01
Okay, so i see that you need help with this problem.
00:03
And so it says females, it is said, make 70 cents to the dollar in the united states.
00:11
To investigate this phenomenon, you collected on weekly earnings from 1 ,744 individuals, 850 females, and 894 males.
00:25
Next, you calculate their average weekly earnings and find that the females in your sample earned, $346 .99.
00:33
Well, the males made $517 .70.
00:36
So it says, a, calculate the female earnings in percent of the male earnings.
00:42
How would you test whether or not this is difference? it's statistically significant.
00:47
So for a, the females make 67 % of the male earnings.
01:02
And i would do a t statistic because, given the equation, $3 .20, which is the only way to test for significance.
01:17
The alternative is to run a regression of earnings on constant and the binary variable.
01:25
So, b, it says, a peer suggested that this is consistent with the idea that there is discrimination against females in the labor market.
01:35
What is your response? so my response is differences in attributes of the individuals, education.
01:43
So individuals, education, ability, tenure, so tenure of an employer are not taken into account.
02:12
So evidence is weak for discrimination.
02:22
Okay.
02:23
Then c.
02:24
So c is you recall from your textbook that additional.
02:27
Years of experience are supposed to result in higher earnings.
02:31
You reason that this is because the experience is related to on -the -job training.
02:35
One frequently used measure for potential experience is age education.
02:41
Explain the underlying rationale, assuming that heroically the education is constant across the 1 ,744 individuals you consider.
02:50
Regression earnings on age and binary variable for your gender.
02:54
You estimate two specifications initially, so then it gives your two equations.
03:02
Ages, earn our weekly where our weekly earning in dollars is measured in years.
03:12
And female is binary variable.
03:15
Which one, which takes on the value of one of the individuals is female, is zero otherwise.
03:23
Interpret each regression carefully.
03:26
For a given age, how much less do families earn on average? should you choose the second specification on grounds of higher regression? so for c, there's a lot going on here.
03:40
So potential experience is a potential experience variable is a reasonable proxy for on -the -job training if the individual started to work after completing his or her education...