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You Have Learned That Earnings Functions Are One of the Most

question 10

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You have learned that earnings functions are one of the most investigated relationships in economics. These typically relate the logarithm of earnings to a series of explanatory variables such as education, work experience, gender, race, etc.
(a)Why do you think that researchers have preferred a log-linear specification over a linear specification? In addition to the interpretation of the slope coefficients, also think about the distribution of the error term.
(b)To establish age-earnings profiles, you regress ln(Earn)on Age, where Earn is weekly earnings in dollars, and Age is in years. Plotting the residuals of the regression against age for 1,744 individuals looks as shown in the figure: $You have learned that earnings functions are one of the most investigated relationships in economics. These typically relate the logarithm of earnings to a series of explanatory variables such as education, work experience, gender, race, etc. (a)Why do you think that researchers have preferred a log-linear specification over a linear specification? In addition to the interpretation of the slope coefficients, also think about the distribution of the error term. (b)To establish age-earnings profiles, you regress ln(Earn)on Age, where Earn is weekly earnings in dollars, and Age is in years. Plotting the residuals of the regression against age for 1,744 individuals looks as shown in the figure: Do you sense a problem? (c)You decide, given your knowledge of age-earning profiles, to allow the regression line to differ for the below and above 40 years age category. Accordingly you create a binary variable, Dage, that takes the value one for age 39 and below, and is zero otherwise. Estimating the earnings equation results in the following output (using heteroskedasticity-robust standard errors): \begin{array} { l } \widehat { \text { LnEarn } = } 6.92 - 3.13 \times \text { Dage } - 0.019 \times \text { Age } + 0.085 \times ( \text { Dage } \times \text { Age } ) , R 2 = 0.20 , \text { SER } = 0.721 . \\ \quad\quad\quad\quad( 38.33 ) ( 0.22 )\quad\quad\quad\quad(0.004)\quad\quad\quad\quad(0.005) \\ \end{array} Sketch both regression lines: one for the age category 39 years and under, and one for 40 and above. Does it make sense to have a negative sign on the Age coefficient? Predict the ln(earnings)for a 30 year old and a 50 year old. What is the percentage difference between these two? (d)The F-statistic for the hypothesis that both slopes and intercepts are the same is 124.43. Can you reject the null hypothesis? (e)What other functional forms should you consider?$ Do you sense a problem?
(c)You decide, given your knowledge of age-earning profiles, to allow the regression line to differ for the below and above 40 years age category. Accordingly you create a binary variable, Dage, that takes the value one for age 39 and below, and is zero otherwise. Estimating the earnings equation results in the following output (using heteroskedasticity-robust standard errors): $\begin{array} { l } \widehat { \text { LnEarn } = } 6.92 - 3.13 \times \text { Dage } - 0.019 \times \text { Age } + 0.085 \times ( \text { Dage } \times \text { Age } ) , R 2 = 0.20 , \text { SER } = 0.721 . \\\quad\quad\quad\quad( 38.33 ) ( 0.22 )\quad\quad\quad\quad(0.004)\quad\quad\quad\quad(0.005) \\\end{array}$
Sketch both regression lines: one for the age category 39 years and under, and one for 40 and above. Does it make sense to have a negative sign on the Age coefficient? Predict the ln(earnings)for a 30 year old and a 50 year old. What is the percentage difference between these two?
(d)The F-statistic for the hypothesis that both slopes and intercepts are the same is 124.43. Can you reject the null hypothesis?
(e)What other functional forms should you consider?

Differentiate between various types of negotiable instruments (e.g., checks, notes, drafts).

Comprehend the roles and responsibilities of parties involved in negotiable instruments.

Explain the characteristics that affect the negotiability of an instrument.

Recognize the difference between order instruments and bearer instruments.

Definitions:

Own Analysis

Own analysis refers to the practice of self-examination or self-reflection to gain insights into one's thoughts, emotions, and behaviors.

Divine Intervention

Divine Intervention refers to the belief in spiritual forces or a deity intervening in human affairs, which can be a source of strength and comfort for some individuals.

Individuation

The process of becoming aware of oneself as an individual distinct from others and the general social environment.

Collaborative Educator Relationship

A partnership model between educators and others (students, parents, community members) emphasizing shared goals and mutual respect.