your 5.11 When estimating wage equations, we expect that young, inexperienced workers will have relatively low wages; with additional experience their wages will rise, but then begin to decline after middle age, as the worker nears retirement. This life-cycle pattern of wages can be captured by introducing experience and experience squared to explain the level of wages. If we also include years of education, we have the equation WAGE=B₁ + B₂EDUC+B3EXPER+B4EXPER² + e a. What is the marginal effect of experience on the mean wage? b. What signs do you expect for each of the coefficients B₂, B3, and B4? Why? c. After how many years of experience does the mean wage start to decline? (Express your answer in terms of B's.) d. Estimating this equation using 600 observations yields WAGE= -16.308 +2.329EDUC+0.5240EXPER-0.007582EXPER² (2.745) (0.163) (se) (0.1263) The estimated covariance between b3 and b4 is cov(b3, b4) = -0.00030526. Find 95% interval estimates for the following: (0.002532) soy i all b 1. The marginal effect of education on mean wage ii. The marginal effect of experience on mean wage when EXPER= 4 iii. The marginal effect of experience on mean wage when EXPER= 25 de iv. The number of years of experience after which the mean wage declines batin odT 5.12 This exercise per dot DE
your 5.11 When estimating wage equations, we expect that young, inexperienced workers will have relatively low wages; with additional experience their wages will rise, but then begin to decline after middle age, as the worker nears retirement. This life-cycle pattern of wages can be captured by introducing experience and experience squared to explain the level of wages. If we also include years of education, we have the equation WAGE=B₁ + B₂EDUC+B3EXPER+B4EXPER² + e a. What is the marginal effect of experience on the mean wage? b. What signs do you expect for each of the coefficients B₂, B3, and B4? Why? c. After how many years of experience does the mean wage start to decline? (Express your answer in terms of B's.) d. Estimating this equation using 600 observations yields WAGE= -16.308 +2.329EDUC+0.5240EXPER-0.007582EXPER² (2.745) (0.163) (se) (0.1263) The estimated covariance between b3 and b4 is cov(b3, b4) = -0.00030526. Find 95% interval estimates for the following: (0.002532) soy i all b 1. The marginal effect of education on mean wage ii. The marginal effect of experience on mean wage when EXPER= 4 iii. The marginal effect of experience on mean wage when EXPER= 25 de iv. The number of years of experience after which the mean wage declines batin odT 5.12 This exercise per dot DE
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Please solve 5.11 a-d and i-iv. Thank you!
![C.
Infall increases me
yield by 0.03 tonnes per hectare against the alternative that the increase is not equal to 0.03.
d. Adding RAIN² to the equation and reestimating yields M-150
Wed YIELD, = -0.6759 +0.011671t+ 0.2229RAIN, -0.008155 RAIN?
(0.3875) (0.00250) (0.0734)
(0.003453)
deno (se)
What is the rationale for including RAIN2? Does it have the expected sign?
e. Repeat part (b) using the model estimated in (d).
f. Repeat part (c) using the model estimated in (d), testing the hypothesis at the mean value of
rainfall. (The estimated covariance between b, and b₁ (the coefficients of RAIN and RAIN) is
cov (b3, b4)=-0.0002493.)
g. Use the model in (d) to forecast yield in 1997, when the rainfall was 9.48 inches.
h. Suppose that you wanted to forecast 1997 yield before the rainfall was observed. What would be
your forecast from the model in (a)? What would it be from the model in (d)?
5.11 When estimating wage equations, we expect that young, inexperienced workers will have relatively
low wages; with additional experience their wages will rise, but then begin to decline after middle
age, as the worker nears retirement. This life-cycle pattern of wages can be captured by introducing
experience and experience squared to explain the level of wages. If we also include years of education,
we have the equation
WAGE=B₁ + B₂EDUC+ B3EXPER+B4EXPER² + e
a. What is the marginal effect of experience on the mean wage?
b. What signs do you expect for each of the coefficients B₂, B3, and B4? Why?
c. After how many years of experience does the mean wage start to decline? (Express your answer in
terms of B's.)
d. Estimating this equation using 600 observations yields
WAGE= -16.308 +2.329EDUC+0.5240EXPER-0.007582EXPER²
(se)
(2.745) (0.163)
(0.1263)
(0.002532)
The estimated covariance between b, and b4 is cov (b3, b4) = -0.00030526. Find 95% interval
estimates for the following:
i. The marginal effect of education on mean wage
ii. The marginal effect of experience on mean wage when EXPER = 4
ili. The marginal effect of experience on mean wage when EXPER= 25
iv. The number of years of experience after which the mean wage declines bailaU edT A
5.12 This exercise uses data on 850 houses sold in Baton Rouge, Louisiana during mid-2005. We will be
concerned with the selling price in thousands of dollars (PRICE), the size of the house in hundreds
of square feet (SQFT), and the age of the house in years (AGE). The following tw
ion models
were estimated:
PRICE = a₁ + a₂AGE+v and SQFT = 8₁ +8₂AGE+
The sums of squares and sums of cross products of the residuals from estimatin
are Eis v = 10377817, Σ
, = 688318.
50
=75773.4,
a. Find the least-squares estimate of Bß, in the model PRICE =B₁ + B₂SQFT +
b. Letê, = -b₂u. Show that
e₁ =
Z-b₂Zvu, where b₂ is the
where U, is
rate Gy is th
adjustment
a. Show th
the une
b. Estima
for B₂.
e. Find an estimate of o² = var (e).
d. Find the standard error for b₂.
e. What is an approximate p-value for testing Ho: B₂ 29.5 against the alternativ
do you conclude from this p-value?
Eston
Use
c. Fin
at
d. Us
مه ده نه ن ن
g.
ag
F
E
5.14 Co
inc
a.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F6b1ec9e1-71c5-41a7-88e5-1ec0b0e62692%2F67974ec7-d368-484b-a6a9-50180697264f%2Fdkaoho_processed.jpeg&w=3840&q=75)
Transcribed Image Text:C.
Infall increases me
yield by 0.03 tonnes per hectare against the alternative that the increase is not equal to 0.03.
d. Adding RAIN² to the equation and reestimating yields M-150
Wed YIELD, = -0.6759 +0.011671t+ 0.2229RAIN, -0.008155 RAIN?
(0.3875) (0.00250) (0.0734)
(0.003453)
deno (se)
What is the rationale for including RAIN2? Does it have the expected sign?
e. Repeat part (b) using the model estimated in (d).
f. Repeat part (c) using the model estimated in (d), testing the hypothesis at the mean value of
rainfall. (The estimated covariance between b, and b₁ (the coefficients of RAIN and RAIN) is
cov (b3, b4)=-0.0002493.)
g. Use the model in (d) to forecast yield in 1997, when the rainfall was 9.48 inches.
h. Suppose that you wanted to forecast 1997 yield before the rainfall was observed. What would be
your forecast from the model in (a)? What would it be from the model in (d)?
5.11 When estimating wage equations, we expect that young, inexperienced workers will have relatively
low wages; with additional experience their wages will rise, but then begin to decline after middle
age, as the worker nears retirement. This life-cycle pattern of wages can be captured by introducing
experience and experience squared to explain the level of wages. If we also include years of education,
we have the equation
WAGE=B₁ + B₂EDUC+ B3EXPER+B4EXPER² + e
a. What is the marginal effect of experience on the mean wage?
b. What signs do you expect for each of the coefficients B₂, B3, and B4? Why?
c. After how many years of experience does the mean wage start to decline? (Express your answer in
terms of B's.)
d. Estimating this equation using 600 observations yields
WAGE= -16.308 +2.329EDUC+0.5240EXPER-0.007582EXPER²
(se)
(2.745) (0.163)
(0.1263)
(0.002532)
The estimated covariance between b, and b4 is cov (b3, b4) = -0.00030526. Find 95% interval
estimates for the following:
i. The marginal effect of education on mean wage
ii. The marginal effect of experience on mean wage when EXPER = 4
ili. The marginal effect of experience on mean wage when EXPER= 25
iv. The number of years of experience after which the mean wage declines bailaU edT A
5.12 This exercise uses data on 850 houses sold in Baton Rouge, Louisiana during mid-2005. We will be
concerned with the selling price in thousands of dollars (PRICE), the size of the house in hundreds
of square feet (SQFT), and the age of the house in years (AGE). The following tw
ion models
were estimated:
PRICE = a₁ + a₂AGE+v and SQFT = 8₁ +8₂AGE+
The sums of squares and sums of cross products of the residuals from estimatin
are Eis v = 10377817, Σ
, = 688318.
50
=75773.4,
a. Find the least-squares estimate of Bß, in the model PRICE =B₁ + B₂SQFT +
b. Letê, = -b₂u. Show that
e₁ =
Z-b₂Zvu, where b₂ is the
where U, is
rate Gy is th
adjustment
a. Show th
the une
b. Estima
for B₂.
e. Find an estimate of o² = var (e).
d. Find the standard error for b₂.
e. What is an approximate p-value for testing Ho: B₂ 29.5 against the alternativ
do you conclude from this p-value?
Eston
Use
c. Fin
at
d. Us
مه ده نه ن ن
g.
ag
F
E
5.14 Co
inc
a.
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