We use the dataset "MASchools" in the package "AER". The dataset contains information on test performance, school characteristics and student demographic backgrounds for school districts in Massachusetts (MA). In this exercise, we shall use R-functions in the packages "estimatr" and "AER" (or "car"). We wish to learn the effect of student-teacher ratio (STR) on the 4th grade score (TestScore), which is defined as the sum of math, English, and science. In order to control for omitted variable bias, we shall include a few other additional variables and consider various functional forms. For all estimation exercises here the type of standard error should be "HC1" or equivalently "stata". QUESTION 1 Estimate the population regression model: TestScore=B+B STR+B Income + B Lunch + u where E[u, ISTR]=0. Here, Income, and Lunch, are the per capita income and percentage of qualified students for reduced-price lunch in school district i. What is the t value for the OLS estimate of the slope coefficient on Lunch, (two decimal places)? QUESTION 2 After estimating the regression model in Question 1, you want to test H₁: B₂=B₂=0 at the 5% significance level. Choose the correct statement. a. We reject H because the standard error of, is approximately 0.128. 0 b. We reject H because the maximum of the p-values associated with 0 -B₂² and is larger than 0.05. OC.We do not have sufficient evidence to reject H because R² = 0.67. 0 Od. We have to test two restrictions jointly and the critical value for this test is 3. e. For this test, the F statistic is 154.9 and we use the F distribution with degrees of freedom 3 and 216. QUESTION 3 Using the estimated coefficients in Question 1 above, predict TestScore for "Marblehead", which is one of the school districts in the sample (two decimal places).
We use the dataset "MASchools" in the package "AER". The dataset contains information on test performance, school characteristics and student demographic backgrounds for school districts in Massachusetts (MA). In this exercise, we shall use R-functions in the packages "estimatr" and "AER" (or "car"). We wish to learn the effect of student-teacher ratio (STR) on the 4th grade score (TestScore), which is defined as the sum of math, English, and science. In order to control for omitted variable bias, we shall include a few other additional variables and consider various functional forms. For all estimation exercises here the type of standard error should be "HC1" or equivalently "stata". QUESTION 1 Estimate the population regression model: TestScore=B+B STR+B Income + B Lunch + u where E[u, ISTR]=0. Here, Income, and Lunch, are the per capita income and percentage of qualified students for reduced-price lunch in school district i. What is the t value for the OLS estimate of the slope coefficient on Lunch, (two decimal places)? QUESTION 2 After estimating the regression model in Question 1, you want to test H₁: B₂=B₂=0 at the 5% significance level. Choose the correct statement. a. We reject H because the standard error of, is approximately 0.128. 0 b. We reject H because the maximum of the p-values associated with 0 -B₂² and is larger than 0.05. OC.We do not have sufficient evidence to reject H because R² = 0.67. 0 Od. We have to test two restrictions jointly and the critical value for this test is 3. e. For this test, the F statistic is 154.9 and we use the F distribution with degrees of freedom 3 and 216. QUESTION 3 Using the estimated coefficients in Question 1 above, predict TestScore for "Marblehead", which is one of the school districts in the sample (two decimal places).
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
![We use the dataset "MASchools" in the package "AER". The dataset contains information on test performance, school
characteristics and student demographic backgrounds for school districts in Massachusetts (MA). In this exercise, we
shall use R-functions in the packages "estimatr" and "AER" (or "car"). We wish to learn the effect of student-teacher ratio
(STR) on the 4th grade score (TestScore), which is defined as the sum of math, English, and science. In order to control
for omitted variable bias, we shall include a few other additional variables and consider various functional forms. For all
estimation exercises here the type of standard error should be "HC1" or equivalently "stata".
QUESTION 1
Estimate the population regression model:
TestScore=B+B STR+B Income + B Lunch + u
i
where E[u ISTR]=0. Here, Income and Lunch are the per capita income and percentage of qualified students for reduced-price
i
lunch in school district i. What is the t value for the OLS estimate of the slope coefficient on Lunch, (two decimal places)?
QUESTION 2
After estimating the regression model in Question 1, you want to test
10: B₁₂ =B₁₂=
at the 5% significance level. Choose the correct statement.
H
=0
a. We reject H because the standard error of
0
16, is approximately 0.128.
b. We reject H because the maximum of the p-values associated with
c. We do not have sufficient evidence to reject H because R² = 0.67.
O d. We have to test two restrictions jointly and the critical value for this test is 3.
O e. For this test, the F statistic is 154.9 and we use the F distribution with degrees of freedom 3 and 216.
QUESTION 3
th and is larger than 0.05.
Using the estimated coefficients in Question 1 above, predict TestScore for "Marblehead", which is one of the school districts in the
sample (two decimal places).](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fd59e17ff-7a7c-4167-8c0b-fb870a3da76d%2F47873c2e-a22d-45ab-bb21-f8b8e0e7eb7c%2Ft1lk4fa_processed.jpeg&w=3840&q=75)
Transcribed Image Text:We use the dataset "MASchools" in the package "AER". The dataset contains information on test performance, school
characteristics and student demographic backgrounds for school districts in Massachusetts (MA). In this exercise, we
shall use R-functions in the packages "estimatr" and "AER" (or "car"). We wish to learn the effect of student-teacher ratio
(STR) on the 4th grade score (TestScore), which is defined as the sum of math, English, and science. In order to control
for omitted variable bias, we shall include a few other additional variables and consider various functional forms. For all
estimation exercises here the type of standard error should be "HC1" or equivalently "stata".
QUESTION 1
Estimate the population regression model:
TestScore=B+B STR+B Income + B Lunch + u
i
where E[u ISTR]=0. Here, Income and Lunch are the per capita income and percentage of qualified students for reduced-price
i
lunch in school district i. What is the t value for the OLS estimate of the slope coefficient on Lunch, (two decimal places)?
QUESTION 2
After estimating the regression model in Question 1, you want to test
10: B₁₂ =B₁₂=
at the 5% significance level. Choose the correct statement.
H
=0
a. We reject H because the standard error of
0
16, is approximately 0.128.
b. We reject H because the maximum of the p-values associated with
c. We do not have sufficient evidence to reject H because R² = 0.67.
O d. We have to test two restrictions jointly and the critical value for this test is 3.
O e. For this test, the F statistic is 154.9 and we use the F distribution with degrees of freedom 3 and 216.
QUESTION 3
th and is larger than 0.05.
Using the estimated coefficients in Question 1 above, predict TestScore for "Marblehead", which is one of the school districts in the
sample (two decimal places).
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
Step by step
Solved in 4 steps with 16 images
Recommended textbooks for you
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman