he data used is from college campuses. The variables used in the analysis below include: crime, total campus crime; enroll, total rollment; police, employed officers. Use the estimated OLS models to answer the questions below: odel A: (crime) = -6.631 +1.270ln(enroll), (.110) (1.034) = 97; R² = .5804 odel B: (crime) = -4.794+.923ln(enroll) + .516ln(police), (.144) (.149) (1.112) = 97; R² = .632 sing Model A, test the null hypothesis that elasticity of crime with respect to enrollment is unit elastic, i.e. equal to one (against a vo-sided alternative). Calculate the t-statistic.
he data used is from college campuses. The variables used in the analysis below include: crime, total campus crime; enroll, total rollment; police, employed officers. Use the estimated OLS models to answer the questions below: odel A: (crime) = -6.631 +1.270ln(enroll), (.110) (1.034) = 97; R² = .5804 odel B: (crime) = -4.794+.923ln(enroll) + .516ln(police), (.144) (.149) (1.112) = 97; R² = .632 sing Model A, test the null hypothesis that elasticity of crime with respect to enrollment is unit elastic, i.e. equal to one (against a vo-sided alternative). Calculate the t-statistic.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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![The data used is from college campuses. The variables used in the analysis below include: crime, total campus crime; enroll, total enrollment; police, employed officers. Use the estimated OLS models to answer the questions below:
**Model A:**
\[
ln(\hat{crime}) = -6.631 + 1.270ln(enroll),
\]
(Standard error in parentheses: \(1.034\) for the intercept, \(0.110\) for \(ln(enroll)\))
\(n = 97; R^2 = .5804\)
**Model B:**
\[
ln(\hat{crime}) = -4.794 + .923ln(enroll) + .516ln(police),
\]
(Standard error in parentheses: \(1.112\) for the intercept, \(0.144\) for \(ln(enroll)\), \(0.149\) for \(ln(police)\))
\(n = 97; R^2 = .632\)
Using Model A, test the null hypothesis that elasticity of crime with respect to enrollment is unit elastic, i.e., equal to one (against a two-sided alternative). Calculate the t-statistic.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ff2c90e6f-21b1-498d-a838-23f699b7822e%2Fab66a8c6-b757-459c-bd25-e35192579952%2Fslrjiwl_processed.png&w=3840&q=75)
Transcribed Image Text:The data used is from college campuses. The variables used in the analysis below include: crime, total campus crime; enroll, total enrollment; police, employed officers. Use the estimated OLS models to answer the questions below:
**Model A:**
\[
ln(\hat{crime}) = -6.631 + 1.270ln(enroll),
\]
(Standard error in parentheses: \(1.034\) for the intercept, \(0.110\) for \(ln(enroll)\))
\(n = 97; R^2 = .5804\)
**Model B:**
\[
ln(\hat{crime}) = -4.794 + .923ln(enroll) + .516ln(police),
\]
(Standard error in parentheses: \(1.112\) for the intercept, \(0.144\) for \(ln(enroll)\), \(0.149\) for \(ln(police)\))
\(n = 97; R^2 = .632\)
Using Model A, test the null hypothesis that elasticity of crime with respect to enrollment is unit elastic, i.e., equal to one (against a two-sided alternative). Calculate the t-statistic.
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