The following regression uses data on illegal downloading of music. A sample of 500 individuals were asked whether they had downloaded music illegally (theft). In addition, respondents also gave answers to the following; caught: a respondent's belief of her chances of getting caught if she attempted to act illegally (0-10, 10 being "great risk") penalty: a respondent's belief regarding how severe her penalty would be if she got caught (0-10, 10 being “great risk) gender: gender, where male is 1 and female is 0 Edu: years of formal education Income: Income of the respondent (£) a. The estimated model was Theft = Bo + B1 caught + B2penalty + B3gender + B4Income + B5Edu Provide an explanation of the expected signs of each of the coefficients, referring to relevant economic theory.
The following regression uses data on illegal downloading of music. A sample of 500 individuals were asked whether they had downloaded music illegally (theft). In addition, respondents also gave answers to the following; caught: a respondent's belief of her chances of getting caught if she attempted to act illegally (0-10, 10 being "great risk") penalty: a respondent's belief regarding how severe her penalty would be if she got caught (0-10, 10 being “great risk) gender: gender, where male is 1 and female is 0 Edu: years of formal education Income: Income of the respondent (£) a. The estimated model was Theft = Bo + B1 caught + B2penalty + B3gender + B4Income + B5Edu Provide an explanation of the expected signs of each of the coefficients, referring to relevant economic theory.
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![The following regression uses data on illegal downloading of music. A sample of 500
individuals were asked whether they had downloaded music illegally (theft). In
addition, respondents also gave answers to the following;
caught: a respondent's belief of her chances of getting caught if she attempted
to act illegally (0-10, 10 being "great risk")
penalty: a respondent's belief regarding how severe her penalty would be if
she got caught (0-10, 10 being “great risk)
gender: gender, where male is 1 and female is 0
Edu: years of formal education
Income: Income of the respondent (£)
a. The estimated model was
Theft = Bo + B1 caught + B2penalty + B3gender + B4Income + B5Edu
Provide an explanation of the expected signs of each of the coefficients, referring
to relevant economic theory.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F3127fffa-6167-4d6b-879a-65215add11cc%2F0b603610-6e60-49fd-a682-847c2cbbd548%2Fgpa46rh_processed.jpeg&w=3840&q=75)
Transcribed Image Text:The following regression uses data on illegal downloading of music. A sample of 500
individuals were asked whether they had downloaded music illegally (theft). In
addition, respondents also gave answers to the following;
caught: a respondent's belief of her chances of getting caught if she attempted
to act illegally (0-10, 10 being "great risk")
penalty: a respondent's belief regarding how severe her penalty would be if
she got caught (0-10, 10 being “great risk)
gender: gender, where male is 1 and female is 0
Edu: years of formal education
Income: Income of the respondent (£)
a. The estimated model was
Theft = Bo + B1 caught + B2penalty + B3gender + B4Income + B5Edu
Provide an explanation of the expected signs of each of the coefficients, referring
to relevant economic theory.
![b. The results of estimating the model are presented in the following table.
(1)
VARIABLES
Theft
Caught
-0.2***
(0.04)
Penalty
0.01
(0.1)
0.12**
Gender
(0.05)
-0.002***
(0.0001)
-0.02*
Income
Edu
(0.011)
Constant
0.35***
(0.1)
Observations
500
Standard errors in parentheses
p<0.01,
***
**
p<0.05, * p<0.1
Provide an interpretation of the regression results, referring back to your answer to
part a.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F3127fffa-6167-4d6b-879a-65215add11cc%2F0b603610-6e60-49fd-a682-847c2cbbd548%2Fdbboodo_processed.jpeg&w=3840&q=75)
Transcribed Image Text:b. The results of estimating the model are presented in the following table.
(1)
VARIABLES
Theft
Caught
-0.2***
(0.04)
Penalty
0.01
(0.1)
0.12**
Gender
(0.05)
-0.002***
(0.0001)
-0.02*
Income
Edu
(0.011)
Constant
0.35***
(0.1)
Observations
500
Standard errors in parentheses
p<0.01,
***
**
p<0.05, * p<0.1
Provide an interpretation of the regression results, referring back to your answer to
part a.
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