Homework Answers
a> The intercept of the equation represent the estimate of the logarithm of the wage of a male employee with no experience and no education and who does not use marijuna.
b> It is basically an interaction term betweed gender and marijuana use. So, it would represent if the marijuna has different effect on wage for male and female, it will represent how the marijuana effect is different for female from male on the logarithm of wage they earn.
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2. (2 marks) log(wage) = Bo + B usage +Bzeduc + Bzexper + Baexper2 + Bsfemale...
3. [40 pts Log of wage rate was regressed on the following explanatory variables: log(wage)0.389 ...
3. [40 pts Log of wage rate was regressed on the following explanatory variables: log(wage)0.389 0.227 female0.082educ0.0056 female educ (0.119) (0.168) (0.008) (0.0131) 0,00n() (0.005) (0.00024) where the female dummy takes on one if the worker is a woman. a) Explain carefully why the interaction term female educ is included in the above regression. (b) Consider two workers: a female worker and a male one with the same amount of experience and tenure. Both of them have no formal education....
III-(15pts) You are given the following estimated equation: log(wage)- 0.18+0.093edu +0.044exp+0.043 female-0.016edu female-0.010exp female-0.00068 exp (0.0001) 0.014) 0.4160 0.003 Std errors (0....
III-(15pts) You are given the following estimated equation: log(wage)- 0.18+0.093edu +0.044exp+0.043 female-0.016edu female-0.010exp female-0.00068 exp (0.0001) 0.014) 0.4160 0.003 Std errors (0.132) (0.009) (0.005) (0.196) n-526 R-square With all the variables described as follows: logiwage)-log of average hourly wage: female is a dummy variable equal to 1 if the observed person is a female, and 0 if male; edu female is an interaction variable equal to education 'female; edu is the number of years of schooling exp is the number...
Consider the following model for wage: log(wage) = ?0 + ?1female + ?2married + ?3educ +...
Consider the following model for wage: log(wage) = ?0 + ?1female + ?2married + ?3educ + ?4exper + u where educ is years of education, exper is years of experience, female = 1 if individual is a woman, = 0 otherwise, and married = 1 if individual is married, = 0 otherwise. (a) What is the benchmark group in this model? 1 (b) Modify this model (using interaction terms) so that the return to education can vary by marital status....
1. (9 pts) Consider the following economic model describing workers' earnings: In(wage) = Bo + Beduc...
1. (9 pts) Consider the following economic model describing workers' earnings: In(wage) = Bo + Beduc + Bztenure + Bzblack + Batenure? + Bseduc. black + Botenure black With all the variables described as follows: In(wage) = natural log of monthly earnings; educ = years of education; tenure = years with current employer; black = 1 if black and 0 if not; tenure? = tenure*tenure educ.black is an interaction variable equal to educ*black; tenure,black is an interaction variable equal to...
? ANSWER FROM LETTER "E" AND DOWNWARDS III- (15pts) You are given the following economic model...
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ANSWER FROM LETTER "E" AND DOWNWARDS
III- (15pts) You are given the following economic model 0.013 -$26 Rsquare- 0.4177 0.0012ten (0.00024 log(wage) 0.478 + 0.085edu + 0.059ten-0.058/emale-0.01 ledu.female-0.02 1/emale./en- Std errors (0.113) (0.008) (0.007) (0.174) (0.006 With all the variables described as follows: log(wage) -log of average hourly wage; female is a dummy variable equal to 1 if the observed person is a female, and O if make; edu female is an interaction variable equal to education'female; edu is...
hi can someone answer part e) f) g) h) with workings olease thanks 2) A cross-sectional study suggests the following wage equation: In(wage,)-α + βι EDUC' + β:FEMALE + β3EXPER, + β4FEMALE EXP...
hi can someone answer part e) f) g) h) with workings olease
thanks
2) A cross-sectional study suggests the following wage equation: In(wage,)-α + βι EDUC' + β:FEMALE + β3EXPER, + β4FEMALE EXPERi + ei Where: In(wage): Natural logarithm of f hourly wage; EDUC: Years of education; EXPER: Years of work experience; FEMALE: Dummy which equals 1 if the respondent is female and 0 otherwise; FEMALE EXPER:Interaction between FEMALE, and EXPER a) What is meant by the population level regression...
Please help with 4. a) b) c)
1. Use the LNU dataset that allows you to estimate a wage equation. Estimate a wage equation including a dummy variable for female (FEMALE). Interpret the estimated coefficient for the variable Female. 2. Estimate the same model adding a dummy variable for public sector (PUBLIC). Interpret the estimated coefficient for the variable PUBLIC. Compare the estimate for FEMALE in this model and the model above where the variable PUBLIC was not included.3. Estimate the wage equations above separately for Men and...
QUESTION 1 Consider the following OLS regression line (or sample regression function): wage =-2.10+ 0.50 educ...
QUESTION 1 Consider the following OLS regression line (or sample regression function): wage =-2.10+ 0.50 educ (1), where wage is hourly wage, measured in dollars, and educ years of formal education. According to (1), a person with no education has a predicted hourly wage of [wagehat] dollars. (NOTE: Write your answer in number format, with 2 decimal places of precision level; do not write your answer as a fraction. Add a leading minus sign symbol, a leading zero and trailing...
Suppose the following model of wage determination: log(w) 5.40 0.0654edu + 0.0140exp + 0.0117tenu + 0.199marr...
Suppose the following model of wage determination: log(w) 5.40 0.0654edu + 0.0140exp + 0.0117tenu + 0.199marr - 0.188f - 0.091south + 0.184urban (0.0025) (0.0032) (0.039) (0.027) (0.11) (0.0063) (0.038) (0.026) n 935, R2 .253. where w monthly earnings, edu = years of education, exp tenu-years with current employer, marr 1 if married, f 1 if female, south 1 if live in south, years of work experience, urban 1 if live in urban area Interpret the coefficient of the variable f....
1. Which of the following conditions will lead to a smaller variance for the intercept estimator...
1. Which of the following conditions will lead to a smaller variance for the intercept estimator for your multiple regression model? (A) X values cluster far from the origin of the X axis (B) X values closely pack around the mean of X in your sample (C) Small sample sizes (D) High correlation among the explanatory variables (E) Small error variance in the population regression function 2. R-squared (A) measures the proportion of variability of the dependent variable that is...
3. [40 pts Log of wage rate was regressed on the following explanatory variables: log(wage)0.389 0.227 female0.082educ0.0056 female educ (0.119) (0.168) (0.008) (0.0131) 0,00n() (0.005) (0.00024) where the female dummy takes on one if the worker is a woman. a) Explain carefully why the interaction term female educ is included in the above regression. (b) Consider two workers: a female worker and a male one with the same amount of experience and tenure. Both of them have no formal education....
III-(15pts) You are given the following estimated equation: log(wage)- 0.18+0.093edu +0.044exp+0.043 female-0.016edu female-0.010exp female-0.00068 exp (0.0001) 0.014) 0.4160 0.003 Std errors (0.132) (0.009) (0.005) (0.196) n-526 R-square With all the variables described as follows: logiwage)-log of average hourly wage: female is a dummy variable equal to 1 if the observed person is a female, and 0 if male; edu female is an interaction variable equal to education 'female; edu is the number of years of schooling exp is the number...
1. (9 pts) Consider the following economic model describing workers' earnings: In(wage) = Bo + Beduc + Bztenure + Bzblack + Batenure? + Bseduc. black + Botenure black With all the variables described as follows: In(wage) = natural log of monthly earnings; educ = years of education; tenure = years with current employer; black = 1 if black and 0 if not; tenure? = tenure*tenure educ.black is an interaction variable equal to educ*black; tenure,black is an interaction variable equal to...
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ANSWER FROM LETTER "E" AND DOWNWARDS
III- (15pts) You are given the following economic model 0.013 -$26 Rsquare- 0.4177 0.0012ten (0.00024 log(wage) 0.478 + 0.085edu + 0.059ten-0.058/emale-0.01 ledu.female-0.02 1/emale./en- Std errors (0.113) (0.008) (0.007) (0.174) (0.006 With all the variables described as follows: log(wage) -log of average hourly wage; female is a dummy variable equal to 1 if the observed person is a female, and O if make; edu female is an interaction variable equal to education'female; edu is...
hi can someone answer part e) f) g) h) with workings olease
thanks
2) A cross-sectional study suggests the following wage equation: In(wage,)-α + βι EDUC' + β:FEMALE + β3EXPER, + β4FEMALE EXPERi + ei Where: In(wage): Natural logarithm of f hourly wage; EDUC: Years of education; EXPER: Years of work experience; FEMALE: Dummy which equals 1 if the respondent is female and 0 otherwise; FEMALE EXPER:Interaction between FEMALE, and EXPER a) What is meant by the population level regression...
QUESTION 1 Consider the following OLS regression line (or sample regression function): wage =-2.10+ 0.50 educ (1), where wage is hourly wage, measured in dollars, and educ years of formal education. According to (1), a person with no education has a predicted hourly wage of [wagehat] dollars. (NOTE: Write your answer in number format, with 2 decimal places of precision level; do not write your answer as a fraction. Add a leading minus sign symbol, a leading zero and trailing...
Suppose the following model of wage determination: log(w) 5.40 0.0654edu + 0.0140exp + 0.0117tenu + 0.199marr - 0.188f - 0.091south + 0.184urban (0.0025) (0.0032) (0.039) (0.027) (0.11) (0.0063) (0.038) (0.026) n 935, R2 .253. where w monthly earnings, edu = years of education, exp tenu-years with current employer, marr 1 if married, f 1 if female, south 1 if live in south, years of work experience, urban 1 if live in urban area Interpret the coefficient of the variable f....
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