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In order to estimate the effect on wage of years of schooling, researcher B analysed the dataset that researcher A collected in the previous question. Researcher B considers the following regression equation, log(income) ;=ß+ß¡educ¡ + ··· + u¡ where educ. is years of school of individual i and includes additional terms associated with other characteristics in the data set. When researcher B was carefully examining omitted factors in the error term ushe realised that unobserved factors such as motivation and work_ethic would increase the income level and be positively correlated with the variable of interest educ. If researcher B's conjecture regarding the unobserved factors is correct, then: i O a. The OLS estimator, would not be computed. O b. The OLS estimator would overestimate the effect on income of educ 1 i O c. The OLS estimator would suffer imperfect multicollinearity. O d. The OLS estimator , would have a large standard error. 1 O e. The OLS estimator , would follow the Student t-distribution with n-k degrees of freedom, where k is the number of coefficients to estimate in the model.

In order to estimate the effect on wage of years of schooling, researcher B analysed the dataset that researcher A collected in the previous question. Researcher B considers the following regression equation, log(income) ;=ß+ß¡educ¡ + ··· + u¡ where educ. is years of school of individual i and includes additional terms associated with other characteristics in the data set. When researcher B was carefully examining omitted factors in the error term ushe realised that unobserved factors such as motivation and work_ethic would increase the income level and be positively correlated with the variable of interest educ. If researcher B's conjecture regarding the unobserved factors is correct, then: i O a. The OLS estimator, would not be computed. O b. The OLS estimator would overestimate the effect on income of educ 1 i O c. The OLS estimator would suffer imperfect multicollinearity. O d. The OLS estimator , would have a large standard error. 1 O e. The OLS estimator , would follow the Student t-distribution with n-k degrees of freedom, where k is the number of coefficients to estimate in the model.

MATLAB: An Introduction with Applications
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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QUESTION 7 In order to estimate the effect on wage of years of schooling, researcher B analysed the dataset that researcher A collected in the previous question. Researcher B considers the following regression equation, + ... +₁² log(income), =B+B₁₂educ; 0 where educ. is years of school of individual i and includes additional terms associated with other characteristics in the data set. When researcher B was i carefully examining omitted factors in the error term u , she realised that unobserved factors such as motivation and work ethic would increase the income i' i level and be positively correlated with the variable of interest educ. If researcher B's conjecture regarding the unobserved factors is correct, then: O a. O b. The OLS estimator would overestimate the effect on income of educ.. i O c. The OLS estimator, would not be computed. O d. O e. The OLS estimator The OLS estimator The OLS estimator would suffer imperfect multicollinearity. 1 would have a large standard error. would follow the Student t-distribution with n-k degrees of freedom, where k is the number of coefficients to estimate in the model.
Transcribed Image Text:QUESTION 7 In order to estimate the effect on wage of years of schooling, researcher B analysed the dataset that researcher A collected in the previous question. Researcher B considers the following regression equation, + ... +₁² log(income), =B+B₁₂educ; 0 where educ. is years of school of individual i and includes additional terms associated with other characteristics in the data set. When researcher B was i carefully examining omitted factors in the error term u , she realised that unobserved factors such as motivation and work ethic would increase the income i' i level and be positively correlated with the variable of interest educ. If researcher B's conjecture regarding the unobserved factors is correct, then: O a. O b. The OLS estimator would overestimate the effect on income of educ.. i O c. The OLS estimator, would not be computed. O d. O e. The OLS estimator The OLS estimator The OLS estimator would suffer imperfect multicollinearity. 1 would have a large standard error. would follow the Student t-distribution with n-k degrees of freedom, where k is the number of coefficients to estimate in the model.
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