(20.7) (1.35) Scenario 38-1. Consider the following OLS model applied to the data for workers wages and years of schooling, where e; stands for the residual: WAGE = -10.7+ 3.16 x SCHOOL + e. Refer to Scenario 38-1. Suppose that the residual term has a zero mean and is uncorrelated with the independent variable. Suppose that the standard error is 1.35. This means that we can be 95 percent confident that the true wage benefit of a year of schooling 000 is equal to $8. is equal to $0.46. lies between $0.46 and $5.86. lies between $8 and $13.4.
(20.7) (1.35) Scenario 38-1. Consider the following OLS model applied to the data for workers wages and years of schooling, where e; stands for the residual: WAGE = -10.7+ 3.16 x SCHOOL + e. Refer to Scenario 38-1. Suppose that the residual term has a zero mean and is uncorrelated with the independent variable. Suppose that the standard error is 1.35. This means that we can be 95 percent confident that the true wage benefit of a year of schooling 000 is equal to $8. is equal to $0.46. lies between $0.46 and $5.86. lies between $8 and $13.4.
Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)
14th Edition
ISBN:9781305506381
Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Chapter4A: Problems In Applying The Linear Regression Model
Section: Chapter Questions
Problem 2E
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Transcribed Image Text:(20.7)
(1.35)
Scenario 38-1. Consider the following OLS model applied to the data for workers wages and years of schooling, where e; stands for the residual:
WAGE = -10.7+ 3.16 x SCHOOL + e.
Refer to Scenario 38-1. Suppose that the residual term has a zero mean and is uncorrelated with the independent variable. Suppose that the standard error is 1.35. This means that we can be 95 percent
confident that the true wage benefit of a year of schooling
000
is equal to $8.
is equal to $0.46.
lies between $0.46 and $5.86.
lies between $8 and $13.4.
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