Consider the following regression estimates (ID6)SourceModelResidualTotalwageeducexperexper2_consinverse u-shapedSSC. lineard. exponential1927.876735232.537567160.41429df-.0046123-3.96489642.6255763522 10.0240183525Coef. Std. Err..5953429.0530251.268287 .0368969.000822.7521526MS13.6388844Number of obsF(3, 522)Prob > FR-squaredAdj R-squaredRoot MSEt P>|t|0.00011.237.27 0.000-5.61 0.000-5.27 0.000=.4911741.1958023-.006227-5.442508===52664.110.00000.26920.26503.1661[95% Conf. Interval].6995118.3407717where wage is hourly wage in US$, educ is years of education, exper is years of work experience and exper2 is experience squared (exper* exper).According to these estimates, what is the functional form of the relationship between experience and predicted wage when we hold education constant?a. u-shapedb.i-.0029975-2.487272

From the given regression results, the coefficient of the constant term is -3.96489, the coefficient…

Consider the following regression estimates (ID6) Source Model Residual Total wage educ exper exper2 _cons SS a.u-shaped O b.inverse u-shaped OC. linear O d. exponential 1927.87673 5232.53756 7160.41429 df .5953429 .268287 -.0046123 -3.96489 3 522 Coef. Std. Err. MS 525 13.6388844 0530251 0368969 .000822 .7521526 642.625576 10.0240183 Number of obs F(3, 522) Prob > F R-squared t P>|t| 11.23 0.000 0.000 7.27 -5.61 0.000 -5.27 0.000 = Adj R-squared = Root MSE = .4911741 .1958023 -.006227 -5.442508 = 526 64.11 0.0000 0.2692 0.2650 3.1661 [95% Conf. Interval] .6995118 .3407717 -.0029975 -2.487272 where wage is hourly wage in US$, educ is years of education, exper is years of work experience and exper2 is experience squared (exper* exper). According to these estimates, what is the functional form of the relationship between experience and predicted wage when we hold education constant?

Consider the following regression estimates (ID6) Source Model Residual Total wage educ exper exper2 _cons SS a.u-shaped O b.inverse u-shaped OC. linear O d. exponential 1927.87673 5232.53756 7160.41429 df .5953429 .268287 -.0046123 -3.96489 3 522 Coef. Std. Err. MS 525 13.6388844 0530251 0368969 .000822 .7521526 642.625576 10.0240183 Number of obs F(3, 522) Prob > F R-squared t P>|t| 11.23 0.000 0.000 7.27 -5.61 0.000 -5.27 0.000 = Adj R-squared = Root MSE = .4911741 .1958023 -.006227 -5.442508 = 526 64.11 0.0000 0.2692 0.2650 3.1661 [95% Conf. Interval] .6995118 .3407717 -.0029975 -2.487272 where wage is hourly wage in US$, educ is years of education, exper is years of work experience and exper2 is experience squared (exper* exper). According to these estimates, what is the functional form of the relationship between experience and predicted wage when we hold education constant?

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

Chapter4: Estimating Demand

Section: Chapter Questions

Problem 8E

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