Regression (1) in Table 1 estimates the effect of additional educationby regressing ln (W age) on Exp, Exp2, W ks, Ed and all the dummyvariables listed above. Does the estimated regression suggest that additional years of schooling increases the wage? A wage equation is analysed in a balanced panel of 595 observations on headsof households. The sample data are drawn from years 1976-1982 of a surveyof income dynamic. The equation to be estimated isIn (Wage it)B₁ + B₂ Expit + B₂Exp²t + B₁Wksit + ß5Occit+B6Indit +B7Southit +P8SMS Ait + BgM Sit+B10Unionit + B11Femit + B12Edit + ß13 Blkit + Uit,where the variables are as follows:Exp...years of work experience,Wks...weeks worked,Occ...1 if blue-collar occupation, 0 if not,Ind...1 if the individual works in a manufacturing industry, 0 if not,South...1 if the individual resides in the south, 0 if not,SMSA...1 if the individual resides in a Standard MetropolitanStatistical Area (SMSA), 0 if not,MS...1 if the individual is married, 0 if not,Union...1 if the individual wage is set by a union contract, 0 if not,Fem...1 if the individual is female, 0 if not,Ed...years of education,Blk...1 if the individual is black, 0 if not.Note that variables Fem, Ed and Blk are time invariant (i.e. constant) inthe sample. The average number of years of experience in the sample is 19. Table 1: Results for estimating regression models for fatalities (standarderrors of the estimated coefficients in parentheses).RegressorExpExp²WksОссIndSouthSMSAMSUnionEdFemBlkIndividual EffectsTime EffectsR²(1)Regression Effects(2)(3)(3)0.0401(0.0042)0.00422(0.00152)-0.000673 -0.000418(0.000093)(0.000060)-0.140(0.027)0.0468(0.0230)-0.0557(0.0253)0.152(0.024)0.0484(0.0384)0.0926(0.0243)0.0567(0.0052)-0.368(0.049)-0.167(0.045)NoNo0.429(2)0.113(0.004)Fixed effectsFixed effectsYear effects0.000836(0.000685)-0.0215(0.0147)0.0192(0.0140)-0.0019(0.0413)-0.0425(0.0196)-0.0297(0.0150)0.0328(0.0198)IYesNo0.8910.112(0.00197)F statistic38.236.248.2-0.000398(0.0000595)0.000652(0.000684)-0.0192(0.0151)0.0206(0.0140)Table 2: Tests for joint significance of effects (null hypothesis: coefficientson effects are jointly zero).0.00314(0.0415)-0.0423(0.0189)-0.0284(0.0146)0.0299(0.0195)YesYes0.892p value<0.0001<0.0001<0.0001

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errors of the estimated coefficients in parentheses). Regressor Exp Exp² Whe (1) els for 0.0401 (0.0042) (2) 0.113 (0.004) -0.000673 -0.000418 (0.000093) (0.000060) 0.00422 0.000836 (3) 0.112 (0.00197) -0.000398 (0.0000595) 0.000652

errors of the estimated coefficients in parentheses). Regressor Exp Exp² Whe (1) els for 0.0401 (0.0042) (2) 0.113 (0.004) -0.000673 -0.000418 (0.000093) (0.000060) 0.00422 0.000836 (3) 0.112 (0.00197) -0.000398 (0.0000595) 0.000652

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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