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Unformatted text preview: 1 Problem Set I: Solutions For this problem set you use the data set NLS.MAT. The variables in this data set are luwe (log weekly wage), educ (years of education), exper (years of experience), age (age in years), fed (father’s education in years), med (mothers education in years), kww (a test score), iq (an iq score), and white (indicator for white). 1. Estimate a linear regression model for log wages on education, experience, and experi ence squared. Report the estimates and standard errors. Table 1: Estimates and Standard Errors intercept educ exper expersquared σ 2 estimate 4.0163 0.0923 0.07910.0020 0.1684 s.e. (0.2223) (0.0076) (0.0249) (0.0009) (0.0078) 2. Predict the effect on average log earnings of increasing everybody’s education level by one year. Let the regression be log(earnings) i = β + β 1 × educ i + β 2 × exper i + β 3 × exper 2 i + ε i . For individual i with current level of education educ i and level of experience exper i , the effect of increasing their education level by one year is...
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This note was uploaded on 07/22/2008 for the course ECON 513 taught by Professor Rashidian during the Fall '07 term at USC.
 Fall '07
 Rashidian
 Econometrics

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