Assignment1 - as well as the residual variance 2 Predict...

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1 Problem Set I For this problem set you will have to use the data set nls.mat or nls.asc which are available on the website for the course. There are 930 observations on nine variables in this data set, 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 ex- perience squared. Report the estimates and standard errors. Also report the full variance/covariance matrix for all parameters, that is both the regression parameters
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Unformatted text preview: as well as the residual variance. 2. Predict the effect on average log earnings of decreasing everybody’s education level by one year. 3. Can you obtain the above effect by running a regression with a redefined set of covari-ates? How? 4. Predict the effect on the average level of earnings of the following policy: increase the level of education for those who currently have earnings below 12 years of education to 12, and leave the level of education for others unchanged. 5. Calculate the standard error for the above policy....
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