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The dataset beauty from Wooldridge contains data on wages and subjective attractiveness. Individuals were rated on a scale of 1-5 for attractiveness. . wage: hourly
The dataset beauty from Wooldridge contains data on wages and subjective attractiveness. Individuals were rated on a scale of 1-5 for attractiveness. . wage: hourly wage . Iwage: log(wage) . belavg: =1 if looks =4 . exper: years of workforce experience . looks: from 1 to 5 union: =1 if union member . goodhlth: =1 if good health . black: =1 if black . female: =1 if female . married: =1 if married . south: =1 if live in south . bigcity: =1 if live in big city . smilcity: =1 if live in small city . service: =1 if service industry . expersq: exper*2 . educ: years of schoolingQuestion 1 How many women are in the sample? How many men? Question 2 What are the mean wages for men? For women?Question 3 Estimate lwage = Bo + Abelavg + Brabvavg + Byfemale + Breduc + Byexper + Beerper + u. Question 4 How much of the variation in log wage is explained by the model? Question 5 Run the Breusch-Pagan test on the regression from question 3. What can you conclude? Question 6 Find the t-test for individual coefficients using heteroskedastic robust errors
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