Suppose you are interested in studying the determinants of wages. You plan to use the following model: wage=β0+β1educ+β2exper+u where wage = annual salary, in thousands of dollars educ = years of education exper = years of work experience You run the regression, and obtain the following results: wageˆ=14+1.8 educ+2.5 exper n = 200 R2 = 0.07 The predicted wage for an individual with 21 years of education and 5 years of experience is . The predicted wage for an individual with the same years of education but one additional year of work experience (that is, 6 years) is . The marginal effect of one extra year of work experience is . The R2 of this regression indicates that % of the variation in wage is explained by educ and exper together. Suppose you suspect that wages might be affected by the weight of each individual, either through discrimination based on weight by employers or decreased productivity, and therefore wages, brought on by an unhealthy weight. You decide to include body mass index (BMI) as a third explanatory variable to your regression. True or False: Assuming you use the exact same data set as before, adding the explanatory variable bmi will always decrease the R2 . True False