For one last time, consider your linear regression model of the relationship between hourly wage, education, and labor-market experience: = wagei bo+beduci + bexperi + ei. Suppose your friend wants to improve the predictive performance of your model by including a third explanatory variable that is equal to the sum of education and labor-market experience. Which of the following statements should you tell your friend? Include it--you should always add as many explanatory variables as possible. Don't include it--it is not correlated with education or labor-market experience, so it won't help with the prediction. Don't include it--it doesn't provide any new information. Include it--adding explanatory variables always improves the goodness-of-fit