Question

Consider the following model: Yi​=β0​+β1​ Eduation i​+β2​ Experience i​+ui​. Suppose you leave out the years of experience variable. What kinds of problems or biases would you expect? Explain verbally (in case there is a bias, determine its sign).

Answer 1

Leaving out the years of experience variable in the model can lead to problems such as omitted variable bias, resulting in biased estimates of the coefficients and an unreliable model. The sign of the bias cannot be determined without additional information.

Step-by-step explanation:

If the years of experience variable is left out in the model, it can lead to several problems and biases. One problem is omitted variable bias, where the omitted variable (years of experience) is correlated with the included variables (education level), leading to biased and unreliable estimates of the coefficients. In this case, the omission of years of experience can result in an overestimate or underestimate of the effect of education on the dependent variable (Yi). The sign of the bias cannot be determined without further information regarding the relationship between years of experience and the dependent variable.