Originally Posted by

**Jiffy22** Can anyone help with this problem?

Would appreciate any partial or full input. Thanks.

Suppose that we estimate a model:

$\displaystyle

wage_i = \beta_0 + \beta_1 \cdot grade_i + \epsilon_i

$

but the true model is

$\displaystyle

wage_i = \beta_0 + \beta_1 \cdot grade_i + \beta_2 \cdot experience_i + \epsilon_i

$

What will the consequences be for our regression estimates? Are these serious; is this something we have to care about? Assume instead that it is the way around; thus, that the true model is.

$\displaystyle

wage_i = \beta_0 + \beta_1 \cdot grade_i + \epsilon_i

$

but we are estimating

$\displaystyle

wage_i = \beta_0 + \beta_1 \cdot grade_i + \beta_2 \cdot experience_i + \epsilon_i

$

what are the consequences on our regression estimates. Are these serious consequences; do we need to care about this? ** Note:** No calculations are needed!