In ols models it's easy to sign omitted variable bias. If z is positively correlated with x and positively correlated with y, omitting z will bias the estimate upwards.

However sometimes in fixed effects models the effect of z on y may be negative even though the correlation between z and y is positive. How do these "flipped signs" impact your ability to sign omitted variable bias in fixed effects models.