Referring to EXAMPLE 12 from CFAI, page 291-

Evaluating Economic Forecasts (2)

…If the forecasts are unbiased, the intercept, *b*_{0}, should be 0 and the slope, *b*_{1}, should be 1. We should also find *E*(Actual change – Predicted change) = 0. If forecasts are actually unbiased, as long as *b*_{0}= 0 and *b*_{1} = 1, the error term [Actual change − *b*_{0} − *b*_{1}(Predicted change)] will have an expected value of 0, as required by Assumption 3 of the linear regression model. **With unbiased forecasts, any other values of b_{0} and b_{1} would yield an error term with an expected value different from 0.**

Can someone pls explain why any other values of *b*_{0} and *b*_{1} would yield an error term with an expected value different from 0?