In a regression, when you get negative coefficient which you know should be positive, why it is necessary to include possible omitted variable that is likely to have positive coefficient and negatively correlated with the variable already in the model? How will this change the sign of the variable?
For example, if the dependent variable is car price, and the independent variable is fuel economy (with the wrong negative sign). Why it is advised to include perhaps curb weight which is negatively correlated with fuel economy and positively with car price?