in theory, people will say that if in your regression equation the value of your predictors = 0 implies that your dependent variable should also = 0 then removing the intercept would make sense...

in reality, removing the intercept tends to bias your results in one way or another because you're forcing the regression to go where you want it in a rather arbitrary way... because, if you think about it, you should leave the data to speak for itself and if it includes the point (0,0) (in the bivariate regression case, please feel free to add as many coordinates as you want) then so be it but if there is no (0,0) point in the collected data to begin with, why force the regression line to include a point that was not observed?

i think (well, better say "hope") that the general consensus is that the intercept should never be removed from the regression equation..