Basically, should any decent regression model overestimate 50% of the time and underestimate 50% of the time (in the limit)?
In a scenario where a regression model outputs a price, which has to be non-negative, would the distribution of the residuals of an unbiased model still be expected to be ~symmetric around 0?
Or does the asymmetry in this price example mean that we expect the residual distribution to have a positive skew, since there's no limit to how much the model can overestimate but there is a limit to how much it can underestimate (due to the non-negativity)? Or does it depend on exactly what model is being used and the assumptions the model makes about its error terms?
If a positively skewed residual distribution is expected, is a simple regression adjustment of the predicted values a viable way to improve model accuracy?