The article explores how bias can occur when spatial effects are left out of a statistical model. By using spatial econometrics techniques, the researchers compared a spatial model (SAR) with a non-spatial model (OLS) using a Monte Carlo experiment. They found that the OLS estimate of the SAR model is biased and inconsistent. The study also revealed that the bias from omitting spatial effects depends on the level of spatial autocorrelation present in the data.