The use of least median of squares in the estimation of land value equations

Ordinary least squares (OLS) regression is relatively sensitive to the presence of outliers in a data set. In this paper, a robust estimation method, least median of squares (LMS) is used to identify outliers in land value data. Once the outliers are identified, are the land value equations re-estimated. The results show that a few observations can have a significant effect on the estimated coefficients. Finally, the observations which were identified as outliers were examined in more detail. One cause of outliers is an omitted variable. In this case, a large fraction of the outliers were found to be observations with high development potential.