Optimal Comparable Selection and Weighting in Real Property Valuation
将统计理论应用于房地产估价中的可比对象选择与加权，发现传统做法并非最优，例如不应优先考虑“最佳”可比对象，且应纳入更多可比对象并优化权重。
This paper formalizes certain aspects of the sales comparison approach to valuation that heretofore have been quite ad hoc. Specifically, it applies statistical theory to decisions about how many comparables to select, what the criteria for comparable selection should be, and how the proper weights for each adjusted value estimate can be determined such that the final value estimate is both unbiased and of minimum variance. Several results are derived that run counter to conventional practice; for example, it may not always be optimal to consider first the “best” comparables because of a lack of independence among their adjusted value estimates. Furthermore, it is always desirable to consider more comparables (regardless of how “bad”) so long as their adjusted value estimates are optimally weighted in the final value estimate. Finally, weights usually selected for “inferior” comparables are typically too small. A final exercise empirically applies the methodology to a sample of sales.