Buildings can be compared to a bundle of goods sold in a market, where each of the building characteristics combined equate to the expected overall transaction value. By collecting data on many different buildings a regression analysis can be used to determine the correlation (relationship) of each characteristic to the transaction price —e.g. physical characteristics and other external influencing elements that may add or subtract from the building value. Each of these correlations can be measured to determine a degree of confidence (i.e. significance) and then subsequently be used to build a hedonic pricing model. Hedonic pricing models can be useful to determine the intrinsic value of each attribute, as well as to predict transaction prices. This can be particularly useful when traditional discounted cash flow models fall short because of the absence of a market, when no comparable buildings exist, and for nonincome generating buildings.