Real Estate News & Commentary

Pair Data Analysis, an Investors Best Friend

13 Articles Written

When sufficient data is available, paired data analysis can be utilized as one of the most persuasive tools in a Comparative Market Analysis. Paired data analysis can be broken down into two categories: Primary pairings (pairs of sales that are identical except for one component) and secondary pairings.

Want more articles like this?

Create an account today to get BiggerPocket's best blog articles delivered to your inbox

Sign up for free

Primary pairings should be used first and carry the greatest weight.  An example of a primary pair would be the sale of the same property over time.  If a house was sold twice within a 5 year period, and both transactions represented an arm’s length transaction, than changes in price would reflect changes in localized market forces during that time.


Be sure to investigate whether prices reflect the behavior of a typical buyer and seller in that market area.  Check for conditions of sale, buyer/seller motivation, favorable financing, and property rights sold.  Besides the bundle of rights, people may purchase additional rights towards personal property, rights to sell, purchase, or manage other homes, or even other business ventures.

If there are multiple elements that warrant adjustment, then different primary pairings may be used to isolate these elements.  Judgment is needed in determining whether adjustments from multiple elements can be isolated and affect the purchase price in a linear fashion.  Care must be taken to ensure that adjustments are supported by market evidence.  Oftentimes, only qualitative adjustments can be made in the absence of market data.


Though theoretically sound, the main issue with this form of analysis is that the required data is rarely available.  An exception to this rule would be in analyzing market data in regards to changes in market forces.  This constant quality methodology is used by influential house pricing indexes published by the S & P (Case/Shiller) and the US Government (OFHEO HPI).  When there is limited data, one can still use this technique for certain adjustments and use secondary data to verify the likely hood that these adjustments are accurate.

Photo Credit: StuSeegerCC 2.0