CompStak's approach to rent data aggregation

While Starting Rents and Effective Rents data are accurate individually, aggregating them directly for lease comparables can lead to misleading results, particularly in time series analysis

Consider this example: In 2020, 80% of leases might have been NNN deals with an average rate of $10, while the remaining 20% were Gross leases averaging $20. By 2021, the distribution shifted to an even split between Net and Gross leases, with averages of $9 and $19, respectively. Simply averaging without considering Lease Type would result in an average of $12 in 2020 and $14 in 2021. This is misleading as it suggests an increase in average rents when, in fact, rents within each Lease Type group have decreased. The perceived increase is due to the shift in Lease Type distribution, a typical example of the Simpson’s Paradox - a statistical phenomenon where a trend appears in different groups of data but reverses or disappears when the groups are combined.

To resolve this aggregation challenge, CompStak calculates Adjusted Starting Rent and Adjusted Effective Rent attributes. These adjustments are crucial for accurately aggregating data in analytical products, especially for trend analysis.