DIRECT STRATIFICATION: A White Paper
For market value estimates of improved commercial, industrial, and multifamily (CIM) real property to be meaningful, those estimates must emanate from current market transactions directly relevant to those properties. The process of attempting to achieve this direct relevance is called Stratification in ad valorem property assessment terms; division of a sample of market data into subsets which relate to the date of valuation as well as to physical, functional, and location attributes of a given property. Another term used in assessment, Direct Match, refers to establishment of value based on direct match to an identical asset.
Combining the terms Direct Match and Stratification into Direct Stratification reasonably describes the ability of well effected income modeling to accurately fill in the generous (and sometimes enormous) stratification gaps emblematic of sales comparison.
Direct Stratification only arises from sufficient transactions reflecting the spectrum of existent properties, yet the market is rare that elicits sufficient sample of sales for anything but extrapolated stratification. The necessity of extrapolation from available sale data invariably reduces its relevance, and often results in a stratification model that is linear, which clearly is not how the market always works.
|Consider three bulk warehouse sales:||100,000 SF||sold for: $40/SF|
|200,000 SF||sold for: $35/SF|
|1,000,000 SF||sold for: $30/SF|
Linear modeling of the market based on those available sales above suggests unit valuation on a declining scale inverse to size; the largest building has the lowest price/SF. Further, it would suggest a 500,000 SF warehouse would sell for somewhere between $30 - $35/SF.
What if the relative proximity of this market to major interstate highways and deepwater ports causes the most desirable bulk warehouse size to be 500,000 SF, and triple net market rents for these structures in this market were as follows?
|100,000 SF||200,000 SF||500,000 SF||1,000,000 SF|
|Rent per SF/Year||$4.00||$3.50||$4.00||$3.00|
|Effective Gross Income (EGI)||$3.60||$3.15||$3.60||$2.70|
|Management & Reserves (% of EGI)||5%||5%||5%||5%|
|Net Operating Income (NOI)||$3.42||$2.99||$3.42||$2.57|
|Overall Capitalization Rate (OAR)||8.5%||8.5%||8.5%||8.5%|
|Estimated Value per SF||$40.24||$35.18||$40.24||$30.24|
Via Direct Capitalization, the 500,000 SF warehouse estimated value ($40.24/SF) is NOT between $30 - $35 indicated by linear analysis of the sales. This result is based on consistent market indicators of vacancy, management & reserve allocation, and OAR.
Even more realistically, since the 500,000 SF size is the most desirable, it could have a slightly lower market vacancy rate and OAR than the prevailing bulk storage market indicators: the value with $4.00 rent, at 8% vacancy, less 5% management and reserve allocation, capitalized at 8.25% = $42.50/SF. If this 500,000 SF property were assessed on available sales only ($30 - $35/SF), the valuation would be significantly understated.
Simply put, there are thresholds of utility, use, and appeal in many (probably most) markets that can completely defy linear pricing relationships:
Size: many sale based models assume inverse size/sale price relationships. The former example demonstrates this is not always true. Further, the opposite can be true as in multi-tenant office properties where scale (size of property and number of tenants) is often perceived as incrementally desirable for both the public appearance of professionalism and the actual provision of professional management services.
Property Subtype: is it a budget hotel or a limited service hotel? Is it bulk storage or distribution? Lumping available sales into general use categories ignores the quite distinct operating and investment realities of these properties.
Tenancy Type and Strength: ignoring whether single or multi-tenanted and the strength of that tenancy will guarantee inaccuracy in real property valuation modeling. These aspects directly affect the lease structures, lease rates, vacancy attributes and resulting investor returns. Proper division of valid sales to reflect these characteristics often relegates the sample to insufficiency.
Location: as in the type of tenancy, division of sales samples into truly comparable location subsets (urban and suburban, airport, medical/university campus, high or low exposure) often precludes meaningful analysis.
Careful, informed modeling of local lease practices reveals and explains these market characteristics like no other methodology can.
Sales-only analysis so often fails to recognize property characteristics and market nuances that can impact value. One of the reasons is that sales are commonly expressed at simple unit rates (often per square foot of building area). Conversely, lease transactions are expressed in a structural context revealing the dollar amount of rent, participant responsibility for expenses, duration, tenant improvements, and extent of commonality of amenities offered.
Lease terms effectively describe the property design and use as well as the type and quality of tenancy. This information is simply a revelation for stratification purposes that sales methodology cannot match without careful description and reporting, and even with complete and consistent sale comparable characterization, this method still lacks sufficient frequency of occurrence.
Comprehensive lease practice modeling based on local market data provides Direct Stratification for CIM real property. The stratification is direct because it mirrors the market surveyed in type, subtype, use and tenancy. Achieved market rents, market vacancy, expense structures/rates, and OARs are surveyed and collected for the existing local property spectrum by size, age, condition, utility, and specific location.
The reason there is significantly more verifiable market data in income analysis compared with sales is obvious - properties capable of producing income are quite often rented. They are purchased for their ability to be rented and investors usually hold them through numerous tenancies. The sale frequency simply does not nearly match the rental frequency, affording the rental analysis through income modeling a distinct and pervasive advantage in accurate stratification.
Finally, while frequency of sales are significantly less than available rental transactions, those that do occur offer proof of desired investor return (OAR) and a transaction unit price to verify the results of income-based modeling. Direct stratification and results from income modeling are proved by available sales. This is truly the best application of sales on a practical basis, and most certainly in a market with constrained liquidity.