RV and Boat Storage Underwriting Method: Registrations, Space Demand and the Self-Storage Code It Shares

Why a yard for trailers, motor homes and boats needs its own method

A storage yard for recreational vehicles and boats sells a single product: a place to leave a large vehicle between trips. Some yards are no more than a fenced and paved lot with a keypad gate. Others put steel canopies over part of the lot, or build rows of enclosed drive-in units with tall overhead doors, and many self-storage facilities rent a strip of outdoor parking beside their buildings. The federal industry definition takes in all of these formats at once: the definition of NAICS 531130 counts outdoor space among the kinds of secure space a self-storage lessor may rent, next to rooms, compartments, lockers and containers ^[1]. That clause is the reason the class sits inside the self-storage code and has no loan record of its own, and it is the first of three features that make the underwriting method different from the method for an ordinary storage building.

The first feature is that demand is counted in vehicles rather than in people. A demand model for ordinary self storage can be built on population and households. A yard for trailers and boats serves only the households that own one, and those owners are recorded: boats in state vessel registers, motor homes and travel trailers in state motor vehicle files. The demand model therefore begins from registration counts, and much of the analyst's work lies in knowing what each count includes and what it leaves out.

The second feature is size. A travel trailer or a boat on its trailer fills a stall several hundred square feet in area, and it needs an aisle wide enough to back it in. Land and paving, not a building, are the main costs, so the site plan is part of the demand evidence: the number of spaces a parcel can hold, by length, decides how much of the counted fleet the yard can serve.

The third feature is the loan record. Because RV and boat storage shares the self-storage code, every SBA figure a lender can read for the class is the self-storage record, with an unknown number of vehicle yards inside it and some yards coded elsewhere. This article says so wherever it prints a loan figure.

Three neighbouring methods have their own articles, linked rather than repeated: drawing the trade area and estimating capture (trade area methods), counting rivals and the pipeline (supply and comparables), and timing the fill of a new facility (ramp-up and absorption). The site's archived guide to RV and boat storage studies covers the market narrative of the sector, and the New Jersey worked example carries a complete 504 study of a yard. What follows is the method particular to the class: the demand equations on public counts, the figures a credit officer reads, the record from the dataset's cells, what its floors can and cannot say, the eligibility rules, and a short model. Every project number in the model is a labelled assumption, every public number is cited to its page, and nothing here values a property: a study is not an appraisal.

The registration base: what federal and state counts hold

Boats are the better documented half of the fleet. In the Coast Guard's 2024 compilation, state registers held 11,674,073 recreational vessels, 1.1% more than the 11,546,512 of the year before ^[2]. The Coast Guard describes a registered vessel as one a state requires to be recorded, and it warns that the states do not share one set of registration requirements ^[3]. Some register only boats with motors; others add sailboats over a stated length, or every watercraft. Oregon, the state used in the model below, registers all motorized vessels and sailboats 12 feet or more in length, and its count was 150,115 in 2024 against 152,440 in 2023 ^[4].

State counts can also move for reasons unrelated to the number of boats afloat. Florida's line in the same table runs from 922,915 vessels in 2023 to 1,171,432 in 2024 ^[5], while California's falls from 672,103 to 596,703 ^[6]. The table does not explain either change, and this article does not guess. The point for a study is procedural: before a year-on-year change in a state's count is read as growth or decline, the analyst should ask the state's boating agency whether the fleet changed or the record system did, and should prefer a multi-year average where the agency cannot say.

In the sources read for this article, recreational vehicles are counted only by the states, and only where a state chooses to publish. Oregon's Driver and Motor Vehicle Services Division publishes, for every county, the vehicles with current registration at the end of each year by category. At the end of 2024 Deschutes County held 11,489 units in the Travel Trailer category, 1,242 campers and 4,875 motor homes ^[7]. Statewide the same categories held 128,544, 10,116 and 44,783 ^[8], against 129,516, 10,534 and 44,984 a year earlier ^[9], so the three classes together were close to flat across the two year-ends.

The categories need reading before they are added up, because they do not all hold what their names suggest. Oregon's Travel Trailer category starts with travel trailers, which provide facilities for human habitation ^[10], but it also holds special use trailers, which are not travel trailers at all: trailers eight and one-half feet wide or less, of any length, used for commercial or business purposes ^[11], trailers used for a time as construction site offices, and mobile modular units ^[12]. The county file prints one figure for the whole category, so the Deschutes County count is travel trailers plus an unknown number of commercial trailers. The other two classes are drawn wider than habitation alone. A camper is, among other conditions, a structure designed for human habitation or for camping ^[13], and a motor home may be a vehicle built or altered for habitation ^[14] or one carrying a permanently attached structure that would otherwise be a camper ^[15]; where habitation is the test, the report defines it as permanent sleeping and cooking facilities at a minimum ^[16]. A boat trailer fits none of these definitions. It falls into the light trailer class, a residual group of trailers with a loaded weight of 8,000 pounds or less other than for-rent, travel, special use and heavy fixed load trailers ^[17], and the definition does not separate boat trailers from utility or cargo trailers. Light trailers therefore cannot stand in for a boat count. The county file also leaves out every vehicle registered to an address in another state ^[18]. In a county with many seasonal residents, a motor home kept there half the year but registered at its owner's home in another state is missing from the count. The two gaps pull in opposite directions. Special use trailers inflate the RV classes, so the summed classes are an upper figure for the RVs registered in the county; out-of-state registration pulls the count of RVs actually kept there the other way. A study should ask the motor vehicle agency for a split of the Travel Trailer category, or at least name both gaps and the direction of each, before the count is relied on.

Counts become comparable once they are divided by residents. The Census Bureau puts Deschutes County at 211,202 residents on July 1, 2024 ^[19] and Oregon at 4,265,324 on the same date ^[20]. The first rows of Table 2 turn those figures into rates: 83.4 units in the three RV classes per 1,000 county residents against 43.0 for the state as a whole, and 35.2 registered boats per 1,000 Oregon residents. A ratio of that kind is a screen, not a conclusion: it shows an unusual concentration of units in those classes, commercial trailers included, not how many are already parked on their owners' land, which the rest of the model has to estimate.

The demand equations, input by input

The model turns registered units into a count of vehicles whose owners will pay for a space, then sets that count against every space that will compete for them. It has six steps.

1. RV class units in the radius equal the units in the county's Travel Trailer, camper and motor home categories, special use trailers included because the file does not split them out, multiplied by the share of the county's residents who live inside the facility's drive radius.
2. Where the state boating agency has not supplied a county figure, boats in the county equal the state's registrations divided by the state's residents and multiplied by the county's residents.
3. Boats in the radius equal boats in the county multiplied by the same radius share.
4. Paid-storage demand equals RV class units in the radius times the share of their owners who store off their own lot for pay, plus boats in the radius times the matching share for boat owners.
5. Market occupancy implied equals paid-storage demand divided by the sum of existing competitive spaces, pipeline spaces weighted by their stage, and the subject's own spaces.
6. Required capture equals the subject's spaces times its stabilized occupancy, divided by paid-storage demand, and it is read against the subject's fair share of the spaces counted.

Table 1 lists every input the article's model uses, from the registration counts to the loan terms of the short model in a later section, with the basis of each. The registration and population inputs are cited counts. The rest are assumptions, and each one names the evidence that would replace it in a real study.

Rounded as shown; lines may not foot by one unit in the last place.

Three of the assumptions carry most of the weight. The radius share comes from a drive-time map: a study draws the area from which owners will tow or drive to the site and counts the residents of the block groups inside it, and the share in the model stands in for that count. The off-site shares are the hardest inputs to evidence, because no public series measures them. A study can build them from three sources: a survey of registered owners inside the radius; the covenants of the residential subdivisions there, many of which restrict parking a trailer or boat in view; and the municipal parking codes, which set what a homeowner may keep in a driveway or side yard. The supply count comes from a competitor census that includes self-storage facilities renting parking and the dry storage of marinas, with the pipeline weighted by stage as the supply article explains. A slip or rack at a marina is supply, not demand: a boat already in one is a customer the subject would have to win from a competitor.

The boat estimate in step 2 is the model's weakest link, and it is printed as an estimate. Spreading the state's registrations across counties by population assumes the county's boats per resident equal the state's. Oregon's own RV counts show how far a county can sit from the state rate, so a study should obtain the county's vessel count from the state boating agency and replace the estimate before the demand figure is relied on.

Read Table 2 down its base column first. Inside the radius the model finds 7,042 units in the RV classes and 2,973 boats, and at the assumed off-site shares 2,355 of them seek paid storage, boats making up 25.2% of that demand. Because the RV classes carry special use trailers, the RV side of that demand is an upper figure. Against 1,900 existing competitive spaces, 300 weighted pipeline spaces and the subject's 260, the market would run at 95.7% once the subject opens. The subject needs 9.9% of paid-storage demand to reach its stabilized occupancy, slightly less than its 10.6% share of the spaces counted, so on these inputs it does not need to outperform the market.

The two other columns show how thin that result is. Taking 5 points off both off-site shares cuts demand to 1,854 and implied market occupancy to 75.4%, and the capture the subject needs rises to 12.6%, above its fair share. Narrowing the radius by 10 points of the county's residents does much the same, to 1,766 units and 71.8%. Neither change is extreme, which is why the owner survey, not the registration count, is the evidence a lender should ask to see first.

Space per unit: the fleet's lengths and the land behind each stall

The second half of the demand model is physical. A yard sells spaces of fixed sizes, so the length mix of the fleet it serves decides both how many spaces a parcel can hold and whether the spaces on offer match the vehicles that need them.

For boats the Coast Guard supplies the mix. Its length table divides 10,852,992 mechanically propelled vessels into five bands: 3,731,822 shorter than 16 feet; 6,480,886 from 16 feet up to 26; 552,622 from 26 up to 40; 76,407 from 40 to 65; and 11,255 longer than 65 ^[21]. Table 3 turns those counts into the shares that matter for a site plan: 94.1% of registered motorized boats are under 26 feet, and 5.9% are 26 feet or longer. A plan that sizes its boat and trailer spaces for the under 26 foot fleet, and lets the few longer boats take RV-length spaces, matches the registered fleet. The figures are national; a study in a coastal or lake market should look for the state agency's length breakdown, because the mix there may differ.

For RVs no public dimension was read for this article, and the model's 12 by 45 foot stall is an assumption. A study should take stall sizes from the subject's own site plan and test them against the vehicles registered in the radius, since a space that is a few feet short is a space the longest motor homes cannot use.

The space table shows why land dominates the cost. The 260 spaces in the plan occupy 125,400 square feet of stall and unit area, but backing a trailer into a stall takes aisle, and the setbacks, the office, the gate and a stacking lane take more. With the assumed 1.1 square feet of aisle and setback per square foot of stall, the yard needs 6.55 acres and holds 39.7 spaces per acre. At the assumed land price, land alone costs $3,147 per space. A study should print this arithmetic, because it ties the demand count to the parcel: a parcel that holds fewer spaces than the demand model supports leaves revenue on the table, and one that holds more is a lease-up risk. The plan gives boats 26.9% of its spaces against the 25.2% share of paid demand the model attributes to them, a close match; a wider gap in either direction would be a finding for the study to explain.

The figures behind a credit decision on a storage yard

For each figure below, the study should say what evidences it and which published series or rule anchors it; the list is the study's method, not a description of any lender's policy.

• Registrations per resident, county against state. Evidenced by the state motor vehicle file and the Coast Guard's state table, each with its date and scope ^{[7] [4]}. A study prints both rates and explains a large gap before using it.
• Paid-storage demand against the spaces counted. The implied market occupancy in Table 2 has no published anchor; it rests on the owner survey and the competitor census, and the study should show both.
• Physical and economic occupancy. Physical occupancy counts spaces let; economic occupancy counts rent collected against rent asked. For a proposed yard both come from the rent rolls or published asking rates of the competitors in the radius; for an existing yard, from its own rent roll and bank deposits.
• Rent per space, by space type. Open, covered and enclosed spaces rent at different rates, so a single average hides the mix. No public series reports them, and the model's rents are assumptions.
• Space mix against fleet length. Anchored nationally by the Coast Guard's length table ^[21] and locally by whatever the state agency publishes.
• Spaces per acre and land per space. Anchored by the civil engineer's site plan, never by a rule of thumb.
• Operating expense ratio. The model's 35% is an assumption; line-by-line expense evidence belongs to the expense article.

Debt service coverage comes next, read against two minimums. The site's own SBA program page sets the 7(a) floor at 1.15x of business coverage with a startup given a two-year window from funding to reach it ^[25]; for 504 the page uses the same multiple, tested either on the borrower's history or on two years of projections ^[33]. The second minimum is a lender assumption of 1.25x, stated as an assumption because 13 CFR 120 does not set it. How the ratio is built, and why the higher of the two binds, is the subject of the coverage article.

Conventions. This article follows the conventions of the Loan Analytics worked examples. Coverage is tested against the program floor the site's program page states, where the program has one, and against a stated 1.25x lender assumption, and the higher of the two binds. Equity is measured at the loan the cash flow supports, with fees recomputed on that loan. An acquisition is tested on the seller's historical earnings, not on projections.

Loan to value is the third test, and for a bank it has a supervisory anchor. The interagency guidelines say a bank should write its own loan-to-value ceilings and keep them at or below the supervisory figures ^[34]. Those figures are 65 percent (raw land) and 75 percent (land development) ^[35], 80 percent (construction, commercial, multifamily and other nonresidential) ^[36] and 85 percent (improved property) ^[37]. Where one loan pays for land, site work and building in sequence, the ceiling that applies is the final phase's, and the guidelines say draws should not run ahead of what was actually spent ^[38]. The guidelines add that a lender should consider a tighter internal ceiling for any subcategory carrying more credit risk than its category as a whole ^[39]. Whether a yard whose improvements are mostly paving and canopies is such a subcategory is the lender's judgment, not the study's; the study's job is to give the lender the cost by component, so the appraiser's value can be set against what was built. The conventional lending article sets those guidelines out in full.

Two state-law items belong on the same list, and Florida shows why. Its sales tax statute treats renting parking or storage spaces for motor vehicles in parking lots or garages, and docking or storage spaces for boats in boat docks or marinas, as a taxable privilege ^[40], taxed at 6 percent of the total rental charged ^[41]. The provision names its settings, so whether a given yard falls inside it belongs with the operator's tax counsel; the study's part is to state every rent net of any such tax, so that a tax collected on top of rent is not counted as revenue. Florida's Self-service Storage Space Act also governs what an operator can do when a customer stops paying. The Act defines a self-service storage facility as real property designed and used for renting individual storage space to tenants who have access to store and remove personal property ^[42], and whether a given yard meets that definition is again a question for counsel. Where it does, once rent on a stored motor vehicle or watercraft has gone 60 days past due ^[43], the owner may either sell it under the section or call a tow ^[44]. Sale proceeds satisfy the owner's lien only where that lien has priority over all other liens, and secured lienholders' rights pass to what remains ^[45]; where the owner's lien lacks priority, the proceeds are held for the holders of the senior liens ^[46]. For an underwriter the consequence is plain: a delinquent account secured by a financed boat or motor home may yield the operator little, and the study's credit loss allowance should reflect the state's statute rather than a self-storage average.

The SBA record the class borrows from self storage

The loan dataset files RV and boat storage under its self-storage class, and the class's cells carry the asset map's limitation that the two cannot be separated; nationally that class holds 1,584 ^[47] 7(a) approvals over fiscal years 2017 to 2026. The record is wider and narrower than the class at the same time. It is wider because every figure below counts climate-controlled storage buildings alongside open yards. It is narrower because some vehicle yards carry other codes. The asset map also points RV and boat storage to other warehousing, a code defined to cover storage facilities other than general merchandise, refrigerated and farm product storage ^[48]. A marina's dry storage belongs to 713930, the marina code, which covers establishments running docks or storage for the owners of pleasure craft ^[49], while storage space rented with no marina attached returns to 531130 ^[50]. The dataset's way of turning codes into classes, and of disclosing a shared code, is explained in the article on assigning loans to classes.

Read with that caution, the self-storage record shows two programs of different shape. Over fiscal years 2017 to 2026, 7(a) approvals coded to self storage, the code RV and boat storage shares, total $2,313,999,900 ^[47] with a median loan of $975,000 ^[47], and half of them fall between $450,375 ^[47] and $2,000,000 ^[47]. The class's 946 ^[51] approvals under 504 carry $1,218,821,000 ^[51], a figure that counts the debenture alone, with a median debenture of $890,000 ^[51]; the third-party bank loan in each 504 project is not in that sum. Approvals appear in 47 ^[47] of the file's project-state codes under 7(a) and 47 ^[51] under 504.

Franchise codes are rare in the record. Of the self-storage 7(a) approvals, 6.82 percent ^[47] carry one, and of the 504 approvals 0.74 percent ^[51]. The dataset gives no reason for the gap between the programs, and none is offered here.

The yearly series moves a good deal. Self-storage 7(a) approvals, RV and boat yards included where they carry the code, numbered 172 ^[47] in FY2017, 296 ^[47] in FY2021 and 109 ^[47] in FY2026; the 504 count for the same class went from 71 ^[51] to 181 ^[51] and then to 59 ^[51] over those years. The dataset holds approval records and nothing on motive, so the series is not evidence of demand for storage of any kind. The program and class pages on the site, self storage under 7(a) and self storage under 504, print the full record with its keys, and the loan-data table that closes this section lists the values this article relies on.

Loan Data Behind This Article

Every figure in this table comes from the Loan Analytics loan dataset, analytics-loan-data freeze-3 (commit 360c856), and carries its key. SBA rates are approval-cohort floors and are withheld when fewer than 30 loans stand behind them.

What the cohort floors can and cannot show for the class

Two rates in the record bear on failure, and both are approval-cohort floors. The first is cancellation: approvals cancelled before any money moved. Self storage's 7(a) approvals of fiscal 2017 through 2024, with whatever RV and boat yards carry the code inside them, show a cancellation floor of 11.14 percent ^[47]; the whole 7(a) program, same cohort, shows 11.24 percent ^[53]. Under 504 the self-storage class runs above its program: 19.15 percent ^[51], while every 504 approval in the cohort taken together gives 13.60 percent ^[54]. Each floor can only rise as approvals still undisbursed are cancelled; counting those as cancelled gives the ceilings, 11.43 percent ^[47] for the class under 7(a) and 23.76 percent ^[51] under 504, where 38 ^[51] of the class's approvals had not disbursed at the data date. The program's 504 ceiling is 16.90 percent ^[55].

The second rate is charge-off to date. Take the self-storage 7(a) loans of the fiscal 2017 to 2021 cohort that went on to disburse: charge-offs recorded so far put their floor at 0.50 percent ^[47], against a program-wide figure of 6.33 percent ^[52]. On the 504 side the program floor for those years is 0.35 percent ^[56], and the class shows 0.00 percent ^[51]. Holding the horizon fixed at five years from approval, the class's 7(a) floor is 0.12 percent ^[47] and the program's 3.72 percent ^[57].

What those floors can say is narrow. Self-storage loans approved in those cohorts have, by the data date, cancelled under 7(a) at about the program's rate and under 504 at a higher one, and few of them have been recorded as charged off. What they cannot say is wider. They cannot say anything about RV and boat yards apart from the rest of the code. They cannot say why an approval was cancelled, since the file records the cancellation and not its reason, as the cancellation article sets out. And they cannot say what losses will be. A charge-off rate here is a floor because the status of an open loan is withheld from the file: of the 806 ^[47] disbursed self-storage 7(a) loans in the cohort, 250 ^[47] were open at the data date, and under 504 267 ^[51] of 412 ^[51]. A loan that is open and troubled adds to the denominator and not to the numerator until it is charged off. The mechanics of that bias are laid out in the floors article.

For a study the floors do one job: they show the lender the recorded outcomes of the code the class shares, set beside the program's, and nothing more. The higher 504 cancellation floor is a fact to report, not one to explain without evidence. A state cell for self storage with fewer than 30 loans behind a rate prints that rate as withheld, for the reasons in the article on the thirty-loan rule, and a study working at state level should report it that way.

Eligibility: operator or landlord, size, jobs and rural location

A storage yard earns its revenue by renting space, and that puts the passive-business rule at the front of every SBA file. The ineligible list in 13 CFR 120.110(c) names "Passive businesses owned by developers and landlords that do not actively use or occupy the assets acquired or improved with the loan proceeds" while sparing Eligible Passive Companies ^[58]. The rule turns on active use, so the study's task is to document it: who staffs the office and the gate, who writes and enforces the customer agreements, who handles access, security, billing and collections, and which services are sold beside the space. A yard run by its owner under month-to-month agreements with many customers presents one set of facts; a parcel leased whole to an outside operator presents another. The study should set the facts down and leave the eligibility decision to the lender and SBA.

Where a holding company owns the land and the operator rents from it, the passive company route has its own conditions. An Eligible Passive Company may spend the proceeds only on property, bought, leased, improved or renovated, refinancing included, which it then leases to one or more Operating Companies to house their operations, among the uses 13 CFR 120.111 permits ^[59]. The rent it charges is capped at the loan payment plus its own direct costs of holding the property, maintenance, insurance and property taxes among them ^[60]. Section 120.130(d) also closes off "Investments in real or personal property acquired and held primarily for sale, lease, or investment (except for a loan to an Eligible Passive Company or to a small contractor under § 120.310)" ^[61], and under 504 the borrower must use the Project Property, with the same exception for a passive company leasing to its Operating Company ^[62]. The 7(a) program article sets those tests in their wider context.

The occupancy rules raise a measurement question particular to a yard. In a new building the borrower keeps 60 percent or more of the Rentable Property for its own permanent use and can lease no more than 20 percent permanently ^[63], and it must plan to occupy part of what is left inside three years and every unleased foot inside ten ^[64]; an existing building shifts the split to 51 percent used and at most 49 percent leased ^[65]. Rentable Property is, in the regulation's words, "the total square footage of all buildings or facilities used for business operations" ^[66]. On a site that is mostly open paving with an office and a few enclosed buildings, how that definition is applied is a question for the lender or CDC, not an assumption for the study. The study should present the space by type and by area, as Table 3 does, so that whichever reading the lender adopts can be applied to it.

The size test is measured with affiliates, which is where it can bite in this industry. SBA's size standard for NAICS 531130 is $34.0 million in annual receipts ^[67], and size standards are expressed in employees or in annual receipts in millions of dollars unless stated otherwise ^[68]. A 7(a) or 504 applicant may instead qualify if, with its affiliates, its tangible net worth is not over $20 million and its average net income after Federal income taxes for the two preceding completed fiscal years is not over $6.5 million ^[69]. Industry structure shows why the affiliate count matters. The Census Bureau counted 8,813 firms and 18,286 establishments in the code in 2022 ^[32], and the 35 firms with enterprise receipts of $100 million or more operated 8,454 of those establishments ^[70]. A yard that belongs to a large storage group, or shares owners with one, should have its size tested with every affiliate before the file goes further.

Under 504 the job test can decide the file, since the code averages under three employees per establishment, as the job table in the next section works out from Census counts. SBA counts a Job Opportunity as a permanent position, full time or its equivalent, that appears within two years of the 504 funds arriving, or one the loan keeps in the community ^[71]. A debenture carries SBA's guarantee on 100 percent of its amount ^[72], and under SBA's notice of September 30, 2025 each $95,000 of that guaranteed funding must be matched by one job created or kept, or each $150,000 where the project belongs to a small manufacturer or meets an energy public policy goal ^[30]; the amounts govern approvals dated October 1, 2025 or later ^[73]. A yard short of the count has a second route: one of the goals listed in 120.862, provided the CDC's 504 portfolio, counting this loan, still meets the Job Opportunity average the CDC must hold ^[74], an average the notice puts at one job for every $150,000 guaranteed ^[31]. The arithmetic for the model's yard is in the next section. The contribution rule adds one more question: a project centred on a structure of limited or single purpose sets the borrower's minimum at 15 percent, the same floor a business no more than two years old faces, and a project meeting both tests needs 20 percent ^[75]. Whether enclosed vehicle units are such a structure is a point the study should ask the CDC to settle in writing. The 504 program article covers the debenture structure itself.

USDA's Business and Industry program is a rural program: a project must be located in a State and meet the rural area requirements of its program section ^[76]. Its definition of a rural area covers "any area of a State not in a city or town that has a population of more than 50,000 inhabitants" ^[77]. Urbanized land adjoining a city of that size is left out as well, except a fringe area that has been determined to be rural in character ^[78], a determination the Under Secretary of Rural Development makes project by project ^[79]. Developing land, buildings or infrastructure for a commercial enterprise is among the project uses the regulation lists ^[80]. Two general exclusions then bear directly on a yard. One reaches "Properties to be used for primarily commercial rental when the borrower has no control over tenants and services offered" ^[81]; speculative real estate investment is barred too ^[82], outside narrow exceptions such as cooperative stock and NMTC projects ^[83]. The facts that answer the SBA passive question answer these as well, which is one reason a study should document operations before it documents the market. The series article on 7 CFR 5001 sets out the rest of the B&I test.

No state license specific to the class turned up in the sources read for this article. State law reaches the class through the storage lien statute and the sales tax, as the Florida examples above show, and through local zoning and parking codes, which a study should quote from the municipality's own text.

A short model: a 260-space yard financed under 7(a)

The short model takes the space plan of Table 3 and asks whether it carries a 7(a) loan. It is an illustration on assumed costs and rents; the New Jersey worked example carries the full analysis under 504.

Table 5 prices the plan. Land and site work follow the 6.55 acres the space table requires; canopies cover the 60 covered spaces and the 20 enclosed units are priced per unit, giving a total project cost of $3,917,182, or $15,066 per space. At full occupancy the four space types would rent for $692,400 a year, an average of $221.92 per space per month. The rents are assumptions; a study replaces each with the asking rents of the competitors in the radius, by type.

The requested loan is 80% of cost. Its rate floats at prime plus 2.75 points, prime standing at 7.00 percent on November 6, 2026 ^[22]. The 2.75 points stay under the most a lender may add on a variable-rate 7(a) loan bigger than $350,000, which is three points over the base rate ^[23]. The loan amortizes over 25 years, the 7(a) maximum, which the real property portion may stretch by the time construction takes ^[24], and it sits inside the $5,000,000 limit on any one 7(a) loan ^[84].

Table 6 gives the answer under the conventions. At the assumed 90% occupancy, net operating income is $405,054 and coverage on the requested loan is 1.21x. That is enough for the 1.15x floor the site's SBA program page gives ^[25] and not enough for the 1.25x minimum the lender is assumed to require, which, being the larger, governs. At the binding minimum the income supports a loan of $3,030,240. The SBA guarantee fee is recomputed on that loan at its statutory ceiling: a guaranteed share of 75 percent, the maximum for a loan above $150,000 ^[26], a fee of up to 3.5 percent on that share ^[27], and 0.25 percent more on any part of the share above $1,000,000 ^[28], or $82,725. The fee SBA actually charges in a given fiscal year may be lower; the ceiling is the conservative reading. With the fee paid in cash, the borrower puts in $969,668, 24.8% of project cost, against the fifth of cost, before fees, that the request assumed. The equity article explains why equity is measured at the supported loan.

The shock columns show what moves the answer. Ten points less occupancy takes coverage to 1.07x and borrower cash to $1,296,891; rents 10% lower take coverage to 1.09x; prime two points higher takes it to 1.04x and raises the cash the borrower must bring to $1,378,523, more than a third of cost. The last row turns the base case into a break-even: the requested loan covers its debt service at 1.00x at 74.5% occupancy, and that point rises to 82.7% when rents are 10% lower. A study should print the break-even beside the stabilized occupancy, because a lender judging a new yard is judging the lease-up as much as the stabilized year, and every month spent below the break-even draws on the borrower's reserve, as the absorption article explains. The sensitivity article treats shock sizes in general.

The same yard under 504 would face the job test before any coverage figure. Table 7 applies it.

With the debenture at an assumed 35% of cost, below the 40 percent of project cost to which a 504 loan is generally held ^[29], the debenture is $1,371,014, and at one job per $95,000 guaranteed ^[30] the project would need 14.4 Job Opportunities. The Census Bureau's count of 47,056 employees across 18,286 establishments in the code ^[32] works out to 2.57 per establishment, and the model assumes 2.0 for this yard, so the shortfall is 12.4. The yard's only path would then be the 120.862 route of community development and public policy goals, open only if the CDC's portfolio average can absorb a loan that, at the $150,000 portfolio average ^[31], counts for 9.1 jobs. That is a question for the CDC's own arithmetic, and the study should put it to the CDC before it spends money on market work.

A checklist for the credit file on a vehicle storage loan

A lender or borrower can test a study of an RV and boat storage yard against these points.

• The counts and their scope. The study names the date, the agency and the coverage of every registration count, says whether the county's boats were counted or estimated, and explains any large change between years before using it ^[3].
• What the counts miss and what they add. Out-of-state registrations ^[18], boat trailers inside a general trailer class ^[17] and boats in states that register only motorized craft are named as gaps, and commercial trailers counted inside an RV class ^[11] as an addition, each with its direction.
• The off-site shares. The study shows the owner survey, the covenant review and the parking codes behind each share, and prints the demand at shares a few points lower, as Table 2 does.
• The competitive set. Self-storage parking and marina dry storage are counted with the dedicated yards, and the pipeline is weighted by stage.
• The space plan. Stall sizes match the fleet's lengths ^[21], the spaces per acre come from the site plan, and the land cost per space is printed.
• Rents and taxes. Rents are quoted by space type from local evidence and net of any tax the state levies on storage rentals ^[40].
• Collections. The credit loss allowance reflects the state's lien statute for stored vehicles and boats, including what happens when a secured lender's lien ranks ahead of the operator's ^[46].
• Eligibility facts. Active operation is documented ^[58], the size test is run with affiliates ^[69], and under 504 the job count is computed and put to the CDC ^[30].
• The loan record. Every SBA figure is labelled as the self-storage record, every rate as an approval-cohort floor, and no rate on fewer than 30 loans is printed.

Related Pages on Loan Analytics

• The Loan Analytics methodology series (all articles)
• How a feasibility study is done: the Loan Analytics methodology
• SBA feasibility studies (7(a) and 504)
• USDA feasibility studies
• Bankable feasibility studies for conventional loans
• RV & Boat Storage Feasibility Study
• Loan data by state
• Loan data by asset class
• Worked examples (case studies)
• Worked Example: SBA 504 RV and Boat Storage Feasibility Study in New Jersey
• The RV and Boat Storage Feasibility Study Guide: How Lenders and Investors Underwrite the Most Undersupplied Niche in Commercial Real Estate
• RV Storage Demand Opportunity Index: Top U.S. Metros Poised for Growth
• Self-Storage Underwriting Method: Square Feet per Capita, Lease-Up and the Class's SBA Record

Commission a Feasibility Study

Loan Analytics prepares lender-grade feasibility studies for SBA 7(a), SBA 504, USDA Business and Industry, conventional and EB-5 financing, built on the methods this series sets out. A study is not an appraisal: it tests whether a project's market, costs and cash flow can carry the debt a lender is asked to approve. To discuss a study for your project, contact Loan Analytics.

Daniel Smith, MAI, Loan Analytics