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INC WUSIO NARY ZO NING ANALYSIS 8

Table 1. Modeled Scenarios

Unit Size and Type Suburban Exit 1 Downtown
10-unit Single Family Xx

25-unit Multifamily (Stick/Podium) X X

50-unit Townhouse Xx

125-unit Multifamily (Stick/Podium) X X

200-unit Multifamily (Stick/Podium) X X

Source: City of Nashua and RKG Associates Inc., 2021

The eight development scenarios include:

* 10-unit single family ownership development in the Suburban subarea

» 25-unit multifamily (stick construction) rental development in the Exit 1/Amherst Street
Downtown subarea

* 25-unit multifamily (podium construction) rental development in the Downtown subarea

= 50-unit townhome ownership development in the Suburban subarea

* 125-unit multifamily (stick construction) rental development in the Exit 1/Amherst Street
subarea

* 125-unit multifamily (stick construction) rental development in the Downtown subarea

* 200-unit multifamily (stick construction) rental development in the Exit 1/Amherst Street
subarea

* 200-unit multifamily (podium construction) rental development in the Downtown subarea

The model has three primary components that drive the financial performance analysis: development
assumptions, financial assumptions, and affordability assumptions. Each component influences the
revenue and expenditure efficiencies of the development.

= Development Assumptions — The development assumptions focus on the ‘bricks and mortar’
facets of the proposed residential developments. Factors such as total unit count, unit breakout
by bedroom count, average unit size by bedroom count, type of parking, and the cost of land
to accommodate the development. These factors influence construction costs, potential
operational revenues (for rental housing) and sale values (for ownership housing).

= Financial Assumptions — The financial assumptions include factors relating to debt and equity
requirements, the cost of development financing (i.e., mortgage rates), inflation and
appreciation rates (for operational costs and revenues), and project return expectations. The
financial data directly affects the project’s financial performance by adjusting the timing and
amount of capital outlays (both debt and equity).

= Affordability Assumptions — The affordability assumptions include the market performance data
such as market rent rates, target income thresholds for the IZ units, assumptions about the
size of the Inclusionary units, and the percent requirement of IZ units of the total development.

INC WUSIO NARY ZO NING ANALYSIS 9

These assumptions further impact potential revenue levels as well as overall construction
costs.

The following section details the individual assumptions used to run the model, and how those data
points were collected. As mentioned, RKG collected primary and secondary data about residential
development in Nashua. RKG also performed several interviews with local real estate professionals
to verify those findings. That said, the model was constructed to enable the city to customize the
proforma analysis through data overrides. This flexibility in modeling allowed RKG to perform
sensitivity analyses on incorporating inclusionary zoning. This effort informed RKG’s findings.

Income Tiers — To assess an inclusionary zoning policy, determinations regarding household income
are required. Table 2 details the 2020 HUD Area Median Income by household size for the City of
Nashua. Household income limits were used to calculate affordable rents in Nashua. Area median
incomes in Nashua are high due to the inclusion of communities in Hillsborough County, which have
significantly median higher incomes than the City of Nashua. The higher income limits affect
affordability because the affordability thresholds are higher due to the higher incomes. For the
modeling exercise, RKG used the 4-person household income as the default for conducting the
analysis.

Table 2. FY 2020 Income Limits Summary - Nashua, NH

Household Size

Income Level 1-Person 2-Person 3-Person 4-Person 5-Person 6-Person
30% of AMI $23,050 $26,350 $29,650 $32,900 $35,550 $38,200
40% of AMI $30,720 $35,080 $39,480 $43,840 $47,360 $50,880
504 of AMI $38,400 $43,850 $49,350 $54,800 $59,200 $63,600
60% of AMI $46,080 $52,620 $59,220 $65,760 $71,040 $76,320
654 of AMI $49,920 $57,005 $64,155 $71,240 $76,960 $82,680
70% of AMI $53,760 $61,390 $69,090 $76,720 $82,880 $89,040
80% of AMI $55,950 $63,950 $71,950 $79,900 $86,300 $92,700
100% of AMI $76,800 $87,700 $98,700 $109,600 $118,400 $127,200
110% of AMI $84,480 $96,470 $108,570 $120,560 $130,240 $139,920
1204 of AMI $92,160 $105,240 $118,440 $131,520 $142,080 $152,640
140% of AMI $107,520 $122,780 $138,180 $153,440 $165,760 $178,080
Source: HUD, RKG, 2021

Rent Thresholds — The model calculates potential gross income by applying the market rate threshold
to market rate units, and a rent threshold equivalent to 30% of gross income (utilities included) for
income-controlled units. The market rate rents were calculated through RKG research of current rent
levels for new apartments built in the city over the last five years. The affordable rents were calculated
based on the HUD AMI thresholds. Table 3 details the thresholds for each income level used in the
financial model. What can be seen from the table is that the market rate rent falls between 80% and
100% of AMI, indicating that the market is building affordable units without an inclusionary zoning

policy.

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INC WSIO NARY ZONING ANALYSIS

10

Affordable Rents (Utilities Included

Unit 40% 50% 60% 65% 70% 80% 100% 110% 120% 140% Market
Type AMI AMI AMI AMI AMI AMI AMI AMI AMI AMI Rate

Efficiency | $711 $889 | $1,067 | $1,156 | $1,245 | $1,422 | $1,778 | $1,956 | $2,134 | $2,489 | $1,779
1BR $829 $1,036 | $1,243 | $1,347 | $1,450 | $1,658 | $2,072 | $2,279 | $2,486 | $2,901 | $1,860
2BR $998 | $1,248 | $1,498 | $1,622 | $1,747 | $1,997 | $2,496 | $2,746 | $2,995 | $3,494 | $2,316
3BR $1,154 | $1,443 | $1,732 | $1,876 | $2,020 | $2,309 | $2,886 | $3,175 | $3,463 | $4,040 | $2,688
Source: HUD, and RKG Associates Inc., 2021

Sales Price Thresholds -The sales price thresholds were established by using New Hampshire
Workforce Housing 2020 Workforce Housing Purchase and Rent Limits to determine affordable sales
prices. As seen in Table 4, home purchase income-controlled price thresholds are substantially lower
than the market rate sales price levels identified by RKG. The market rate data was compiled by

parsing the city’s property assessment and sales database over the last ten-years to determine average
sales values.

Table 4. Maximum Affordable Rents (Utilities

Unit | 40% 50% 60% 65% 70% 80% 100% 110% 120% 140% Market
Type | AMI AMI AMI AMI AMI AMI AMI AMI AMI AMI Rate
1BR $94,560 | $118,200 | $141,840 | $153,660 | $165,480 | $189,180 | $236,400 | $236,400 | $262,800 | $330,960 | $300,000
2BR $126,080 | $157,600 | $189,120 | $204,880 | $220,640 | $252,240 | $315,200 | $315,200 | $350,400 | $441,280 | $350,000
3BR $157,600 | $197,000 | $236,400 | $256,100 | $275,800 | $315,300 | $394,000 | $394,000 | $438,000 | $551,600 | $550,000
Source: HUD, and RKG Associates Inc., 2021

Inclusionary Thresholds — The model built by RKG allows the user to select three different AMI
percentages to test the impact of inclusionary zoning. These percentages can be set for both rental and
ownership projects, the tables below illustrate the default settings of the model. To measure the impact
of inclusionary zoning, RKG scaled the inclusionary zoning percentage with the size of a development
— the larger the project the higher the inclusionary percentage. For example, projects greater than 100
units would be required to have 20% of the units designated as affordable, which would be spread
across three tiers of varying income limits. Additionally, the model allows the user to identify the AMI
thresholds to apply the inclusionary units. For the purposes of this modeling exercise, RKG used 80%
of AMI as the baseline for all tiers in the financial feasibility model. However, the model allows for
the city to test any variation of income thresholds ranging from 50% AMI to 120% AMI.

Table 5. Modeled Inclusionary Zoning Percentages for Both Rental and Ownership Developments

Tier Tier 2 | Tier 3
Rental Units 50% - 120% AMI 50% - 120% AMI 504% - 120% AMI Total
1-25 new units 5% 5% 0% 10%
26-50 new units 10% 5% 0% 154
51+ new units 5% 10% 5% 20%
Source: City of Nashua and RKG Associates Inc., 2021

Development Revenues

RKG collected rental rate data for relatively new luxury developments which included efficiency
(studio), one-bedroom, two-bedroom, and three-bedroom apartments. The market rental rates were
used as a baseline for the analysis and compared to information obtained from developers. Generally,
new units rent for between $2.24 and $3.38 per square foot depending on the unit type. Within the
model the rents can be modified by the user. For more information about rental rates, see Appendix
1.

The sales values of housing units were determined through a combination of market research and
utilizing the City Assessor database to parse the most recent sales values by bedroom count. The
results are used for the baseline assumption in the model. For more information about sales values,
see Appendix 1.

Income streams outside of traditional rent and sales value stem from parking revenues. For rental
units, it was assumed in the model that parking revenues of $75 per space were attainable. No parking
revenues are included in ownership units because the parking space is inherently included in the price
of the unit.

Development Costs

The amount of money a developer can pay for a piece is land is a critical component to the financial
feasibility of a project. The higher the land value, the more a developer needs to offset their costs
through things like higher density, lower parking rates, or increased sales prices and rents. The price
of land is one of the key factors that can affect financial feasibility; and this is especially true for projects
on the financial margin. From a cost perspective, the cheaper a developer can obtain the land, the
greater the potential financial return. This is because in terms of development, construction and
financing costs are relatively fixed. Whereas the price of land and its developable potential can
significantly impact the viability of a project.

The price of land in Nashua has become high in recent years and fluctuates based on the underlying
zoning and the total number of units which can be developed. An example being that a single-family
home with a double lot can easily sell for $400,000 as a tear-down project which is then replaced with
two units each selling for $500,000. This indicates that developable land is in scarcity in and around
Nashua.

Developers typically calculate the residual value of the land to determine what they would be willing
to pay for the land on a per unit basis. This calculation considers construction costs, financing
expenditures, and expected returns. The general approach towards determining the land value is to
calculate the income expectations for the developed land, subtract all expenses associated with this

development, and the remainder is the land residual. The decision to pursue the project depends on
whether the developer can acquire the land at a favorable price.

Within the model RKG created a land value override where the model user can input their own land
value assumption. This allows the user to test financial feasibility based on the different land costs,
since they may vary significantly based on development size and underlying zoning.

To determine construction costs, RKG interviewed several developers and utilized the March 2021
Marshall & Swift Valuation Services booklet to build out customized per square foot construction
costs for traditional townhouse, stick, and stick over podium construction. RKG assumed that new
construction would have either “excellent” or “good” interior or exterior finishes. Construction costs
are adjusted by using a local Nashua multiplier supplied by Marshall and Swift. The Marshall and
Swift numbers are an industry standard based on market data. However, in conversation with local
developers the price of materials and labor has been rising quickly since the start of the COVID-19
pandemic, and the Marshall and Swift data does not capture these pricing changes. RKG therefore
factored into the Marshall and Swift construction cost number adjustments based on the price inflation
identified by developers.

Within the model the appropriate construction cost is applied to the development based on its type
and size. RKG quantified the costs for the three different construction styles, and these costs can be
assigned to the typologies (Fee Simple, Multifamily Stick, and Multifamily Podium) the City of
Nashua wants modeled. RKG assumed for this model that all projects would take one year to
complete, and construction would begin in 2021. Appendix 1 has more detailed information about
construction costs.

Within the model two types of parking costs were included: surface and structured podium parking.
The types of parking have dramatically different cost estimates. Surface parking is by far the cheapest
option for parking. Typically, this type of parking is done on smaller projects which have sufficient
land area to accommodate the parking requirements under zoning. Structured podium parking
typically occurs in multifamily developments which are constrained for space.

The parking calculations are based on the number of parking spaces required by the city based on the
total number of residential units and typology. The City of Nashua requires two parking spots for
every single family or townhome and requires 1.5 spots per multifamily unit. Appendix 1 has more
detailed information about parking costs.

Financing

Development financing is possibly the most important element of any real estate deal. The ability to
secure long-term financing at an affordable rate allows a developer to complete their project. Different
types of financing are available depending on the scale of the project. For very large projects, financing
might be obtained from a national bank, institutional investors, or a debt fund. These types of entities
invest capital in projects for investors, and typically provide favorable interest rates given the track
records of large-scale developers.

Smaller scale developers utilize traditional bank financing as the main source of funding. Local banks
typically act as partners with smaller scale developers and provide funding to projects which meet
their lending standards and risk profiles. Lending at the small scale is very much relationship based.

Modeling the financing component of development requires assumptions to be made about the
equity, loan terms, and interest rates. As part of the data collection process, RKG interviewed several
local developers who provided reality-based data regarding project financing.

The equity investment on the part of the developer which is required to obtain financing is dependent
on many factors, some of which include: financial wherewithal, experience, project type, etc. Lenders
require developers to contribute funding towards the project. The percentage of equity required is a
variable within the model that can have a significant impact on the overall financial return. Typically,
if a developer can secure financing which requires a smaller percentage of equity contribution, then
the overall project return will be greater because the initial out-of-pocket cost will be less. The benefit
to the developer is that they minimize their risk when they do not have to contribute large amounts
of equity. For the modeling exercise, the default equity requirement was set at 25% for both owner
and rental developments, this value can be changed within the model by the user.

The length of the loan is dependent on the type of project under construction. For for-sale units, the
loan is repaid once the units have sold. In this case, the loan period might last for 1 or 2 years
depending on the time it takes for a project to be constructed and the units sold. For rental projects,
the loan term can be variable. Developers have different exit strategies depending on their investment
philosophies; some developers will hold a project for 10 years and then sell it, while others just build
and hold the property. For the analysis, the model was calibrated to assume as a default that the loan
for a for-sale development would be two years, and that for rental properties the loan term would be
20 years.

Financial institutions provide funding based on the viability and potential success of a project, and
the interest rates charged are evaluated against the developers financial standing and ability to
complete the project. A range of interest rates could be charged to a developer depending on their
track record, development program, or equity contribution. The higher the interest rate, the greater
the overall cost to the developer. Small fluctuations in interest rates can have large impacts on the
project financial return because the cost of debt service can substantially increase, thus rendering a
project infeasible. Some developers contribute greater amounts of out-of-pocket equity as a means of
lowering the interest rate on the loan. The default model assumptions for interest rates were 5.5% for
rental developments and 5.0% for ownership developments. The higher interest rate for rental
developments was used because the loan term is longer than that of the ownership developments.

Density Bonus
Density bonus is a regulatory tool that provides a developer the right to build a greater number of
units than the existing underlying zoning dictates in exchange for some public benefit (in this case,

the inclusion of income-controlled housing units). This incentive works well in cases where a
community is focused on building lower cost housing without providing substantial cash incentives
to developers. In other words, the density bonus provides a developer with an incentive to create units
at deeper levels of affordability, in exchange for the ability to build more market rate units.

The key concept of the density bonus is to entice the developer to build affordable units at deeper
levels of affordability, while at the same time offering an incentive for the developer to regain lost
value from the creation of the affordable units by supplementing with market rate units. Within the
model that RKG produced, it is possible to adjust the density bonus to test the implications on the
financial feasibility of the project. Density bonus units tend to have greater importance on smaller
projects which, from a financial perspective, may not be viable without the addition of market rate
units above by-right thresholds.

For the purposes of this analysis, RKG tested how many bonus density units would be required to
make the financial return of the proposed inclusionary policy equal to the by-right scenario for each
tested development program.

Cash Payment/Payment in Lieu

As a method to capture the full value of affordable units that do not get built under the inclusionary
ordinance, RKG created the financial feasibility model to include a cash payment amount for fractional
units. The cash payment amount is applied to fractional units which result from applying the
appropriate inclusionary percentage across Tier’s One, Two, and Three. The modeled scenarios do not
round any of the units, rather it prescribes each full unit be built, and any fractional piece be captured
by a cash payment. This protects the developers from having to incur a cost greater than the policy
requires, as having to build a full affordable unit for a fractional calculation (i.e., 0.5 units) will have a
greater financial impact than a cash contribution equal to the fractional value of the net value
difference between a market rate unit and an income-controlled unit.

Within the model there is an affordable unit and cash payment calculator which determines both the
number of affordable units and potential payments in lieu based on the assumptions made in the
model. The model also calculates the dollar value of the payment in lieu of an affordable unit using
either: Total Residential Development Cost Limits ($200,000); construction hard costs, or the value gap
approach.

As part of the modeling process, three options were explored regarding the value of the cash payment
amount for fractional units. The first option was a generic fee of $200,000 per unit. The second option
was to use the construction hard costs for developing the affordable unit. The construction hard costs
can be defined as the cost of construction for the actual unit, which excludes the price of the land.
Utilizing this cost method enables the city to match the cost of building the unit with payment amount
requested.

The third approach towards determining the payment amount is to utilize the “value gap” approach.
The value gap is the difference between the value of a market rate unit and that of an affordable unit.
The value of a rental unit is determined by the net operating income and the capitalization rate; for an

INC WSIO NARY ZONING ANALYSIS 1 5

ownership unit it is determined by the sales value of the unit. In the case of affordable units, the
amount of rent or sale price is limited to the target income threshold of the inclusionary zoning policy.
This results in lower revenue to a developer. This loss of revenue translates into a loss of value (hence,
the value gap) and negatively impacts the overall financials of a developer because the cost of
construction and land to build either an affordable or market rate unit are essentially the same. As
part of the modeling process, an option was created to utilize the difference in value due to the loss of
revenue in determining the fee amount to charge for fractional units.

Table 6 presents an example case of the calculation of the payment-in-lieu across the affordability tiers
for a development that has 25 units, utilizing the value gap approach.

Inclusionary Percentage

Calculated Units Based on IZ Perce
Whole Units

Fractional Units

Cash P nt Amount on Fractional

Total Project Units
Inclusionary Units
Market Rate Units
Cash P ent in Lieu

Source: RKG Associates, Inc.

From a financial standpoint, the calculated fee in-lieu payment is added to the initial cost of the
development, which ultimately influences the overall financial return. Depending on the project size,
a large fee in-lieu could have a detrimental impact. Typically, asmall project tends to be more sensitive
to greater upfront costs because small dollar amount changes can have an outsized impact as
compared to larger projects.

SCENARIO ANALYSIS

Development Programs

To test the model and the underlying development assumptions, RKG ran eight development
scenarios. Table 7 presents the model calibration for each of the eight scenarios. The scenarios were
chosen by the city to understand the impact of the IZ changes on prototypical developments. One key
difference in terms of development costs is that of parking; in multifamily scenarios podium level
parking was assumed for developments located in the Downtown subarea.

INC WSIO NARY ZONING ANALYSIS 1 6

Number _ of Inclusionary
Scenario Tenure Unit T Location Units e
1 Ownershi Single Fam Suburban 100% Surface 10 10%
2a Rental Multifam Amh 100% Surface 2 10%
2b Rental Multifam Downtown Podium 2 10%

Ownershi Townhome Suburban 100% Surface 1
Rental Multifam Amherst/Exit1 | 100% Surface 12 20%
b Rental Multifam Downtown Podium 12 20%
a Rental Multifam Amherst/Exit1 | 100% Surface 20%
b Rental Multifam Downtown Podium 20%
Source: of Nashua, and RKG Associates Inc.

Comparative Scenarios

The financial analysis conducted by RKG provides key insights regarding the relative impact on
development finance resulting from the creation of an IZ ordinance. RKG modeled each of the eight
scenarios by calibrating the model with market-tested assumptions. For each development program,
RKG Associates analyzed four different scenarios. These scenarios include:

CURRENT MARKET/BASELINE SCENARIO
First scenario uses the current market conditions assumptions collected during the analysis to ensure

the model is properly calibrated with accurate assumptions. The baseline scenario provides an
assessment of how a project would perform (financially) based on market averages for acquisition,
construction, operation, and reversion.

TARGET RETURN SCENARIO

The second scenario adjusts the land acquisition cost to have the proposed development program
achieve the target IRR return levels (20% for ownership development and 15% for rental projects).
Within real estate development, the only true cost/revenue variable is the cost of the land. Vertical
construction costs, debt/equity requirements, and operational revenues are established by the market.
For example, rents cannot be inflated for market rate units to offset the rent/price losses of income-
controlled units. Thus, this scenario adjusts the land costs to reach the return threshold for the
proposed development.

INCLUSIONARY POLICY SCENARIO

The third scenario measures the financial impact of the model inclusionary zoning policy (detailed
earlier) on the target return scenario. This analysis was done to understand the fiscal impact of this
proposed policy on a project that met the minimum return threshold. Instances where this scenario
returned a lower IRR indicate the policy creates a financial disincentive, while instances where this
scenario has a higher IRR than the target return scenario indicates the policy creates a positive
financial impact.

INCLUSIONARY/BONUS DENSITY SCENARIO
The final scenario calculates how many additional market rate units (the bonus density) would be

needed above the baseline unit count for the inclusionary zoning scenario to meet the minimum return
threshold. In other words, RKG calculated how much bonus density would need to be granted for an

inclusionary zoning project to not adversely impact the return of the developer or the inherent value
of the land. This effort was done to understand the feasibility of a non-financial incentive (additional
units) could be applied to minimize impact to the local real estate market and return expectations.

Interpreting Results

The financial model calculates the basic go/ no-go decision a developer must make about a potential
project. The decision to pursue a project comes down to overall financial return and risk exposure. If
there is confidence that the desired returns will be reached, then the project will be pursued, otherwise
the project will not be undertaken.

From a financial perspective, the model calculates outputs that can be helpful when determining
whether a developer or a lender will choose to go forward with a project. Of these outputs, both the
Internal Rate of Return (IRR) and Net Present Value (NPV) are industry standard financial viability
metrics for a given project. While these are important metrics, they are not the sole arbitrators of
financial viability, as project risk assessment and developer track record are also important factors.
The IRR and NPV when examined together, offer significant insight to both a lender and developer.
The IRR is the calculated annual return on investment, taking into consideration net operating income,
investment holding period, and sales value. The NPV is the present value of all future cash flows (both
revenues and expenditures) for the project based on an expected return rate (discount rate) and over
the course of the determined holding period.

Based on the size of the initial upfront capital investment in a project, small percentage changes in the
IRR can have dramatic effects on the net present value. The decision factor for not pursuing a project
is if the IRR does not meet the required rate of return, or if the NPV is below zero. It is possible that a
project results in a positive NPV and a lower than desired IRR. In cases such as this, the decision
process becomes more nuanced as the developer would have to get comfortable with realizing a lower
return. Within the development industry, IRR return thresholds of 15% for a new construction rental
project and 20% for new construction ownership units.

Analysis Limitations

The undertaken analysis is not without limitations. The financial model is based upon assumptions
which were collected through developer interviews, market research, and professional judgement.
These assumptions are the main drivers of the financial model. The developments that are modeled
in this analysis are prototypical developments that could potentially be found in Nashua, and not
actual developments. While all the assumptions that drive the model can be customizable, RKG
calibrated the model such that the base assumptions are the default. There are countless permutations
that can be modeled, but RKG in consultation with the city, chose to model prototypical developments
with relatively standardized inputs.

The model is not able to test every variable or possibility, rather it can be used as an ordinance tool to
help inform the decision-making process. The model output helps show the relative impact of
ordinance changes on development financial feasibility.