MISSION:
BUILD A PLATFORM
TO MAKE FIDI
A MODEL DISTRICT
FOR THE FUTURE
SUMMARY:
Invent City is a proposed economic platform for FiDi. It builds a global urban solutions innovation district around three forces reshaping cities: demographic change, the climate crisis, and AI and robotics.
At the center is an urban Trade Mart with immersive showrooms. Together, the cluster, Trade Mart, events, media, and digital channels help companies get seen, trusted, funded, and deployed faster.
MODELED RESULTS:
- $4B annual economic activity
- 15,000 jobs
- $380M annual tax revenue
STRATEGY:
LEAD WITH ECONOMICS,
USE WHAT WORKS,
ACTIVATE FIDI,
SCALE WITH AI
Economics is the fastest path to scale. Invent City starts with a simple market truth: the cost of inaction is rising fast — and the value of action is rising just as fast.
For investors and companies, cities are a at different speeds. More than 4 billion people currently live in cities, and 6 billion are expected by 2100. Cities are increasingly being shaped by : AI and robotics, climate risk, and demographic change.
Deployment of critical solutions depends on the various with different needs and wants. Stakeholders control funding, approvals and procurement. Invent City will focus relentlessly on for various stakeholders: more jobs, stronger businesses, a larger tax base for cities, higher returns for investors, and greater sales for companies.
Climate damages could reach about $38 trillion annually by 2050. The urban-solutions markets Invent City targets could exceed $43 trillion in annual revenue by mid-century.
Demographics
Urban growth is expanding demand for housing, mobility, services, and infrastructure.
Rising Urban Populations
Growth in Developing Cities
AI impact
AI is reshaping city systems, improving performance while raising new risks and governance questions.
AI Spendingby Area
Immediate potential of AI in NYC
Environmentals
Heat, flooding, and climate stress are driving demand for more resilient urban systems.
Sea Level Rise
Rising Temperatures
The to ascertain the value for cities, investors and companies today and in the future, and how to transform that into market intelligence.
An concentrates companies, buyers, talent, capital, suppliers and all key players so they move faster together. Similar to innovation districts like [*Kendall Square*], [*22@Barcelon*8], Invent City proposes to turn a portion of FiDi’s millions of square feet of vacant office and retail space into a living lab and showcase of what need next. 100% cities.
include stronger sales and deployment of critical solutions, more investment, new companies, and greater demand.
Invent City targets urban needs: water stress, flooding, sea-level rise, subsidence, extreme heat, mobility, housing, energy, and public services. These are also opportunities because the problems are urgent, costly, and hard to ignore.
Invent City anchors the innovation district with an Urban Trade Mart: a year-round marketplace built from FiDi’s vacant and underused urban assets. The model draws from such as Chicago Merchandise Mart, AmericasMart Atlanta, EUREF-Campus Berlin, and Zhangjiang Science City / Zhangjiang Hi-Tech Park. Invent City brings that logic to FiDi as a permanent marketplace for the technologies cities need next.
the Mart concentrates customers, partners, investors, agencies, and project teams. it makes solutions easier to find, compare, test, finance, and deploy.
The trade mart is populated by which make complex urban solutions visible, testable, and easier to buy. Events bring buyers in. Digital platforms keep the market active everywhere.
turn marketing into proof. Buyers can walk through future streets, buildings, parks, rooftops, waterfronts, and city systems before they invest.
Buildings
Urban Agriculture
Consumer Products
Energy & Power
Urban Robotics
Urban AI
Wastewater
Water Systems
Transportation
gives Invent City instant global credibility. It concentrates capital, media, talent, tourism, culture, real estate, public agencies, major employers, universities, and the decision-makers cities and companies follow. NYC is the world's second home.
Within NYC, gives Invent City strategic leverage: unmatched transit, Wall Street capital, global visibility, historic identity, waterfront resilience needs, underused office and retail space, and direct access to buyers, investors, agencies, founders, media, and civic leaders.
could be a major public-realm upside, including support for projects such as Gotham Park. It is not required, but Gotham Park could be an urban park of the future showcasing water innovations, mobility, vegetation and lighting among others.
John Street
Nassau Street
S William and Beaver
Under the FDR
Broad Street @ NYSE
William Street @ Fosun Plaza
Wall Street
Gotham Park
The venue strategy is simple: use existing vacant office, retail, and public-realm assets like POPs and parks needing upgrades like . A use what exists strategy lowers cost, speeds launch, and turns underused FiDi space into productive space. becomes an economic asset when it is filled with companies, showrooms, events, services, and street activity. Lower cost, faster to revenue, and flexible.
could combine package logistics, Blue Highway freight transfer, e-bike charging, battery exchange, micromobility, waste collection, storage, public bathrooms, worker support, shade, water, information, and emergency services.
FiDi can become a living lab for urban AI and robotics: a place to prove value, test performance, expose risk, and set better deployment standards.
AI can cut costs, improve services, optimize infrastructure, sharpen forecasts, automate routine work, and change how cities operate. It can also deepen inequality, displace workers, weaken privacy, increase surveillance, and create black-box decisions. Invent City should make both visible.
Invent City is designed to extend far beyond FiDi, creating a global platform for continuous visibility, engagement, and market activity. Through events, media, data, digital platforms, and AI, Invent City keeps its ecosystem active every day and positions the companies within the cluster for sustained demand and international reach. connects Invent City with founders, buyers, investors, policymakers, operators, delegations, and press, expanding awareness and opportunity for participating companies. enables audiences across time zones to explore, compare, share, and engage with the platform at any moment. integrates physical and digital channels to build trust over time, converting initial attention into repeat engagement, investment, procurement, pilots, and deployment.
Events
Live programming turns attention into meetings, pilots, partnerships, and deal flow.
Events
Media
Content expands the Trade Mart beyond FiDi and keeps buyers engaged between visits.
Media
Digital reach
Digital and AI channels keep discovery, comparison, and follow-up active 24/7.
DigitalReach
FOR NYC:
$4B IN ECONOMIC ACTIVITY,
15,000 JOBS,
$380M TAX REVENUES
Tourism brings outside dollars into New York. Invent City adds a high-value business and innovation visitor stream to FiDi, supporting hotels, restaurants, retail, culture, transit, events, and local services.
1.1 Tourism matters to NYC → Tourism is one of New York’s strongest economic engines. Invent City can add buyers, delegations, trade events, and global attention.
1.2 International visitors matter more → They tend to stay longer, spend more, and support hotels, food, retail, transportation, culture, and services.
1.3 Business visitors are especially valuable → They spend more, travel year-round, and create steadier demand. Invent City is designed for that visitor: targeted, practical, and tied to deals.
| Tourism summary | Mid |
|---|---|
| Annual visitors | 1,000,000 |
| Traveler spending ($/yr) | $1,348,750,000 |
| Total economic impact ($/yr) | $2,090,562,500 |
| Tourism-supported jobs | 6,034 |
| Modeled taxes and fees ($/yr, no PIT) | $159,240,625 |
| Rounded taxes and fees ($/yr, no PIT) | $159,200,000 |
| Note: PIT excluded to avoid double counting with Trade Mart payroll impacts. | |
| Tourism summary | Low | Mid | High |
|---|---|---|---|
| Annual visitors | 1,000,000 | 1,000,000 | 1,000,000 |
| Traveler spending ($/yr) | $1,035,000,000 | $1,348,750,000 | $1,768,750,000 |
| Total economic impact ($/yr) | $1,604,250,000 | $2,090,562,500 | $2,741,562,500 |
| Tourism-supported jobs | 6,034 | 6,034 | 6,034 |
| Modeled taxes and fees ($/yr, no PIT) | $123,684,375 | $159,240,625 | $206,796,875 |
| Rounded taxes and fees ($/yr, no PIT) | $123,700,000 | $159,200,000 | $206,800,000 |
| Note: PIT excluded to avoid double counting with Trade Mart payroll impacts. | |||
| 1. Base assumptions: 1.0M visitors/yr | Visitors/year | Avg nights | Hotel room-nights | Visitor-days |
|---|---|---|---|---|
| International overnight | 250,000 | 5 | 1,250,000 | 1,250,000 |
| Domestic overnight | 250,000 | 2 | 500,000 | 500,000 |
| Domestic day | 500,000 | 0 | 0 | 500,000 |
| Total | 1,000,000 | — | 1,750,000 | 2,250,000 |
| 2. Spending inputs | Low | Mid | High |
|---|---|---|---|
| Hotel room-nights | 1,750,000 | 1,750,000 | 1,750,000 |
| ADR ($/room-night) | $250 | $325 | $425 |
| International other spend ($/day) | $350 | $450 | $600 |
| Domestic overnight other spend ($/day) | $200 | $275 | $350 |
| Domestic day other spend ($/day) | $120 | $160 | $200 |
| Note: ADR = average daily hotel room rate. “Other spend” = non-hotel visitor spending. | |||
| 2A. Hotel and other traveler spending | Low ($/yr) | Mid ($/yr) | High ($/yr) |
|---|---|---|---|
| Hotel revenue | $437,500,000 | $568,750,000 | $743,750,000 |
| Other spending (non-hotel) | $597,500,000 | $780,000,000 | $1,025,000,000 |
| Total traveler spending | $1,035,000,000 | $1,348,750,000 | $1,768,750,000 |
| Formula: Other spend = sum of (visitor-days by segment × spend/day by segment). | |||
| 2B. Total economic impact | Low | Mid | High |
|---|---|---|---|
| Traveler spending ($/yr) | $1,035,000,000 | $1,348,750,000 | $1,768,750,000 |
| Impact ratio | 1.55x | 1.55x | 1.55x |
| Total economic impact ($/yr) | $1,604,250,000 | $2,090,562,500 | $2,741,562,500 |
| Rounded total economic impact ($/yr) | $1,604,000,000 | $2,091,000,000 | $2,742,000,000 |
| Formula: Total economic impact = traveler spending × 1.55. | |||
| 3. Tourism-supported jobs | Input / Output | Value |
|---|---|---|
| NYC visitors (2024) | 64.3M visitors | |
| NYC tourism-supported jobs (2024) | 388,000+ jobs | |
| Jobs per 1M visitors | 6,034+ jobs | |
| IC annual visitors (assumption) | 1.0M visitors | |
| IC tourism-supported jobs (modeled) | 6,034+ jobs | |
| Formula: Jobs per 1M visitors = 388,000 / 64.3. | ||
| 4A. Hotel room taxes and fees | Low | Mid | High |
|---|---|---|---|
| NYS sales tax on hotel rooms (4.0%) | $17,500,000 | $22,750,000 | $29,750,000 |
| NYC sales tax on hotel rooms (4.5%) | $19,687,500 | $25,593,750 | $33,468,750 |
| MCTD sales tax on hotel rooms (0.375%) | $1,640,625 | $2,132,813 | $2,789,063 |
| NYC hotel occupancy tax (5.875%) | $25,703,125 | $33,414,063 | $43,695,313 |
| NYC per-room hotel tax ($2.00 × room-nights) | $3,500,000 | $3,500,000 | $3,500,000 |
| NYS hotel unit fee ($1.50 × room-nights) | $2,625,000 | $2,625,000 | $2,625,000 |
| 4B. Sales tax on other spending | Low | Mid | High |
|---|---|---|---|
| NYS sales tax (4.0%) | $23,900,000 | $31,200,000 | $41,000,000 |
| NYC sales tax (4.5%) | $26,887,500 | $35,100,000 | $46,125,000 |
| MCTD sales tax (0.375%) | $2,240,625 | $2,925,000 | $3,843,750 |
| Total sales tax on other spending | $53,028,125 | $69,225,000 | $90,968,750 |
| 4C. Tax totals roll-up (no PIT) | Low | Mid | High |
|---|---|---|---|
| NYS total (hotel + other) | $44,025,000 | $56,575,000 | $73,375,000 |
| NYC total (hotel + other) | $75,778,125 | $97,607,813 | $126,789,063 |
| MCTD total (hotel + other) | $3,881,250 | $5,057,813 | $6,632,813 |
| Grand total (no PIT) | $123,684,375 | $159,240,625 | $206,796,875 |
| Rounded grand total (no PIT) | $123,700,000 | $159,200,000 | $206,800,000 |
| 4D. Tax formulas and notes | Low | Mid | High |
|---|---|---|---|
| Hotel revenue formula | room-nights × ADR | room-nights × ADR | room-nights × ADR |
| NYS hotel-room sales tax | Hotel revenue × 4.0% | Hotel revenue × 4.0% | Hotel revenue × 4.0% |
| NYC hotel-room sales tax | Hotel revenue × 4.5% | Hotel revenue × 4.5% | Hotel revenue × 4.5% |
| MCTD hotel-room sales tax | Hotel revenue × 0.375% | Hotel revenue × 0.375% | Hotel revenue × 0.375% |
| NYC hotel occupancy tax | Hotel revenue × 5.875% | Hotel revenue × 5.875% | Hotel revenue × 5.875% |
| NYC per-room hotel tax | $2.00 × room-nights | $2.00 × room-nights | $2.00 × room-nights |
| NYS hotel unit fee | $1.50 × room-nights | $1.50 × room-nights | $1.50 × room-nights |
| NYS sales tax on other spending | Other spending × 4.0% | Other spending × 4.0% | Other spending × 4.0% |
| NYC sales tax on other spending | Other spending × 4.5% | Other spending × 4.5% | Other spending × 4.5% |
| MCTD sales tax on other spending | Other spending × 0.375% | Other spending × 0.375% | Other spending × 0.375% |
| Scope note: PIT excluded to avoid double counting with Trade Mart payroll impacts. | |||
The Trade Mart turns urban innovation into recurring commercial activity: jobs, payroll, procurement, buyer traffic, events, travel, regional spillovers, and tax revenue.
2.1 Job creation → A Trade Mart can support on-site jobs, event work, local services, building operations, hospitality demand, and wider knock-on activity.
2.2 Recurring demand → Repeat traffic from buyers, sellers, delegations, trade events, project teams, and business visitors can support steadier hotel, restaurant, retail, and service demand.
2.3 Tax generation → The upside includes payroll, rent, property-value support, sales taxes, hotel taxes, permits, business activity, and multiplier effects.
| Trade Mart summary | Mid |
|---|---|
| Direct on-site jobs | 8,500 |
| Direct payroll ($/yr) | $1,427,500,000 |
| Local procurement ($/yr) | $428,250,000 |
| Total direct activity ($/yr) | $1,855,750,000 |
| Note: Direct activity shown here is kept separate from tourism and real-estate modules to reduce double counting. | |
| Trade Mart summary | Low | Mid | High |
|---|---|---|---|
| Direct on-site jobs | 8,500 | 8,500 | 8,500 |
| Direct payroll ($/yr) | $1,140,000,000 | $1,427,500,000 | $1,790,000,000 |
| Total jobs incl. indirect + induced | 12,750 | 15,300 | 17,850 |
| Knock-on jobs | 4,250 | 6,800 | 9,350 |
| Note: Only direct jobs should be treated as additive across modules to avoid double counting. | |||
| 1. Jobs based on area | Area | Density | Direct jobs |
|---|---|---|---|
| Showrooms | 1,000,000 sf | 1,000 sf/job | 1,000 |
| Support offices | 1,500,000 sf | 200 sf/job | 7,500 |
| Trade Mart total | 2,500,000 sf | — | 8,500 |
| Formula: Jobs = Area / Density. Example: 1,500,000 sf / 200 sf per job = 7,500 jobs. | |||
| 2A. Low-case payroll detail | Jobs | Low wage ($/yr) | Payroll ($/yr) |
|---|---|---|---|
| Showrooms | 1,000 | $90,000 | $90,000,000 |
| Support offices | 7,500 | $140,000 | $1,050,000,000 |
| Total for direct | 8,500 | $1,140,000,000 |
| 2B. Mid-case payroll detail | Jobs | Mid wage ($/yr) | Payroll ($/yr) |
|---|---|---|---|
| Showrooms | 1,000 | $115,000 | $115,000,000 |
| Support offices | 7,500 | $175,000 | $1,312,500,000 |
| Total for direct | 8,500 | — | $1,427,500,000 |
| 2C. High-case payroll detail | Jobs | High wage ($/yr) | Payroll ($/yr) |
|---|---|---|---|
| Showrooms | 1,000 | $140,000 | $140,000,000 |
| Support offices | 7,500 | $220,000 | $1,650,000,000 |
| Total for direct | 8,500 | — | $1,790,000,000 |
| 2D. Direct jobs | Jobs | Low wage | Mid wage | High wage |
|---|---|---|---|---|
| Showrooms | 1,000 | $90,000/yr | $115,000/yr | $140,000/yr |
| Support offices | 7,500 | $140,000/yr | $175,000/yr | $220,000/yr |
| Total direct jobs | 8,500 | — | — | — |
| Total payroll ($/yr) | 8,500 | $1,140,000,000/yr | $1,427,500,000/yr | $1,790,000,000/yr |
| 3. Local procurement | Low | Mid | High |
|---|---|---|---|
| Procurement assumption (% of payroll) | 20% | 30% | 40% |
| Local procurement ($/yr) | $228,000,000 | $428,250,000 | $716,000,000 |
| Formula: Local procurement = Payroll × Procurement share. | |||
| What it reflects: Tenant and campus operating spend—security, cleaning, repairs, IT/AV, catering, event staffing, printing/signage, and local logistics; excludes landlord building OpEx. | |||
| 4. Direct campus activity (Economic expansion) | Low | Mid | High |
|---|---|---|---|
| Payroll ($/yr) | $1,515,000,000 | $1,902,500,000 | $2,390,000,000 |
| Local procurement ($/yr) | $303,000,000 | $570,750,000 | $956,000,000 |
| Total direct activity ($/yr) | $1,818,000,000 | $2,473,250,000 | $3,346,000,000 |
| Formula: Total direct activity = Payroll + Local procurement. | |||
| 5. Indirect and induced jobs | Low | Mid | High |
|---|---|---|---|
| Direct jobs | 8,500 | 8,500 | 8,500 |
| Total jobs incl. indirect + induced | 12,750 | 15,300 | 17,850 |
| Knock-on jobs | 4,250 | 6,800 | 9,350 |
| Implied total multiplier | 1.50x | 1.80x | 2.10x |
| What this shows: Additional off-site jobs supported through suppliers, vendors, and household spending. | |||
| Definitions: Direct = on-site Trade Mart jobs. Indirect = supplier and vendor jobs supported by Trade Mart spending. Induced = jobs supported by household spending from wages. Knock-on = indirect + induced combined. | |||
| 6. Modeled tax revenues | Low | Mid | High |
|---|---|---|---|
| NYS PIT | $62,700,000 | $85,650,000 | $116,350,000 |
| NYC resident PIT | $34,200,000 | $45,680,000 | $60,860,000 |
| MCTMT | $10,203,000 | $12,774,125 | $16,020,500 |
| Sales tax on employee spending | $17,688,469 | $22,150,602 | $27,779,445 |
| Sales tax on local procurement | $10,117,500 | $18,998,344 | $31,772,500 |
| Total modeled taxes ($/yr) | $134,908,969 | $185,253,070 | $252,782,445 |
| Rounded total modeled taxes ($/yr) | $134,900,000 | $185,300,000 | $252,800,000 |
| NYS stands for New York State, NYC for New York City, PIT for personal income tax, and MCTMT stands for the Metropolitan Commuter Transportation Mobility Tax. | |||
| 6A. Tax assumptions and formulas | Low | Mid | High |
|---|---|---|---|
| NYS PIT effective rate | 5.5% | 6.0% | 6.5% |
| NYC resident PIT rate | 3.0% | 3.2% | 3.4% |
| MCTMT rate | 0.895% | 0.895% | 0.895% |
| Employee spending sales tax assumption | Payroll × 35% local spend × 50% taxable × 8.875% | ||
| Procurement sales tax assumption | Local procurement × 50% taxable × 8.875% | ||
| Procurement assumption | Payroll × 20% | Payroll × 30% | Payroll × 40% |
| NYS PIT formula | NYS PIT = Payroll × NYS PIT rate | ||
| NYC resident PIT formula | NYC PIT = Payroll × NYC resident PIT rate | ||
| MCTMT formula | MCTMT = Payroll × 0.895% | ||
| Employee spending sales tax formula | Payroll × 35% × 50% × 8.875% | ||
| Procurement sales tax formula | Local procurement × 50% × 8.875% | ||
| 6B. Scope note and caveat | Value |
|---|---|
| Scope note | NYC resident PIT assumes employees are NYC residents. If some workers commute from outside NYC, this line should be reduced accordingly. NYS PIT would still apply. |
| Additivity note | To avoid double counting across modules, only direct jobs should be treated as additive; indirect and induced jobs should not be added again in Tourism or other spillover modules. |
Real estate matters because underused FiDi space can become productive again. Filling 3.0 million square feet can support NOI, values, refinancing, reinvestment, street life, and revenue.
3.1 Tax revenues → Filling 3.0 million square feet could expand NYC’s recurring revenue base through more income, stronger values, and higher long-term tax capacity.
3.2 Market repair → The real-estate case is direct: absorb vacant office and retail space, improve NOI, support valuations, and rebuild confidence in FiDi.
3.3 Why this matters now → Vacancy is the opening. Existing space can move faster and cost less than ground-up development while AI reshapes tenant demand.
The Trade Mart can also attract companies. A year-round FiDi marketplace gives firms a reason to locate near buyers, investors, agencies, partners, media, talent, and customers.
| Real estate summary | Low | Mid | High |
|---|---|---|---|
| Stabilized leased area (sf) | 3,000,000 | 3,000,000 | 3,000,000 |
| Annual rent ($/yr) | $165,000,000 | $165,000,000 | $165,000,000 |
| NOI ($/yr) | $111,750,000 | $106,860,000 | $102,000,000 |
| Illustrative implied value at 6.0% cap ($) | $1,862,500,000 | $1,781,000,000 | $1,700,000,000 |
| Modeled recurring NYC revenue capacity ($/yr) | $69,704,500 | $70,675,890 | $71,313,250 |
| Rounded recurring NYC revenue capacity ($/yr) | $69,700,000 | $70,700,000 | $71,300,000 |
| Note: This module is kept separate to avoid double counting with jobs, tourism, and construction modules. | |||
| 1. Leasing assumptions | Area | Asking rent | Annual rent |
|---|---|---|---|
| Trade Mart - Showrooms | 1,000,000 sf | $40/sf/yr | $40,000,000/yr |
| Trade Mart - Support offices | 1,500,000 sf | $60/sf/yr | $90,000,000/yr |
| Trade Mart - Total | 2,500,000 sf | — | $130,000,000/yr |
| Additional offices (separate) | 500,000 sf | $70/sf/yr | $35,000,000/yr |
| IC rent total (all space) | 3,000,000 sf | — | $165,000,000/yr |
| 1A. Average gross rent across all space | Value |
|---|---|
| Total area (sf) | 3,000,000 |
| Total annual rent ($/yr) | $165,000,000 |
| Average gross rent ($/sf/yr) | $55.00/sf/yr |
| 1B. Operating expense assumptions | OpEx ($/sf/yr) |
|---|---|
| Low | $17.75 |
| Mid | $19.38 |
| High | $21.00 |
| 1C. Cap-rate assumptions | Cap rate |
|---|---|
| Low cap | 5.5% |
| Base cap | 6.0% |
| Higher cap | 7.0% |
| High cap | 8.0% |
| 1D. Property-tax uplift assumptions | Value |
|---|---|
| NYC Class 4 assessment ratio | 45% |
| NYC Class 4 tax rate | 10.848% |
| Illustrative phase-in | 50% / 75% / 100% |
| 1E. CRT assumptions | Value |
|---|---|
| Rent base proxy ($/yr) | $165,000,000 |
| Effective CRT rate | 3.9% |
| Coverage factor | 70% / 85% / 95% |
| CRT gross upper bound ($/yr) | $6,435,000 |
| 1F. Vacancy context | Value |
|---|---|
| FiDi Financial East office vacancy (a) | 26.0% |
| FiDi Insurance office vacancy (a) | 29.5% |
| Retail storefront vacancy in FiDi/BPC (Q3 2024) (b) | 24% |
| Source note | (a) Cushman & Wakefield, Q4 2025; (b) Small Business Services |
| 2. Real-estate logic | Definition |
|---|---|
| Gross rent | Total annual rent collected |
| OpEx | Building operating expenses |
| NOI | Gross rent minus OpEx |
| Implied value | NOI divided by cap rate |
| 2A. NOI per square foot | Gross rent ($/sf/yr) | OpEx ($/sf/yr) | NOI ($/sf/yr) |
|---|---|---|---|
| Low expense | $55.00 | $17.75 | $37.25 |
| Mid expense | $55.00 | $19.38 | $35.62 |
| High expense | $55.00 | $21.00 | $34.00 |
| 2B. Total NOI on 3.0M sf | NOI ($/sf/yr) | Area (sf) | Total NOI ($/yr) |
|---|---|---|---|
| Low expense | $37.25 | 3,000,000 | $111,750,000 |
| Mid expense | $35.62 | 3,000,000 | $106,860,000 |
| High expense | $34.00 | 3,000,000 | $102,000,000 |
| 2C. Implied value from capitalized NOI | Cap rate | Implied value ($) | Value per sf |
|---|---|---|---|
| Low expense | 5.5% | $2,031,818,182 | $677.27/sf |
| Low expense | 6.0% | $1,862,500,000 | $620.83/sf |
| Low expense | 7.0% | $1,596,428,571 | $532.14/sf |
| Low expense | 8.0% | $1,396,875,000 | $465.63/sf |
| Mid expense | 5.5% | $1,942,909,091 | $647.64/sf |
| Mid expense | 6.0% | $1,781,000,000 | $593.67/sf |
| Mid expense | 7.0% | $1,526,571,429 | $508.86/sf |
| Mid expense | 8.0% | $1,335,750,000 | $445.25/sf |
| High expense | 5.5% | $1,854,545,455 | $618.18/sf |
| High expense | 6.0% | $1,700,000,000 | $566.67/sf |
| High expense | 7.0% | $1,457,142,857 | $485.71/sf |
| High expense | 8.0% | $1,275,000,000 | $425.00/sf |
| 2D. Plain-English economic benefits | Value |
|---|---|
| Benefit 1 | Fills vacant office and retail space |
| Benefit 2 | Creates steady rental income |
| Benefit 3 | Improves NOI |
| Benefit 4 | Supports stronger building values |
| Benefit 5 | Helps owners refinance, reinvest, and stabilize assets |
| Benefit 6 | Can improve confidence in the broader FiDi market |
| 3. Job-counting treatment | Value |
|---|---|
| Approach | This module does not claim incremental job creation, to avoid double counting with separate Trade Mart operations, tourism, and construction modules. |
| Why | It shows how filling vacant space can improve building income, support asset value, and expand recurring city revenue. |
| Caveat | Stabilizing vacant space can still support employment indirectly by making buildings more viable and attracting more tenants, activity, and investment. |
| 4A. Commercial Rent Tax (CRT) | Low | Mid | High |
|---|---|---|---|
| CRT gross upper bound ($/yr) | $6,435,000 | $6,435,000 | $6,435,000 |
| Coverage factor | 70% | 85% | 95% |
| CRT modeled ($/yr) | $4,504,500 | $5,469,750 | $6,113,250 |
| Rounded CRT modeled ($/yr) | $4,500,000 | $5,500,000 | $6,100,000 |
| 4B. Property-tax capacity uplift (mid-case illustration) | Value |
|---|---|
| Mid-case implied value ($) | $1,781,000,000 |
| Assessment ratio | 45% |
| Class 4 tax rate | 10.848% |
| Phase-in | 75% |
| Property-tax capacity uplift ($/yr) | $65,206,140 |
| Rounded property-tax capacity uplift ($/yr) | $65,200,000 |
| Formula: Property-tax capacity uplift ≈ market value × 45% × 10.848% × phase-in | |
| 4C. Total modeled recurring NYC revenue capacity | Low | Mid | High |
|---|---|---|---|
| Property-tax capacity uplift ($/yr) | $65,200,000 | $65,206,140 | $65,200,000 |
| CRT modeled ($/yr) | $4,504,500 | $5,469,750 | $6,113,250 |
| Total recurring NYC revenue capacity ($/yr) | $69,704,500 | $70,675,890 | $71,313,250 |
| Rounded total recurring NYC revenue capacity ($/yr) | $69,700,000 | $70,700,000 | $71,300,000 |
| 4D. Plain-English tax benefits | Value |
|---|---|
| Benefit 1 | More leased space can support higher building income |
| Benefit 2 | Higher income can support higher property value |
| Benefit 3 | Higher value can support higher NYC property-tax revenue capacity |
| Benefit 4 | Leased commercial space can also generate CRT revenue |
| 4E. Scope note |
|---|
| This section models recurring NYC revenue capacity from stabilized leasing and value. It excludes one-time transaction taxes such as RPTT, RETT, and mortgage recording tax, and keeps jobs separate to avoid double counting. |
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