MISSION:
BUILD A PROPOSED
ECONOMIC PLATFORM
TO HELP MAKE FIDI
A MODEL DISTRICT
FOR THE FUTURE
SUMMARY:
Invent City is a proposed economic development platform for New York City’s Financial District (FiDi). It would establish a global urban solutions industrial cluster addressing the forces beginning to reshape cities: demographic change, the climate crisis, and the rapid rise of AI and robotics.
The cluster would be anchored by an urban Trade Mart filled with immersive showrooms focused on urban industries. Together, the FiDi cluster, Trade Mart, immersive showrooms, events, media, and digital channels would reduce market friction, increase visibility, accelerate adoption, and create significant economic value for New York City.
MODELED RESULTS:
- $4 billion in annual economic activity
- 15,000 jobs
- $380 million in annual tax revenues
STRATEGY:
LEAD WITH ECONOMICS,
USE PROVEN MODELS,
ACTIVATE WHAT EXISTS,
SCALE WITH AI
Economics is the fastest path to scale. City governments cannot finance the urban upgrade cycle alone. Invent City is designed to mobilize companies, investors, buyers, and global incubators around one goal: accelerate critical urban solutions and turn demand into growth for New York City.
AI and robotics, climate risk, and demographic change are becoming direct economic forces in cities. Robots can inspect sewers, support emergency response, and handle dangerous work. AI can improve operations, but also disrupt jobs and governance. Climate risk is shifting from long-term mitigation to urgent local adaptation. Fast-growing cities such as Lagos show the scale of future demand for housing, mobility, power, water, food systems, jobs, and infrastructure.
The economics are clear: under-investment is getting more expensive, and solving urban problems is becoming a massive market. The PIK Institute estimates climate damages could cost the global economy about $38 trillion annually by 2050, while the urban-solutions markets Invent City targets could exceed $43 trillion in annual revenue by mid-century.
More than half the world already lives in cities, and the urban share is projected to reach about 68% by 2050. That concentrates people, infrastructure, spending, data, and risk in one place. The costs will rise. So will the opportunity. This is not just a challenge. It is a market.
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
Stakeholder value is the operating discipline. Invent City is designed to accelerate products and services that solve real needs for the stakeholders who fund, approve, buy, operate, visit, work in, and live in cities. That means tracking what stakeholders need now, anticipating what they will need next, and turning those signals into a stronger market for critical urban solutions.
is the mandate. Invent City will recruit companies and partners that create measurable value across the system: better city outcomes, stronger quality of life, higher asset values, quality jobs, business growth, and recurring tax revenue for NYC.
decide what moves. They fund, approve, buy, regulate, operate, visit, work in, and live with urban change. Their priorities shape budgets, procurement, standards, timelines, approvals, risk, public trust, and future demand.
will turn stakeholder demand into market intelligence. Roundtables, interviews, outreach, data, and AI will track needs, willingness to pay, barriers, and future priorities — helping shape the right mix of companies, capital, and A/E partners.
Invent City will establish an urban industrial cluster in FiDi: a concentrated marketplace for buyers, sellers, capital, talent, institutions, and proof. The goal is simple — make urban innovation faster, more visible, more investable, and more valuable for New York City.
is the growth model. From Napa wine to South Korean robotics, clusters work by concentrating companies, buyers, talent, suppliers, capital, and institutions in one place. Density builds trust, speeds learning, increases deal flow, and turns place into advantage.
will focus on the systems cities must upgrade: transportation, buildings, energy, water, waste, logistics, AI, robotics, and resilience. The goal is cross-industry convergence around high-growth, high-margin urban demand.
will make FiDi a shared marketplace, not just a location. Companies, investors, agencies, operators, project teams, researchers, and experts will evaluate, finance, pilot, and scale solutions together.
will be economic: faster innovation, stronger sales, better hiring, lower friction, more investment, new business formation, stronger place identity, and greater demand for FiDi real estate. AI makes the model even more powerful.
Invent City will focus where urban demand is large, urgent, and recurring: buildings, energy, mobility, logistics, water, waste, resilience, AI, robotics, and city operations.
defines the opportunity. Cities are entering a long upgrade cycle as population pressure, aging infrastructure, climate risk, and AI-driven change reshape demand. That creates recurring markets across buildings, energy, mobility, logistics, water, waste, resilience, security, and city operations.
defines the business case. These markets can support premium value because the problems are expensive and buyers need performance. Solutions that cut downtime, energy waste, labor burden, risk, or procurement friction can command stronger economics — especially when they address existential risks like water shortages in Phoenix or rising seas in Jakarta, Miami, and Shanghai.
An urban Trade Mart will be the commercial engine of Invent City: a year-round marketplace where urban-solution companies reach buyers, investors, agencies, project teams, and global delegations. The model draws from proven innovation platforms such as Hannover Messe, Messe München, SIAL Paris, and major annual events like CES — updated for urban systems, AI, finance, and New York City.
is the heart of Invent City. It gives companies a permanent market presence in FiDi — a place to demonstrate products, meet buyers, host delegations, launch pilots, and build partnerships year-round.
it creates a stronger route to market: more visibility, more qualified traffic, better demonstration space, stronger credibility, and a shorter path from first meeting to pilot, procurement, financing, or deployment.
it reduces search cost and comparison friction. Solutions become easier to discover, evaluate, test, finance, and advance — including in live FiDi settings where performance can be seen, not just promised.
The Trade Mart anchors the cluster. Immersive showrooms bring it to life — making complex urban systems visible, tangible, testable, and easier to buy.
make the market tangible. Complex urban solutions become visible, comparable, testable, and easier to buy. Events bring buyers in. Digital platforms take the market global. AI matches needs to solutions, models outcomes, and turns interest into action.
turn marketing into proof. Buyers can walk through future streets, buildings, parks, rooftops, waterfronts, and operating systems before they invest. AI simulation, live data, and scenario testing make value easier to see — and risk harder to hide.
Buildings
Urban Agriculture
Consumer Products
Energy & Power
Urban Robotics
Urban AI
Wastewater
Water Systems
Transportation
NYC gives Invent City global credibility. FiDi gives it leverage: transit, capital, visibility, history, waterfront risk, underused space, and direct access to the buyers, investors, agencies, and institutions that can move urban solutions from idea to deployment.
because New York is a global center of finance, media, culture, tourism, talent, public agencies, and decision-makers. That gives Invent City immediate scale, credibility, visibility, and market reach.
is the launch platform. It has deep transit access, major real estate assets, financial institutions, waterfront risk, historic identity, and investor networks — plus vacant office and retail space that can be reactivated faster and at lower cost than ground-up development or wholesale conversion.
could be a major public-realm upside of Invent City, including support for projects such as Gotham Park. It is not required for the concept to work, but phased pedestrian upgrades can increase foot traffic, strengthen retail, improve the visitor experience, and make FiDi a more livable, future-facing district.
John Street
Nassau Street
S William and Beaver
Under the FDR
Broad Street @ NYSE
William Street @ Fosun Plaza
Wall Street
Gotham Park
FiDi can become a living lab for urban AI and robotics: a real-world platform to demonstrate value, test performance, expose risk, and set better deployment standards. The goal is clear: use AI and robotics to make cities more efficient, resilient, and humane — not more unequal, opaque, or automated without accountability.
fast. AI can cut costs, improve service delivery, optimize infrastructure, sharpen forecasting, automate routine work, and reshape how cities operate and compete. Invent City gives cities and companies a place to test those gains in real conditions.
fast. AI can displace workers, widen inequality, weaken privacy, increase cyber exposure, and push critical decisions into opaque systems. Invent City will examine both sides: what AI can do, what it should do, where it should be constrained, and who benefits.
The venue strategy is practical: use existing vacant office, retail, and public-realm assets first. That lowers cost, speeds activation, and turns underused FiDi space into productive economic infrastructure.
By filling underused space with a high-growth urban innovation economy, Invent City can help stabilize commercial real estate, strengthen property values, support small businesses, attract visitors, and give global companies a new reason to come to Lower Manhattan. Existing space also lowers upfront cost, reduces time to market, and improves phasing flexibility.
Office vacancy
Vacant FiDi office space can become productive economic infrastructure faster than major redevelopment.
OfficeVacancy
Retail vacancy
Vacant storefronts can become street-level showrooms, pop-ins, pilots, and visitor-facing demonstrations.
RetailVacancy
Lower cost
Existing FiDi space can be activated faster and at far lower cost than conversion or ground-up development.
RedevelopmentCosts
Faster revenue
A Trade Mart can move from vacant space to market activity much faster than major redevelopment.
Time toRevenue
Flexible rollout
The platform can start small, prove demand, and expand as companies, buyers, and capital follow.
FlexibleRollout
could consolidate essential street-level services in one place: package logistics, Blue Highway freight transfer, e-bike charging and battery exchange, micromobility, micro-waste collection, public toilets, seating, water, and shelter for delivery workers. Building on models like NYC Deliverista Hubs, these nodes can reduce street clutter, improve last-mile operations, support cleaner logistics, and make the city more humane, efficient, and easier to manage.
Invent City will extend the cluster beyond FiDi. Events, media, data, digital platforms, and AI can keep the market active globally — expanding discovery, deepening relationships, and supporting sales around the clock.
Events, media, and digital channels will carry Invent City far beyond FiDi, attracting founders, buyers, investors, policymakers, operators, delegations, and press while expanding awareness, credibility, and market reach.
Digital tools and AI will keep the platform active across time zones, making it easier to explore, compare, share, and engage at any time. That supports continuous lead generation, buyer education, and always-on commercial activity.
Together, physical and digital channels will build trust over time, keep high-value prospects engaged longer, and turn one-time attention into repeat business, partnerships, and long-term platform value.
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,
$380M TAX REVENUES
Tourism imports outside dollars into New York’s local economy. Invent City can add a higher-value business and innovation visitor stream to FiDi — supporting hotels, restaurants, retail, culture, transportation, jobs, and taxes.
Tourism is already one of New York’s largest economic engines. A proposed platform that brings buyers, delegations, trade events, and global attention to FiDi could add a valuable business and innovation layer to that base.
International visitors tend to stay longer, spend more, and create a larger ripple across hotels, food, retail, transportation, culture, and services. That makes them especially valuable to a district designed for global visibility and deal flow.
Business travelers often spend more per trip, visit year-round, and generate steadier demand. Invent City is designed to attract exactly that kind of visitor: buyers, sellers, operators, investors, project teams, and delegations.
| Tourism summary | Mid |
|---|---|
| Annual visitors | 1,000,000 |
| Traveler spending ($/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 | $1.50 × room-nights |
| NYS sales tax on other spending | Other spending × 4.0% | Other spending × 4.0% | Other spending × 4.0% |
| NYC sales tax on other spending | Other spending × 4.5% | Other spending × 4.5% | Other spending × 4.5% |
| MCTD sales tax on other spending | Other spending × 0.375% | Other spending × 0.375% | Other spending × 0.375% |
| Scope note: PIT excluded to avoid double counting with Trade Mart payroll impacts. | |||
The Trade Mart converts urban innovation into recurring commercial activity. The economic case is jobs, payroll, procurement, buyer traffic, events, business travel, regional spillovers, and a larger tax base.
A Trade Mart can support direct on-site jobs, event and production work, local services, building operations, hospitality demand, and wider knock-on activity. The value is not just jobs alone, but recurring commercial activity anchored in one place.
The model is designed to generate repeat traffic from buyers, sellers, delegations, trade events, project teams, and business visitors. That can support steadier hotel demand, more year-round activity, and stronger spending across the district.
The economic upside is broad: payroll, commercial rent, property value support, sales taxes, hotel taxes, business activity, permits, and multiplier effects. The larger point is simple: more productive space and more recurring activity can expand the city’s tax base.
| Trade Mart summary | Mid |
|---|---|
| Direct on-site jobs | 8,500 |
| Direct payroll ($/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 recurring NYC revenue capacity.
Filling 3.0 million square feet could expand NYC’s recurring revenue base. More occupancy means more income, stronger values, and greater long-term tax capacity.
The real-estate case is direct: absorb vacant office and retail space, improve NOI, support valuations, and rebuild confidence in FiDi.
Vacancy is the opening. Existing space can move faster and cost less than ground-up development, while AI is reshaping what tenants need from buildings, systems, and districts.
The Trade Mart could also become a company-attraction engine. A year-round marketplace in FiDi would give firms a reason to locate near buyers, investors, agencies, partners, media, and talent — strengthening New York City as the global base for urban innovation.
| 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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