The Big Apple is gearing up for runners from all over the world to converge for the iconic TCS New York City Marathon on November 3, 2024. The marathon usually attracts more than 50,000 runners, 11,000 volunteers and over 1 million spectators 1. Beyond the pounding feet and roaring crowds, an invisible force will be at play – one that will spark economic activity throughout the city, driving energy and excitement far beyond the finish line.

As part of Mastercard Economics Institute’s ongoing exploration into the intersection of major events and economic trends under the series Eventful Economy, we uncover the economic impact of the NYC marathon, focusing on last year’s event.

Using a “synthetic control” methodology, we constructed a scenario to estimate what spend activity would have looked like without the marathon. Leveraging high-frequency, anonymized Mastercard transaction data, we isolated the incremental spend boost directly attributable to the marathon, including spending specific to small businesses.

Mapping the economic impact: When and where

Just as the runners journeyed through New York City from the starting point on Staten Island to the triumphant finish in Central Park, we’ll explore the economic impact of the 2023 TCS New York City Marathon hour by hour, and neighborhood by neighborhood, to see how this iconic event supported local businesses. We are measuring spending at restaurants and bars that qualify as “small businesses” based on our proprietary methodology and are located within 1,000 meters of the marathon route. Henceforth, throughout the piece, we will refer to these businesses as “small restaurants”.

Lift in spending between actual and synthetic series for small/medium restaurants around the marathon course

Early hours: The economic kickoff (Morning, 8-11 a.m.)

As the marathon kicked off in Staten Island and made its way into Brooklyn, spending activity saw a gradual increase. The chart above shows that between 8 a.m. and 11 a.m, small restaurants along the route 2 experienced a steady rise in economic activity, with spending starting at around 3% above baseline at 8 a.m. and reaching nearly 15% by 10 a.m.. This initial period set the stage for the day, as early spectators and participants began to spend at small restaurants.

Midday momentum: Brooklyn and Queens take center stage (11 a.m.-2 p.m.)

The race’s progression through Brooklyn and Queens saw a significant increase in economic activity. Between 11 a.m. and 1 p.m., spending increased, peaking at around 35% above the synthetic baseline during the 12 p.m. to 2 p.m. window. This period captured the vibrant energy of neighborhoods like Williamsburg and Long Island City, where both spectators and participants contributed to an already bustling economic environment.

The accompanying map highlights these areas, showing substantial positive impacts across Brooklyn and Queens as the marathon energized local restaurants. Due to street closures, certain small restaurants experienced a negative lift. Spending was reallocated to more accessible locations, and despite these localized challenges, our analysis finds a net positive effect on small restaurant spending along the marathon route.

Peak performance: Manhattan’s economic boost (2-5 p.m.)

As the more than 51,000 runners made their way into Manhattan through the Bronx, approaching the finish line at different times, the economic impact surged in waves. The peak occurred between 2 p.m. and 3 p.m., when spending spiked nearly 40% above baseline levels. This surge aligned with the influx of runners along the marathon’s final stretch through the Upper East Side and Central Park—areas where the collective energy of both participants and spectators ignited substantial economic activity.

The map reveals the widespread effect, with the most significant positive impacts concentrated in Manhattan. In particular, small restaurants near the finish line saw the greatest increases, reflecting the cumulative excitement as staggered waves of runners arrived.

Post-race celebration: Sustained economic vibrancy (5-7 p.m.)

The race starts to wind down, but the economic boost extended well into the evening. From 5 to 7 p.m., reflecting increased activity throughout the area, spending near the course remained 10% above typical levels. As runners and spectators celebrated , they flocked to local bars and restaurants throughout Manhattan, particularly in areas near the finish line. This period underlined the marathon’s sustained economic impact, as the energy and excitement of the day translated into ongoing support for local restaurants, extending the economic vitality well beyond the race itself.

Conclusion

The “when and where” of TCS New York City Marathon’s impact tells a story of continuous economic engagement, with spending that rippled through the city from the starting gun to well after the final finisher crosses the line.

These findings from our “Eventful Economy” series demonstrate how major events like the TCS New York City Marathon serve as powerful drivers of economic activity, particularly benefiting small restaurants.

To learn more about economic insights from the Mastercard Economics Institute, contact your Mastercard representative or request a demo.

Notes & Disclaimer

About the Mastercard Economics Institute

Mastercard Economics Institute launched in 2020 to analyze macroeconomic trends through the lens of the consumer. A team of economists, analysts and data scientists draws on Mastercard insights - including Mastercard SpendingPulse™ - and third-party data to deliver regular reporting on economic issues for key customers, partners and policymakers.

Disclaimer

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  1. New York City Marathon Fast Facts↩︎

  2. The marathon route was mapped using approximately 3,000 geographic points (latitude/longitude), each assigned a route ID. The closest distance between small restaurants and these points was calculated, with restaurants assigned to the nearest route ID. Restaurants within 1,000 meters were categorized as treated, while those over 2,000 meters formed the donor pool (restaurants sets used to create the synthetic).↩︎