What is an event's economic impact, and what's the formula?
An event's economic impact is the net new money that flows into the host economy (a city, region or Italian comune) because the event took place, and would not otherwise have been spent there. It is not the total amount everyone spent; it is only the additional, event-attributable spend.
The core relationship most economic-impact methods share is simple to state: Economic Impact = Visitors x Average Spend per Head x Multiplier. The discipline is in what you feed into it: only non-local visitors, only genuinely new spending, and a defensible regional multiplier applied to that net-additional figure. The formula is easy; the credibility lives in the inputs.
Two spend streams count as direct impact: additional visitor spend in the local area (tickets, accommodation, food and drink, retail, local transport) and net additional organiser spend placed with local suppliers (staging, services, local staff). Money spent with suppliers outside the area does not count.
- Economic impact = NET new spend, not gross turnover
- Formula: Visitors x Average Spend per Head x Multiplier
- Two direct streams: visitor spend + local organiser spend
- Only non-local, event-driven spend qualifies
What's the difference between direct, indirect and induced impact?
The multiplier exists because one pound or euro spent at your event circulates through the local economy in three layers. Understanding these layers is what separates a credible report from a headline number.
DIRECT impact is the initial spend by visitors and the organiser in the local area. INDIRECT impact is the supply-chain re-spend: your local caterer buys produce from a local wholesaler, who pays a local driver. This is captured by an output multiplier on business turnover. INDUCED impact is the household-income re-spend: local staff and suppliers earn wages and spend part of them locally, captured by an income multiplier.
A regional multiplier bundles these knock-on effects into a single figure, and the correct value is region-specific rather than universal. Input-output models or a regional/tourism authority's local multiplier are the usual sources. Be conservative: an inflated multiplier is one of the most common reasons event impact figures get challenged, so use the lowest defensible value and state where it came from.
- Direct: initial visitor and local organiser spend
- Indirect: supply-chain re-spend (output multiplier on turnover)
- Induced: household-income re-spend (income multiplier)
- Use a conservative, region-specific multiplier and state its source
How do you get from gross spend to a defensible net figure (additionality)?
Gross spend flatters. To make the number credible you must convert it to net-additional spend by netting out three things, collectively called additionality.
DEADWEIGHT is activity that would have happened anyway (a local resident who would have eaten out that weekend regardless). DISPLACEMENT is existing local activity merely crowded out, not created (spend that shifted from one local venue to your event). LEAKAGE is money that flows straight out of the local economy (a national ticketing fee, or a non-local supplier). The most important single adjustment is stripping out local visitors: a resident's spend is not new money to the area, so only non-local, out-of-area attendees drive genuine impact.
This is exactly where most spreadsheet methods rely on a visitor survey and an educated guess. The stronger approach is to ground the split in your real audience data: derive the percentage of non-local attendees, and returning versus new visitors, directly from ticketing and scan records rather than a small exit poll.
- Deadweight: would have happened anyway
- Displacement: existing local activity crowded out
- Leakage: money leaving the local economy
- Strip out local visitors: only non-local spend is new
Illustrative worked example (hypothetical numbers)
The following is an illustrative example only, using round, made-up numbers to show the method. These are not real audited results, and every figure would be adjusted to your own data and region.
Say a festival records 20,000 unique attendees. Ticketing and scan data suggest 60% are non-local, giving 12,000 relevant visitors. Assume an illustrative average per-head local spend of EUR 90 (with any spend that leaks out of the area, such as a national ticketing fee, already excluded). Gross visitor spend = 12,000 x EUR 90 = EUR 1,080,000. Now apply additionality: reduce by an assumed 15% for deadweight and displacement, leaving roughly EUR 918,000 of net-additional direct spend.
Apply an illustrative regional multiplier of 1.4 to capture indirect and induced effects: EUR 918,000 x 1.4 = approximately EUR 1.29m total economic impact. Net local organiser spend would be added the same way. The point is not the number; it is that every input (the visitor count, the 60% non-local split, the EUR 90 per head, the 15% additionality haircut, the 1.4 multiplier) is stated, sourced and adjustable, so a reader can challenge or re-run any assumption.
- 12,000 non-local visitors x EUR 90 = EUR 1.08m gross (illustrative)
- Less 15% additionality = ~EUR 918k net-additional direct spend (illustrative)
- x 1.4 illustrative regional multiplier = ~EUR 1.29m total impact
- Every assumption is labelled, sourced and adjustable, not asserted as fact
How does Solco turn your data into an audit-ready report for the comune and sponsors?
Typical impact tools give you a formula and a spreadsheet calculator, and leave the survey-and-guesswork grind to you. Solco connects your ticketing, scan, box-office and QR data (from sources such as DICE, Eventbrite and SIAE), unifies the audience, and helps you derive the inputs the method needs from real records rather than estimates.
From one dataset it supports two deliverables: a territorial economic-impact report structured for the comune or council, and an audience and impact proof pack for sponsors. Because the visitor count, the non-local split and the returning-versus-new breakdown come from your own data, the report is easier for a municipality to trust, and the year-on-year view can show returning-audience value building over time.
Solco is deliberately honest about the method's limits. Multipliers and additionality assumptions stay transparent and adjustable, and every euro figure is presented as an illustrative, editable estimate rather than an audited fact, so you can produce a defensible number instead of an indefensible one. You keep control of your underlying audience data throughout.
- Connect ticketing, box-office, scan and QR data (e.g. DICE, Eventbrite, SIAE)
- Derive visitor numbers, % non-local and returning-vs-new from real records
- One dataset, two reports: comune/council impact + sponsor proof pack
- Transparent multipliers and clearly labelled estimate figures, no invented metrics
Frequently asked questions
How do you calculate the economic impact of an event?
A widely used estimate multiplies the number of relevant visitors by their average local spend per head, then applies a regional multiplier: Economic Impact = Visitors x Average Spend x Multiplier. Count only non-local, event-driven spend and net out deadweight, displacement and leakage before applying the multiplier for indirect and induced effects.
Why do you only count non-local visitor spending?
A local resident's spend is not new money to the host area, as they would likely have spent it locally anyway. Only genuinely new, out-of-area visitors bring additional spend into the economy, so stripping out locals is the key additionality adjustment that makes the figure credible to a council.
What should an economic impact report for the council include?
Scope (the host economy and study period), visitor numbers and average per-head spend, the local versus non-local split, net additional spend after deadweight, displacement and leakage, the multiplier used and where it came from, and a clear statement that all monetary figures are transparent, adjustable estimates rather than audited facts.
Why are event economic impact figures often criticised?
Because they can be inflated: using gross rather than net spend, counting local visitors, or applying an over-generous multiplier. The credible fix is transparency: net out additionality, use a conservative region-specific multiplier, ground inputs in real ticketing and scan data, and label every figure as an adjustable estimate.