The Cost of Hate: Putting a Number on Threats of Violence

A threat of violence does damage even when no attack ever happens. Swatting calls, bomb threats, and hate-driven intimidation empty buildings, frighten communities, and consume an emergency response — costs that are real, measurable, and almost never counted. This is how TDR puts a defensible number on that harm, why the measurement is so difficult, and why getting it right matters for prosecution, restitution, and policy.

Why put a dollar figure on fear?

Because a harm nobody measures is a harm nobody prevents. When a threat leaves no physical injury, it is easy to treat it as if it cost nothing — and that assumption lets the behavior continue. A credible cost figure is what lets a prosecutor pursue restitution, lets a judge weigh damage that left no mark, lets a school board justify prevention spending, and lets policymakers grasp a burden measured in hundreds of millions of dollars a year.

A fake threat is still a terrorist act

A threat of a shooting or a bombing is designed to do exactly what a real one does: terrify people into believing they are about to be harmed. When the person responsible later says “I was only joking,” what they are really admitting is that they found it entertaining to watch people react to a terrorist threat. At the moment it is made, the victims cannot tell the difference — the fear, the fight-or-flight response, and the disruption to their day are the same as if the danger were real. What TDR’s research does is measure that impact and put a dollar figure on it.

That figure routinely surprises the person who made the threat. “Nobody was hurt, nothing was damaged” is the most common defense — and it misses the point entirely. The harm of a threat is the fear it manufactures and the time, learning, and stability it destroys, none of which leave a mark on an invoice. The largest of these costs are invisible, which is exactly why they go unpaid and unaddressed.

Published research is clear on the direction of the harm: lockdowns triggered by violent threats measurably raise anxiety and stress; anticipatory fear predicts later anxiety even when no attack occurs; and stress demonstrably impairs attention, memory, and learning. Distress also spreads well beyond the directly targeted site — through families, staff, shared transportation, and news coverage.

The four kinds of loss

TDR’s model separates harm into four distinct components, so nothing is double-counted:

• Immediate operational loss — time and productivity gone during the shutdown, lockdown, or evacuation.
• Non-return — people who leave and don’t come back that day or the next.
• Impairment — those who stay but function poorly, rattled and distracted.
• Lasting stress — a smaller group carrying the effect for days or weeks.

Naming these components openly is part of what makes the accounting credible. What stays proprietary is only the calibration — the field-derived rates and formulas that turn these components into a defensible dollar figure.

Why the numbers are not fixed

A fair question is why TDR does not simply publish a table of percentages. The honest answer is that the numbers change — sometimes quickly — and any single published figure would misrepresent a moving target. The problem itself is accelerating: when TDR spoke with The New York Times in September 2024, monthly school threats had already grown from 29 five years earlier to 785; in TDR’s 2024–25 reporting, that figure has risen to nearly 4,000 schools impacted every month.

How institutions respond has also shifted — from mass evacuation toward lock-and-hold — and COVID-era isolation moved the mental-health baseline against which every event is measured. A model built on frozen numbers would misread all of it, which is why TDR treats its parameters as a living, versioned system rather than a fixed constant.

Why it takes more than a formula

A credible per-event figure weighs many factors at once — the kind of loss, how the institution responded, who was genuinely exposed, how the threat was delivered and how credible it was, whether it’s part of a pattern, the community’s current state, who was affected, the setting, any tangible costs, the local value of an hour, and a local baseline for comparison. Each takes a different value for every event, so no two threats produce the same result.

That depth cannot be shortcut. For nearly ten years, TDR has studied approximately 100,000 real and fake threats and produced court-admissible documentation defending these figures. That reach extends well beyond TDR’s own walls: TDR is the only organization that tracks the victims and the true cost of swatting and related threats. That is why its data helps train thousands of law enforcement officers every month, and why law enforcement and prosecutors often rely on it to help establish the damages these events cause. Because no comparable resource exists, TDR is also the name practitioners point to when a colleague asks who to turn to. Grounding real-world training and real cases in this evidence speaks to its depth more than any self-assessment could. The equations are the easy part; the decade of evidence behind them is what makes the numbers mean anything.

Why it matters

Naming the cost is the first step toward preventing it. Threats of violence are a learned, repeatable behavior — and with screening technology, real consequences, and education, they can be intercepted before they cause harm and deterred afterward. That is what TDR’s SAM (School Access Manager) suite was built to do.

Go deeper: This overview intentionally leaves out the underlying formulas and parameters. The full peer-reviewed methodology is published in the book TDR co-authored — Policing, Violence, and Society (Springer, 2026), available from the publisher.

See also: For journalists · Data by state · What is swatting?

Source: TDR Technology Solutions, Annual School Threat Impact Report 2024–2025. Methodology background: Bernhardt & Beeler (2026), Policing, Violence, and Society (Springer). Threat-volume figures reported in The New York Times, Sept. 25, 2024. This edition omits proprietary model parameters and formulas.