Attention economy
The attention economy is the allocation of human attention as a scarce resource across competing demands — and, in its current form, the industry whose dominant business model is to capture attention in order to sell advertising against it. The concept predates the internet (Herbert Simon’s 1971 observation that “a wealth of information creates a poverty of attention”), but the contemporary version is defined by algorithmic short-form video and engagement-optimized feeds, whose success is measured in time-on-device rather than user welfare.
The revealed-preference puzzle
Matthew Yglesias frames the modern attention economy as a revealed-preference trap: by what people actually do, video “absolutely felicity-moggs” every prior medium, yet the result “doesn’t make for a very appealing vignette about modern life.”1 The dominant use of the internet’s abundance is algorithmic short-form video (Reels, TikTok, YouTube Shorts), and the largest technology companies are, in practice, vendors of streaming video and the devices it plays on. Yglesias’s provocation: the 75-year “rolling moral panic” about television was essentially correct — television displaced exactly the communal, social-capital-building time that Putnam documented in Bowling Alone, and the smartphone generalizes that substitution. See trust-and-social-capital for the Putnam cohort evidence and abundance-agenda for the supply-side frame this critiques.
The empirical record: two NBER experiments
Two large randomized/structured experiments give the puzzle quantitative teeth.
Deactivation improves emotional state. Allcott, Gentzkow, and co-authors ran two large randomized experiments before the 2020 U.S. election in which participants deactivated Facebook or Instagram for six weeks.2 Deactivating Facebook produced a 0.060 standard-deviation improvement on an index of happiness, depression, and anxiety (relative to controls who deactivated for only the first week); deactivating Instagram produced a 0.041 SD improvement. The effects are statistically significant (p < 0.01). Exploratory cuts: the Facebook effect concentrates in users over 35, the Instagram effect in women under 25. People who leave feel better — yet they largely return.
The collective trap. Bursztyn, Handel, Jimenez, and Roth (“When Product Markets Become Collective Traps”) separate individual consumer surplus from product-market surplus by eliciting both willingness-to-accept (WTA) to deactivate and willingness-to-pay (WTP) to deactivate the entire market.3 On the standard individual measure, users derive large positive surplus — averaging 47 (Instagram), with 92% / 86% of users positive. But accounting for the externality that non-use imposes (being the only one off the network is costly), the picture inverts: a large share of users experience negative welfare from the product’s existence, and users would on average pay 6 (Instagram) to have the whole product market shut down. This is the product-market trap: it is individually rational to use a product you would collectively pay to abolish — the same structure as an arms race or a positional good.
Policy levers and their shape
Yglesias draws the policy implication explicitly: not prohibition (“we’re not going to un-invent the smartphone”), but rebalancing the tax burden — taxing digital advertising revenue and other parts of the “compulsive video industry” while shifting the burden off activities that build social capital (his example: making it “cheaper and easier and more lucrative” to bowl, dine out, or exercise than to run a “glowing screen, home alone” business).4 The logic mirrors Pigouvian taxation of cigarettes: if the externality is real (the collective-trap evidence says it is), the tax nudges the margin without banning the behavior. The Bursztyn et al. framing sharpens why individual willpower fails — the trap is structural, so the remedy is structural (price, default, or market-shape), not exhortation.
Open questions
- Effect durability. Do the deactivation gains persist past six weeks, or does hedonic adaptation / substitution to other screens erode them?
- Generalizability. Both NBER studies are U.S. samples around the 2020 election; does the collective-trap result hold for non-student, non-U.S. populations?
- Subscription vs. ad models. Does shifting platforms from advertising to subscription (as Yglesias suggests) actually reduce compulsive use, or merely re-price it?
- Regulation of the externality. If the harm is a collective externality rather than individual overuse, does that argue for market-level intervention (ad taxes, design mandates) over screen-time tools aimed at individuals?
Related pages
- trust-and-social-capital — the social-capital stock the attention economy draws down
- abundance-agenda — the supply-side celebration this critiques on the demand side
- infinite-game-cooperation — the repeated-interaction substrate that communal time feeds
- moral-economy-price-tag — another case of a market mechanism colliding with a non-market good
- bullshit-jobs — a rival account of modern work/consumption malaise
- post-literacy-debate — the civilizational-decline framing of the same screen ecosystem, and the education-system counter-evidence
Sources
- Matthew Yglesias 2026 — The real reason nobody feels good about technological progress
- Hunt Allcott, Matthew Gentzkow, et al. 2026 — The Effect of Deactivating Facebook and Instagram on Users’ Emotional State
- Leonardo Bursztyn, Benjamin R. Handel, Rafael Jimenez, Christopher Roth 2024 — When Product Markets Become Collective Traps: The Case of Social Media
Footnotes
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Matthew Yglesias 2026 — The real reason nobody feels good about technological progress ↩
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Hunt Allcott, Matthew Gentzkow, et al. 2026 — The Effect of Deactivating Facebook and Instagram on Users’ Emotional State ↩
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Leonardo Bursztyn, Benjamin R. Handel, Rafael Jimenez, Christopher Roth 2024 — When Product Markets Become Collective Traps: The Case of Social Media ↩
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Matthew Yglesias 2026 — The real reason nobody feels good about technological progress ↩