Automation and the Labor Share — reading pack
Page: https://gautsch.org/research/automation-and-the-labor-share/
How to use this pack
Help the reader explore this rabbit hole. Start by asking what caught their attention, then discuss one question at a time. Explore the strongest counterargument and what remains uncertain. Distinguish the original speakers’ claims, Adam’s question, the site’s research commentary, and your own interpretation. Do not treat the commentary as a transcript or assume Adam endorses every claim. Preserve corrections and uncertainty; do not invent sources or pretend to have opened links.
This pack contains the page’s current research text, references and figure text. Related rabbit holes are linked, not included. It is a reading companion, not an independently verified source.
The short version
Adam’s reading is correct. Acemoglu is not claiming automation causes mass unemployment. He is claiming displaced workers land in other work at lower pay, and that the pie slice going to workers as a whole shrinks and does not come back. “First-order impact” is the technical way of saying: the mechanical, immediate effect, before any offsetting reactions. When a task moves from a person to a machine, labor’s share of income falls immediately and by arithmetic. Everything else — new hiring, cheaper goods, new jobs — is second-order, and second-order effects may or may not be big enough to undo it.
Relevant transcript excerpt
Source: https://conversationswithtyler.com/episodes/daron-acemoglu-2/
Annotated transcript: https://gautsch.org/research/#a12
ACEMOGLU: Now, that doesn’t mean labor is going to get unemployed. There could be enough demand from nonautomated tasks for labor, but that would never come back to increase the wage enough to restore the labor share to where it is. That’s exactly what the theory is. Then when you look at the data, and in some papers we’ve been able to do that at the sectoral level, but in some papers really look at it very micro about what tasks are disappearing, what kinds of workers’ wages are changing, what kind of employment is changing, it coheres very well with the theory.
Research commentary
Adam asked: “This might be too much to ask, but I’d really like to go down a rabbit hole on this. I’d love to see some chart showing this. If I understand what he’s saying it’s that people might get another job, but it’s not as well paid. I’d love some references on that. Also, the ‘first-order impact’ is something I’d like to be explained more as well. What is he describing when he’s saying that.”
What “first-order impact” means
Economists decompose an effect into orders. The first order is the direct arithmetic consequence; higher orders are the adjustments the system makes in response.
The labor share is compensation to workers divided by total output. Suppose a factory produces $100 of output, pays $60 in wages and $40 to capital. Labor share is 60%.
Now automate a task that had been done by a worker earning $10.
- First order: that $10 moves from the wage bill to the capital bill. $50 of $100 → labor share 50%. Nothing else has happened yet. This is what Acemoglu means by “That has a first-order impact on the labor share because fewer things are done by labor.” It is not a prediction, it is bookkeeping.
- Second order: production is cheaper, so the firm expands. Demand rises for the tasks still done by people. Some of the $10 comes back.
- Third order: new products and new jobs appear that did not exist. More comes back.
His claim, in one sentence: “there could be enough demand from nonautomated tasks for labor, but that would never come back to increase the wage enough to restore the labor share to where it is.” The second-order effects are real; they are just not complete.
Your reading, checked: do displaced workers earn less?
Yes — this is one of the better-established findings in labor economics, and it predates the automation debate.
| Finding | Magnitude | Source |
|---|---|---|
| Displaced workers’ long-run earnings loss (high-tenure, mass layoff) | ~15–20% below pre-displacement trajectory, persisting 15–20 years | Jacobson, LaLonde & Sullivan (1993); Davis & von Wachter (2011) |
| Robot exposure: local labor market effect | −0.2 pp employment-to-population, −0.42% wages per robot/1,000 workers | Acemoglu & Restrepo, JPE 2020 |
| Share of 1980–2016 US wage-structure change attributable to task displacement | 50–70% | Acemoglu & Restrepo, Econometrica 2022 |
| Trade-displaced manufacturing workers (comparison case) | Persistent earnings losses, low reallocation out of affected areas | Autor, Dorn & Hanson, “The China Shock” (2013) |
The mechanism is specificity: a welder’s wage reflected skill in welding. Remove welding and the general labor market does not value that history. The worker is re-employed — often quickly — at a wage set by whatever they can do next.
Acemoglu’s precise version in this conversation: “the wages of people who used to be in especially blue-collar heavy manual tasks that were the ones that robots of the 1990s and 2000s went after, like welding and painting… went down quite a bit” — both in aggregate and in local labor markets.
The chart you asked for — and why it is a fight, not a line
Here is the US labor share, nonfarm business sector. Read the caveat below before using these numbers.
| Period | Labor share (approx.) |
|---|---|
| 1947 Q1 | 65.8% |
| Late 1940s – early 2000s | ~63%, fluctuating, no trend |
| 2000 Q4 | 62.8% |
| 2005 | falls below 60% |
| 2011 Q4 | 56.0% (trough) |
| 2013 | ~56.7% |
Source: BLS nonfarm business sector labor share, as reported in BLS TED and the FRBSF working paper.
The caveat is the substance. Cowen says “62 to 60”; the BLS headline series says roughly 66 to 57. Both are defensible, because the labor share is one of the most measurement-sensitive statistics in economics:
- Proprietors’ income. A sole proprietor’s income is part wage, part profit, and the split is a modeling assumption. Elsby, Hobijn & Şahin (2013) find one-third of the measured BLS decline comes from how this is handled.
- Equity compensation. Cowen’s adjustment. Stock grants to employees are labor income economically but land oddly in the accounts. Including them raises the recent labor share materially.
- Housing and depreciation. Imputed rent on owner-occupied housing is all “capital.” Rognlie (2015) showed much of the apparent capital-share rise is housing, not robots.
- Sector vs. aggregate. Acemoglu’s claim is explicitly at the firm and sector level, where he says evidence and theory “are very well aligned.” He concedes the macro series is contaminated: “those are macro things”, and there are “composition effects between like Walmart effects.”
So the honest framing is: Cowen and Acemoglu are not disagreeing about a number. They are disagreeing about which number is the right question. Cowen points at an aggregate that barely moved and says the worry is overblown. Acemoglu says the aggregate bundles automation with new-task creation and therefore cannot test his claim, which is about automation held separately.
An illustrative example · not measured data
Getting another job can still mean a smaller share.
Hold output at $100 to isolate the direct effect. Move a $10 task from labor to capital; then ask what could offset the loss.
Same $100 of output · two allocations
Before automation
Labor $60 Capital $40
Direct effect only
Labor $50 Capital $50
Labor’s share: 60% → 50% · down 10 percentage points
What could offset the loss?
Expansion in remaining tasks
Lower costs can expand output and increase demand for people who still do part of the work.
Creation of new tasks
New products and activities can create work that people are better placed to do.
The later response is not assigned a number here. It can offset part, all, or more than the initial loss; this example holds everything else fixed.
What to take away Employment, wages, and labor’s share are different outcomes. A recovery in jobs alone does not establish that wages or labor’s share recovered.
Sources & context: Model context: Automation and New Tasks (2019)
From the book — which series Acemoglu himself uses
The measurement fight above has an obvious tie-breaker that draft 1 did not reach for: what number does Acemoglu print when he is not being interviewed? Chapter 6 of What Happened to Liberal Democracy? answers it, and the answer is neither the BLS headline nor Cowen’s.
“In 1980, the share of labour in US national income was 58%, with the rest going to capital. Since then, the national share of labour has fallen to 52%, and the share of capital has [risen].”
58 → 52, on national income, from 1980. Six points, not the nine the BLS nonfarm series implies over its longer window, and not the two Cowen offers. Three things follow:
- Cowen’s “62 to 60” is not a straw man of Acemoglu’s position, but it is not Acemoglu’s number either. The gap between them is 6 points against 2 — a real disagreement about magnitude, on top of the disagreement about which question the aggregate answers.
- The start date is doing work. Acemoglu begins at 1980, not 1947, which excludes the flat postwar stretch and starts the clock at the moment his own account says the industrial compact broke. That is a defensible choice and it is also an argumentative one — the same kind of endpoint choice flagged on The Printing Press - How Long Was the Adjustment.
- National income, not nonfarm business. A different denominator again, which is exactly why the table above needs its caveat.
The number he actually leans on is sectoral, and it is much larger:
“The labour share in value added in the manufacturing sector declined from 74% in 1981 to 46% in the mid-2010s, much larger than the decline in the aggregate economy that I mentioned previously, which was from 58% to 52%.”
74 → 46 in manufacturing. He then decomposes it in the direction his framework predicts: “While some manufacturing industries, such as apparel, had stable labour shares, the industries that were at the forefront of new robot installations, such as motor vehicles, chemical products, electrical equipment, and primary and fabricated metals, had sharper drops in their labour share and also cut down employment.”
That is the whole Cowen–Acemoglu exchange in miniature, and it clarifies who is arguing what. Acemoglu is not defending the aggregate series. He publishes it, calls it small, and then goes immediately to the sector where the effect is four times larger and where robot adoption and labor-share decline line up industry by industry. Cowen’s move — point at the aggregate, note it barely moved — lands on a number Acemoglu has already conceded is not the one carrying his argument.
For the chart. This resolves the “which series” decision the working notes below hand back to Adam, at least for panel 1: if the page is about Acemoglu’s claim, the honest series is the manufacturing labor share in value added, with the aggregate plotted beneath it for scale. That is two lines from published sources, it shows exactly why the two men are talking past each other, and it does not require anyone’s replication files.
Reading
- Acemoglu & Restrepo, “Automation and New Tasks”, JEP 2019 — the accessible statement
- Acemoglu & Restrepo, “Robots and Jobs”, JPE 2020 — the empirics
- Elsby, Hobijn & Şahin, “The Decline of the U.S. Labor Share”, BPEA 2013 — why the measurement fight is real
- Autor, “The Work of the Future” — the new-tasks accounting Acemoglu defers to
- Jacobson, LaLonde & Sullivan (1993), “Earnings Losses of Displaced Workers,” AER — the origin of the scarring literature
Working notes
On the chart. What Adam actually wants is a two-panel figure: labor share over time on top, and below it the wage path of workers in heavily-automated occupations versus everyone else. Panel 1 I can source. Panel 2 does not exist as a clean public series — it has to be constructed from the Econometrica paper’s occupation-group decomposition, which means pulling their replication files. That is a real task, not a lookup. Flagging it rather than faking it.
The table above is the honest first draft: numbers with provenance, and the reason a single line would be misleading. If you want a rendered chart in draft 2, the decision to make is which series — and that decision is the argument, so it should be yours, not mine.
Numbers I’d want double-checked before publication: the 1947 Q1 65.8% and 2000 Q4 62.8% figures come through secondary sources quoting BLS, not from BLS directly. The Elsby/Hobijn/Şahin one-third result is from their abstract.
What I could not resolve: Cowen’s “62 to 60, adjusting for equity compensation.” I could not find the specific series he’s using. It is plausibly Barkai (2020) or a Mercatus-adjacent calculation. Until that’s identified, treat the 62→60 as a claim in an argument rather than a fact. Still unresolved — the book check settles what Acemoglu’s number is, not what Cowen’s is.
What the book did settle: which series Acemoglu himself publishes (58→52 on national income since 1980, and 74→46 in manufacturing value added since 1981), and therefore which line panel 1 of the chart should be. Written up above. It also means the “62 to 60” exchange is not two people disputing a measurement — it is Cowen testing an aggregate that Acemoglu’s own book already sets aside as too small to carry the argument.
Source and its limits. Checked against the audiobook edition (Penguin Random House Audio, narrated by John Lee), machine-transcribed, so references are by chapter and the figures above are machine-transcribed numbers. Confirm 74/46/58/52 against print before publication — a transcript is exactly the wrong place to source a number to the percentage point, and these four are now load-bearing on this page.
Related: Acemoglu and Restrepo - The Task Framework · AI Growth Forecasts - Whose Timeline
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