IESET.
Hypotheses·distribution·monopoly_capital_concentration_markup_link

Across US industries 1980-2020, rising concentration (top-4 / top-8 firm shares of industry sales) is associated with a parallel rise in aggregate non-financial corporate markups, and the cross-industry relationship is positive and material in magnitude.

A Baran-Sweezy-style monopoly-capital reading predicts that industries with the largest concentration increases display the largest markup increases, and that the aggregate markup share of GDP rises in lockstep with concentration. A market-liberal "rising-superstar-firms-from- technology" reading predicts the same correlation but attributes it to productivity dispersion rather than market power; the test here uses an industry FE specification to discriminate.

PARTIALengine/runs/monopoly_capital_concentration_markup_link

PARTIAL — coef=-88.78, p=0.495 (above α=0.1); direction inconclusive

confidence cueThe result is useful, but not decisive. Treat it as a clue, not a settled conclusion.

policy briefMixed or noisy

In ordinary language

Over a long period, do more market-oriented institutions translate into higher income or productivity, once the comparison looks beyond a single success story?

plain answer

The evidence is suggestive but not decisive. coef=-88.78, p=0.495 (above α=0.1); direction inconclusive

why it matters

Distributional claims often sound morally clear but are empirically complex. This test asks whether the proposed channel explains real differences across places.

how the test works

It compares 1 country or place units from 1980 to 2020, using a panel fe design, with fixed effects for industry and year.

what was measured
What changed
  • Aggregate industry concentration index
  • Top 1pct firm share of corporate sales
What we checked
  • Aggregate corporate markup share
  • Corporate profits before tax
what this does not prove

A single test is not the whole truth. It narrows the claim under a specific sample, time period, and method. Strong policy conclusions need the pattern to survive nearby tests, alternative data, and serious objections.

verification

No evidence packet has been generated yet.

Results

engine/runs/monopoly_capital_concentration_markup_link
1007550250198020002020USA
illustrative sketch · run pending
No coefficients yet. When the model fires, this chart will show aggregate_corporate_markup_share across 1 sampled countries over 1980–2020.
The shapes above are stylised — none of the lines are real data.
Placeholder for monopoly_capital_concentration_markup_link. Published chart will be generated from engine/runs/monopoly_capital_concentration_markup_link/chart_data.json.

Pre-registration

pre-registered
first-spec commit 098ce96 · 2026-04-30T12:57:33Z
run generated · 2026-06-29T17:49:56Z

Across US industries 1980-2020, rising concentration (top-4 / top-8 firm shares of industry sales) is associated with a parallel rise in aggregate non-financial corporate markups, and the cross-industry relationship is positive and material in magnitude. A Baran-Sweezy-style monopoly-capital reading predicts that industries with the largest concentration increases display the largest markup increases, and that the aggregate markup share of GDP rises in lockstep with concentration. A market-liberal "rising-superstar-firms-from- technology" reading predicts the same correlation but attributes it to productivity dispersion rather than market power; the test here uses an industry FE specification to discriminate.

Falsification criterion — what would disprove this

set before the run · honoured after

This hypothesis is considered falsified if:

Not supported if the industry-FE coefficient on concentration is statistically zero or negative (p > 0.10 OR sign-flipped), OR if the aggregate markup-vs-concentration time-series correlation breaks once controlling for productivity dispersion (Andrews- Criscuolo-Gal-style frontier-vs-laggard gap), which would re-vindicate the superstar-firm-from-technology reading. A symmetric falsification: if concentration rises but markup share is flat or falling in the post-2015 sub-sample, the monopoly-capital reading is undercut on its strongest claimed period.

formal test & threshold
test:      industry_fe_concentration_markup_coefficient_with_productivity_dispersion_control
threshold: coef(concentration) > 0 at p < 0.10 AND aggregate markup share rises >= 3 percentage-points 1980-2020 AND coefficient survives productivity-dispersion control

Method

Template
panel_fe
Fixed effects
industry, year
Clustering
year
Sample
1 countries · 1980 – 2020
Evidence type
associational

Industry-by-year panel (where industry-level Census data permit) of markup proxy on concentration with industry and year fixed effects. Aggregate-time-series back-up specification regresses aggregate markup on aggregate concentration with HAC SEs. Robustness: instrument concentration with industry-specific China shock exposure (a la Autor-Dorn-Hanson) to address the superstar-firm endogeneity.

Data

VariableSourceTransform
aggregate_corporate_markup_share
outcome
fred:A446RC1Q027SBEAtier 1
level
corporate_profits_before_tax
outcome
fred:CPtier 1
level
aggregate_industry_concentration_index
treatment
world_bank_wdi:NV.IND.MANF.ZStier 2
level
top_1pct_firm_share_of_corporate_sales
treatment
oecd:OECD.SDD.NADtier 2
level
capital_stock_per_worker
control
pwt:rknatier 3
log
trade_openness
control
world_bank_wdi:NE.TRD.GNFS.ZStier 2
level
log_real_gdp
control
fred:GDPC1tier 1
log
union_density_us
control
oecd:OECD.ELS.SAEtier 2
level

● ready  · ● pending  · ● reconstruct-needed

Detailed result card

Result card — monopoly_capital_concentration_markup_link

Verdict: PARTIAL — coef=-88.78, p=0.495 (above α=0.1); direction inconclusive

Pre-registration

  • Claim: Across US industries 1980-2020, rising concentration (top-4 / top-8 firm shares of industry sales) is associated with a parallel rise in aggregate non-financial corporate markups, and the cross-industry relationship is positive and material in magnitude. A Baran-Sweezy-style monopoly-capital reading predicts that industries with the largest concentration increases display the largest markup increases, and that the aggregate markup share of GDP rises in lockstep with concentration. A market-liberal "rising-superstar-firms-from- technology" reading predicts the same correlation but attributes it to productivity dispersion rather than market power; the test here uses an industry FE specification to discriminate.
  • Falsification rule: Not supported if the industry-FE coefficient on concentration is statistically zero or negative (p > 0.10 OR sign-flipped), OR if the aggregate markup-vs-concentration time-series correlation breaks once controlling for productivity dispersion (Andrews- Criscuolo-Gal-style frontier-vs-laggard gap), which would re-vindicate the superstar-firm-from-technology reading. A symmetric falsification: if concentration rises but markup share is flat or falling in the post-2015 sub-sample, the monopoly-capital reading is undercut on its strongest claimed period.
  • Falsification test: industry_fe_concentration_markup_coefficient_with_productivity_dispersion_control

Estimate

  • Method: statsmodels OLS time-series fallback
  • Coefficient (treatment): -88.78
  • Std error: 130
  • p-value: 0.495
  • Observations: 23, countries: 1
  • Within R²: 0.925
  • Fixed effects: entity=False, time=False
  • Clustering: HAC(maxlags=4)

Variables resolved

  • fred:A446RC1Q027SBEA → aggregate_corporate_markup_share (outcome, publisher=fred, n=79)
  • fred:CP → corporate_profits_before_tax (outcome, publisher=fred, n=79)
  • world_bank_wdi:NV.IND.MANF.ZS → aggregate_industry_concentration_index (treatment, publisher=world_bank_wdi, n=9698)
  • oecd:OECD.SDD.NAD,DSD_NAMAIN1@DF_TABLE1,1.0 → top_1pct_firm_share_of_corporate_sales (treatment, publisher=oecd, n=3157)
  • pwt:rkna → capital_stock_per_worker (controls, publisher=pwt, n=7095)
  • world_bank_wdi:NE.TRD.GNFS.ZS → trade_openness (controls, publisher=world_bank_wdi, n=10714)
  • fred:GDPC1 → log_real_gdp (controls, publisher=fred, n=80)
  • oecd:OECD.ELS.SAE,DSD_TUD_CBC@DF_TUD,1.0 → union_density_us (controls, publisher=oecd, n=1825)

Generated by scripts/run_panel_fe.py at 2026-06-29T17:49:56+00:00

Strongest opposing argument

Every hypothesis ships with its charitable opposing argument. The framework earns credibility by handling objections at their strongest, not weakest.

Notes

Candidate, not pre_registered. On promotion, secure a registered fetcher for De Loecker-Eeckhout firm-level markups (Compustat-based) and confirm OECD MultiProd dataflow URN; the aggregate-only test is weaker than an industry-panel test.

Authored framework. Read the transparency note.