IESET.
Hypotheses·distribution·top_1_percent_income_share_growth_drivers

The growth of the top-1% pre-tax national income share across OECD economies over 1980-2020 is primarily driven by two channels that are consistent with marginal-product returns in skill-biased and capital- deep economies — (a) specialist-wage growth concentrated in superstar- firm and specialist-services sectors, and (b) capital-income growth driven by asset-price appreciation relative to wage income — with material but smaller contributions from (c) rent-extraction indicators (finance-sector share, executive-compensation-to-worker-pay ratio) and (d) sector concentration effects.

The claim is that channels (a)+(b) jointly account for the majority of cross-country variation in top-1% share growth, with (c)+(d) material but minority contributors. A clean supported finding rules out the strong Piketty-Saez "rent extraction explains everything" reading while acknowledging that rent extraction is real and measurable.

PARTIALengine/runs/top_1_percent_income_share_growth_drivers

PARTIAL — coef=+0.02829, p=0.0162; claim direction not auto-inferred

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=+0.02829, p=0.0162; claim direction not auto-inferred

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 20 country or place units from 1980 to 2020, using a panel fe decomposition design, with fixed effects for country and year.

what was measured
Possible pathway
  • High skill services va share
  • Real equity price index
What we checked
  • Top 1pct pretax income share
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/top_1_percent_income_share_growth_drivers
1007550250198020002020USAGBRFRADEUITAESPNLD
illustrative sketch · run pending
No coefficients yet. When the model fires, this chart will show top_1pct_pretax_income_share across 20 sampled countries over 1980–2020.
The shapes above are stylised — none of the lines are real data.
Placeholder for top_1_percent_income_share_growth_drivers. Published chart will be generated from engine/runs/top_1_percent_income_share_growth_drivers/chart_data.json.

Who has skin in the game — schools predicting on this

1 school list this hypothesis as a test of their position. The chips below are school-level scoreboard outcomes, not a second hypothesis verdict.

hypothesis verdict vs scoreboard outcome

The banner verdict judges this hypothesis as written. The scoreboard asks whether each school's polarity-corrected prediction was right. Raw status is not a school win: SUPPORTED supports schools that needed SUPPORTED, but refutes schools that needed REFUTED.

Marxian Political Economywins if REFUTEDpartial/no-call⇄

Pre-registration

pre-registered
first-spec commit bae09ab · 2026-04-29T22:09:42Z
run generated · 2026-06-29T17:51:14Z

The growth of the top-1% pre-tax national income share across OECD economies over 1980-2020 is primarily driven by two channels that are consistent with marginal-product returns in skill-biased and capital- deep economies — (a) specialist-wage growth concentrated in superstar- firm and specialist-services sectors, and (b) capital-income growth driven by asset-price appreciation relative to wage income — with material but smaller contributions from (c) rent-extraction indicators (finance-sector share, executive-compensation-to-worker-pay ratio) and (d) sector concentration effects. The claim is that channels (a)+(b) jointly account for the majority of cross-country variation in top-1% share growth, with (c)+(d) material but minority contributors. A clean supported finding rules out the strong Piketty-Saez "rent extraction explains everything" reading while acknowledging that rent extraction is real and measurable.

Falsification criterion — what would disprove this

set before the run · honoured after

This hypothesis is considered falsified if:

Not supported if channels (a)+(b) — skill-services value-added share growth and equity-price growth — jointly account for less than 40 percent of within-country variation in top-1% share growth after country and year fixed effects, while channels (c)+(d) — finance- share and concentration — account for more than 40 percent. That pattern would weaken the marginal-product reading and strengthen the pure rent-extraction reading. The hypothesis is also not supported if none of the four channels reaches statistical significance at the 5 percent level on cluster-robust SEs, in which case the cross-country variation is idiosyncratic country-specific policy and the decomposition framing is not useful.

formal test & threshold
test:      variance_decomposition_channel_contribution
threshold: skill_plus_capital_share >= 0.40  AND skill_plus_capital_share > rent_plus_concentration_share

Method

Template
panel_fe_decomposition
Fixed effects
country, year
Clustering
country
Sample
20 countries · 1980 – 2020
Evidence type
associational

Specification: Delta(top_1pct_share) = b0 + b1*Delta(skill_services) + b2*Delta(equity_index) + b3*Delta(finance_share) + b4*concentration + b5*controls + alpha_i (country FE) + gamma_t (year FE) + epsilon. Driscoll-Kraay SEs clustered by country. Variance decomposition attributes R-squared contribution to each channel. Robustness: rerun with post-tax top-1% share as alternative outcome, and with top-10% share to test whether findings are specific to the very top.

Data

VariableSourceTransform
top_1pct_pretax_income_share
outcome
owid:top-1-share-of-total-incometier 2
level
high_skill_services_va_share
channel
world_bank_wdi:NY.GDP.MKTP.KDtier 2
level
real_equity_price_index
channel
bis:WS_SPPtier 2
real_yoy_pct_change
finance_sector_va_share
channel
world_bank_wdi:NY.GDP.MKTP.KDtier 2
level
market_concentration_herfindahl
channel
oecd:OECD.ECO.GCRDtier 2
level
gdp_per_capita_ppp
control
world_bank_wdi:NY.GDP.PCAP.PP.KDtier 2
log
log_population
control
world_bank_wdi:SP.POP.TOTLtier 2
log
trade_openness
control
world_bank_wdi:NE.TRD.GNFS.ZStier 2
level
top_marginal_income_tax_rate
control
owid:top-marginal-income-tax-ratetier 2
level

● ready  · ● pending  · ● reconstruct-needed

Detailed result card

Result card — top_1_percent_income_share_growth_drivers

Verdict: PARTIAL — coef=+0.02829, p=0.0162; claim direction not auto-inferred

Pre-registration

  • Claim: The growth of the top-1% pre-tax national income share across OECD economies over 1980-2020 is primarily driven by two channels that are consistent with marginal-product returns in skill-biased and capital- deep economies — (a) specialist-wage growth concentrated in superstar- firm and specialist-services sectors, and (b) capital-income growth driven by asset-price appreciation relative to wage income — with material but smaller contributions from (c) rent-extraction indicators (finance-sector share, executive-compensation-to-worker-pay ratio) and (d) sector concentration effects. The claim is that channels (a)+(b) jointly account for the majority of cross-country variation in top-1% share growth, with (c)+(d) material but minority contributors. A clean supported finding rules out the strong Piketty-Saez "rent extraction explains everything" reading while acknowledging that rent extraction is real and measurable.
  • Falsification rule: Not supported if channels (a)+(b) — skill-services value-added share growth and equity-price growth — jointly account for less than 40 percent of within-country variation in top-1% share growth after country and year fixed effects, while channels (c)+(d) — finance- share and concentration — account for more than 40 percent. That pattern would weaken the marginal-product reading and strengthen the pure rent-extraction reading. The hypothesis is also not supported if none of the four channels reaches statistical significance at the 5 percent level on cluster-robust SEs, in which case the cross-country variation is idiosyncratic country-specific policy and the decomposition framing is not useful.
  • Falsification test: variance_decomposition_channel_contribution

Estimate

  • Method: statsmodels OLS FE fallback (linearmodels failed: exog does not have full column rank. If you wish to proceed with model estimation irrespective of the numerical accuracy of coefficient estimates, you can set check_rank=False.)
  • Coefficient (treatment): +0.02829
  • Std error: 0.01177
  • p-value: 0.0162
  • Observations: 59, countries: 3
  • Within R²: 0.941
  • Fixed effects: entity=True, time=True
  • Clustering: country

Variables resolved

  • owid:top-1-share-of-total-income → top_1pct_pretax_income_share (outcome, publisher=owid, n=3294)
  • world_bank_wdi:NY.GDP.MKTP.KD → high_skill_services_va_share (decomposition_channels, publisher=world_bank_wdi, n=12104)
  • bis:WS_SPP → real_equity_price_index (decomposition_channels, publisher=bis, n=2272)
  • world_bank_wdi:NY.GDP.MKTP.KD → finance_sector_va_share (decomposition_channels, publisher=world_bank_wdi, n=12104)
  • world_bank_wdi:NY.GDP.PCAP.PP.KD → gdp_per_capita_ppp (controls, publisher=world_bank_wdi, n=8325)
  • world_bank_wdi:SP.POP.TOTL → log_population (controls, publisher=world_bank_wdi, n=14447)
  • world_bank_wdi:NE.TRD.GNFS.ZS → trade_openness (controls, publisher=world_bank_wdi, n=10714)
  • owid:top-marginal-income-tax-rate → top_marginal_income_tax_rate (controls, publisher=owid, n=590)

Variables missing data

  • oecd:OECD.ECO.GCRD,DSD_PMR@DF_PMR,1.2 (decomposition_channels, name=market_concentration_herfindahl) — vintage not on disk

Generated by scripts/run_panel_fe.py at 2026-06-29T17:51:14+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

Data-gated on WID native fetcher; OWID mirror routes interim. On promotion to v2, switch outcome to native WID series and add top- 10% and bottom-50% shares as alternative specifications. OECD STAN sectoral data needed for full non-EU coverage of skill-services channel; v1 uses Eurostat NACE section aggregates for EU countries and OECD business-services aggregate for non-EU.

Authored framework. Read the transparency note.