IESET.
Hypotheses·fiscal·rnd_spending_patent_intensity_panel

R&D spending intensity predicts higher patent intensity only where government effectiveness or rule of law is high.

PARTIALengine/runs/rnd_spending_patent_intensity_panel

PARTIAL — coef=+7.645e+04, p=0.177 (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

Does the policy environment make innovation easier to fund, build, and scale, or does it slow down useful new technology?

plain answer

The evidence is suggestive but not decisive. coef=+7.645e+04, p=0.177 (above α=0.1); direction inconclusive

why it matters

This matters because fiscal claims should change belief only when they survive a pre-declared empirical test.

how the test works

It compares 1 country or place units from 1980 to 2024, using a panel fe design, with fixed effects for country and year.

what was measured
What changed
  • Research and development intensity
What we checked
  • Resident patents
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/rnd_spending_patent_intensity_panel
1007550250198020022024GLOBAL
illustrative sketch · run pending
No coefficients yet. When the model fires, this chart will show resident_patents across 1 sampled countries over 1980–2024.
The shapes above are stylised — none of the lines are real data.
Placeholder for rnd_spending_patent_intensity_panel. Published chart will be generated from engine/runs/rnd_spending_patent_intensity_panel/chart_data.json.

Who has skin in the game — schools predicting on this

17 schools 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.

Austrian Business Cycle Theory (ABCT)wins if REFUTEDpartial/no-callChicago School Monetarismwins if REFUTEDpartial/no-callClassical Liberalwins if REFUTEDpartial/no-callDegrowth / Ecological Macroeconomicswins if MIXEDpartial/no-callDemocratic Socialism (Bernsteinian revisionism + modern)wins if SUPPORTEDpartial/no-callStructuralist / Developmentalistwins if SUPPORTEDpartial/no-callEco-Socialism / Red-Greenwins if SUPPORTEDpartial/no-callEmpirical Pragmatist (the framework's house position)wins if MIXEDpartial/no-callNew Institutional Economicswins if SUPPORTEDpartial/no-callMarket Socialism (Lange-Lerner tradition)wins if SUPPORTEDpartial/no-callMarxian Political Economywins if SUPPORTEDpartial/no-callMarxism-Leninism (central-planning implementation)wins if MIXEDpartial/no-callModern Monetary Theorywins if SUPPORTEDpartial/no-callNew Keynesian (mainstream synthesis)wins if MIXEDpartial/no-callOrdoliberalism (Freiburg School)wins if MIXEDpartial/no-callPost-Keynesianwins if SUPPORTEDpartial/no-callSocial Democraticwins if SUPPORTEDpartial/no-call

Pre-registration

registration ordering unverified
first-spec commit 4c8ce8e · 2026-07-18T22:11:21Z
run generated · 2026-06-29T17:52:33Z
Run timestamp predates this path's first git-add commit (rebase, rename, or pre-git local run). Spec hash is still the path's first-add commit — not repository HEAD — but ordering is not a clean pre-registration proof.

R&D spending intensity predicts higher patent intensity only where government effectiveness or rule of law is high.

Falsification criterion — what would disprove this

set before the run · honoured after

This hypothesis is considered falsified if:

SUPPORTED if the primary treatment coefficient has the pre-registered + sign at p<=0.10 with minimum sample gates. REFUTED if the coefficient has the opposite sign at p<=0.10. Otherwise PARTIAL; missing data or failed sample gates are INCONCLUSIVE_DATA_PENDING.

formal test & threshold
test:      panel_fe_rnd_spending_patent_intensity_panel
threshold: [object Object]

Method

Template
panel_fe
Fixed effects
country, year
Clustering
country
Sample
1 countries · 1980 – 2024
Evidence type
associational

First-pass panel fixed effects screen. Multi-outcome or threshold language from the source backlog should be upgraded to a bespoke replication before scoreboard conversion.

Data

VariableSourceTransform
resident_patents
outcome
wipo:patent_applications_residenttier 2
per_capita
research_and_development_intensity
treatment
world_bank_wdi:GB.XPD.RSDV.GD.ZStier 2
level_lagged_one_year
log_gdp_pc
control
world_bank_wdi:NY.GDP.PCAP.KDtier 2
log
trade_openness
control
world_bank_wdi:NE.TRD.GNFS.ZStier 2
level
government_effectiveness
control
wgi:GE.ESTtier 4
level

● ready  · ● pending  · ● reconstruct-needed

Detailed result card

Result card — rnd_spending_patent_intensity_panel

Verdict: PARTIAL — coef=+7.645e+04, p=0.177 (above α=0.1); direction inconclusive

Pre-registration

  • Claim: R&D spending intensity predicts higher patent intensity only where government effectiveness or rule of law is high.
  • Falsification rule: SUPPORTED if the primary treatment coefficient has the pre-registered + sign at p<=0.10 with minimum sample gates. REFUTED if the coefficient has the opposite sign at p<=0.10. Otherwise PARTIAL; missing data or failed sample gates are INCONCLUSIVE_DATA_PENDING.
  • Falsification test: panel_fe_rnd_spending_patent_intensity_panel

Estimate

  • Method: linearmodels.PanelOLS
  • Coefficient (treatment): +7.645e+04
  • Std error: 5.66e+04
  • p-value: 0.177
  • Observations: 1406, countries: 93
  • Within R²: -0.031
  • Fixed effects: entity=True, time=True
  • Clustering: country

Variables resolved

  • wipo:patent_applications_resident → resident_patents (outcome, publisher=wipo, n=4180)
  • world_bank_wdi:GB.XPD.RSDV.GD.ZS → research_and_development_intensity (treatment, publisher=world_bank_wdi, n=3140)
  • world_bank_wdi:NY.GDP.PCAP.KD → log_gdp_pc (controls, publisher=world_bank_wdi, n=12104)
  • world_bank_wdi:NE.TRD.GNFS.ZS → trade_openness (controls, publisher=world_bank_wdi, n=10714)
  • wgi:GE.EST → government_effectiveness (controls, publisher=wgi, n=5168)

Generated by scripts/run_panel_fe.py at 2026-06-29T17:52:33+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

Source shard: engine/audits/swarm_2026-05-22_200_hypotheses_worker_D_sectoral_data_rich.md. Backlog source families: WDI/Eurostat R&D, WIPO patents, WGI.. Initial promotion pass left scoreboard mapping empty; mapped by the 2026-05-22 swarm scoreboard conversion v1. v2 wiring: Added Eurostat NUTS2 regional R&D expenditure and patent applications as subnational-level evidence panels. Country-level WDI/WIPO remain primary; Eurostat NUTS2 provides regional variation across 240+ EU regions.

Authored framework. Read the transparency note.