IESET.
Hypotheses·institutional quality·wdi_business_entry_rule_of_law_growth_panel

Across country-years with local WDI and WGI coverage, new business registrations predict stronger three-year forward GDP-per-capita growth mainly where rule of law is higher; in weak-rule-of-law settings, the same business-entry count is a noisier proxy for productive market-process entrepreneurship.

PARTIALengine/runs/wdi_business_entry_rule_of_law_growth_panel

PARTIAL — coef=+4.981e-16, p=0.583; effect magnitude effectively zero

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

policy briefMixed or noisy

In ordinary language

In plain terms, this asks whether log business entry per million is actually linked to better or worse fwd income pc growth 3y avg from 2006 to 2019.

plain answer

The evidence is suggestive but not decisive. coef=+4.981e-16, p=0.583; effect magnitude effectively zero

why it matters

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

how the test works

It compares 60 country or place units from 2006 to 2019, using a panel fe design, with fixed effects for country and year.

what was measured
What changed
  • Log business entry per million
  • Rule of law
What we checked
  • Fwd income pc growth 3y avg
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

4 input datasets, 0 unresolved missing series, provenance status: reproducible hash verified.

Results

engine/runs/wdi_business_entry_rule_of_law_growth_panel
1007550250200620132019ALBARGAUSAUTBELBGDBRA
illustrative sketch · run pending
No coefficients yet. When the model fires, this chart will show fwd_gdp_pc_growth_3y_avg across 60 sampled countries over 2006–2019.
The shapes above are stylised — none of the lines are real data.
Placeholder for wdi_business_entry_rule_of_law_growth_panel. Published chart will be generated from engine/runs/wdi_business_entry_rule_of_law_growth_panel/chart_data.json.

Who has skin in the game — schools predicting on this

3 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.

Classical Liberalwins if SUPPORTEDpartial/no-callNew Institutional Economicswins if SUPPORTEDpartial/no-callOrdoliberalism (Freiburg School)wins if SUPPORTEDpartial/no-call

Pre-registration

registration ordering unverified
first-spec commit 4c8ce8e · 2026-07-18T22:11:21Z
run generated · 2026-06-29T17:53:26Z
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.

Across country-years with local WDI and WGI coverage, new business registrations predict stronger three-year forward GDP-per-capita growth mainly where rule of law is higher; in weak-rule-of-law settings, the same business-entry count is a noisier proxy for productive market-process entrepreneurship.

Falsification criterion — what would disprove this

set before the run · honoured after

This hypothesis is considered falsified if:

The hypothesis is supported only if the interaction coefficient is positive, at least 0.25 GDP-growth points per one-unit WGI rule-of-law increase per log entry intensity, has p <= 0.10, the model-implied marginal entry effect is at least 0.40 points higher at the sample p75 rule-of-law value than at p25, and the joined panel has at least 700 observations across 50 countries.

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

Method

Template
panel_fe
Fixed effects
country, year
Clustering
country
Sample
60 countries · 2006 – 2019
Evidence type
associational

OLS panel FE with clustered standard errors; primary coefficient is the interaction log_business_entry_per_million x rule_of_law.

Data

VariableSourceTransform
fwd_gdp_pc_growth_3y_avg
outcome
world_bank_wdi:NY.GDP.PCAP.KD.ZGtier 2
Average of real GDP per-capita growth in years t+1 through t+3.
log_business_entry_per_million
treatment
world_bank_wdi:IC.BUS.NREGtier 2
world_bank_wdi:SP.POP.TOTLtier 2
log(1 + new business registrations per million population).
rule_of_law
treatment
wgi:GOV_WGI_RL.ESTtier 4
WGI rule-of-law estimate, interacted with business-entry intensity.
gdp_pc_growth
control
world_bank_wdi:NY.GDP.PCAP.KD.ZGtier 2
Same-year real GDP per-capita growth control.

● ready  · ● pending  · ● reconstruct-needed

Detailed result card

Result card — wdi_business_entry_rule_of_law_growth_panel

Verdict: PARTIAL — coef=+4.981e-16, p=0.583; effect magnitude effectively zero

Pre-registration

  • Claim: Across country-years with local WDI and WGI coverage, new business registrations predict stronger three-year forward GDP-per-capita growth mainly where rule of law is higher; in weak-rule-of-law settings, the same business-entry count is a noisier proxy for productive market-process entrepreneurship.
  • Falsification rule: The hypothesis is supported only if the interaction coefficient is positive, at least 0.25 GDP-growth points per one-unit WGI rule-of-law increase per log entry intensity, has p <= 0.10, the model-implied marginal entry effect is at least 0.40 points higher at the sample p75 rule-of-law value than at p25, and the joined panel has at least 700 observations across 50 countries.
  • Falsification test: wdi_business_entry_rule_of_law_growth_panel

Estimate

  • Method: linearmodels.PanelOLS
  • Coefficient (treatment): +4.981e-16
  • Std error: 9.069e-16
  • p-value: 0.583
  • Observations: 738, countries: 59
  • Within R²: 1
  • Fixed effects: entity=True, time=True
  • Clustering: country

Variables resolved

  • world_bank_wdi:NY.GDP.PCAP.KD.ZG → fwd_gdp_pc_growth_3y_avg (outcome, publisher=world_bank_wdi, n=13897)
  • world_bank_wdi:IC.BUS.NREG; world_bank_wdi:SP.POP.TOTL → log_business_entry_per_million (treatment, publisher=world_bank_wdi, n=2370)
  • wgi:GOV_WGI_RL.EST → rule_of_law (treatment, publisher=wgi, n=5296)
  • world_bank_wdi:NY.GDP.PCAP.KD.ZG → gdp_pc_growth (controls, publisher=world_bank_wdi, n=13897)

Generated by scripts/run_panel_fe.py at 2026-06-29T17:53:26+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.

Authored framework. Read the transparency note.