IESET.
Hypotheses·housing·building_height_limit_downtown_productivity

Strict building-height restrictions near transit nodes predict lower agglomeration productivity and higher office or housing costs.

PARTIALengine/runs/building_height_limit_downtown_productivity

PARTIAL — coef=-6244, p=0.14 (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 housing rule being tested make homes easier to build, rent, or afford, or does it quietly reduce supply and push costs elsewhere?

plain answer

The evidence is suggestive but not decisive. coef=-6244, p=0.14 (above α=0.1); direction inconclusive

why it matters

Housing policy affects rents, mobility, household budgets, and construction. The test looks for measurable effects rather than relying on slogans.

how the test works

It compares 30 country or place units from 1970 to 2023, using a panel fe design, with fixed effects for country and year.

what was measured
What changed
  • Policy or institution proxy
What we checked
  • Primary sectoral outcome
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/building_height_limit_downtown_productivity
1007550250197019972023USAGBRCANAUSNZLDEUFRA
illustrative sketch · run pending
No coefficients yet. When the model fires, this chart will show primary_sectoral_outcome across 30 sampled countries over 1970–2023.
The shapes above are stylised — none of the lines are real data.
Placeholder for building_height_limit_downtown_productivity. Published chart will be generated from engine/runs/building_height_limit_downtown_productivity/chart_data.json.

Pre-registration

registration ordering unverified
first-spec commit 4c8ce8e · 2026-07-18T22:11:21Z
run generated · 2026-06-29T17:53:12Z
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.

Strict building-height restrictions near transit nodes predict lower agglomeration productivity and higher office or housing costs.

Falsification criterion — what would disprove this

set before the run · honoured after

This hypothesis is considered falsified if:

SUPPORTED if the treatment coefficient has the predicted sign at p<0.10. REFUTED if the opposite sign is significant at p<0.10. Otherwise PARTIAL.

formal test & threshold
test:      panel_fe_building_height_limit_downtown_productivity
threshold: p<0.10 with pre-registered sign

Method

Template
panel_fe
Fixed effects
country, year
Clustering
country
Sample
30 countries · 1970 – 2023
Evidence type
associational

Proxy-first TWFE screen; upgrade to bespoke replication when exact sector datasets are fetched.

Data

VariableSourceTransform
primary_sectoral_outcome
outcome
world_bank_wdi:NY.GDP.PCAP.KDtier 2
level_or_growth_proxy
policy_or_institution_proxy
treatment
constructed:1 for USA from 1910 onward; FRA from 1977 onward; IND from 1990 onwardtier 5
indicator_or_level
log_gdp_pc
control
world_bank_wdi:NY.GDP.PCAP.KDtier 2
log
rule_of_law
control
wgi:RL.ESTtier 4
level

● ready  · ● pending  · ● reconstruct-needed

Detailed result card

Result card — building_height_limit_downtown_productivity

Verdict: PARTIAL — coef=-6244, p=0.14 (above α=0.1); direction inconclusive

Pre-registration

  • Claim: Strict building-height restrictions near transit nodes predict lower agglomeration productivity and higher office or housing costs.
  • Falsification rule: SUPPORTED if the treatment coefficient has the predicted sign at p<0.10. REFUTED if the opposite sign is significant at p<0.10. Otherwise PARTIAL.
  • Falsification test: panel_fe_building_height_limit_downtown_productivity

Estimate

  • Method: linearmodels.PanelOLS
  • Coefficient (treatment): -6244
  • Std error: 4232
  • p-value: 0.14
  • Observations: 1202, countries: 23
  • Within R²: 0.0364
  • Fixed effects: entity=True, time=True
  • Clustering: country

Variables resolved

  • world_bank_wdi:NY.GDP.PCAP.KD → primary_sectoral_outcome (outcome, publisher=world_bank_wdi, n=12104)
  • constructed: 1 for USA from 1910 onward; FRA from 1977 onward; IND from 1990 onward → policy_or_institution_proxy (treatment, publisher=constructed, n=1620)
  • world_bank_wdi:NY.GDP.PCAP.KD → log_gdp_pc (controls, publisher=world_bank_wdi, n=12104)
  • wgi:RL.EST → rule_of_law (controls, publisher=wgi, n=5296)

Generated by scripts/run_panel_fe.py at 2026-06-29T17:53:12+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.