IESET.
Hypotheses·labour·eurostat_power_cost_unemployment_slack_panel

Higher industrial electricity-price growth predicts higher unemployment in European country panels, especially during the post-2021 energy-cost shock window when power-intensive producers faced larger input-cost pressure.

PARTIALengine/runs/eurostat_power_cost_unemployment_slack_panel

PARTIAL — coef=+0.005075, p=0.253 (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

In plain terms, this asks whether industrial power price growth is actually linked to better or worse unemployment rate from 2008 to 2025.

plain answer

The evidence is suggestive but not decisive. coef=+0.005075, p=0.253 (above α=0.1); direction inconclusive

why it matters

Labor-market rules often help some workers while risking job loss or slower hiring for others. This test looks for that tradeoff in observable employment or unemployment data.

how the test works

It compares 31 country or place units from 2008 to 2025, using a panel fe design, with fixed effects for country and year.

what was measured
What changed
  • Industrial power price growth
What we checked
  • Unemployment rate
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/eurostat_power_cost_unemployment_slack_panel
1007550250200820172025AUTBELBGRCHECYPCZEDEU
illustrative sketch · run pending
No coefficients yet. When the model fires, this chart will show unemployment_rate across 31 sampled countries over 2008–2025.
The shapes above are stylised — none of the lines are real data.
Placeholder for eurostat_power_cost_unemployment_slack_panel. Published chart will be generated from engine/runs/eurostat_power_cost_unemployment_slack_panel/chart_data.json.

Pre-registration

pre-registered
first-spec commit e29141a · 2026-05-22T17:36:53Z
run generated · 2026-06-29T17:53:36Z

Higher industrial electricity-price growth predicts higher unemployment in European country panels, especially during the post-2021 energy-cost shock window when power-intensive producers faced larger input-cost pressure.

Falsification criterion — what would disprove this

set before the run · honoured after

This hypothesis is considered falsified if:

SUPPORTED only if industrial_power_price_growth is positive at p<=0.10 with at least 250 observations and 20 countries. REFUTED if it is negative at p<=0.10.

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

Method

Template
panel_fe
Fixed effects
country, year
Clustering
country
Sample
31 countries · 2008 – 2025
Evidence type
associational

Two-way FE screen; a bespoke follow-up should add energy-intensity interactions once Eurostat sector energy-use panels are normalized.

Data

VariableSourceTransform
unemployment_rate
outcome
eurostat:une_rt_atier 1
level
industrial_power_price_growth
treatment
eurostat:nrg_pc_205tier 1
annual_pct_change
real_gdp_growth
control
eurostat:nama_10_gdptier 1
annual_pct_change

● ready  · ● pending  · ● reconstruct-needed

Detailed result card

Result card — eurostat_power_cost_unemployment_slack_panel

Verdict: PARTIAL — coef=+0.005075, p=0.253 (above α=0.1); direction inconclusive

Pre-registration

  • Claim: Higher industrial electricity-price growth predicts higher unemployment in European country panels, especially during the post-2021 energy-cost shock window when power-intensive producers faced larger input-cost pressure.
  • Falsification rule: SUPPORTED only if industrial_power_price_growth is positive at p<=0.10 with at least 250 observations and 20 countries. REFUTED if it is negative at p<=0.10.
  • Falsification test: panel_fe_eurostat_power_cost_unemployment_slack_panel

Estimate

  • Method: linearmodels.PanelOLS
  • Coefficient (treatment): +0.005075
  • Std error: 0.00443
  • p-value: 0.253
  • Observations: 485, countries: 29
  • Within R²: 0.0525
  • Fixed effects: entity=True, time=True
  • Clustering: country

Variables resolved

  • eurostat:une_rt_a → unemployment_rate (outcome, publisher=eurostat, n=634)
  • eurostat:nrg_pc_205 → industrial_power_price_growth (treatment, publisher=eurostat, n=709)
  • eurostat:nama_10_gdp → real_gdp_growth (controls, publisher=eurostat, n=1424)

Generated by scripts/run_panel_fe.py at 2026-06-29T17:53:36+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

This is designed as a clean Eurostat-only companion to the manufacturing real GVA power-cost test.

Authored framework. Read the transparency note.