We use only the cookies needed to run the site and keep you signed in. No analytics, no advertising. Your answer covers anything optional we add later.

Cookie statement
IPMERC Futures

How a cell is computed.

version 2026-08-1

Everything below is read from the code that scores the cells. Nothing is retyped, so this page cannot drift from what is running.

The formula

Every signal gets a weight, and the score is the weighted mean of the directions. Direction is +1 when hiring gets harder and -1 when it gets easier. Magnitude runs from 0 to 1 and comes off a published ladder rather than out of a judgement.

weight  =  source × age × distance × saturation × sample
score   =  Σ (weight × direction × magnitude)  /  Σ weight

The score is computed twice, once over the movements and once over the levels. Those answer different questions. Construction went from 7.5% to 7.4%, so the movement is nil, while 7.4% is nearly three times the European rate for the same sector. Only together are they true.

What a source weighs

European statisticsHarmonised, machine readable, and anyone can pull the same figure again.1.00
National statisticsSame, for the national offices.1.00
InstitutesMethod published, but not always re-pullable from an open table.0.80
Sector programmesDeep on one sector and narrow beyond it, with definitions that vary.0.70
Partner agency dataThe most specific data we hold and the hardest for an outsider to check. Discounted for that reason, not for quality.0.60
Market and industryTimely, often without a published method or reuse licence.0.50

Sources in use: Eurostat, CBS, UWV, DNB, ROA, CPB, SCP, ACM, Algemene Rekenkamer, EIB, Netbeheer Nederland, AZW, ABF Research, IPMERC partner data, ING, Indeed Hiring Lab.

How fast evidence ages

Weight halves after a fixed number of quarters, counted from the end of the reference period. A vacancy figure and a demographic projection do not age at the same speed, so each has its own half-life.

Demandvacancies, vacancy rate, job advertisements, hiring intentions6 quarters
Supplylabour force, graduates, inflow, slack, unused part-time hours6 quarters
Frictionfill rate, unfilled share, time to hire, applications per vacancy6 quarters
Costsalary medians, labour cost index, negotiated wage growth6 quarters
Structurereplacement demand, age profile, demographic and capacity projections20 quarters

This is why the outlook moves when nothing is published. Evidence that fades can push a cell below the floor, at which point it goes back to reading not enough evidence.

Distance, and why sector wins

Measured on this region and this job family1.00
This region, borrowed from a wider job family0.40
This job family, borrowed from a wider region0.40
Borrowed on both0.15
A neighbouring region or job family0.00

A German figure never counts toward a Dutch cell. And a borrowed figure counts toward the weight but never decides the direction while the cell has a figure of its own. Without that rule the national vacancy rate outvoted the construction rate, and the tightest market in the country came out as easing.

When a direction becomes a claim

Below 0.15, the cell reads flat
At 0.45 or above, it reads sharply
A level of 0.35 or more counts as a tight base
When the smaller side holds 30% of the weight or more, the reading is divergent and no net direction is shown

The dead band is there so a near-zero score is never rounded into a claim. A headline also comes only from friction and demand. Knowing what labour costs says nothing about whether you can hire.

The ladders

A ladder turns a measured difference into a magnitude between 0 and 1, interpolated straight between the points below. This is the weakest link in the whole system, so it is published: anyone who disagrees can argue with a breakpoint instead of with an opinion.

vacancy rate, percentage points

0 = 0 0.25 = 0.1 0.5 = 0.25 1 = 0.4 2 = 0.7 3 = 1

vacancy rate, ratio to benchmark

1 = 0 1.2 = 0.2 1.5 = 0.5 2 = 0.75 2.5 = 1

share, percentage points

0 = 0 2 = 0.1 5 = 0.25 10 = 0.5 20 = 0.8 30 = 1

share, ratio to benchmark

1 = 0 1.15 = 0.15 1.3 = 0.35 1.75 = 0.6 2.3 = 0.8 3 = 1

index, percent change

0 = 0 5 = 0.2 10 = 0.4 20 = 0.7 30 = 1

salary median, percent change

0 = 0 3 = 0.2 5 = 0.35 10 = 0.6 20 = 0.85 30 = 1

required headcount, share of the relevant workforce

0 = 0 0.02 = 0.2 0.05 = 0.45 0.1 = 0.7 0.2 = 1

share of the prior trend that disappears

0 = 0 0.25 = 0.3 0.5 = 0.55 0.75 = 0.8 1 = 1

people required, absolute

0 = 0 5000 = 0.25 25000 = 0.5 75000 = 0.75 150000 = 1

share of firms reporting, no published benchmark

0 = 0 0.1 = 0.15 0.25 = 0.35 0.5 = 0.6 0.75 = 0.85 1 = 1

What this is not

Not a prediction. A cell says what the published evidence adds up to right now, and nothing about next year. Not a model that learns on its own: every number traces back through a signal to a paper, and through that paper to a primary source.

Signals are written by hand by whoever read the source, and nothing reaches a cell before a person has accepted it.

Back to the outlook

Every source behind this research