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Taking the guesswork out of ONS data

The possibility of overcounting infrastructure output by the ONS could have some serious knock-on effects for the industry.

The ONS has said it is “possible” its monthly output data could include the total cost of some infrastructure projects, rather than just construction costs.

The first thing a contractor might think is, ‘So what?’

Although it might seem like a simple issue of overcounting, there are a number of important issues that could have ramifications for the construction industry.

Why care?

The way the ONS gathers its data is laid out in its official methodology. New orders data, which feeds into the ONS’s output model, is sourced from provider Barbour ABI. This data, together with responses to the ONS’s business survey, is then used to model output.

But if the entire cost of a project is included in the new orders and output data, it can dramatically alter the figures.

“If the value of electricity output is overestimated, then rail, roads, or water could well be underestimated”

Take the example of onshore wind farm projects. Estimates of construction costs for onshore wind from forecasters, as well as from the trade body RenewableUK, range from 10 per cent of the total capital expenditure, to 20 per cent of the value, to £1.32m of construction per MW.

If applying the latter estimate, a 228 MW onshore windfarm such as the Pen y Cymoedd project in Wales would be worth £300.9m in construction value – despite the fact that the total capital expenditure of the project is listed at £376.1m in the National Infrastructure Pipeline.

However, if you applied a 10 per cent construction cost it would be worth £37.6m, making the project much less of a windfall to the contractor that might win the work.

The ONS has admitted it is possible that it’s including the full value of the project, rather than just these construction costs, which could inflate what a wind farm is worth in the data by as much as 10 times.

Major consequences

This creates several problems. One senior economist I spoke to points out that if one sector’s orders are measured incorrectly, its output is boosted and all other sector output values are reduced as a result, due to the way the ONS’s data modelling works.

It then has a knock-on effect – if the value of electricity output is overestimated, then rail, roads, or water could well be underestimated.

“For contractors, a sector might not be worth as much as they think, which muddies the waters for investment decisions”

And if the ONS data for just one part of the infrastructure sector is overestimated, it means other sectors could be reported inaccurately.

The ONS data is used by key government stakeholders, particularly the Treasury and the Department for Business, Innovation and Skills, to determine the size of the industry and consequently, how the industry is performing – which doubtless plays heavily into government policy.

Question marks

For contractors, what might seem like a strongly performing sector might not be worth as much as they think, which muddies the waters for investment decisions. If you want to invest in winning a pipeline of work that the ONS says is worth £400m, but is in fact only worth £40m, where does that leave your business?

What’s more, the way the ONS classifies companies means that works on a project such as a wind farm could be recorded differently, or not recorded at all.

For example, if Balfour Beatty, classed as a construction company, was to undertake a wind farm project, this would be included in the output survey. But if Bechtel, an engineering firm, was to undertake the exact same work, it would not be included.

It is therefore hard to say with certainty whether electricity and energy output values issued by the ONS are reliable. What is clear is that a way needs to be found to accurately estimate construction costs for electricity projects, and feed this into the ONS’s model.

Whether changes to the methodology need to be applied at source – that is, Barbour ABI’s new orders data – or by the ONS, a solution is needed to help the industry accurately estimate the true size of the sector.

 

 

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