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UK inflation number for April too high after data blunder

June 5, 2025
in Business
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UK inflation number for April too high after data blunder
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The UK’s statistics agency has said the headline inflation rate for April was too high after it discovered it had been given incorrect road tax data by the Department for Transport.

The Office for National Statistics (ONS) said the pace of general price rises should have been 3.4%, instead of the 3.5% it had reported.

It comes as the ONS faces a crisis of confidence in its work after concerns about the quality of its data.

These concerns make it more difficult for the government and companies to make fully informed decisions about the UK economy.

The ONS said it had spotted an error in Vehicle Excise Duty data. It found that the number of vehicles people were paying road tax on in the first year of registration was too high in the data that was given.

The statistics agency said it would not be amending April’s inflation figure, in line with a policy that it only carries out revisions in exceptional circumstances.

But it did say it would be reviewing how it checks the quality of data from outside the agency “in light of this issue”.

Both the Consumer Prices Index (CPI) and Retail Prices Index (RPI) inflation figures were 0.1 of a percentage point too high for the year to April.

Last month, the ONS’s former head Sir Ian Diamond resigned with immediate effect due to health reasons.

In April, the UK’s Office for Statistics Regulation had set out its concerns about the quality of the data provided by the ONS itself.

These concerns focused on, but were not limited to, widely-recognised problems with the Labour Force Survey which is used to measure the unemployment rate in the UK.

Since the pandemic, statistics agencies around the world have struggled to get good enough response rates to ensure their data is of the quality they would like.

The regulator said it would like more assurance that the ONS had sufficient steps in place to regularly review and improve sample design and representativeness, tackling bias, survey methodology, and imputation.

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