Producer Price Indices QMI

• Statistical designation: official statistics 
• Survey name: PPI, EPI, IPI
• Data collection: administrative and survey data
• Frequency: monthly
• How compiled: sample-based surveys 
• Geographic coverage: UK
• Related publications: Producer price inflation, UK

This Quality and Methodology Information (QMI) report contains information on the quality characteristics of the data (including the European Statistical System's five dimensions of quality) as well as the methods used to create it.

The information in this report will help you to:

• understand the strengths and limitations of the data
• learn about existing uses and users of the data
• understand the methods used to create the data
• decide suitable uses for the data
• reduce the risk of misusing the data

• The Producer Price Indices (PPIs) are a set of monthly surveys that measure the price changes of goods bought and sold by UK manufacturers.
• The PPIs provide an important measure of inflation.
• The factory gate price (the output price) is the price of goods sold by UK manufacturers; it includes costs such as labour, raw materials and energy as well as interest on loans, site or building maintenance, and rent, but it excludes taxes.
• The input price indices measure change in the prices of materials and fuels bought by UK manufacturers for processing; these include materials used in the final product and by the company in its normal day-to-day running.
• Export Price Indices (EPI) measure the average change in prices of goods sold by UK manufacturers to foreign markets.
• Import Price Indices (IPI) track the average change in prices of goods purchased from abroad by UK manufacturers.
• PPIs classify goods according to the economic activity that generates them, using the European statistical classification of products by activity, 2.1 (CPA 2.1) framework; this structure enables PPIs to accurately track price movements across industries and allows harmonised statistical comparisons.
• To maintain confidentiality, indices that risk disclosing business information are subject to data suppression.
• The last two months of data are provisional, with the last 12 months being subject to revisions.
• PPI data are used to monitor inflation, guide economic policy and analyse industry trends.

Overview

The Producer Price Indices (PPIs) are a collection of price indices that measure inflation in goods bought and sold by UK manufacturers. The indices are split into the PPI, Export Price Indices (EPI) and Import Price Indices (IPI).

The products included in the PPIs are based on the European statistical classification of products by activity (CPA 2.1), which is maintained by Eurostat. The PPIs cover products from CPA 2.1 sections A to E. The prices for goods are then weighted to reflect their relative importance within the index.

There are two main types of PPI:

• gross sector output - these are the factory gate prices of the finished manufactured product sold to a third-party customer (this can include other manufacturers)
• gross sector input - these are the prices that manufacturers pay for materials used in the manufacturing process (these can be provided by any sector or through imports)

Uses and users

The PPIs have a number of users both within and outside of government. Within the Office for National Statistics (ONS), the PPIs are mainly used by the UK National Accounts as a deflator in the Index of Production (IoP) and gross domestic product (GDP). Exports are used to deflate the export component of the IoP as well as the value of exports of manufactured goods recorded in the balance of payments.

Externally, the Bank of England (BoE), HM Treasury (HMT) and business economists at City institutions use the PPIs as a measure of inflation in the economy. The Department for Business and Trade (DBT), HM Revenue and Customs (HMRC) and industrial economists also use PPIs for monitoring price pressures in subsectors of UK industry.

The Ministry of Defence (MoD), private companies and industrial bodies also use the indices as an impartial measure of prices for contractual purposes and for comparing their own patterns of purchases and sales. For example, the British Electrotechnical and Allied Manufacturers Association (BEAMA) and the Building Cost Information Service (BCIS) use PPIs to produce bespoke indices for their members for electrical engineering and construction industries, respectively.

Strengths and limitations

The main strengths of the PPIs include:

• the PPIs have a wide coverage of manufactured goods used in the UK market; PPI covers the prices of products from CPA divisions A01 to E36
• the indices are internationally comparable with any country using the CPA or Central Product Classification (CPC) system
• the indices provide timely monthly measures of inflation in the manufacturing sector; these can give early indications of inflation trends that can impact consumers
• use of rotational sampling for the PPI enables new products and new respondents to be captured

The main limitations of the PPI include:

• to maintain confidentiality, indices that risk disclosing business information are subject to data suppression
• the sampling frame for the PPIs does not cover businesses who manufacture as a secondary activity; the sampling frame covers Standard Industrial Classification (SIC) codes 08 to 33, so any business classified outside of these divisions, even though manufacturing may account for an important part of their income, is not covered by the survey
• as PPIs use survey data, non-response from businesses can affect data quality, requiring imputation methods to estimate missing prices, which may introduce uncertainty or bias into the indices

This section provides a range of information that describes the quality of the output and details any points that should be noted when using the output.

We have developed Guidelines for measuring statistical quality; these are based on the European Statistical System's five dimensions of quality. This report addresses these quality dimensions and other important quality characteristics, which are:

• relevance
• timeliness and punctuality
• coherence and comparability
• accuracy and reliability
• output quality trade-offs
• assessment of user needs and perceptions
• accessibility and clarity

More information is provided about these quality dimensions in upcoming subsections.

Relevance

(The degree to which the statistical outputs meet users' needs.)

Producer Price Indices (PPIs) measure the average change in prices received by UK manufacturers for their goods over time. They are an important economic indicator used to monitor inflationary pressures at the production level and support a wide range of decision-making across government, industry and international organisations.

Important users include government departments (such as HM Treasury and the Bank of England), businesses, trade bodies, researchers and international organisations such as Eurostat and the Organisation for Economic Co-operation and Development (OECD). These users rely on PPIs for policy development, contract pricing, cost forecasting, deflation and international comparisons.

To better meet user needs, the PPIs apply a chain-linking methodology that updates index weights annually, ensuring the data reflects current production patterns and remains relevant in a changing economic landscape. Additionally, the use of the European statistical classification of products by activity (CPA 2.1) classification system aligns the indices with international standards, enhancing consistency and comparability across sectors.

PPIs are produced using the CPA 2.1 classification framework from December 2008, with annual chain-linking being applied to index values from December 2013 onwards. Where available, index back histories have been added with data going back to January 1996. These extended series are created by linking on previously published re-based indices produced using older classification systems. The headline Output PPI (GB7S), series is linked back to January 1957, the headline Input PPI (GHIP) series is linked back to January 1984. 

Accuracy and reliability

(The degree of closeness between an estimate and the true value.)

Accuracy

Estimates from the PPIs are subject to various sources of error. The total error consists of two elements: the sampling error and the non-sampling error.

Sampling error occurs because estimates are based on a sample rather than a census.To minimise sampling errors, the sample allocation is reviewed to maximise coverage with the available resources.

Non-sampling errors are not easy to quantify and include errors of coverage, measurement processing and non-response.

Various procedures are in place to ensure that errors are minimised. Validation checks on data, based on percentage movements from month to month and year to year, are conducted to highlight unusual price changes for products. Disparities in data are investigated by contacting the respondent.

Reliability

Assessing the difference between the first published estimate and the final revised figure provides an indication of reliability. Figures for the latest two months are provisional, and the latest 12 months are subject to revisions because of late and revised respondent data. Office for National Statistics (ONS) guidance and policies on revisions can be found on our Revisions and corrections of errors webpage.

Coherence and comparability

(Coherence is the degree to which data that are derived from different sources or methods, but refer to the same topic, are similar. Comparability is the degree to which data can be compared over time and domain, for example, geographic level.)

Coherence across time series

To ensure effective comparability, it is essential that the PPI reflects the price movements of products of fixed quality. When the specification of a product changes, only the "pure" price change is recorded for PPI purposes, and this generally relies on advice from respondents.

Coherence with international PPIs

While the coverage of various sectors may not be equal in all countries, the use of the European CPA ensures that all products are measured in a way that allows comparability across Europe. This means that the PPIs are broadly comparable internationally. For more information on how the CPA 2.1 compares with other classifications, see our Standard and other national and international classifications.

Accessibility and clarity

(Accessibility is the ease with which users can access the data, also reflecting the format in which the data are available and the availability of supporting information. Clarity refers to the quality and sufficiency of the release details, illustrations and accompanying advice.)

Our recommended format for accessible content is a combination of HTML web pages for narrative, charts and graphs, with data being provided in usable formats such as CSV and Excel. Our website also offers users the option to download the narrative in PDF format. In some instances, other software may be used or may be available on request.

Available formats for content published on our website but not produced by us, or referenced on our website but stored elsewhere, may vary. For further information, please refer to the contact details at the beginning of this report.

For information regarding conditions of access to data, please refer to:

• terms and conditions (for data on the website)
• accessibility

Timeliness and punctuality

(Timeliness refers to the lapse of time between publication and the period to which the data refer. Punctuality refers to the gap between planned and actual publication dates.)

The PPIs are published monthly with approximately two to three weeks between publication and the reference month to which the PPI data refer.

For more details on related releases, our release calendar provides advance notice of release dates. If there are any changes to the pre-announced release schedule, public attention will be drawn to the change and the reasons for the change will be explained fully at the same time, as set out in the Code of Practice for Statistics.

Why you can trust our data

The ONS is the UK's largest independent producer of statistics and its national statistical institute. The data policies and information charter detail how data are collected, secured and used in the publication of statistics. We treat the data that we hold with respect, keeping them secure and confidential, and we use statistical methods that are professional, ethical and transparent.

How we collect the data, main data sources and accuracy

There are two main types of data used in the calculation of the Producer Price Indices (PPIs). These are the prices quoted by manufacturers for their products and the sales values that are used to provide a weight for the prices.

Price data collection

The survey price data used to compile PPI come from a statutory monthly survey. Businesses included in this survey are required to provide price data within 10 days of the request. However, it may take several months to fully validate all data returns, as well as contacting businesses that have not responded. Therefore, figures for the latest two months are considered provisional, and figures for the latest 12 months are all subject to revisions resulting from late or revised data.

All businesses included in the survey are asked to provide the price data for transactions that occur on or near to the first of each month. Therefore, price changes that occur part of the way through the month will always be reflected in the following month's index.

All index numbers exclude Value Added Tax (VAT). Although the headline rate excludes excise duty on cigarettes, manufactured tobacco, alcoholic beverages and petroleum products, prices inclusive of excise duty are also collected from businesses. All indices that exclude or include excise duty are labelled accordingly where this is relevant. The same is also true of indices affected by the Aggregates Levy on quarried minerals or the Climate Change Levy on coal, electricity and gas.

Administrative data

Most of the price data used to compile PPI come from the statutory monthly surveys collected by the Office for National Statistics (ONS). However, some PPI are supplemented by third-party administrative data, which are used to calculate index values with the same methodology as applied to survey prices. These sources are:

• International Coffee Organization
• The National Cotton Council of America
• International Tea Committee
• Forestry Commission
• Water Regulation Services Authority
• Metal Bulletin
• Industrial minerals
• Marine Management Organisation
• Department for Environment, Food and Rural Affairs
• Department for Energy Security and Net Zero
• Bloomberg

The International Coffee Organization is the source of the monthly average of daily price data for Brazilian and other natural Arabica beans, which is used to compile the Import Price Index (IPI) "Imports of beverage crops" (A0127).

The National Cotton Council of America (NCCA) is the source of price data for upland cottons used to produce the IPI "Imports of fibre crops" (A0116). This IPI is compiled using an existing index provided by the NCCA. Their index is calculated as an average of the five cheapest price quotes from a selection of internationally traded upland cottons. These price quotes primarily derive from Asia.

The International Tea Committee (ITC) is the source of import data for various teas such as Kolkata, Columbo and Kochi, which are used to produce the IPI "Imports of processed tea and coffee" (C1083). This index, based on the monthly average price calculated from weekly auction prices, uses data sourced from central brokers at various tea auctions. The ITC data are considered the industry's most comprehensive.

The Forestry Commission is the source of domestic price data for the Producer Price Inflation (PPI) index "Support services to forestry for domestic market" (A0240). This index tracks changes in the average price per cubic metre of softwood, including bark, sold by Forestry England, Forestry and Land Scotland, and Natural Resources Wales, with harvesting done by the purchaser.

The Water Regulation Services Authority (Ofwat) is the source of domestic data for the PPI index "Natural water; water treatment and supply services for domestic market" (E3600). The index uses water and sewerage revenue, property counts, and average bills from 12 regional UK providers to calculate a price per cubic metre each April, which remains constant for 12 months.

The Metal Bulletin is the source of import data used within a number of IPI indices, which are compiled by calculating an average price for the month from a number of spot prices taken throughout the month, for a range of non-ferrous metals. These indices are:

• Imports of other non-ferrous metal ores and concentrates (B0729)
• Imports of other inorganic basic chemicals (C2013)
• Imports of basic iron and steel and of ferro-alloys (C2410)
• Imports of cold drawn wire (C2434)
• Imports of precious metals (C2441)
• Imports of lead, zinc and tin (C2443)
• Imports of other non-ferrous metal (C2445) 

The Fastmarkets website is the source of import data on industrial minerals that are used to produce multiple IPI indices, which are compiled using monthly price data gathered from the supplier's website for minerals such as bauxite, rutile, potash and feldspar. These indices are:

• Imports of other non-ferrous metal ores and concentrates (B0729)
• Imports of chemical and fertiliser minerals (B0891)
• Imports of other mining and quarrying products not elsewhere classified (B0899)

The Marine Management Organisation (MMO) provides UK domestic price data for the main economic fishing species. They calculate a monthly price based on the live weight and value at first point of sale. The price data received are used to calculate index values for "Fish and other fishing products; aquaculture products; and support services to fishing for domestic market" (A0300).

The Department for Environment, Food and Rural Affairs (Defra) is the source of domestic price data for various commodities such as cereals, livestock, fruit, vegetables, milk, eggs and more. These data are collected monthly and are used to produce various PPI indices:

• Cereals (except rice), leguminous crops and oil seeds for domestic market (A0111)
• Vegetables and melons, roots and tubers for domestic market (A0113)
• Pome fruits and stone fruits for domestic market (A0124)
• Other tree and bush fruits and nuts for domestic market (A0125)
• Dairy cattle, live and raw milk from dairy cattle for domestic market (A0141)
• Sheep and goats, live; raw milk and shorn wool from sheep and goats for domestic market (A0145)
• Swine, live for domestic market (A0146)
• Poultry, live and eggs for domestic market (A0147)

All price data provided by Defra are collected by market inspectors although they are supplemented with data from the Agriculture and Horticulture Development Board (AHDB), other government sources and trade bodies.

The Department for Energy Security and Net Zero (DESNZ) is the source of domestic and imported energy and fuel-related data for several PPI indices:

• Hard coal excluding Climate Change Levy for domestic market (B0510)
• Imports of hard coal (B0510)
• Crude petroleum for domestic market (B0610)
• Imports of crude petroleum (B0610)
• Refined petroleum products for domestic market (C1920)
• Electricity for domestic market (D3511)
• Manufactured gas for domestic market (D3521)

The oil data are collected from five crude oil refining businesses by DESNZ. As DESNZ is not always in receipt of a full panel of responses, the average price is calculated from the responses provided each month. This figure is often revised as new data come in after one to two months. 

The gas data we receive are an average price for the month from a panel of suppliers relating to the supply of gas to end-users. The data include a mixture of fixed price contracts and flexible price contracts compiled by DESNZ.

The electricity data are also collected by DESNZ from a panel of energy companies who provide prices paid by users and therefore reflect a mixture of fixed price contracts and flexible price contracts.

Both gas and electricity include provision to industrial and commercial users, which differs from the data provided for the purposes of the Consumer Prices Index (CPI).

The coal data are now produced by DESNZ using the Quarterly Fuels Inquiry from an ONS source. DESNZ use these data to produce monthly estimates from the quarterly returns using a rolling three-month average. 

The petrol and diesel data are sourced from pump prices from a range of business types. 

The diesel data are sourced from the DESNZ oil derivatives survey while the unleaded petrol data are based on weekly petrol data with the necessary tax elements removed.

Bloomberg track the prices of important commodities traded globally, such as agricultural commodities, and are used to supplement several IPI indices. These indices are:

• Imports of cereals (except rice), leguminous crops and oil seeds (A0111)

• Imports of other tree and bush fruits and nuts (A0125)

• Imports of oleaginous fruits (A0126)

• Imports of other perennial crops (A0129)

• Imports of imported wild growing non-wood products (A0230)

• Imports of other processed and preserved fruit and vegetables (C1039)

• Imports of oils and fats (C1041)

Sales data collection

Sales data are gathered from several different organisations and surveys to ensure full coverage and representativeness of all product groups. These are all price updated before being used as weights in the PPIs.

UK manufacturers' sales by product (ProdCom)

Most sales values for UK manufacturing are collected by the UK manufacturers' sales by product (ProdCom) survey. ProdCom estimates the total sales of a product, which include export sales. Export sales values are removed from the reported ProdCom sales to estimate sales from UK manufacturers to the UK domestic market only. The source for the export sales values is HM Revenue and Customs (HMRC) trade data. The sales data excluding exports are then price updated as part of the chain-linking process to serve as weights.

Department for Energy Security and Net Zero (DESNZ)

The ProdCom survey for annual UK manufacturing sales values does not cover crude oil, petroleum products, coal, gas and electricity industries. These industries' annual sales values are instead sourced from the DESNZ. Export sales are removed using the same method applied for ProdCom sales. The only exception is crude oil, which has export sales removed based on DESNZ source data. The sales data excluding exports are then price updated as part of the chain-linking process to serve as weights.

International Steel Statistics Bureau (ISSB)

The ProdCom survey only offers partial annual sales values coverage of the UK steel industry in the PPI gross sector output (GSO); the remainder is covered by surveys conducted by the International Steel Statistics Bureau (ISSB). Export sales values are removed using the same method conducted for ProdCom before being price updated as part of the annual chain-linking process.

Annual Business Survey (ABS)

The Annual Business Survey (ABS) is a sample survey that collects annual sales data for UK businesses across the whole economy, including businesses within the manufacturing sector, and was also used during the last rebasing exercise. ABS data are used for calculating annual sales values that include duty, annual sales values for the water and forestry support service indices, and annual sales values for products that are not covered by other sources. Exports are removed using the same approach as ProdCom before being price updated as part of the annual chain-linking process.

Department for Environment, Food and Rural Affairs (Defra) and Marine Management Organisation (MMO)

The Department for Environment, Food and Rural Affairs (Defra) and Marine Management Organisation (MMO) provide annual sales values for the home-produced food indices in the PPI. Unlike sales values provided by other sources, export sales values are not removed, as most raw foods are not exported without some form of operation or preservative treatment, and therefore become a UK manufactured food product.

HM Revenue and Customs (HMRC)

HM Revenue and Customs (HMRC) supply the Office for National Statistics (ONS) with annual export and import sales value data for use as weights in the Import Price Index (IPI) and Export Price Index (EPI). The coverage is split between trade to or from an EU and non-EU country, which correlates with the index structure in the IPI and EPI.

Main PPI methodologies

Our aim is to construct indices that track producer price movements at several different levels of detail in the manufacturing sectors.

We collect price data for many UK manufactured products in the form of a basket of goods. These are weighted together to form indices that measure the price behaviour of broad groupings, up to the headline Producer Price Index (PPI). These measure the price movements in the manufacturing sector.

We construct weights using sales data from ONS surveys and administrative data for specific periods. The sales data represent the turnover generated by UK companies selling each manufactured product to the UK market. For the Import Price Index (IPI) and Export Price Index (EPI), sales of manufactured products are sourced from HM Revenue and Customs' (HMRC's) records.

The weight for any index into a higher aggregate is equal to the proportion of its products' sales within the total sales for the aggregate. The higher the sales value for an index, the higher its weight into the aggregated price index.

Index methods

The PPIs measure the change over time in the selling prices received by producers for their output. International best practice is to calculate PPIs as an annually chain-linked Laspeyres price index. The Laspeyres formula can be expressed:

where:

• R_bti is the price relative for product i, comparing current period t with base period b

• w_bi is the weight for product i in base period b (the weight is the proportion of base period turnover attributable to the product)

• the summation is over all products being aggregated

To implement chain-linking, a series of Laspeyres indices is calculated, each using a different base year:

where:

• b_j represents each base year (for example, 2015, 2016, 2017…)

Each index series is then linked to the previous one through scaling, resulting in a single continuous chain-linked series. This method introduces a new base year annually, allowing the index to reflect more current economic structures and price patterns.

Each index series is then linked to the previous one through scaling, resulting in a single continuous chain-linked series. This method introduces a new base year annually, allowing the index to reflect more current economic structures and price patterns.

Index weights

The primary aim of index weights in the PPI is to ensure the index accurately reflects the relative economic importance of different products within the economy. Weights are based on the value of sales, allowing the PPI to represent average price changes in a way that mirrors real-world production patterns.

The weight, _wbjk, of any index k in aggregate h with base year b_j is:

where:

• _xbjk is the sales relating to index k in base period b_j
  
• k’ represents the indices contributing to aggregate h

Export removal

The purpose of PPI weights is to represent domestic production activity, which means export transactions need to be removed from the ProdCom source data when calculating weights for domestic PPIs. To address this, HMRC sales data are used to estimate the proportion of sales attributed to exports. These export figures are then removed from the ProdCom data to derive an estimate of sales from UK manufacturers to the domestic market only.

Price uprating

When sales data for a base year are not directly available, price uprating is applied to sales figures from an earlier year to estimate their value in the base year. To align these figures appropriately, a relevant price index is used to calculate the rate of inflation between the annual average of the year that the sales data originate from and the annual average of the base year.

For instance, to produce weights for the 2025 PPI, sales data sourced from ProdCom for the year 2023 are price uprated to estimate their value in 2024. These uprated 2024 sales figures are then used as weights for PPIs during the 2025 calendar year.

Within the PPI framework, price uprating factors are calculated at the (CPA 2.1) four-digit level, while for the EPI and IPI, they are calculated at the (CPA 2.1) two-digit level.

How we analyse and interpret the data

To ensure that the PPI results are accurate, quality assurance checks and analysis are carried out on the data received. Once the data have been validated, they can be accepted into our database and processed through our calculation systems and pipelines. Following processing and calculation, further quality assurance and analysis are done on the results, and any unusual behaviour in the results identified is investigated before publication.

We go through a series of analysis tasks once the preliminary PPI results have been calculated, which help us to understand and interpret the results. This includes (but is not limited to):

• calculation of growth rates to see how price levels have changed or moved in different product groups
• calculation of contributions to understand the relative impact that price changes in particular products or product groups are having on an index
• investigating indices with particularly large changes in price level, to understand what is causing those movements and check that they have been correctly validated
• check revisions to results for in-spectrum periods (in-spectrum periods are those which are still open to revisions in the current period, under our revisions policy)

Once analysis is complete, we go through an internal assurance process where we present our initial results to internal groups, panels and directors. These meetings provide additional scrutiny to the results, which can draw out new angles for further investigation and analysis, helping to build our interpretation before completion of the bulletin and publication.

How we quality assure and validate the data

Quality assurance takes place at various stages in the production process, but before the price data can be passed through the system they go through a validation process to ensure only appropriate data are being taken on for use in our calculations.

Any products showing price movements exceeding a certain threshold are flagged for validation. At this stage the data provided by the respondent are reviewed and the respondent may be contacted to verify the price movement and provide further explanation of any notes provided in the survey response.

The thresholds vary for different product groups, for example, more volatile product groups (such as foods) will have different thresholds to products subject to tighter restrictions (such as alcohol and tobacco). These thresholds are also reviewed regularly and are subject to change.

Changes to product specifications and quality

Quality improvements to products or changes to the specification of a product as well as alterations to the terms of sale or units of sale can all influence changes in the price of a product. However, only the actual price change is reflected in the PPI. So, if a product changes in specification and the price changes as a result, the price change resulting from the specification change is masked.

Common specification changes we adjust for in PPI include:

• replacement of an old product model with a new model resulting in a price change
• a cosmetic change to a product resulting in a price change

How we disseminate the data

The PPI are published alongside other price indices produced by the ONS, the Consumer Prices Index including owner occupiers' housing costs (CPIH), Retail Prices Index (RPI) and the UK House Price Index (HPI) on a monthly basis. The Services Producer Price Indices (SPPI) are published alongside these releases on a quarterly basis.

Aggregate-level PPIs are published in our monthly statistical bulletin for producer price inflation, with PPIs for lower-level product aggregates included in the PPI dataset and PPI time series accompanying the bulletin.

Future publication dates can be found in our release calendar.