1. Overview of real-time indicators data

Since the beginning of the coronavirus (COVID-19) pandemic, we have been providing timely indicators of the effect of the disease on the UK economy and society in our Economic activity and social change in the UK, real-time indicators.

These statistics have been produced quickly in response to developing world events. The Office for Statistics Regulation, on behalf of the UK Statistics Authority, has reviewed them against several important aspects of the Code of Practice for Statistics and regards them as consistent with the Code’s pillars of Trustworthiness, Quality and Value.

The real-time indicators are compiled using a variety of different data sources. On a regular basis, the following indicators are included:

  • fortnightly Business Insights and Conditions Survey (BICS), a voluntary business survey to deliver real-time information to help assess issues affecting UK businesses and economy
  • weekly Companies House data for company incorporations, voluntary dissolutions, and compulsory dissolution first gazettes in the UK
  • weekly Energy Performance Certificates (EPCs) data for new and existing dwellings in England and Wales
  • daily indices of footfall in retail destinations at a UK level, using data from Springboard, a provider of data on customer activity
  • weekly experimental online job advert indices covering the UK job market, using data from job advert aggregating website Adzuna
  • weekly data from OpenTable showing how seated diners from online, phone, and walk-in reservations compared with 2019
  • weekly transport use and developing faster indicators of transport activity
  • data provided by Kantar Public, recording item availability of 23 popular products across the UK and English regions
  • weekly and daily shipping data from exactEarth using the UN Global Platform
  • fortnightly Opinions and Lifestyle Survey (OPN), looking at the social impact of the coronavirus
  • daily and weekly changes in gas prices, using the system average price (SAP) from the National Grid
  • experimental daily traffic camera counts data for busyness indices covering the UK
  • weekly transactional data for Pret A Manger, comparing weekly in-store transactions against the average level of the first four weeks of 2020
  • daily CHAPS payments from the Bank of England made by credit and debit card payment processors to around 100 major UK retail corporates
  • daily flights data from EUROCONTROL comprising international arrivals and departures to and from the UK (including crown dependencies) and domestic UK flights, but excluding overflights (flights that pass over UK territory)
  • monthly value-added tax (VAT) diffusion indexes and new VAT reporters using data from HM Revenue and Customs (HMRC) VAT returns
  • daily and monthly counts and average speeds of vehicle flows around English ports
  • weekly advanced notification of potential redundancies from HR1 forms submitted by employers to the Insolvency Service’s Redundancy Payments Service
  • monthly data on sales and jobs in small businesses, taken from Xero, a global cloud-based accounting software platform with 785,000 small business subscribers in the UK.

New experimental data and indices are included as and when new data become available, either on a stand-alone or regular basis as appropriate, with the relevant methodology information listed on this page.

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2. How we measure real-time indicators

This section details how we measure the various real-time indicators included in the bulletin with links to more detailed methodology pages where required. It will be updated regularly as new indicators are added to the bulletin or methodological improvements are made to existing indicators.

Advanced notification of potential redundancies

Advanced notification of potential redundancies is provided to the Insolvency Service's Redundancy Payments Service by employers. Employers provide this information using an HR1 form when they are proposing to dismiss 20 or more employees at a single establishment within a period of 90 days. A separate form is required for each establishment where it is proposed that 20 or more employees will be dismissed, meaning that an employer may be required to file multiple HR1 forms where redundancies are proposed at multiple establishments.

The HR1 form submissions can also include contractual changes, changes to pensions, or employees being transferred to new sites. As we are only concerned with permanent dismissals, an automated cleaning process has been applied to remove cases that are not planned dismissals. Firstly, all cases with less than 20 proposed dismissals are removed as HR1 forms should only be submitted if the employer intends to make 20 or more dismissals. Secondly, we remove any observations containing any of the following words:

  • "pension"
  • "contractual"
  • "terms" and "conditions"
  • "transfer"
  • "move"
  • "TUPE" (Transfer of Undertakings (Protection of Employment))

Insolvency Service publish monthly data on the total number of potential redundancies submitted in HR1 forms. IS data has had limited treatment to remove dismissals and reengagement in comparison with the data published here. We therefore expect our data to be consistently below IS published data but still follow a similar trend.

More information on HR1 forms can be found on GOV.UK

Business Insights and Conditions Survey (BICS)

More quality and methodology information on strengths, limitations, appropriate uses, and how the data were created is available in the Business Insights and Conditions Survey (BICS) QMI, published on 20 May 2021.

The BICS is voluntary, and the results are experimental.

Company incorporations, voluntary dissolutions and compulsory dissolutions

Weekly indicators of company creation and closures are based on data from Companies House, working in collaboration with us. These include weekly series of the number of company incorporations (creations), voluntary dissolutions (one type of closure) and compulsory dissolution first gazettes (a second type of closure) per working day in that week, along with a quarterly back series to Quarter 1 (Jan to Mar) 2019.

More detailed information on the data source, quality and methodology for the weekly indicators of company incorporations, voluntary dissolutions and compulsory dissolution first gazettes is available in Weekly indicators of company creations and closures from Companies House methodology: August 2020.

Energy Performance Certificates

An Energy Performance Certificate (EPC) contains information on the energy efficiency of a property and is a requirement when a property is built, sold or rented in England and Wales. New building(s) or conversions of existing buildings require an EPC once construction has been completed. To note, an EPC is valid for 10 years and can be reused as many times as required during this period. Therefore, where a property holds a valid EPC and is sold or let, it will not require a new EPC and will not appear in the data.

These data are experimental and based on the number of total EPCs lodged on the register held by the Ministry of Housing, Communities and Local Government (MHCLG). In accordance with the regulations, once the assessment is lodged on the register, MHCLG cannot alter data that have been lodged on the register. Please note, the EPC figures used in our faster indicators release will include cancelled or not for issue reports and multiple reports on a single Unique Property Reference Number, although be aware individual buildings may have more than one certificate.

These administrative data are subject to continuing quality investigation and improvement. They have been released because they have been judged to be of immediate value to interested parties and to encourage user feedback. Further technical information on data quality and technical notes are available in the Energy Performance of Buildings Certificates quarterly statistics collection.

A consolidated glossary of all the terms related to Energy Performance of Buildings Certificates is available on GOV.UK.

Footfall

Springboard’s footfall data are captured via a network of automated counters located in high streets, shopping centres and retail parks across the UK. The counter employs technology that identifies humans within a defined “zone” and logs each human as a number in a file. The counters operate 24 hours a day, seven days a week and data are captured continuously. The technology is highly accurate and able to identify individual humans even where there are very large volumes of people.

Types of establishment included and not included

Springboard’s footfall data include footfall within three main types of retail destination – high streets, shopping centres and retail parks. It does not include footfall in leisure and sports venues, conference venues, transport interchanges, motorway service stations, art galleries, museums and historic monuments.

Definitions

Overall footfall

The overall footfall is the sum of the average footfall in each destination type (high streets, retail parks and shopping centres) weighted by their respective footfall volumes.

Shopping centre

A shopping centre is a space, fully owned and managed by a single landlord, which can be fully or partially enclosed or completely open but does not form part of the public highway. A shopping centre is distinguished from a retail park by a smaller unit size.

High street

High street refers to a town centre rather than a shopping centre (defined previously). It is the central part or main business and commercial area of a town, comprising the high street, which is the traditional site for the majority of shops, banks, and other businesses.

Retail park or shopping park

A retail park or shopping park is a space wholly owned and managed by a single landlord, solely comprising retail warehouse units and generally comprising a minimum of 30,000 square feet of retail space. Retail parks have a minority of units occupied by traditional high street non-food retailers, while in a shopping park the majority of units are occupied by high street non-food retailers.

Unit of measurement

Springboard’s footfall data record the volume of activity entering a retail park or shopping centre, or within a town centre. It is not recording footfall into stores, but into retail destinations.

Online job advert estimates

These experimental job advert estimates covering the UK job market are created based upon job adverts provided by Adzuna. These data include information on several million job advert entries live from February 2018 broken down by job category and by region, based on the information included in the job advert.

These estimates are experimental and will be developed over the coming weeks. More information on the methodology used to compile these estimates is available in Using Adzuna data to derive an indicator of weekly vacancies: Experimental Statistics.

OpenTable seated diners

This indicator uses data from OpenTable to compare the volume of seated diners from online, phone, and walk-in reservations in 2021 and 2020, with 2019, for regions with fifty or more restaurants on the OpenTable network.

Further information, including data including the profile of recovery only at restaurants that have chosen to reopen, and how these data are compiled is available at The restaurant industry in recovery.

Road traffic in Great Britain

These statistics on transport use are published weekly.

For each day, the Department for Transport produces statistics on domestic transport:

  • road traffic in Great Britain
  • rail passenger journeys in Great Britain
  • Transport for London (TfL) tube and bus routes
  • bus travel in Great Britain (excluding London)
  • cycling in England

Economic activity and social change in the UK, real-time indicators only publish estimates based on road traffic in Great Britain. The full-time series for these statistics, starting 1 March 2020, is usually published every Wednesday at 9.30am.

The associated methodology notes set out information on the data sources and methodology used to generate these headline measures.

For the charts previously published alongside daily coronavirus press conferences, please see the slides and datasets to accompany coronavirus press conferences.

Sales and Jobs in small businesses

Data on sales and jobs in small businesses are taken from Xero, a global cloud-based accounting software platform with 785,000 small business subscribers in the UK.

Sales are measured based on the face value of invoices issued by firms within each month (including via apps attached to the Xero account). Subscriber base changes are accounted for by measuring sales growth in one specific month using the sample of firms, which also operated in the previous year.

Jobs are measured by the number of unique employees of a business who are issued a payslip in a month. One individual is one “payslip” in a particular month if they work at least one hour in that specific month. The sample of small businesses is restricted based on the employment size band and erroneous payslips or those identified for non-wage purposes are excluded. Percentage change in payslips is calculated using the weighted average of within-firm year-on-year growth in jobs. As such, this accounts for any change in subscriber base and firms that shutdown entirely because of the coronavirus pandemic and this measure will not capture employees who were on furlough for the full month.

This definition of sales and jobs does not align with definitions of official estimates of turnover and employment.

Small businesses are defined by Xero as organisations with fewer than 20 employees.

This series is publicly available through Xero's Small Business Insights programme.

Shelf availability of items from UK shops

These data are provided to the Office for National Statistics (ONS) by Kantar Public. Collectors visit shops and gather information on a range of items from up to three different stores across multiple locations, recording availability across four categories: "none", "low", "medium", or "high".

This indicator is currently suspended while we review alternative options.

Shipping indicators

These weekly and daily faster shipping indicators data are created through new experimental methods and are not official statistics. More quality and methodology information is available in Faster indicators of UK economic activity: more timely and relevant shipping indicators.

The seasonally adjusted and trend estimates are estimated using a version of the seasonal adjustment method TRAMO-SEATS modified to deal with higher frequency time series. This method is available in an R package “rjdhf” (National Bank of Belgium Research Department) that calls an experimental version of the seasonal adjustment software JDemetra+. The seasonally adjusted and trend estimates are based on decomposing an ARIMA model that results in a set of moving average filters whose weights are determined by the model. The seasonal adjustment method may be limited as the available shipping data are a short time series; it will be fine-tuned in future releases.

Social impact of the coronavirus (OPN)

Data on the social impact of the coronavirus on Great Britain were collected from the Opinions and Lifestyle Survey (OPN).

The questions asked of respondents that are used for the estimates provided in this publication are:

  • in the past seven days, for what reasons have you left your home?
  • in the past seven days, have you worked from home because of the coronavirus (COVID-19) outbreak?
  • in the past seven days, have you used a face covering when outside your home to help slow the spread of the coronavirus (COVID-19)?

Further breakdowns of these estimates (for example by age, sex or region) as well as other estimates to help understand the impact of the coronavirus (COVID-19) pandemic on people, households and communities in Great Britain are available in the regular Coronavirus and the social impacts on Great Britain bulletin.

More information on the quality and methodology of the OPN survey is available in the Opinions and Lifestyle Survey Quality and Methodology Information.

System average price (SAP) of gas

Data is collected from Data Item Explorer from the National Grid. The daily SAP determines the futures price and is therefore used to indicate supply constraints and demand pressures. For this bulletin, the actual day value (p/kWh) and the preceding seven-day rolling average (p/kWh) of these values are reported. These data are accessed weekly, in a Monday to Sunday format.

Traffic camera activity

Traffic cameras are a widely and publicly available data source allowing transport professionals and the public to assess traffic flow in different parts of the country via the internet. The UK has thousands of publicly accessible traffic cameras, with providers ranging from national agencies to local authorities.

The images that traffic cameras produce are publicly available, low resolution and do not permit people or vehicles to be individually identified. They allow for the construction of counts of objects (such as pedestrians or cars) that capture the levels of activity at different times of day throughout the entire week.

More methodology information on the compilation of these time series is available in the Data Science Campus blog.

Transactions at Pret A Manger

These data are delivered to the ONS from Headland Consultancy and give indexed values from 10 regions and transport locations: Scotland, Yorkshire, Manchester, Regional Towns, London: Suburban, London: West End, London: City Worker, London: Airports, London: Stations and Regional Stations. The index shows total weekly till transactions at Pret A Manger stores as a proportion of the companies’ average weekly level in the first four weeks of 2020, between 3 January 2020 and 30 January 2020. These data are delivered weekly from Friday to Thursday in a week-ending format.

Definitions:

London: City Worker

Pret A Manger stores in the Square Mile and Canary Wharf.

London: West End

Pret A Manger stores in popular retail areas within Central London.

London: Suburbs:

Pret A Manger stores outside of Zones 1 and 2, but within Central London; predominantly in residential areas of London.

London: Stations

Pret A Manger stores in three large train stations in London.

London: Airports

Pret A Manger stores in four major airports in London.

Regional Towns:

Pret A Manger stores in towns not listed in the index.

Regional Stations:

Pret A Manger stores in stations in towns not listed in the index.

UK spending on debit and credit cards

The Bank of England has identified regular daily CHAPS payments from merchant acquirers to approximately 100 “large” retail corporates within its transactional data. A large retailer is defined for this purpose as one with a minimum of £5 million card purchase proceeds received through CHAPS in 2020. The large retailers are each mapped to one of 15 different retail sectors (comparable to the ONS Consumer Trends series), based on their primary business.

These 15 retail sectors have in turn been mapped into four consumption category series:

  • "staples" refers to companies that sell essential goods that households need to purchase, such as food and utilities 
  • "work-related" refers to companies providing public transport or selling petrol 
  • "delayable" refers to companies selling goods whose purchase could be delayed, such as clothing or furnishings
  • "social" refers to spending on travel and eating out

Each sector in the series has been weighted according to its (relative) share of annual UK household consumption in Quarter 4 (Oct to Dec) 2019.

A monthly CHAPS index is also produced. The monthly data time series is calculated by the ONS, rather than being an additional series that is produced and validated by the Bank of England.

More information, including the mapping of the retail sectors to the four consumption category series, and the weighting into the total spending on credit and debit cards series is available on the Bank of England’s CHAPS Faster Indicators methodology article.

UK flight data

These data are daily flight figures from the European Organisation for the Safety of Air Navigation (EUROCONTROL). Daily flight numbers for the UK alongside other countries are available in EUROCONTROL's dashboard. EUROCONTROL is a pan-European, civil-military organisation dedicated to supporting European aviation. Its Aviation Intelligence and Performance Review Unit provides independent collection and validation of air navigation services performance-related data and intelligence gathering.

The flights data include international arrivals and departures to and from the UK (including crown dependencies) and domestic UK flights, but exclude overflights (flights that pass over UK territory). They capture all flight movements that operate under Instrument Flight Rules (IFR), where the pilot uses instruments in the flight deck to control, guide and adjust the plane. This includes commercial flights carrying passengers and cargo as well as non-commercial flights such as private and military flights.

!

Data from EUROCONTROL do not include information on the volume of passengers or cargo carried on UK flights. Especially in the context of the coronavirus pandemic, flights might not be operating at full capacity and therefore trends in passengers and cargo will differ from trends in flights presented here.

Value Added Tax

Value Added Tax (VAT) diffusion indices are created through new experimental methods and are not official statistics.

VAT indicators are split into two sections; diffusion indices and reporting behaviours.

Diffusion indices

Diffusion indices show changes in business turnover (total value of all sales and other outputs excluding VAT), and expenditure (total value of purchases and all other inputs excluding VAT), for both quarter-on-quarter, and month-on-month. The growth rates are analysed as both quarter-on-quarter a year ago, quarter-on-quarter non-seasonally adjusted (NSA) and seasonally adjusted (SA), month-on-month a year ago, and month-on-month NSA and SA.

In summary, for all VAT returns values where we can find a match, we apply:

The diffusion index is therefore bound between 1 and negative 1.

VAT returns where both returns are zero, or implausible information is submitted, are discarded.

To bind the SA values between 1 and negative 1, and prevent implausible SA values in Quarter 2 (Apr to June) 2020, we applied a modified logit transform, as follows:

We then seasonally adjust using the X-13ARIMA-SEATS method. To produce the final, SA value, we untransform as follows:

These transformations have minimal impact on the series prior to 2020.

Quarterly diffusion index

The quarterly diffusion index includes businesses reporting on a three-monthly or monthly basis, where monthly values are aggregated to quarters. This is published with all data received by the final date of the reporting period.

To increase data content, quarterly returns are allocated to the calendar quarter in which two or more of the months lie. For example, a quarterly return covering the period March to May 2020 will be allocated to Quarter 2 (Apr to June) 2020. At the time of publication in early July, most VAT submissions available will refer to the earlier stagger, those reporting March to May.

For more information on how the quarterly reporting periods are derived, see VAT reporting periods in Section 2 of the VAT methodology article.

Monthly diffusion index

The monthly diffusion index only includes businesses reporting monthly for VAT. Around 3% of all VAT-registered businesses report monthly. The index is published twice per month.

Flash estimates

VAT reporters received in the first seven days after the reporting period are included. Given that there are normally five working days in the first seven days of the month, the data content is relatively consistent month to month. This cut-off date was chosen to increase timeliness, while also being the earliest date when the key economic sectors provided a sufficiently accurate indicator of economic performance.

Month 2 estimates

VAT reporters received in the first calendar month after the reporting period are included. Given that businesses typically have one month and seven days after the end of the reporting period to submit a VAT return, data content is relatively mature at the point of Month 2 (M2) publication.

We have previously also produced Month 1 (M1) estimates, containing only data received by the end of the reporting period. Very low data content meant these were inaccurate, and mostly redacted to prevent disclosure, so we have stopped producing these.

Please note the monthly and quarterly diffusion indices can exhibit different trends because of the quarterly stagger offset, and that only a subset of firms contribute towards the monthly diffusion indices.

For more information on how the quarterly reporting periods are derived, see VAT reporting periods in Section 2 of the VAT methodology article.

Reporting behaviours

Reporting behaviours cover counts of all VAT reporters, regardless of reporting period or record type. These are broken down by section and grouped into sections based on the VAT unit's primary Standard Industrial Classification (SIC).

The stated month is when the return was received by HM Revenue and Customs (HMRC), not the reporting period.

New reporters are counts of VAT reporters, which have never previously submitted a VAT return, broken down by section.

Record type is all VAT reporters, broken down by whether the business is paying tax, reclaiming tax, re-inputting to pay or reclaim tax (correcting a mistake prior to submitting the return), or replacement to pay or reclaim tax (correcting a mistake after submitting the return).

After this, we seasonally adjust, using an additive decomposition under the X-13ARIMA-SEATS method.

Understanding the heatmap

The heatmap displays the VAT turnover diffusion index "standard deviations from the mean". This guide aims to explain how to derive and interpret the data shown in the heatmap using the turnover diffusion indices given in the dataset.

Step 1

Calculate the mean and the standard deviation of the turnover diffusion index between 2008 and 2019. This calculation produces a unique mean and standard deviation of the turnover diffusion index for each industry and time frequency (monthly or quarterly data). The heatmap illustrates the all industry index and is broken down by agriculture, production, construction and service sectors.

Standard deviation is a statistical calculation that measures how widely values in a dataset are dispersed from the average. A smaller standard deviation indicates most values are close to the average, whereas a larger standard deviation indicates values are widely spread from the average.

To calculate the standard deviation for each diffusion index:

  • subtract the mean from each individual diffusion index and square the result which gives the square differences

  • each individual squared difference result of step one is summed, and an average of the square differences is derived

  • this gives the variance, taking the square root of the variance gives the standard deviation

Step 2

Calculate the "standard deviations from the mean" displayed in the heatmap using the formula:

Standard deviations from the mean =

(diffusion index minus mean of series) divided by standard deviation of series

Step 3

The thresholds for the calculated "standard deviations from the mean" in step 2 are based on the current rule and allocated the relevant colour.

Between 7.0 and 4.0 standard deviations from mean - dark green

Between 4.0 and 1.5 standard deviations from mean - light green

Between 1.5 and 0.5 standard deviations from mean - lightest green

Between 0.5 and negative 0.5 standard deviations from mean - white

Between negative 0.5 and negative 1.5 standard deviations from mean - light red

Between negative 1.5 and negative 4.0 standard deviations from mean - dark red

Between negative 4.0 and negative 10.0 standard deviations from mean - very dark red

Between negative 10 and negative 17.0 standard deviations from mean - brown

Interpreting the heatmap

As at data published on 9 July 2020, the latest diffusion indices were available up to Quarter 2 (Apr to June) 2020 for quarterly data, May 2020 for monthly data, and June 2020 for new reporters.

For example, the all industry quarter-on-quarter diffusion index for Quarter 2 2020 was negative 14.6. This can be interpreted as the all-industry turnover diffusion index for Quarter 2 2020 compared with Quarter 1 2020 was 14.6 standard deviations below its own diffusion index historical average from 2008 to 2019. Therefore, the larger negative indicates the diffusion index is significantly below its historical average. The underlying all industry turnover diffusion index for Quarter 2 2020 is negative 0.38. The negative figure indicates that far more firms had decreasing turnover than increasing turnover in the latest period.

More quality and methodology information is available in Faster indicators of UK economic activity: Value Added Tax returns.

Vehicle flows around ports

We construct average traffic counts and average speed indicators for the whole of England and for 13 major English ports, from traffic flow data from Highways England.

Average counts and average speed data for traffic on English motorways and major A-roads were obtained from Highways England’s TRIS dataset, which lists the roads covered. The data are made available around three weeks after the reference period. The data can be split by four categories of vehicle length as follows:

  • less than 5.2 metres – for example, cars, motorcycles
  • 5.2 metres to 6.6 metres – for example, panel vans, minibus
  • 6.6 metres to 11.66 metres – for example, rigid lorries, buses
  • greater than 11.66 metres – for example, larger rigid lorries and coaches, articulated lorries

More methodology information on the compilation of these time series is available in the Data Science Campus blog.

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3. Strengths and limitations of real-time indicators

This section details the strengths and limitations of the various real-time indicators included in the bulletin with links to more detailed methodology pages where required.

Advanced notification of potential redundancies

Comparing HR1 potential redundancy data with Labour Force Survey (LFS) redundancy data finds that HR1 data peaks earlier than LFS data. This is to be expected as HR1 is a notification of intention to dismiss whereas the LFS picks up redundancies that have occurred. The HR1 data are consistently lower than the LFS redundancy data, but this is also expected as the LFS picks up redundancies from smaller businesses and includes Northern Ireland data.

Business Insights and Conditions Survey (BICS)

The Business Insights and Conditions Survey (BICS) is voluntary, and responses are qualitative, which should be treated with caution as results reflect the characteristics of those who responded and not necessarily the wider business population.

These data should not be used in place of official statistics. The survey was designed to give an indication of the impact of coronavirus on businesses and a timelier estimate than other surveys.

More information on the strengths and limitations of the BICS data is available in the Business Insights and Conditions Survey (BICS) QMI, published on 20 May 2021.

Company incorporations, voluntary dissolutions and compulsory dissolutions

The indicator is high frequency and timely – the only weekly data on company creations and closures available for the UK, published 6 days after the reference period.

Experimental data based on a new processing system at Companies House, data subject to revision, and not entirely consistent with quarterly official statistics publication from Companies House.

More detailed information on the strengths and limitations of the weekly indicators of company incorporations and voluntary dissolutions is available in Weekly indicators of company creations and closures from Companies House methodology: August 2020.

Energy Performance Certificates

The weekly data will differ from daily and monthly figures published on the Landmark Information website because of overlaps of weekly figures (that is, Week 27 includes five days in July as well as days in June).`

Footfall

Year-on-year footfall estimates compare the same day rather than date; for example, Tuesday 30 June 2020 is compared with Tuesday 2 July 2019 (last year was two days ahead of this year because of the leap year).

However, there are no adjustments for bank holidays. For example, as the date of Easter changes each year, the data will be comparing Easter Sunday in 2019 with a Sunday in 2020 that is not Easter.

Online job advert estimates

These estimates are experimental and will continue to be developed.

The Adzuna categories used do not correspond to Standard Industrial Classification (SIC) categories, so these values are not directly comparable with the Office for National Statistics’ (ONS) Vacancy Survey.

Information on the strengths and limitations of these estimates is available in Using Adzuna data to derive an indicator of weekly vacancies: Experimental Statistics.

OpenTable seated diners

Data from OpenTable is based on a sample of approximately 20,000 restaurants, which provide OpenTable with information on all of their inventory in states or metros with fifty or more restaurants on the OpenTable network.

The data does not account for the changes in the number of restaurants in a given area on the OpenTable platform. While coronavirus is likely to have impacted the number of restaurants closures, this would not be directly captured in this data.

Further information is available at The restaurant industry in recovery.

Road traffic in Great Britain

All of the statistics published are National Statistics. These statistics were assessed by the UK Statistics Authority and confirmed as a national statistic in February 2013. We provide further details on the status of these statistics and changes to them.

Our geographical website allows users to view and download estimated traffic flows on every link of the “A” road and motorway network in Great Britain. The interactive map provides a mapped background to identify traffic flows in specific areas of the country.

DfT road traffic statistics team conducted a review of the traffic estimates for Great Britain. The aim of the review was to ensure robust traffic estimates continue to be produced, seeking innovation and greater value for money in their production while protecting user needs.

A report summarising the review so far and detailing individual projects is available.

Shelf availability of items from UK shops

Shelf availability does not imply stock availability in warehouses or storage units and is simply the level of available products in a selected sample of shops at the time of data collection.

It is important to note that the allocations of items to the categories “none”, “low”, “medium” and “high” are subjective as they are recorded by individual collectors.

Social impact of the coronavirus (OPN)

More information on the strengths and limitations of the Opinions and Lifestyle Survey (OPN) is available in the "Strengths and limitations" section of the Coronavirus and the social impacts on Great Britain bulletin.

System average price (SAP) of gas

These data from the national grid are timely, with data recorded on a Sunday being published by Faster Indicators the following Thursday. However, these data can be subject to extreme within-day trading prices, which can lead to skewing of actual traded prices. It must also be noted that while these prices reflect spot prices on the day, traders can opt for futures contracts where the buyer and the seller agree the market-determined price for gas for a future date. Other markets also exist for wholesale gas trading in Great Britain. Despite this, the scope of SAP is sufficient to provide a representation of supply constraints and demand pressures in the gas industry.

Traffic camera activity

Coverage is limited. Although many traffic cameras are available, they are clustered in towns and cities. It is more difficult to locate traffic cameras in smaller settlements. Currently we do not produce any series for Wales.

Accuracy depends on external factors. Accuracy of detecting different object types depends on many factors outside our control. The positioning of cameras can make it difficult to detect certain object types, for example, and the image quality depends on weather and technology.

Counts are always underestimated. Sensors placed on roads can be used to count every vehicle passing by the sensor, but the traffic camera images only provide images at regular intervals and depend on the accuracy of the machine-learning model for counting objects. Therefore, this source is more suited for estimating trends rather than absolute numbers.

Transactions at Pret A Manger

The Pret A Manger index is a timely and robust indicator, used in the real-time indicators bulletin as a proxy of consumer spending, high street footfall and passenger movement around the UK. The regions in the index cover the majority of England and Scotland. However, the index offers no national figure, and because of the backward-looking structure of the index, new Pret A Manger stores are omitted from this Index. Lastly, the “Yorkshire” region is comprised of four stores, meaning it is considerably more volatile than other regions.

UK spending on debit and credit cards

Users should note the daily payment data is the sum of card transactions processed up to the previous working day, so there is a slight time lag when compared with real-life events on the chart.

Value Added Tax (VAT)

Accuracy of diffusion indices

Here, we consider the revisions between the monthly VAT indices for M1 (data available at the end of the reporting period), day seven (data received up to seven days after the reporting period) and M2 (data received up to one month after the reporting period). This gives confidence as to the consistency of different publication vintages.

Revisions between different vintages of diffusion indices have a standard deviation of less than 0.05 in the four industries (agriculture, production, construction, and services) between day seven and M2 estimates. Industries with fewer responders tend to show a larger expected revision. There is a small tendency to revise upwards for monthly turnover, and a larger tendency to revise downwards in the monthly expenditure indices.

Vehicle flows around ports

These data are taken from the Strategic Road Network (SRN). The SRN is made up of the motorways and major trunk roads in England managed by National Highways. In 2019, the SRN comprised approximately 2.4% of the English network. It does not cover local motorways or B roads.

The quality of the data for various ports can be influenced by the number of sensors captured in the vicinity of the port. Note the number of sensor observations can vary dramatically from roadworks and software updates, which can lead to volatility and step changes in the data.

These data are compiled using different methods and sensors than the Department for Transport's (DfT) daily time series on road traffic in Great Britain. The DfT series are based on the automatic traffic sensor sites used in the Quarterly Road Traffic National Statistics publication.

Publication of coronavirus-related data

We will publish this bulletin on a weekly basis during the coronavirus pandemic. This is to ensure we are meeting user needs for more timely data. We will be adding new data and experimental indicators as and when data become available each week.

This publication will include regularly updated data on the fortnightly BICS survey, Companies House, Energy Performance Certificates, footfall, online job advert estimates, OpenTable seated diners, road traffic in Great Britain, shelf availability of items from UK shops, shipping indicators, the social impact of coronavirus (OPN), system average price (SAP) of gas, traffic camera activity, transactions at Pret A Manger, UK spending on debit and credit cards, UK flight data, value-added tax (VAT) and vehicle flows around ports.

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Contact details for this Methodology

Emelia D’Silva-Parker
faster.indicators@ons.gov.uk
Telephone: +44 1633 455120