1.
Economic Statistics
Working Group – Real
Time Indicators
27 April 2022

2.
Welcome
Martin Weale
King’s College London and Economic Statistics Centre of
Excellence (ESCoE)

3.
Agenda
Chair – Professor Ana Galvao, Warwick Business School
12:00 – 12:05 Welcome and introduction – Martin Weale, Kings College London and Economic
Statistics Centre of Excellence (ESCoE)
12:05 – 12:15 ONS’ response to COVID or data after COVID – Grant Fitzner, Chief Economist,
Office for National Statistics
12:15 – 12:35 Faster indicators: The only game in GDP-town – Nick Bate, Bank of England
12:35 – 12:55 Real Time Indicators: Capturing the economic and social impact to society within the
UK – Emelia D’Silva-Parker, Office for National Statistics
12:55 – 13:05 BICS - the survey that can adapt to the ever-changing economic picture – Heather
Bovill, Deputy Director for Surveys and Economic Indicators, Office for National
Statistics
13:05 – 13:25 Panel discussion and Q&A – Professor Ana Galvao, Warwick Business School
13:25 – 13:30 Close – Martin Weale, Kings College London and Economic Statistics Centre of
Excellence (ESCoE)

4.
Faster, better, stronger*
Why we all need real time
indicators
Grant Fitzner
Chief Economist | Director of Macroeconomic
Statistics and Analysis GrantFitzner
* With apologies to Daft Punk
ESWG seminar, 27 April 2022

5.
What are real time indicators?
ESWG seminar, Real Time Indicators, April 2022
• Data which is published early (near real time) or at
higher frequencies which is both timely and intrinsically
informative
- aka: ‘high frequency data’, ‘faster indicators’
• They are generally not official statistics
• They potentially offer a vast array of timely and relevant data
on a wide range of economic and social areas

6.
Why real time indicators?
Official statistics are accurate and reliable, but may lack:
• timeliness
• granularity
• relevance
ESWG seminar, Real Time Indicators, April 2022
In addition, policy making in real time (e.g during the pandemic)
expose major data gaps which existing statistics can’t answer

7.
Limitations and
opportunities
ESWG seminar, Real Time Indicators, April 2022

8.
Key data sources for ONS RTIs
ESWG seminar, Real Time Indicators, April 2022
• UK flights (EUROCONTROL) d, w
• Online job adverts by region and industry (Adzuna) d, w
• Seated diner restaurant reservations (OpenTable) d, w
• Retail footfall by category (Springboard, BEIS) d, w
• Traffic camera data: vehicles and pedestrians (ONS) d
• GB motor vehicle traffic by type (Department for Transport) d
• UK ship visits by category (exactEarth, ONS) d, w
• Google mobility data d, w
• Company incorporations and dissolutions (Companies House) w
• CHAPS spending on debit and credit cards (Bank of England) d, m
• Value Added Tax turnover and expenditure diffusion indexes (HMRC) m, q
Third party
data suppliers
Data science
methods
Administrative
data
Source: ONS - Economic activity and social change in the UK, real-time indicators * Note: (d) daily, (w) weekly, etc

9.
The 5 dimensions of statistical quality*
ESWG seminar, Real Time Indicators, April 2022
Source: Eurostat (2003) Methodological documents - Definition of quality in statistics,
Doc. Eurostat/A4/Quality/03/General/Definition
Dimension Key questions for real time indicators
Relevance Do they meet users’ needs? Are there significant gaps?
Accuracy and reliability How close are estimates to true value? How consistent?
Timeliness Time lag between period estimated and release date?
Coherence and
comparability
Can they be reliably combined in different ways or uses?
How do they compare between regions, sectors, over time?
Accessibility and clarity Easy to obtain? Fomats? Metadata? Easy to understand?

10.
The 5 dimensions of statistical quality*
ESWG seminar, Real Time Indicators, April 2022
Source: Eurostat (2003) Methodological documents - Definition of quality in statistics,
Doc. Eurostat/A4/Quality/03/General/Definition
Dimension Key questions for real time indicators
Relevance Do they meet users’ needs? Are there significant gaps?
Accuracy and reliability How close are estimates to true value? How consistent?
Timeliness Time lag between period estimated and release date?
Coherence and
comparability
Can they be reliably combined in different ways or uses?
How do they compare between regions, sectors, over time?
Accessibility and clarity Easy to obtain? Fomats? Metadata? Easy to understand?

11.
The 6 dimensions of statistical quality*
ESWG seminar, Real Time Indicators, April 2022
Source: Eurostat (2003) Methodological documents - Definition of quality in statistics,
Doc. Eurostat/A4/Quality/03/General/Definition
Dimension Key questions for real time indicators
Relevance Do they meet users’ needs? Are there significant gaps?
Accuracy and reliability How close are estimates to true value? How consistent?
Timeliness Time lag between period estimated and release date?
Coherence and
comparability
Can they be reliably combined in different ways or uses?
How do they compare between regions, sectors, over time?
Accessibility and clarity Easy to obtain? Fomats? Metadata? Easy to understand?
Granularity and
richness
Does the level of detail enable you to drill down? Are there a
lot of variables for analysis?

12.
Key limitations
• Representativeness: Corporate indicators
are often partial
• Volatility: often not seasonally adjusted,
may not be quality assured
• Time series are often quite short
• Data generation: the underlying data
drivers may not be well understood
• Cost to acquire, ingest, quality assure
• Analysis: RTIs often need interpretation;
they should not be taken at face value
ESWG seminar, Real Time Indicators, April 2022

13.
To paraphrase the quote by George E. P. Box (1978):
All real time indicators
are wrong, but some
are useful
ESWG seminar, Real Time Indicators, April 2022

14.
ESWG seminar, Real Time Indicators, April 2022
An (illustrative) balanced scorecard approach
Dimension Key questions for real time indicators
Relevance Do they meet users’ needs? Plug significant data gaps?
Timeliness Frequency? How far ahead of existing statistics?
Accuracy and reliability How close is it to official statistic estimates? How volatile?
Accessibility Is the data published? Can the data be linked?
Granularity and richness Regional, industry, or other breakdowns? Many variables?
Coherence and
comparability
How representative is it? Can it be reliably combined? How
does it compare between regions, sectors, or over time?
Additionality Does it plug key data gaps? Add value to what’s available?
Cost and value for money How much would it cost to produce or purchase? Is it vfm?
Continuity and longevity Is continuity of supply assured? Long or short time series?
Nowcasting Is it suitable for nowcasting, forecasting or leading index?

15.
ESWG seminar, Real Time Indicators, April 2022
The ultimate goal – the four quadrants
Official statistics
Accuracy and reliability
Coherence and comparability
Accessibility
Real time indicators
Relevance
Timeliness
Granularity and richness
Data, linked datasets
Accuracy
Granularity and richness
Accessibility
Analysis
Relevance
Coherence
Clarity

16.
Nick Bate, Current Economic Conditions Division
Faster indicators: the only
game in GDP-town
Official: Green - April 2022

17.
Official: Green - April 2022
• Why faster indicators?
• How can faster indicators help nowcast GDP?
 Top-down indicators
 Bottom-up indicators
• What can faster indicators tell us about behavior?
• What does the future hold?
• We are currently in an MPC quiet period: not covering data since December 2021
here.
Outline

18.
GDP nowcasting prior to Covid
• Business surveys the mainstay of GDP
nowcasting prior to Covid (PMIs, CBI).
• Combined with lags of monthly GDP for a
model of quarterly GDP
.
• Focus primarily on GDP from the
expenditure side.
A simple pre-Covid PMI-based
model of GDP
Official: Green - April 2022
-2
-1
0
1
2
07 09 11 13 15 17 19
GDP, % 3m/ 3m
Simple PMI-based
model

19.
GDP nowcasting prior to Covid…couldn’t cope with Covid
Either in magnitude…. Or in timeliness….
• UK enters lockdown 1 in late-March 2020
 March GDP published mid-May
 April GDP published mid-June
• We needed a steer more quickly than that !
Official: Green - April 2022
-25
-20
-15
-10
-5
0
5
10
15
20
07 09 11 13 15 17 19 21
GDP, % 3m/ 3m
Simple PMI-based
model

20.
A change in what we were looking to model/nowcast
• Far more focus on monthly GDP output components
 More timely
 More granular
• Cast the net far and wide for faster indicators
 Little a priori knowledge of what was out there
 Working closely with the Bank’s data scientists
• Completely re-wrote our nowcasting approach
Official: Green - April 2022

21.
• Why faster indicators?
• How can faster indicators help nowcast GDP?
 Top-down indicators
 Bottom-up indicators
• What can faster indicators tell us about behavior?
• What does the future hold?
Outline
Official: Green - April 2022

22.
How can faster indicators help nowcast GDP?
Official: Green - April 2022
The ONS BICS survey Mapped to GDP
….
(level of GDP vs 19Q4, %)
40
50
60
70
80
90
100
Jun-20 Dec-20 Jun-21 Dec-21
% firmsopen
Turnover
-30
-25
-20
-15
-10
-5
0
5
Jan-20 Jul-20 Jan-21 Jul-21
GDP vs 19Q4 (%)
% firmsopen
Turnover

23.
Furlough was a useful indicator while it lasted
Furlough was the mirror image of
GDP
*Full time equivalent
Official: Green - April 2022
-30
-20
-10
0
10
20
30
40
Jan-20 Jul-20 Jan-21 Jul-21
GDP vs19Q4 (%)
Furlough (%, FTE*)

24.
Furlough was a useful indicator while it lasted
Furlough was the mirror image of
GDP
-30
-20
-10
0
10
20
30
40
Jan-20 Jul-20 Jan-21 Jul-21
GDP vs19Q4 (%)
Furlough (%, FTE*)
Furlough-based
model of GDP
*Full time equivalent
Official: Green - April 2022

25.
Furlough was a useful indicator while it lasted
Frequency distribution of monthly
GDP growth
Furlough was the mirror image of
GDP
0%
10%
20%
30%
40%
50%
60%
70%
80%
-18 -15 -12 -9 -6 -3 0 3 6 9
1997 - 2019
2020 - 2021
-30
-20
-10
0
10
20
30
40
Jan-20 Jul-20 Jan-21 Jul-21
GDP vs19Q4 (%)
Furlough (%, FTE*)
Furlough-based
model of GDP
*Full time equivalent
Official: Green - April 2022

26.
Where to start?
A framework for consumer
spending
Social Work-related Delayable Staple
Entertainment Travel fares Clothing Food/drink
Air travel Fuel Cars Rent/bills
Culture/sport Household goods
Recreational goods
-25
-20
-15
-10
-5
0
5
19Q4 20Q2 20Q4 21Q2 21Q4
Staple
Social
Work-related
Delayable
Consumer spending vs
19Q4 (%)
Official: Green - April 2022

27.
Where to start?
A framework for consumer
spending
Social Work-related Delayable Staple
Entertainment Travel fares Clothing Food/drink
Air travel Fuel Cars Rent/bills
Culture/sport Household goods
Recreational goods
How to monitor via monthly
GDP output
Consumer-facing services
Retail & vehicle output
Travel services
Restaurant output
Official: Green - April 2022

28.
Using debit/credit card data to proxy consumer spending
Raw CHAPS credit/debit
card spending data
A CHAPS-based model of
consumer-facing services
Official: Green - April 2022
-60
-40
-20
0
20
40
Jan-20 Jul-20 Jan-21 Jul-21
-50
-40
-30
-20
-10
0
Jan-20 Jul-20 Jan-21 Jul-21
CHAPS-based model
ONSconsumer-facing
services

29.
Faster indicators: beware of….
 The real world is not seasonally adjusted
o Faster indicators are often not seasonally adjusted
 Faster indicators are sometimes nominal, not always real
 Faster indicators might not be representative
Official: Green - April 2022

30.
Social and work-related spending indicators
Modelling restaurant output
using Opentable data
Modelling air travel services
using flight tracking
Official: Green - April 2022
-100
-80
-60
-40
-20
0
Jan-20 Jul-20 Jan-21 Jul-21
ONSair travel output
Flight
tracking
-100
-80
-60
-40
-20
0
20
Jan-20 Jul-20 Jan-21 Jul-21
ONSrestaurant output
Opentable-based
model

31.
The speed vs reliability trade-off
Fuel consumption: monthly
model
Fuel consumption: weekly
model
Official: Green - April 2022
-70
-60
-50
-40
-30
-20
-10
0
10
20
2019 2020 2021
% change vs 19Q4
DfTmobility model
Apple mobility
model
ONSretail salesof fuel
-70
-60
-50
-40
-30
-20
-10
0
10
20
2020 2021
% change vs 19Q4
DfTmobility model
Apple mobility
model
ONSretail sales of fuel

32.
Faster indicators: beware of….
 The real world is not seasonally adjusted
o Faster indicators are often not seasonally adjusted
 Faster indicators are sometimes nominal, not always real
 Faster indicators might not be representative
 Faster indicators can be too fast !
o Beware of short term daily/weekly volatility
 Faster indicators can be high maintenance!
Official: Green - April 2022

33.
Public sector output has also varied significantly during Covid
A sizeable contributor to the
swings in GDP since Covid hit
Health strong, education weak
Official: Green - April 2022
-30
-25
-20
-15
-10
-5
0
5
Jan-20 Jul-20 Jan-21 Jul-21
Health &
education
Consumer-facing
services
Other output
GDP
-50
-40
-30
-20
-10
0
10
20
Jan-20 Jul-20 Jan-21 Jul-21
Education
GDP
Health

34.
Measuring education output and Test & Trace
Daily school attendance (%)
0
10
20
30
40
50
60
70
80
90
100
Mar-20 Sep-20 Mar-21
Government dashboards track
testing and vaccines
Official: Green - April 2022

35.
• Why faster indicators?
• How can faster indicators help nowcast GDP?
 Top-down indicators
 Bottom-up indicators
• What can faster indicators tell us about behavior?
• What does the future hold?
Outline
Official: Green - April 2022

36.
Are people using the tube less because they’re working from home more or
because they’re social distancing?
Consumer travel journeys Tube journeys into the City
hit the hardest
Official: Green - April 2022
-100
-80
-60
-40
-20
0
Mar-20 Sep-20 Mar-21 Sep-21
Driving
London Tube
National Rail
-100
-80
-60
-40
-20
0
Feb-20 Aug-20 Feb-21 Aug-21
Bank
Outer suburbs

37.
Are people using the tube less because they’re working from home more or
because they’re social distancing?
Consumer travel journeys People happier travelling to
Oxford street for leisure?
Official: Green - April 2022
-100
-80
-60
-40
-20
0
Mar-20 Sep-20 Mar-21 Sep-21
Driving
London Tube
National Rail
-100
-80
-60
-40
-20
0
Feb-20 Aug-20 Feb-21 Aug-21
Weekend
Weekday

38.
Covid effects vary markedly by population density
Official: Green - April 2022

39.
Caveats in assuming that mobility = spending
Official: Green - April 2022
But online purchases are far more
important than before...
Mobility around retail centres
*Car traffic at selected out-of-town shopping centres,
using Highways England traffic data
-50
-40
-30
-20
-10
0
10
20
30
Jan-20 Jul-20 Jan-21 Jul-21
In-store
Online
Total
-80
-70
-60
-50
-40
-30
-20
-10
0
10
Feb-20 Aug-20 Feb-21 Aug-21
Retail car traffic*
Google retail &
recreation mobility

40.
There are still sizeable gaps in what we can track
Main GDP sectors
Consumer-facing services
Government
Manufacturing and construction
Business services
Official: Green - April 2022
As shown, plus many more
As shown. Regular health outputs
BICS
BICS
Faster indicators

41.
What does the future hold?
Importance in nowcasting (%)
0
20
40
60
80
100
19 20 21 22 23
Faster indicators
Pre-Covid models
Official: Green - April 2022
 Big data, real time data becoming more
mainstream
 Will faster indicators be a part of the
“normal times” toolkit?
o Or are they for crisis times only?
 Testing them alongside/within pre-Covid
models
 Useful for assessing future shocks
o Regional shocks
o Sectoral shocks

42.
Real Time Indicators:
Capturing the economic
and social impact to
society within the UK
Emelia D’Silva-Parker
Real-Time Indicators, National Accounts Co-ordination
Division
Office for National Statistics

43.
Contents
•Background, purpose and aims
•​Current suite of indicators
•The story behind the numbers
•Future and enhanced indicators

44.
Background, purpose
and aims

45.
Background: Origins of ONS real time indicators
• 2016: Bean Review recommended greater use of ‘big data’
• 2017: ONS Data Science Campus established
• 2019: Monthly Faster Indicators bulletin began

46.
Our initial pandemic response
• Daily data to Cabinet Office’s Civil Contingencies Secretariat (CCS),
as part of Covid dashboard
• Established the fortnightly Business Impact of COVID-19 Survey
(BICS) in early April
• Moved the Opinion and Lifestyle (OPN) household survey to
fortnightly basis, and later weekly
• Moved the monthly Faster indicators bulletin to weekly

47.
Purpose and aims
Purpose ​
• To provide decision makers with data in real time
• To showcase emerging trends within the UK’s socio-economic landscape
• To facilitate further research into the effectiveness of real time indicators
Aims​
• Collaborate with data suppliers to improve production process
• Update suite of indicators relevant to emerging economic situations
• Liaise with topic experts and improve methods
• Engage with users to assess effectiveness
• Improve publication and data representation e.g. automatic dashboards

48.
Current suite of
indicators
As at 27 April 2022

49.
Indicators span across four main themes
Business Insights and Workforce
Weekly Monthly
Business Insights and
Conditions Survey (BICS)
VAT administrative
dataset
Incorporations and
Dissolutions
XERO: Small
business resilience
Online job adverts HR1 Redundancies
Consumer Behaviour
Weekly Fortnightly
Restaurant seated diners OPN Survey results
Google Mobility Shelf availability *
Pret A Manger Index
CHAPS card payments
Retail Footfall *
Transport
Weekly Monthly
Roads sensor data Vehicles around ports
Traffic Cams
Shipping visits
Flights to and from UK
Energy and Housing
Weekly
Energy Performance Certificates
Wholesale gas prices

50.
The story behind the
numbers

51.
The immediate effects of the pandemic
In the past seven days, have any of your plans been postponed or cancelled because of the coronavirus
(COVID-19) outbreak?
Great Britain, 20 to 30 March 2020, OPN results

52.
Fuel Crisis
Source: Bank of England Source: Opinions and Lifestyle Survey Data, ONS
Percentage of adults experiencing shortage of goods by type of goods

53.
Impacts of supply chain issues

54.
HGV driver shortages
Adzuna Online job adverts: Transport, logistics and
warehouse continues to have the highest level of online
job adverts when compared with its February 2020 pre-
coronavirus average level at 230%.
Average counts of HGV vehicles on the Strategic Roads
Network around Felixstowe saw continued decline since
June 2021 picking up slightly post September.

55.
Impact of Omicron variant
Business Insights and Conditions Survey (BICS) OpenTable data: Seated Diners in UK restaurants

56.
Impact of Omicron variant

57.
Lifting of travel restrictions
Open in Power BI
PretvsFlights
Data as of 4/20/22, 9:25 AM
Source: Pret A Manger and Eurocontrol

58.
Cost of living: Opinions and Lifestyle Survey
86%
13% 1%
Over the last month,
has your cost of living
changed?
My cost of living has increased
My cost of living has stayed the same
My cost of living has decreased
1
3
4
8
15
17
77
83
88
0 10 20 30 40 50 60 70 80 90 100
Over the last month, for what reasons has your…
I have lost my job or stopped working
My hours of work have reduced
Other
My income or earnings have reduced
The price of my public transport has increased
My rent or mortgage costs have increased
The price of my fuel has increased
My gas or electricity bills have increased
The price of my food shop has increased
Over the last month, for what reasons has
your cost of living increased?
Results covering period 16 to 27 March 2022

59.
Future and enhanced
indicators

60.
Looking to the future – Our priorities
1. Expansion of indicator suite via evolving roadmap
• Shipping improvements
• Energy data
2. ...but adaptable approach to developments in ONS outputs and
society
3. Ongoing development work to enhance quality and accessibility of
bulletin and datasets
4. Contribute to research and development of real-time indicators
across broader landscape ("levelling up", government, academia and
beyond)

61.
Thank you and any questions?
Please contact Emelia.D’Silva-Parker@ons.gov.uk or any of the team
for more information on faster.indicators@ons.gov.uk

62.
BICS – the survey that can
adapt to the ever changing
economic picture
Heather Bovill
Head of Surveys and Economic Indicators
bics@ons.gov.uk

63.
Business Insights and Conditions Survey (BICS)
• The ONS (UK) created a new innovative fortnightly business
survey to monitor the impact of COVID-19
• Started this new online survey quickly and it went live within two
weeks. Typically 6+ months.
• The BICS voluntary fortnightly business survey has provided us
with a rapid and flexible survey to respond quickly to changing
policy needs
• Detailed results are published each fortnight with headline
figures published each week in a Faster Indicators bulletin

64.
BICS sample and waves
• Responses are collected from businesses during a two
week period. Now up to Wave 54 with plans to continue.
• We have increased sample size over the waves to
improve coverage of regions and business sizes.
• Wave 7 sample re-design implemented to improve
coverage of smaller size businesses
• Wave 17 sample boost again and will now go to ~39,000
businesses each fortnight
• March 2020
• Unweighted
estimates
• Waves 1-6
17,000
• June 2020
• Weighted
estimates
• Waves 7-16
24,000
• Nov 2020
• Subnational
estimates
• Waves 17
onwards
39,000
Wave Sample size
Actual Response
Rate
Number of response
Wave 1 17,786 25.8% 4,598
Wave 2 17,735 33.4% 6,171
Wave 3 17,623 34.7% 6,114
Wave 4 18,506 33.5% 6,196
Wave 5 20,566 30.9% 6,364
Wave 6 20,548 35.3% 7,245
Wave 7 24,473 24.2% 5,927
Wave 8 24,496 22.6% 5,527
Wave 16 24,315 23.7% 5,755
Wave 17 38,760 26.8% 10,377
Wave 18 38,743 27.6% 10,688
Wave 35 38,763 23.3% 9,036
Wave 36 38,646 22.3% 8,614

65.
Adaptable
• Weighted estimates
• Weighted results allow comparison over time (across
waves)
• Three possible weighting methods; count, employment
and turnover
• Back series now available Wave 7 to date.
• Subnational estimates
• Single site approach
• Additional ad-hoc splits of data
• Microdata available through the SRS

66.
Questions over time
Financial
performance
Workforce
size
Furlough
Grants and
Schemes
EU Exit
International trade
& supply chains
Net zero
Shortage of
workers
Global supply
chains
Increase in prices
(energy)

67.
No longer a “COVID” survey
Regular
question and
comms reviews
Introduction of
core questions
Adapting to free
text responses
provided
businesses

68.
BICS vs Other Estimates

69.
Impact of BICS
• Working closely with
stakeholders to see how
BICS data being used
• “Gold figures” &
“invaluable”
• Policy decisions
• Media

70.
Future developments
• BICS will continue to measure the impact of challenges facing
the economy and other events on UK businesses, helping to
inform policymakers.
• Collaboration across government departments.
• Adding and editing questions dependent on
stakeholder requirements.
• Improved subnational estimates

71.
Links

72.
Closing remarks
Martin Weale
King’s College London and Economic Statistics Centre of
Excellence (ESCoE)

73.
Thank you for attending the
Economic Statistics Working Group –
Real Time Indicators Seminar
You can keep up to date on all up coming events via
ons.gov.uk/economicevents
If you would like to ask a question or provide any feedback, please do so
via economic.engagement@ons.gov.uk