Challenges for Economic Statistics in the Digital Age: Services and Intangibles Seminar

1. Services and Intangibles Seminar
Challenges for Economic Statistics in
the Digital Age

2. Measuring the Service Sector
RES/ONS/RSS seminar 5 July 2017
Diane Coyle
University of Manchester/ESCoE
ONS Fellow

4. ONS progress in measuring services
• Index of Services 2001
• Atkinson Review 2004 – public services
• SIC 2007 improvements
• 2008 FISIM introduced
• 2012 reviews of service industries started
• Improvements to financial data (2016 review)
• Services prices (2018 on)
• Services survey SERVCOM

5. Introducing ESCoE
An independent research
centre funded by the
ONS
An academic network
supporting the ONS
Economic Statistics
Analysis Strategy
A partnership between
the research
community and ONS
Based at the National Institute of Economic and
Social Research (NIESR)
Delivered with partner institutions,
King’s College London, Nesta, University of
Cambridge, Warwick Business School (University
of Warwick) and Strathclyde Business School,
and a broad network of researchers,
34 senior research staff (on fractional
appointments) from partner institutions, as well
as LSE, Nottingham, Royal Holloway, Stanford,
Sussex and Queen Mary,
and further underpinned by
our international expert network and academic
advisory panel (to be expanded).

6. Research Programme
National
Accounts and
Beyond GDP
Productivity and
the Modern
Economy
Regional and
Labour Market
Statistics
• Historical National
Accounts data
• Nowcasting GDP
• Democratic
measures of income
• Modelling and
communicating data
uncertainty
• Measuring service
sector activities
• Measurement issues
in the modern
economy
• Sectoral productivity
estimates
• Granularity in trade
in value added data
• Developing firm-
level data for
productivity analysis
• Admin data for
labour force and
migration statistics
• New data for labour
market modelling
• Regional nowcasting
• Improving regional
economic indicators

7. Questions being addressed by ESCoE
• Measuring the output of the financial services
– Need to take account of risk
• Insurance sector output
– Include value of goods and lives protected
• Public sector output
– Reasonable volume measures for individual services
(health, education) but need to take account of
quality
– How to measure the volume of collective services, e.g.
criminal justice system

8. Questions being addressed by ESCoE
• Deflators for service sector output
– Is there an feasible alternative to using time rates for
professional and business services (implicit
assumption of no productivity change)
– Need to include Business to Consumer as well as
Business to Business in Services Producer Price
Indexes
– Estimating margin prices in retail trade
• Nominal values and deflators for trade in services
– Difficulties in dealing with MNCs

9. But a wide range of other issues
• Sector classification
• Hard to measure sectors – some examples
• Constant innovation
• Servitization
• Factoryless manufacturing
• Digital transformation
• Public services

10. Service sector classifications
Source: Nesta 2015

11. Source: Nesta 2014

12. Services prices

13. Mobile data traffic
W. Europe, petabytes/month (Ericsson Mobility Report)

14. Constant innovation
Messages
Chat
Money transfer
Entertainment
Data transfer
Telephony
Conference calls
Location services

15. Servitization
• CorporateCare®
• ‘Power-by-the-Hour’
• TotalCare®
• SelectCare™
• TotalCare®Flex
• Services account for
32%-63% of divisions’
revenues

16. • Phillips to provide
Schiphol with LED
lighting-as-a-service
• Lightbulbs are
‘connected IoT’
• Philips can monitor
each lamp & replace
faulty units, often
before the fault occurs

17. Factoryless Manufacturing
Source: Bayard, Byrne
& Smith 2017

18. Market/government Household
Routine
Telecoms
Retail
Cleaning,
Driving
Non-
routine
Consultancy, accountancy, law
Medicine
Travel agency
Home cooking, gardening,
care
Laundry
(washing
machine)
Car repair,
Plumbing
Childcare (TV)
Domestic robots
Self-driving cars
(SMS to WhatsApp)
Medicine
Consultancy, accountancy, law
Retail
Travel agency
Less
time
More
time/bett
er quality

19. Public services

20. Table 1: Definitions of output measures
Output
Measure
Service areas
Coverage
1
(%)
Definition
Quantity
output
Social security
administration
100
The number of activities performed and services delivered.
Growth in individual activities are weighted together using the relative
cost of delivery.
Adult social care 100
Children’s social
care
40
Public order and
safety
100
Education 25
Quality-
adjusted
output
Healthcare 90
Quantity output is adjusted for the quality of the services delivered. If the
quality adjustment is positive, estimates of output growth will increase.
Healthcare quality is measured using a combination of indicators including
survival rates, waiting times and patient satisfaction.
Education quality is measured using examination performance.
Education 75
“Inputs =
output”
Police 100
Some services we cannot measure output directly, so we assume the
volume of output equals the volume of inputs used to create them,
meaning that productivity growth will always be zero.
Defence 100
Other services 100
Healthcare 10
Children's social
care2 60
Source: Office for National Statistics
Notes:
1. Coverage refers to the proportion of service area’s output accounted for by the associated type of output measure.
2. For children's social care inputs isn’t strictly equal to output. Expenditure data are deflated to produce the inputs and outputs
series, meaning that outputs are indirectly measured. However, different data sources are used for the inputs and output series so
productivity growth is not expected to be zero.

21. Multiple digital measurement
artefacts
• Substitution across the production
boundary – market to household
• Activities in GDP – affected by digital
business models
• Activities in GDP – quality changes
and nominal/real split

22. New digital production boundary
questions
• Do-it-yourself digital intermediation
• Sharing economy
• Home digital production

23. Inside the production boundary: digital
business models
• Sampling: Prices of digital equivalent goods; outlet substitution bias.
• Composition effects: Shift in industry composition especially to hard-to-measure sectors
• Intangibles: Hard to measure though increasingly included in investment statistics; investment in data?
• Digitisation
– Reducing sales of some marketed products – often substitution to zero price goods
– Reduced fixed investment in commercial property (higher sales/bricks ratio, greater productivity of
brick services)
• Second hand goods: increased sales enabled by digital platforms
– Nets out of HHFCE but may be substituting for some new purchases
• Ad-funded free goods
– Same in principle as commercial TV, bigger in scale
– Deduct an imputation for cost of watching ads?
– Substitution between ad-funded vs subscription vs purchase to own consumption
• Cross-border effects
– Substitution between different national GDP totals as consumers switch to overseas intermediaries;
– Multinational operating services and intangible activities across borders
– Attribution of value added in digital value chains; value is emailed overseas, products shipped back?
• Software as a service, cloud services
• Factory-less manufacturing

24. Discussion
Led by Peter Van De Ven - OECD

25. Closing Address
Professor Giuliana Battisti
Warwick Business School , ONS Fellow
.

26. Look out for our next event:
“Measuring Public Sector Productivity”
29th November 2017
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