Transcript Service Lives of R&D Assets: Comparing survey and patent based approaches Daniel Ker UNECE Conference of European Statisticians Geneva, 7th May 2014

Service Lives of R&D Assets:
Comparing survey and patent based approaches
Daniel Ker
UNECE Conference of European Statisticians
Geneva, 7th May 2014
Overview
 Measuring and capitalising R&D – brief intro
 How long is R&D useful for and why does this
matter?
 Estimating R&D service lives
 Results
 Conclusions
Measuring and Capitalising R&D
 R&D: creative, systematic work to produce
knowledge, use of this knowledge for new
products or processes of production
 Can be bought in, usually produced by user
 Treated as investment in SNA08
Measuring and Capitalising R&D
3 key questions to answer:
1. How much R&D is there?
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Sales for specialists
Sum-of-costs for non-market, own-account
 expenditure data from ‘Frascati Manual’ sources
2. Who uses it?
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Funders of R&D (from FM sources)
Exports of R&D (from ITIS)
Survey questions on intended owners
3. How long is it useful for?
How long is R&D useful for?
Service life: ‘the total period during which
[the asset] remains in use, or ready to be
used, in a productive process’
The period over which the R&D is used in:
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Products sold
Licences granted
Policies implemented
Research papers published
Not infinite:
 Superseded by new R&D  obsolescence
 Gradually becomes ‘common knowledge’
Why do R&D service lives matter?
 Knowledge capital thought to explain differing economic
performance (between countries, industries)
 2 key determinants of knowledge stock:
 the amount of knowledge produced (i.e. R&D output)
 how long it remains in the stock
“the accuracy of capital stock estimates derived from a PIM
is crucially dependent on service lives” (OECD 2009)
“Specifying
a service life of 10 years rather than 5 years
would make a huge difference to estimates of capital
measures. Net capital stock would be approximately double,
and with a typical scenario of strong growth, consumption of
fixed capital would be appreciably smaller.” (OECD 2010)
Estimating R&D asset lives
Not practical to gather information on each individual asset
 Need representative (average, max, min) service lives
1. Estimate from questions on R&D surveys
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‘general’ approach – ‘over how many years would the business
expect to benefit from a typical investment in R&D?’
‘specific’ approach (USA) – identify a specific product which
embodied R&D; over how many years did the business sell
this product?
2. Estimate from data on patent renewals
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Assume patents protect the results of R&D
In each year the patent renewal fee is paid, the R&D must be
worth at least as much as the renewal fee
Examine number period over which patents are renewed
(‘patent lives’)
Strengths and limitations
Survey approach
+ specifically targets R&D performed by the respondent
+ more timely
+ can distinguish different types of R&D
+ linked to different industries (via respondent NACE codes)
- may be challenging for respondents – response burden
- delay while responses are collected
Patent approach
+ readymade administrative source
+ direct observations for large population of patents
- assumes patent lives are representative of R&D lives
- have to wait to observe patent ‘death’
- assumes patents only renewed if of value
- ‘artificial’ maximum life due to patent rules
- industry breakdown requires linking to information on owner
Different methods
Mean or Median average lives
 Frequency distribution of lives highly positively skewed
  median preferable, less prone to bias
 But mean common in literature
Weighted or un-weighted averages
 Desirable to give greater weight to:
 Survey responses from firms which perform the most R&D
 Patents of highest value
Different methods
Survival analysis (patents only)
 patents can be renewed for up to 21 years (in the UK)
 patent data covered the 24 years between 1986 and 2010
 so relatively few patents had the opportunity to reach the
maximum age of 21 years (only those filed before 1989)
  downward bias in average life
 Many cases are “censored”
 Observe many patents surviving a number of years (e.g. from
1990 to 2010 = 20 years)
 BUT do not get to observe the time of death (as it is after 2010)
Kaplan-Meier survival analysis uses the information
we have about these patents to produce improved
estimates of average patent lives
R&D survival profiles
Proportion of R&D/Patents surviving
100
90
Questionnaire: unweighted
composite life
80
Questionnaire: expenditure
weighted composite life
70
Patents: unweighted life
60
Patents: value weighted life
50
40
Patents: average life
30
20
10
0
0
2
4
6
8 10 12 14 16 18 20 22 24 26 28 30 32 34
Age of R&D/Patents in years
Illustrative impact of different service lives on R&D stocks
Stock of R&D
200
180
20.0
160
18.8
140
16.9
120
14.1
100
14.0
10.5
80
10.0
60
9.5
40
8.2
20
8.0
0
6.0
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20
Years
These are all average R&D lives from the above sources and methods!
Large spread (14 years):
 shortest = 6 years…un-weighted median from survey
 longest = 20 years…from Kaplan-Meier analysis of patent lives
Conclusions
 R&D service lives are a key determinant of
knowledge stocks and hence economic
performance
 Countries face choices over the data sources
used to estimate R&D asset lives
 Countries also face choices of the methods
applied to these data
 Different choices will introduce artificial variation
in R&D service lives and reduce the international
comparability of R&D stock statistics