XIV EWEPA Conference
Helsinki, Finland, 15-18 June, 2015
1
THE PRODUCTIVITY OF THE INTERNET
FROM THE PERSPECTIVE OF HOUSEHOLDS
Proposition:
Russel Cooper
University of New South Wales In an integrated view of
what an ‘economy’ is all
UNSW, Canberra, PO Box
about, the entire business
7916, Canberra BC ACT
sector should really be seen
Australia
as simply an intermediary in
the provision of well-being
R.Cooper@adfa.edu.au
to consumers
Agenda
2

1.
Measuring the Internet Economy

2.
Thought Provokers

3.
Explanations

4.
Modelling Issues

5.
Key Findings

6.
Conclusion
Measuring the Internet
Economy
3
Where are the clues?
What are we
looking for?
A blueprint for
measuring the
Internet Economy

OECD (2013). Measuring the Internet economy: a
contribution to the research agenda. OECD Digital
Economy Papers, No. 226, OECD Publishing.

Approach 1: KLEMS

Approach 2: Growth Accounting

Approach 3: Consumer Surplus
4
OECD Approach 1
Value added approach
5
KLEMS
Y = f ( K,L,E,M,S )
Instead, think of this as:
X = f ( K,L,E,M,S )
The ‘input’ branch of a
transformation function
OECD Approach 2
Growth
6
How does behaviour change with technology?
Can technological change be predicted?
OECD Approach 3
Indirect
7
Well-being
Consumer surplus
Willingness to pay
Can technical
progress
deliver a
free lunch?
Agenda
8

1.
Measuring the Internet Economy

2.
Thought Provokers

3.
Explanations

4.
Modelling Issues

5.
Key Findings

6.
Conclusion
Thought provokers
9
How can we possibly
measure the value of
something that is
‘free’?
What is ‘new’ about
the ‘New Economy’?
Where is the ‘new’
bit in our models?
Try this quick quiz
10
This is
George
Study
the
picture
Quiz to
follow
Hint for the quiz to come: Y = C + I + G + X – M
Old idea?
…. Or still relevant?
Remarkable result
11
Honestly, it was this big
More than
10 times
bigger than
previously
found
Median Results by Country
12
Table 6.1: Average Internet benefits by country
France Germany
Italy
Spain
UK
5 countries
Combined
52.8
53.6
50.1
Percentage
of annual
income in
2011
37.0
56.3
51.1
Annual
benefit –
Euros
12,925
13,649
12,885
12,555 15,369
13,461
Comparison
13
The most
widely
quoted
result to
date
Goolsbee A., Klenow, P.J. (2006). Valuing consumer products by the
time spent using them: an application to the Internet. American
Economic Review, Papers & Proceedings, 96(2), 108-113.
Agenda
14

1.
Measuring the Internet Economy

2.
Thought Provokers

3.
Explanations

4.
Modelling Issues

5.
Key Findings

6.
Conclusion
Explanations
Three quiz questions
Question 1 (very easy)
Question 2 (moderate)
Question 3
Remember George?
Does he know
15
something Ed
doesn’t know?
Some traditional
economic concepts
Whatnow
wasseem
George
doing?
to operate
Whatdifferently
was George’s mood?
Was George producing or consuming?
There are some things our focus groups (traditional
data providers) don’t seem to be able to tell us
We need to rethink how to deal with time
Who would believe an effect could be so strong?
Internet Usage as Investment
16
Some traditional economic
concepts now seem to
operate differently
A
mobile
school
The hidden economy
17
There are some things our
focus groups (traditional
data providers) don’t seem
to be able to tell us
How
much
are you
seeing?
An underlying layer of public capital
– courtesy of a technological revolution
Opportunity Cost
18
We need to rethink how to deal with time
Who gets
an extra
hour’s
pay for
an extra
hour’s
work?
The actual value of time is person specific but …
The relative value of time is occupation specific
Networks
Anybody
can
benefit
from a
network
But it’s
tastier if it
arrives
gratis
19
Traditional analysis never told me that
network effects could be so strong
Yes, we
even have
networks in
Australia
Networks
are not
new …
… but what is new is the sheer size of
network externalities created by modern ICT
Agenda
20

1.
Measuring the Internet Economy

2.
Thought Provokers

3.
Explanations

4.
Modelling Issues

5.
Key Findings

6.
Conclusion
Modelling Issues
21
The ‘consistent modelling’ triangle
What’s this?
The data
dilemma
I never expected this
Estimation
options
The Consistent Modelling
Triangle
22
The Objective
(Indirect utility function)
The Behaviour
(estimating
equation)
The Evaluation
(compensating
variation)

Occupations
Data

Demographics
23
The Data Dilemma
A marriage of different kinds of data
Something old – official data may
be accurate – but out of date
Something new – but can an
expensive survey be justified?

Incomes Something borrowed – but will
someone else’s survey really do?
Something blue – but can survey
responses be trusted?

Internet activities
Econometric Issues
Fraction of time
spent on an
Internet activity
Effective time =
𝛼
+ 𝛽
𝐸𝑓𝑓𝑒𝑐𝑡𝑖𝑣𝑒 𝑇𝑖𝑚𝑒
+ 𝛾 𝐼𝑛𝑐𝑜𝑚𝑒
1
+
𝐸𝑓𝑓𝑒𝑐𝑡𝑖𝑣𝑒 𝑇𝑖𝑚𝑒
+
=
depends on:
𝐼𝑛𝑐𝑜𝑚𝑒
𝐴𝑐𝑡𝑢𝑎𝑙 𝑇𝑖𝑚𝑒 1+𝑒𝑥𝑡𝑒𝑟𝑛𝑎𝑙𝑖𝑡𝑦
Demographics
Intercept’ 𝛼
24
Occupation
Agenda
25

1.
Measuring the Internet Economy

2.
Thought Provokers

3.
Explanations

4.
Modelling Issues

5.
Key Findings

6.
Conclusion
Key Findings
A big effect…
… and progressive
26
Results by income ranges
Income
France Germany
Range
Euros
p.a. <
57.8
87.2
18,000
18,001 –
47.3
57.5
27,000
27
Italy
Spain
UK
All
75.4
73.0
91.1
77.6
54.8
57.3
62.0
56.4
27,001 –
36,000
39.8
57.7
49.4
51.9
53.3
49.5
36,001 –
54,000
34.0
45.0
41.3
45.2
46.8
42.3
54,001 –
72,000
28.4
37.1
41.2
39.5
38.5
36.4
> 72,000
28.9
33.0
35.4
31.7
37.8
32.8
Results by
age groups
Benefit as percentage of annual income in 2011
Age
France Germany Italy
Spain
UK
16 to 34 years
34.9
67.0
55.0
59.7
57.9
35 to 49 years
40.5
53.3
52.9
50.7
54.3
50 to 75 years
35.1
48.0
43.8
44.4
48.8
All participants
37.0
56.3
51.1
52.8
53.6
28
All
56.4
50.0
43.8
50.1
Agenda
29

1.
Measuring the Internet Economy

2.
Thought Provokers

3.
Explanations

4.
Modelling Issues

5.
Key Findings

6.
Conclusion
Conclusion
TP = Y/X
30
If I can achieve my objective at level ‘Y’ using resources ‘X’ my utilityconsistent ‘true’ productivity must be TP = Y/X
The
Internet
Economy

A revolution

A hidden layer of capital

OECD ‘Approach 3’ should be
oriented to measuring Y

OECD ‘Approach1’ (KLEMS)
concerns not Y, but X

‘True’ Productivity: TP = Y/X
31
X = f ( K,L,E,M,S )
Postscript

32
Where will it all end?
Might you have
access to additional
relevant data?
Would you be
interested in having
YOUR data stretch the
capabilities of this model?
Contact details:
Russel Cooper
R.Cooper@adfa.edu.au
‘Have model. Will travel.’