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Weak ICT Investment in Canada and theUnited States: the Role of Cloud Computing

Myeongwan Kim
Prepared for Innovation, Science, and Economic Development Canada

CSLS Research Report 2018-4

1

Weak ICT Investment in Canada and the United States: the Roleof Cloud Computing

Abstract
After robust growth in ICT investment in Canada and the United States during the 1980s and 1990s,
growth in ICT investment started to slow after 2000 and its share in GDP entered a downward trajectory.
In an increasingly digitalized economy, weak ICT investment seems puzzling. To explain this trend, thisreport focuses on two facets of the changing ICT spending pattern driven by the rise in cloud computing
starting in the mid-2000s. Instead of investing in ICT capital goods, organizations now purchase cloudservices from cloud service providers that appear to be more efficient in producing computing services.
Second, cloud service providers undertake substantial own-account investment in ICT equipment which is
not counted in official statistics. Based on input-output tables, we find that the impact of cloud computing
on the ICT spending pattern is potentially substantial: during the 2006-2014 period, the purchase of cloudservices rose at an annual rate of 25.3 per cent to reach $2,554 million CAD in Canada and at an annual
rate of 20.4 per cent to reach $32.1 billion USD in the United States. During this period, adding ownaccount ICT equipment investment by the IT service sector results in additional 1.71 percentage-points inannual growth for nominal ICT investment in Canada and additional 1.12 percentage-points in the UnitedStates.

i

Weak ICT Investment in Canada and the United States: the Roleof Cloud Computing
Executive Summary
With dramatic changes brought about by digital computing and communication technology,
weak ICT investment in Canada and the United States seems puzzling. ICT investment grew at amuch slower rate after 2000. Also, ICT investment as a share of nominal GDP entered adownward trajectory since the early 2000s. The slowdown in ICT investment as a share of GDP
following the burst of the dot-com bubble in 2001 continued until the present.
This report explores the potential role of cloud computing in explaining the weak ICT
investment in Canada and the United States. We focus on the rapid diffusion of cloud computing
in the two countries starting in the mid-2000s. Cloud computing is important in understanding
the weak ICT investment statistics since an increasing number of organizations have adopted
cloud computing and the adoption of such new computing system has important implications fortheir ICT spending pattern.

Two Issues with rising cloud computingFirst, cloud computing has changed not only the way organizations access computing
resources but also the way they pay for such technologies. With cloud computing, they accesscomputing resources in the form of services. Hence, it allows them to divert capital expenditure
on ICT tangibles and intangibles to purchase of intermediate services since cloud computing
does not require ICT infrastructure on premises. Instead, cloud service providers now invest in
ICT capital goods and they appear to be more efficient in producing computing services.
Second, there is a number of signs that major cloud service providers engage in own-accountinvestment (assembling servers and building other cloud infrastructures internally). A large
increase in the capital expenditure reflected in their financial filings does not seem to translate
into an equivalent increase in the official ICT equipment investment statistics. Indeed, inputoutput tables indicate that they have purchased a large amount of computer and electronics
components as intermediate goods especially since the mid-2000s suggesting that they haveassembled ICT equipment internally.
Some non-market production is included in the official statistics such as own-accountsoftware production (included as "own-account software investment" in the United States and"Own-account software design and development services" in Canada). However own-account
ICT equipment production is not included in the accounts. Therefore, we believe that weak ICT
investment statistics is explained in part by this measurement issue.

ii

Empirical Approach
In order to assess the impact of these two facets of cloud spending on ICT investment in
Canada and the United States, we carry out a quantitative analysis using the data from thedetailed input-output tables published by Statistics Canada and the Bureau of Economic Analysis.
For the first issue, we conduct a simple counterfactual analysis exploiting a break in the timeseries of the intensity (defined as a share of GDP) of the intermediate purchase of computing
services made in the total economy. We assume that the break was induced by a rise of cloudcomputing. Second, we estimate the value of own-account investment in ICT equipment by
cloud service providers based on the value of their input purchase of computer and electronics
components adjusted for the value added from assembling and installing ICT equipment.

Results
We summarize our main findings as follows. First, our estimates indicate that organizations
are increasingly shifting their resources to purchasing cloud services. We find that the purchaseof cloud services in the total economy grew substantially since the mid 2000s in both Canada andthe United States:In Canada, the purchase of cloud services stood at $2,554 million CAD in 2014, up from
$420 million CAD in 2006 (25.3 per cent annual growth).

In the United States, the purchase of cloud services reached $32.1 billion USD, up from
$7.3 billion USD in 2006 (20.4 per cent annual growth).

Second, we find that own-account investment by "IT service sectors" (which presumably
cover core activities of cloud service providers) was significant in Canada and the United States:

Own-account investment in Canada reached $5.1 billion CAD by 2014, up from $1.7
billion in 2006 (14.5 per cent annual growth).

In the United States, it reached $53.9 billion USD in 2014, up from $22.6 billion USD in2006 (12.1 per cent annual growth).

Our estimates are consistent with the data from external sources including a private sector
consultancy and financial filings of major cloud service providers in the United States.
Most importantly, adding our estimates of own-account investment to ICT investment
statistics changes the trend in the ICT investment series significantly. For Canada, ICT
investment grew by 1.71 percentage-points more per year during the 2006-2014 period if ownaccount investment is added to the official statistics (2.19 per cent instead of 0.48 per cent). Also,
ICT investment as a share of GDP somewhat stabilizes after 2006 instead of falling. From 2.70
per cent in 2005, the share falls to only 2.65 per cent instead of 2.14 per cent in 2014.

iii

Similarly, in the United States, augmenting ICT investment with own-account investment
leads to additional 1.12 percentage points for the annual growth rate during the 2006-2014 period.
This suggests that ICT investment grew at an annual rate of 3.34 per cent instead of 2.22 per centduring this period. Adding own-account investment leads to a slight upward trend in the ICT
investment as a share of GDP from 2006. By 2014, the share recovers to 3.73 per cent for theshare from 3.22 per cent in 2005 instead of falling to 3.11 per cent.
The key takeaway is that the ICT spending in both Canada and the United States did respondto the rise of cloud computing from the mid-2000s. Our results imply that a significant part of
the “weak ICT investment story” can be explained by own-account equipment investment by
cloud service providers. At the same time, some portion of ICT investment could have beenredirected permanently to other part of the economy as organizations shift their resources fromexpenditure on ICT capital to current expenditure on computing services (e.g. purchasing cloudservices such as SaaS, PaaS, and IaaS).
This report is exploratory in nature in addressing the two important facets of the changing
ICT spending pattern driven by a rise of cloud computing. This report proposes a line of researchon the impact of cloud computing on the ICT spending pattern in Canada and the United States.
In doing so, this report also addresses a need for official data on cloud services. We hope ourresearch leads to further debate on cloud computing as well as a better data collection on thecloud services sector by statistics officials.

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Weak ICT Investment in Canada and the United States: the Roleof Cloud Computing
Table of Contents
Abstract .......................................................................................................................................................... i
Executive Summary ...................................................................................................................................... ii
List of Tables ............................................................................................................................................... vi
List of Charts................................................................................................................................................ vi
List of Appendix Tables and Charts ........................................................................................................... vii
I. Introduction ............................................................................................................................................... 1
II. Cloud Computing ..................................................................................................................................... 7
A. Definition and service/deployment models of cloud computing ........................................................ 7
B. Cloud market in North America and related IT spending patterns ..................................................... 9
1. Service deployment models ........................................................................................................ 10
2. Serivce models ............................................................................................................................ 11
3. Cloud infrastructure investment .................................................................................................. 12
III. Issue One: Resources diverted from ICT investment to purchasing cloud services. ............................ 14
A. Proxy for the purchase of cloud services ......................................................................................... 14
B. Trend in the intermediate purchase of data processing, hosting, and related services in Canada
and the United States .................................................................................................................................. 15
C. Counterfactual analysis .................................................................................................................... 19
1. Methodology ............................................................................................................................... 19
2. Results for Canada and the United States ................................................................................... 21
IV. Issue Two: Own-account investment in ICT by IT service sectors ...................................................... 26
A. Trends in the intermediate purchase and output in IT services sectors ........................................... 28
B. Estimates of own-account investment ............................................................................................. 32
V. Augmented ICT investment in Canada and the United States ............................................................... 34
A. Augmented investment in ICT equipment....................................................................................... 34
B. Augmented ICT investment ............................................................................................................. 37
VI. Conclusion ............................................................................................................................................ 41
References ................................................................................................................................................... 44VII. Appendix: Additional Tables and Charts ............................................................................................ 46
A.Tables ................................................................................................................................................ 46
B. Charts ................................................................................................................................................ 51v

Weak ICT Investment in Canada and the United States: the Roleof Cloud Computing

List of Tables
Table 1: Annual growth rates of ICT investment and its components, per cent, Canada
and the United States, 1997-2014 ....................................................................................................2
Table 2: Intermediate purchase of data processing, hosting, and related services(I-O commodity code MPS 518), basic price, Canada, millions of CAD, 1997-2014 ..................16
Table 3: Intermediate purchase of data processing, hosting, and related services(BEA I-O commodity code 512), producers' price, the United States, billions of USD, 1997-2016 ....................................................................................................................................17
Table 4: Average intensity of industries' purchase of data processing, hosting,and related services (as average % GDP), all industries,
Canada and the United States, per cent ..........................................................................................17
Table 5: Annualized growth rates of the purchase of data processing, hosting,and related services, total economy, Canada and the United States ..............................................18
Table 6: Breakdown of sales in Data processing, hosting, and related services(NAICS 51821), per cent, 2008-2012 ............................................................................................21
Table 7: Counterfactual intermediate purchase of data processing, hosting, and related
services(I-O commodity code MPS 518),all industries,
Canada, millions of CAD, 2006-2014 ...........................................................................................22
Table 8: Counterfactual intermediate purchase of data processing, hosting, and related
services(BEA I-O commodity code 512), all industries,
United States, billions of USD, 2006-2016 ...................................................................................22
Table 9: Purchase of cloud computing proxied by the purchase of data processing,hosting, and related services(I-O commodity code MPS 518),Canada, 2006-2014 ......................23
Table 10: Purchase of cloud computing proxied by the use of data processing,hosting, and related services(BEA I-O commodity code 512), United States, 2006-2014 ...........24
Table 11: Intermediate purchase of Computer and electronic productsby the IT service sector, millions of CAD, Canada, 1997-2014 ....................................................29
Table 12: Intermediate purchase of Computer and electronic productsby the IT service sector, millions of USD, United States, 1997-2016 ...........................................31
Table 13: Estimates of own-account investment, Canada and the United States, 2006-2014 .......32

List of Charts
Chart 1: Nominal ICT investment as a share of nominal GDP, total economy, Canada and theUnited States, per cent, 1976-2014 .................................................................................................1
Chart 2: Nominal investment in IT equipment as a share of nominal GDP, total economy,
Canada and the United States, per cent, 1976-2014 ........................................................................4vi

Chart 3: Nominal investment in Computer Software and Databases as a share of
nominal GDP, total economy, Canada and the United States, per cent, 1976-2014 ......................5
Chart 4: Capital expenditure of selected IT service providers in the United States, based on
financial filings, billions of USD, 1997-2015 ................................................................................26
Chart 5: Investment in ICT equipment, total economy, 1997-2014 ..............................................27
Chart 6: ICT equipment investment augmented by own-account investment,
Canada, billions of CAD, 1997-2014 ............................................................................................35
Chart 7: ICT equipment investment augmented by own-account investment,
United States, 1997-2014 ...............................................................................................................36
Chart 8: ICT investment (augmented and actual), Canada, billions of CAD, 1997-2014 .............38
Chart 9: ICT investment (augmented and actual), billions of USD, United States,1980-2014 .....40

List of Appendix Tables and Charts
Table A1: Augmented investment in IT equipment, Canada and the United States,
2006-2016 ......................................................................................................................................46
Table A2: Augmented ICT investment, Canada and the United States, 2006-2016 .....................47
Table A3: Average share of ICT investment in GDP, Canada and the United States,
per cent, 2006-2014 .......................................................................................................................48
Table A4: Gross Domestic Product, Actual and Augmented, current prices, 2006-2014 .............49
Table A5: Gross Domestic Product, Actual and Augmented, current prices, 2006-2014 .............50
Chart A1: Actual and Counterfactual Intermediate purchase of Data processing, hosting
and related services, millions of CAD, Canada, 1997-2014 ..........................................................51
Chart A2: Actual and Counterfactual Intermediate purchase of Data processing, hosting
and related services, billions of USD, the United States, 1997-2016 ...........................................52vii

Weak ICT Investment in Canada and the United States: the Roleof Cloud Computing 1

I.

Introduction

Since the mid-1970s, we have experienced dramatic changes brought about by digitalcomputing and communication technology. With the mass production and a rapid diffusion ofdigital logic circuits and its derivatives (e.g. computer, cellular phones, the internet), digital
information and communication technologies have transformed traditional production andbusiness techniques. As a result, attention has been increasingly devoted to the role ofinformation and communication technology (ICT) investment in capital formation and in
productivity growth (e.g. Thomas, 2016).
ICT investment in Canada and the United States has been weak since 2000. ICT investment(in the total economy) as a share of nominal GDP has been on a downward trajectory since 2000
in both countries (see Chart 1). The share fell significantly following the burst of the dot-com
bubble and it has not recovered to the level observed around 2000.

5.0
4.5

Chart 1: Nominal ICT investment as a share of nominal
GDP, total economy, Canada and the United States, percent, 1976-2014

4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0

CanadaUnited States

Note: ICT investment consists of investment in ICT equipment and investment in computer software and databases.
Source: CSLS database for ICT investment. Available at http://www.csls.ca/data/ict.asp
1This reported was written by CSLS economist Myeongwan Kim under the supervision of CSLS Executive Director
Andrew Sharpe for Innovation, Science, Economic Development Canada. The Centre for the Study of Living
Standards would like to thank Innovation, Science, Economic Development Canada for financial support for thisresearch. The author thanks Andrew Sharpe, Bert Waslander, and Jianmin Tang at Innovation, Science, Economic
Development Canada for comments. The author also thanks officials at Statistics Canada, especially Andreas Trauin the Industry Accounts Division for providing us with data.

1

Table 1: Annual growth rates of ICT investment, per cent, Canada and the United States, 1997-2014
CanadaUnited States
Panel A: ICT investment

NominalReal

NominalReal

1976-1981

17.42

6.50

22.50

26.15

1976-2000

10.81

8.69

11.95

13.19

1981-1989

10.33

9.00

11.33

15.94

1989-2000

8.27

9.46

10.52

18.09

2000-2014

1.55

3.80

1.35

4.30

2000-2006

2.98

8.30

0.20

4.99

2006-2014

0.48

0.55

2.22

3.79

NominalReal

NominalReal

1976-1981

16.95

3.63

24.25

30.61

1976-2000

9.50

6.97

11.95

20.95

1981-1989

7.66

5.41

8.95

15.07

1989-2000

7.60

9.69

8.89

21.10

2000-2014

-1.38

3.56

-1.67

4.63

2000-2006

0.56

9.75

-3.24

6.17

2006-2014

-2.82

-0.85

-0.48

3.50

Panel B: ICT equipment

Panel C: Computer software and databases
NominalReal

NominalReal

1976-1981

19.97

12.81

18.27

15.53

1976-2000

14.96

11.46

15.14

15.66

1981-1989

19.51

13.71

16.56

17.49

1989-2000

9.61

9.25

12.74

14.41

2000-2014

5.01

4.02

3.74

4.06

2000-2006

6.70

6.78

3.45

4.28

2006-2014
3.76
2.00
3.95
3.90
Note: Real ICT investment in Canada is based on Constant Prices (2007 CAD, millions). Real ICT
investment in the United States is based on Chained Prices (2009 USD, millions).
Source: The CSLS database on ICT investment. Available at http://www.csls.ca/data/ict.asp

Weak ICT investment can also be observed in terms of an annual growth rate. Table 1 reports
annual growth rates of both nominal and real ICT investment (total, ICT equipment, andsoftware and databases) in Canada and the United States. We observe a general trend of thedecreasing annual growth rate in both nominal and real terms over time. Notably, the annual
increase decelerates substantially after 2000 in both countries. This is true for the twocomponents of ICT investment: ICT equipment and computer software and databases (see Panel
B and C in Table 1).2
2

Note that during the 1970s and 1980s, the aggregate price of ICT investment in Canada increased. Hence, theannual growth rate in nominal terms is higher than that in real terms. The aggregate price of ICT investment in2

Given a rapid diffusion of information and communication technologies, the downward trend
in ICT investment (as a share of GDP and as a growth rate) seems puzzling. Among the otherfactors that could have contributed to the weak ICT investment, this report focuses on two
important facets of the changing ICT spending pattern in light of a rising adoption of cloudcomputing.
Cloud computing has brought about a big change in accessing computing services for firms,
households and governments. A transition to this new computing platform allows users to docomputing on a network of off-site computing resources accessed through the internet. Cloudcomputing provides firms with a new model for accessing computing resources that can be easily
provisioned, customized, scaled up or down to meet varying needs.
Relevant to our analysis is that cloud computing has changed how organizations budget andpay for technologies: organizations can access computing resources by purchasing services
rather than by direct fixed investment in related ICT tangibles and intangibles (trade capital
expense for variable expense). In turn, cloud service providers now invest in ICT capital goods
to provide computing services but they can spread out the overhead cost over their customers.
Cloud service providers are much more efficient in producing computing services since they canpool resources and allocate them based on an on-demand basis. This implies that a given unit ofcloud-related capital goods can generate more services than the conventional computing system.
We argue that this is likely to have led to a decline in the demand for ICT capital goods on net,and hence weak ICT investment.
Indeed, the rate of ICT resource utilization tends to be higher among firms adopting cloudcomputing3 and that nearly 93 per cent of organizations in North America have already adopted
at least one cloud service.4 For example, the number of server units theoretically required forbusiness operations can be reduced greatly due to improved efficiency via integration of
conventional computing resources into cloud-based infrastructure. The impact of cloudcomputing on ICT investment is expected to be larger in the near future as full migration to a
cloud-based system among firms gains momentum.
Second, there seems to be a measurement issue in ICT investment statistics. The possibility
that cloud service providers assemble ICT equipment on an own-account basis may explain why
Canada increased by 10.2 per cent per year during 1976-1981 and 1.2 per cent per year during 1981-1989. In the
United States, it declined (-1.6 per cent per year during 1970-1981 and -4.0 per cent per year during 1981-1989).
Thus, the real growth rates are higher than the nominal growth rates during the 1970s and 1980s. For the period after
2000, both countries experienced declining ICT prices but the United States experienced more rapidly declining ICTprices. This results in a larger difference between nominal and real growth rates in the United States compared tothan in Canada. See Thomas (2015) and Thomas (2016) for detail.
3
Prior to the introduction of cloud computing, most firms had to install servers and storage devices separately foreach system and each department. Due to differences in servers’ busy and idle periods and in system life cycles, afirm’s average utilization of resources (e.g. servers) was often very low. According to Kuwazu (2015), the averageutilization of servers among Japanese firms without a cloud system is estimated to be less than 30 per cent.
Migration to cloud-based infrastructure would shift conventional IT tasks to the cloud that is more efficient.
4This is based on the survey conducted by Spiceworks, a professional network for IT. It is also found that 30 per
cent of organizations in North America expect more than half of their IT services to be cloud-based in two to three
years. See "The annual report on IT budgets and tech trends" at https://www.spiceworks.com/marketing/state-ofit/report/3

rapidly expanding capital expenditure (as reflected in their financial statement) does not translate
into strong investment in ICT equipment statistics. For example, data from financial filings
reveal that capital expenditure by big cloud service providers- "hyperscale" data centre operators- rose at an annual rate of 17 per cent over the 2010-2015 period reaching $50 billion USD by2015 (see Byrne, Corrado, and Sichel, 2017a,b). It could be the case that a large portion of thecapital expenditure has been on components used for own-account investment in ICT equipment
not on already assembled IT equipment.
Some non-market production is included in the official statistics. For example, own-accountsoftware production (produced within establishments for internal use) is explicitly included as"own-account software investment" in the United States and "Own-account software design anddevelopment services" in Canada. However, it is unclear whether own-account ICT equipment isincluded. For example, the questionnaire for the business survey conducted by Statistics Canada
does not contain any question regarding own-account capital and infrastructure investment.
Indeed, investment in ICT equipment reflected in official statistics has been weak in bothcountries. The share of investment in ICT equipment in GDP has been on a downward trend
since the early 2000s (see Chart 2). Although the share of investment in software and databases
in GDP has not been on a downward trajectory, it has been nearly flat since the early 2000s(Chart 3).
Chart 2: Nominal investment in IT equipment as a share of nominal
GDP, total economy, Canada and the United States, per cent, 19762014
2.5
2.0
1.5
1.0
0.5
0.0

CanadaUnited States

Source: CSLS database for ICT investment. Available at http://www.csls.ca/data/ict.asp

4Chart 3: Nominal investment in Computer Software and Databases
as a share of nomial GDP, total economy, Canada and the UnitedStates, per cent, 1976-2014
2.5
2.0
1.5
1.0
0.5
0.0

CanadaUnited States

Source: CSLS database for ICT investment. Available at http://www.csls.ca/data/ict.asp

To address the importance of the two issues, we attempt to quantify the amount of spending
related to cloud computing not captured in the official statistics in Canada and the United States.
Since official data related to cloud computing are very limited, we carry out our analysis using a
set of data from multiple sources.
First, we rely heavily on the input-output tables available from Statistics Canada and the
Bureau of Economic Analysis. We also use data produced by private consultancies and researchfirms as a reference to which we compare our estimates. The aim of this quantitative analysis is
to capture the changing ICT investment pattern spurred by cloud computing within a scope ofcurrently available data. We suggest that the readers view our estimates cautiously by taking
them as rough guidance.
Based on a simple counterfactual analysis, we estimate that the purchase of cloud services
ranges from $448 million CAD to $497 million CAD in 2006. By 2014, it ranges from $2,554
million CAD to $2,660 million CAD, with an annual growth rate of 23.3 per cent to 25.3 per centover the 2006-2014 period. For the United States, our estimates suggest that the purchase ofcloud services ranges from $32.1 billion USD to $36.1 billion USD in 2014, up from $7.3 billion
USD and $10.5 billion USD in 2006. This implies that the annual growth rate is between 19.7
per cent and 23.7 per cent over the 2006-2014 period. This indicates that a quite significant
amount of resources has been reallocated from ICT capital goods to purchasing ICT services.

5

In return, cloud service providers now purchase a substantial amount of ICT capital goods as
they build cloud-based infrastructures. However, they are also building ICT equipment internally.
To address this second issue, we adopt a simple approach introduced in Byrne, Corrado, andSichel (2017a) to estimate the amount of own-account investment in IT equipment by cloudservice providers. The approach is motivated by the fact that the IT service sector (which
presumably covers all core activities of cloud service providers) purchases a large amount ofcomputer and electronic parts and products but produced nearly zero output using these inputs.
This suggests that these intermediates are used for own-account investment.
Our estimates indicate that if own-account investment in ICT equipment were included in theofficial ICT investment statistics, the investment in ICT equipment in Canada would have grownby 3.81 percentage points more per year over the 2006-2014 period. In terms of a share in
nominal GDP, adding own-account investment in ICT equipment results in stabilization of theshare instead of falling. From 1.47 per cent in 2005, the share falls to 1.42 per cent instead of
0.91 per cent in 2014. In the United States, adding own-account investment would lead to
additional 3.12 percentage points annual growth rate over the 2006-2014 period. In terms of ashare of GDP, it results in an upward trend instead of a downward trend as reflected in theofficial statistics. By 2014, the share recovers to 1.69 per cent for the share from 1.34 per cent in2005 instead of falling to 1.07 per cent.
The key takeaway from our estimates is that the role of cloud computing is potentiallysubstantial in driving the ICT investment statistics in Canada and the United States. However,there is a great deal of lag for official statistics to reflect an increasing role of cloud computing inchanging the ICT spending pattern. Hence, it is important to develop official statistics for cloudservices and the cloud services sector so that we have a better understanding of the changing ICT
spending pattern and its impact on ICT investment.
We emphasize that this report is an exploratory work to shed light on the impact of thechanging ICT spending pattern on ICT investment by providing rough estimates of the role
played by cloud computing. A primary goal of this report is to provide a broad picture of thechanging ICT spending pattern driven by a rise of cloud computing and to promote further
debate on the issue among statistics officials and researchers.
The rest of the report is organized as follows. The following section discusses definitions ofcloud computing. It also summarizes key trends in North American cloud computing markets.
Section III and Section IV present our quantitative analysis on the two issues for Canada and theUnited States. Section V discuss the impact of own-account investment on a general trend of ICT
investment in the two countries. Section VI concludes.

6

II.

Cloud Computing
A. Definition and service/deployment models of cloud computing

In this section, we discuss some key definitions and features of cloud computing. We startwith the definition of cloud computing. The National Institute of Standards and Technology(NIST) first created a definition of cloud computing in 2009 and officially published it in 2011
after consultations with industry and government experts and stakeholders (Mell and Grance,2011). NIST defines cloud computing as follows (Mell and Grance, 2011:2):
Cloud computing is a model for enabling ubiquitous, convenient, on-demand network accessto a shared pool of configurable computing resources that can be rapidly provisioned andreleased with minimal management effort of service provider interaction.
The first milestone in cloud computing history was the emergence of Salesforce, an IT
service firm in 1999. It introduced the concept of delivering enterprise applications through asimple website. Such a move paved the way for software firms to deliver their applications using
the internet. In 2001, Amazon introduced Amazon Web Services to provide cloud-based services
such as data storage, computation and human intelligence via the Amazon Mechanical Turk.
Subsequently, in 2006, Amazon launched Elastic Compute cloud (EC2), which was acommercial web service that allowed small companies and individuals to rent computers. It was
the first widely accessible cloud infrastructure service. Following the introduction of EC2,
Google and Microsoft subsequently launched more advanced cloud computing infrastructures.
With the advent of more reliable cloud computing infrastructures during the mid 2000s,
commercial cloud services started to take off. A significant number of firms (93 per cent of thefirms in North America) now access computing resources through cloud services available inthree main product classes.
The NIST definition includes a description of cloud service models or "product classes" (Melland Grance, 2011:2.3):
Software as a Service (SaaS): The capability provided to the consumer is to use theprovider’s applications running on a cloud infrastructure. The applications are accessible
from various client devices through either a thin client interface, such as a web browser(e.g., web-based email), or a program interface. The consumer does not manage orcontrol the underlying cloud infrastructure including network, servers, operating systems,
storage, or even individual application capabilities, with the possible exception of limiteduser specific application configuration settings.

Platform as a Service (PaaS): The capability provided to the consumer is to deploy onto
the cloud infrastructure consumer-created or acquired applications created using
programming languages, libraries, services, and tools supported by the provider. The
consumer does not manage or control the underlying cloud infrastructure including7

network, servers, operating systems, or storage, but has control over the deployed
applications and possibly configuration settings for the application-hosting environment.


Infrastructure as a Service (IaaS): The capability provided to the consumer is toprovision processing, storage, networks, and other fundamental computing resources
where the consumer is able to deploy and run arbitrary software, which can include
operating systems and applications. The consumer does not manage or control theunderlying cloud infrastructure but has control over operating systems, storage, anddeployed applications; and possibly limited control of select networking components(e.g., host firewalls).

The service models highlighted above are distinct in the sense that cloud users can abstractfrom (or ignore) the underlying infrastructure in a varying degree. For IaaS, the user needs tothink about not only the deployed application but also underlying operating systems and storage.
On the other hand, the user of PaaS need to think about only the deployed application ignoringother aspects of the infrastructure. Finally, the SaaS user simply uses the deployed application
without any control over it (e.g. its configuration settings).
Next, there are four distinct models of service deployment. According to NIST (Mell and Grance,
2011:3), they are:
1. Private cloud: The cloud infrastructure is provisioned for exclusive use by a single
organization comprising multiple consumers (e.g., business units).It may exist on or off
premises.
2. Community cloud: The cloud infrastructure is provisioned for exclusive use by aspecific community of consumers from organizations that have shared concerns; it may
exist on or off premises.
3. Public cloud: The cloud infrastructure is provisioned for open use by the general public;
it exists on the premises of the cloud provider.
4. Hybrid cloud: The cloud infrastructure is a composition of two or more distinct cloudinfrastructures (private, community, or public) that remain unique entities, but are boundtogether by standardized or proprietary technology that enables data and application
portability (e.g., cloud bursting for load balancing between clouds).
The private cloud is a form of an internal cloud maintained on a firm’s intranet or data centre.
This can be a great option for firms who already have established data centres or those concernedwith security (e.g. government agencies, financial institutions, large-size corporations). However,with the private cloud, the user is responsible for all management, maintenance and updating ofdata centers. Moreover, it is expected that servers will need to be replaced after their life cycle,
which can be very expensive.

8

The public cloud has advantages in terms of costs - no need to purchase hardware or software;
maintenance –the service provider provides maintenance; and scalability - near-unlimited scalewith on-demand resources to meet business needs. With the advantages of both deployment
models, the hybrid cloud dominates enterprise cloud strategies (IDC, 2015). With the hybrid
cloud, users can move between public and private deployment options for their operation
depending on their needs.
Finally, NIST also describes the infrastructure that underlies cloud computing as the following(Mell and Grance, 2011:2):

A cloud infrastructure is the collection of hardware and software that enables the fiveessential characteristics of cloud computing. The cloud infrastructure can be viewed as
containing both a physical layer and an abstraction layer. The physical layer consists of the
hardware resources that are necessary to support the cloud services being provided, andtypically includes server, storage and network components. The abstraction layer consists ofthe software deployed across the physical layer, which manifests the essential cloud
characteristics. Conceptually the abstraction layer sits above the physical layer.

In summary, a core advantage of cloud computing is that organizations can substantiallyreduce their IT spending by shifting conventional IT tasks to the cloud that is much cheaper andmore efficient (i.e. a higher utilization rate of existing IT resources). Cloud computing brings
natural economies of scale. A cloud service provider's computing resources are pooled to serve
many customers based on a multi-tenant model with different physical and virtual resources
dynamically assigned and reassigned depending on customers' demand. Customers can easily
scale up or down to meet their real-time demand for computing resources with a cloud system
automatically controls and optimizes resource use by leveraging a metering capability (on a payper-use or charge-per-use basis).
These features of cloud computing imply lower unit costs for computing resources. Hence,
every dollar decrease in IT budget spent on conventional computing services and related ICT
capital goods would lead to a less-than-a-dollar increase in the budget spent on cloud services fora given amount of IT operation. Organizations can expand their IT operation with cheaper
computing resources or less binding IT budget constraint (in real terms).5
B. Cloud market in North America and related IT spending patterns
Cloud computing is a fast-changing market characterized by very limited publicly accessible
data. There are no predetermined metrics we can use to assess all aspects of the cloud market.
Therefore, we summarize some important trends in cloud computing in North America based on
5

A given amount of cloud computing resources results in larger output since it leads to a higher utilization rate. For
example, different departments within a firm can be free from the inefficiency due to the difference between servers’
busy and idle periods. Cloud computing solves this problem by optimally assigning resources among thosedepartments depending on the usage.

9

multiple studies and surveys done by various research and consulting firms. We are unlikely toperfectly capture every facet of the cloud market. However, we think our review is still usefulbackground that motivates our quantitative analysis in the following sections.
The cloud in different markets has developed in varying ways due to factors such as market
maturity, cultural preferences, and available infrastructure. Being a more mature market withadvanced network infrastructures, firms in North American were able to quickly obtain access tolarge, state-of-the-art, centralized data centres that offered cloud services. The diffusion of cloudcomputing in North America has also been facilitated by the high-quality delivery infrastructure
and the relatively short distance between users and data centres/service providers. Users wereassured of reliable performance.
1. Service deployment models
North American firms are in a more favourable situation to adopt public cloud as a
deployment model than firms in other markets (IDC, 2015). Cloud markets in emerging
economies did not have a comparable network coverage or quality to support use of public cloudservices. As a result, private cloud or hosted private cloud services became the preferred modelof deployment in those markets. This trend was also driven by long-held cultural preferences for
IT asset ownership and management of the IT systems by the enterprise itself (IDC, 2015).
Although hybrid cloud is still an important strategy for organizations adopting cloud due
mainly to security concerns, there are a number of signs that firms are increasing the share of
public cloud in their IT activities. This is mainly driven by "the growing understanding thatcloud vendors offer state of-the-art security; the innovative security-related services actually
being marketed by those vendors; a gathering boom in value-added offerings available throughpublic clouds; the popularity of “cloud first” approaches in procurement ecosystems; and greater
overall trust in public clouds.", according to International Trade Administration of the U.S.
Department of Commerce (ITA, 2016:7).
Bain and Company, a consultancy, also found that while security remains as a major concern
inhibiting large firms from adopting the public cloud, that concern has lessened with the
emergence of new considerations such as compliance, vendor lock-in, and data portability (Bainand Company, 2017).The survey by Spiceworks, a professional network for IT, supports thisfinding. According to them, in North America, large firms are planning to allocate as large ashare of their IT budget to cloud services as smaller firms. For example, firms with 1,000-4,999
employees are allocating 31 per cent of the total IT budget on cloud services on average. This iscomparable to the range of 31per cent to 33 per cent found for smaller-sized firms (e.g. 1-99,
100-499, 500-999 employees).
As firms gain maturity and familiarity in the usage of cloud computing over time, public
cloud services are likely to play an even more important role than they do today. The
International Trade Administration predicted that spending on public cloud expenditure willgrow six times as quickly as overall IT spending over the 2013-2018 period, reaching $127
billion by 2018 (ITA, 2016). According to the IDC World Semiannual Public Cloud Services
10Spending Guide released in 2018, worldwide spending on public cloud computing is expected
reach $277 billion USD by 2021, achieving a compound annual growth rate of 21.9 per cent overtheir forecast horizon (2016-2021).6 The United States is expected to account for 60 per cent ofworldwide spending throughout the forecast (roughly $166 billion USD in 2021). Lastly,
spending on public cloud in Canada reached $2.3 billion CAD in 2015 and is expected to double
by 2020 reaching $5.5 billion CAD (IDC, 2016).
On the other hand, we expect that the role of the private cloud in driving the total demand forcloud services is likely to shrink due to its disadvantage in terms of cost and maintenance effort.
For example, according to Wikibon, an IT research firm, the share of private cloud in the total
revenue of Amazon Web Services is expected to decline over the next two decades.7 The shareof private cloud services accounted for only a small share of the total global cloud IT market
revenue in 2015 and is projected to remain so over the next 5 years (Bain and Company, 2017).
Trends in the adoption of different service deployment models have important implications
for the pattern in ICT investment in cloud computing. Cloud users opting for the public cloud do
not undertake IT equipment/software investment directly for the purpose of accessing computing
resources. On the other hand, those adopting the private cloud may have to purchase related IT
equipment/software in order to set up private cloud infrastructures for exclusive use, ownership,and management of computing resources.
Based on the trend that cloud services are increasingly delivered via the public cloud, we
believe that the amount of ICT investment related to cloud computing in the private sector (net ofcloud service providers) has been and will be shrinking. A significant portion of capital
expenditure on accessing computing resources is likely to have been diverted to current
expenditure on purchasing services.
Indeed, North American firms have increased their IT budget allocation for cloud services
and plan to spend proportionally more than they do on software or hardware. According to the2016 survey conducted by Spiceworks, on average, firms in North America plan to allocate 31
per cent of the total IT budget on cloud services in 2018.8 This is higher than the 22 per cent and26 per cent of their 2018 IT budget allocated to hardware and software, respectively.
2. Service models
Most of the cloud services used by organizations are in the form of Software as a Service(SaaS). According to the joint research done by IDC and Canadian Channel Chiefs Council, a
non-profit IT group, 9.7 per cent and 12.2 per cent of the total IT spending in 2016 was spent on
6

IDC has continued to revise upwardly its forecast for spending on the public cloud. In their 2017 release, they
forecasted that spending on the public cloud would reach $266 billion USD in 2021 achieving a five-year compound
annual growth rate of 21.0% . The press releases of the forecast are available athttps://www.idc.com/getdoc.jsp?containerId=prUS43511618 andhttps://www.idc.com/getdoc.jsp?containerId=prUS42889917&pageType=PRINTFRIENDLY
7
See "How Big can Amazon Web Services get?" at https://siliconangle.com/blog/2017/02/20/wikibon-reportpreview-big-can-amazon-web-services-get/
8
The survey is available at https://www.spiceworks.com/marketing/state-of-it/report

11

SaaS in Canada and the United States, respectively (Canadian Channel Chiefs Council,
2017).These are much higher than 1.7 per cent and 1.4 per cent spent on IaaS or 1.1 per cent and1.7 per cent on PaaS in Canada and the United States, respectively.
This pattern is not limited to Canada and the United States. According to Bain and Company(2017), among all cloud product classes, SaaS accounted for the largest share of the global cloud
IT market revenue in 2015 and it is projected to remain so over the next decade. IDC also
predicts that SaaS will continue to be the largest cloud computing category, accounting fornearly two thirds of all public cloud spending in 2018.
SaaS consists of applications and system infrastructure software. Spending on SaaS tends tobe dominated by applications purchases. Among the SaaS applications, IDC predicts thatenterprise resource management (ERM) applications and customer relationship management(CRM) applications will account for the largest SaaS spending in 2018, followed bycollaborative applications and content applications.9
Although Platform as a Service (PaaS) accounts for a small share of public cloud spending,its share is expected to increase substantially in the near future. According to KPMG, while
spending on SaaS and IaaS will continue to increase, “spending on PaaS will increasesignificantly as chief information officers (CIO's) adopt cloud computing as their strategic
development and production platform for both new applications and services, and as they begin
the process of paying down technical debt and migrating or modernizing their legacy IT estate”(KPMG, 2016:2).IDC also predicts that PaaS spending will exhibit the fastest growth over theirprojection horizon (2016-2021).10
3. Cloud infrastructure investment
Most of the investment in cloud infrastructures is done by cloud service providers. Since themid-2000s, cloud service providers have invested heavily in cloud infrastructures. Accordingly,
their capital expenditure has increased significantly over the past years. The financial filings oflarge cloud service providers or "hyperscale" data centre operators reveal that they spent morethan $50 billion USD worldwide as capital expenditure in 2015 (Byrneet al., 2017a).11 This is theresult of an annual growth rate of 17 per cent in their capital expenditure over the 2010-2015
period.
Importantly, as commercial cloud services started to take off in North America since the mid2000s, the cloud model has rapidly dominated the data centre market as well. According to
Kuwazu (2015), in North America, server shipments to data centres (or cloud vendors) already
9

Although SaaS has been and will be the most common cloud service model, it may not be straightforward tocategorize it as a cloud service. For example, Byrne et al. (2017a) treat SaaS as a category of software productservices rather than cloud services per se, thereby excluding SaaS in their analysis. We discuss this issue in moredetails in the following section.
10
See "Worldwide Public Cloud Services Spending Forecast to Reach $160 Billion This Year, According to IDC" athttps://www.idc.com/getdoc.jsp?containerId=prUS43511618
11
Hyperscale is the terms used to describe a data centre operator whose revenue is at least $1 billion USD in
IaaS/PaaS or $2 billion USD in SaaS or $4 billion USD from internet/search/social networking or $8 billion USD
from e-commerce/payment processing.

12

exceeded those to end-user as of 2010. Cloud service providers now account for 90 percent ofdata centre traffic and accounted for essentially all growth in traffic since 2010 (Byrne et al.,2017a).
This implies that server business models have been changing. The conventional flow of“server manufacturer → distributor and system integrators→ end users” is changing to “server
manufacturers → cloud service providers”. End users are now paying cloud service providers
rather than directly buying servers. As a result, the server manufacturers are tailoring mattersrelated to product development, sales, product specifications, and marketing for cloud service
providers rather than for end users. According to Kuwazu (2015), in North America, nearly 70
percent of server shipments go to cloud service providers. Server shipments per order havegrown to be considerably larger than those for orders issued from end users to distributors.
The practice of end-user companies individually establishing servers has become marginal.
There is a trend towards server manufacturers producing servers as “white boxes” without amanufacturer’s brand name and in “designating optimal specifications”. As a result, servers havebecome very similar to manufacturing equipment for factories rather than office equipment.
Moreover, some of North America's major cloud providers are placing large volume orders
directly with electronic component producers (e.g. electronic manufacturing services) bypassing
server manufacturers (Kuwazu, 2015). This implies that they are producing ICT equipment on an
own-account basis. As a result, the role of equipment manufactures in producing servers has
been rapidly shrinking.
For example, Google and Facebook now design electronics components to be produced bymanufacturers for their data centers (e.g. servers, network switches, and data storage devices).12
According to Byrne, Corrado, and Sichel (2017b: footnote 6), "some major cloud providerscommonly have those designs fabricated under contract by other companies, but add software
essential to the operation of the device within the data center. Under this arrangement, the outputof the contract manufacturer would be recorded as electronic components (e.g. circuit boards),
rather than final electronics and would be recorded as intermediate inputs in the Bureau of
Economic Analysis input-output tables, rather than investment".
In summary, we have identified two important facets of the changing ICT spending pattern.
First, it is increasingly common for organizations to purchase services from cloud providers
instead of purchasing related capital from equipment manufacturers. In this case, resources
previously used for investment to access computing are diverted to purchasing services (e.g.
SaaS, IaaS, and PaaS) from cloud vendors. Organizations opting for the private cloud could
invest in cloud infrastructures by ordering products from distributors as final demand. However,this will be reflected in official statistics for ICT investment. Second, most of the investment incloud-related capital is likely to be carried out by cloud vendors either by purchasing alreadyassembled equipment directly from server manufacturers or by own-account investment. Official
statistics would be underestimated by the amount of own-account investment.

12

See "Facebook and Google Try Self Help," at https://www.wsj.com/articles/facebook-and-google-try-self-help1377460750

13

III.

Issue One: Resources diverted from ICT investment to purchasing
cloud services.

As highlighted in the previous section, with an increased use of cloud services, the focus of
ICT spending by firms has shifted away from equipment to services. An obvious first-order
impact of the shift would be a decline in the demand for ICT investment goods. For a given levelof ICT services, the demand for ICT equipment is likely to have declined as firms use cloudservices as a substitute for ICT equipment and as cloud service providers can produce morecomputing services with a given unit of ICT capital goods (i.e. they are more efficient).We
conjecture that this phenomenon could partly explain the weak ICT investment as reflected in
official statistics in Canada and the United States.
In this section, we attempt to quantify the value of the purchase of cloud services in Canada
and the United States over the period 2006-2014. This is to demonstrate an important facet of thechanging ICT spending pattern driven by cloud computing: the reallocation of resources topurchasing computing services. The purchase of cloud services by firms is not counted as ICT
investment but as a purchase of intermediate inputs. Therefore, one way to assess the impact ofcloud adoption on ICT investment statistics is to examine trends in intermediate services
supplied by cloud service producers to cloud service users. For this we turn to the input-output
tables published by Statistics Canada and the Bureau of Economic Analysis.
A. Proxy for the purchase of cloud services
Unfortunately, official data for spending on cloud services are not available in Canada andthe United States. Hence, we focus on the commodity category under which cloud services areclassified. Following Byrne et al. (2017a), we choose the intermediate purchase of dataprocessing, hosting, and related services as a (imperfect) proxy for the purchase of cloud services
in the economy. We recognize that it is an imperfect proxy since it includes not only cloudcomputing but also traditional computing services.
Data processing, hosting, and related services is categorized under Input-Output Commodity
Classification code MPS518 for Canada and BEA Input-Output commodity Code 512 for theUnited States. In Canada, Input-Output Commodity Classification (IOCC) is based on North
American Product Classification System (NAPCS). In NAPCS, data processing, hosting, andrelated services (NAPCS code 75111) includes: website hosting and domain name registration
services (NAPCS 751111); application service provisioning (NAPCS 751112); business process
management services (NAPCS 751113); other information technology infrastructure
provisioning services (NAPCS 751114); information technology infrastructure and network
management services (NAPCS 751115); and information and document transformation services(NAPCS 751116).
Among these sub-categories, cloud services are classified under application service
provisioning (NAPCS 751112) and other information technology infrastructure provisioning
services (NAPCS 751114). First, application service provisioning (NAPCS 751112) represents
14

"Provision of leased software applications from a centralized, hosted, and managed computing
environment, customized to the needs of individual clients". The definition includes softwaredelivered via cloud from cloud service providers (i.e. SaaS). Moreover, from NAPCS 2017, SaaS
is assigned a code: Software as a service, on cloud (NAPCS 7511122).13 Other information
technology infrastructure provisioning services (NAPCS 751114) includes Data storage
infrastructure provisioning services (NAPCS 751142). From NAPCS 2012, "cloud storage
services" is explicitly listed as an illustrative example for this category.
Statistics Canada started to explicitly include some cloud services in its commodity
classification from 2012. By definition, however, cloud services were still categorized under dataprocessing, hosting, and related services prior to NAPCS 2012. Prior to NAPCS 2012, the survey
respondent firms producing the data processing, hosting, and related services were asked tocomplete the question in the same characteristics cell as they do after NAPCS 2012.14 Hence,
data processing, hosting, and related services is still a valid proxy for the period prior to 2012.
Using this proxy, we attempt to estimate the amount explained by cloud computing based ona counterfactual analysis. Specifically, we estimate the intermediate purchase of the service inaddition to what would have been purchased in the world of no cloud computing. We attribute
this quantity to the adoption of cloud computing.
As highlighted in the previous section, SaaS has been the most common cloud service model.
Hence, a significant portion of the purchase of cloud service in the economy would represent thepurchase of SaaS. Yet, Byrne et al. (2017a) argue that SaaS is best understood as a category ofsoftware product services rather than cloud services per se. So it should be regarded as software
products sold via an online subscription business model. Consequently, they exclude SaaS fromtheir analysis on cloud computing.
It is debatable whether or not SaaS should be categorized as cloud services. In this report, we
do not exclude SaaS for two reasons. First, we follow the NIST definition that SaaS is one of the
product classes of the cloud. Second, we cannot explicitly exclude SaaS due to data limitations
even if we opted for exclusion. Data processing, hosting, and related services includes not only
SaaS but also other services such as traditional data centres. Since it is the most detailed
classification available to us, we cannot differentiate the individual components.
B. Trends in the intermediate purchase of data processing, hosting, and related
services in Canada and the United States
Table 2 presents the intermediate purchase of data processing, hosting, and related services(by all industries) for Canada over the period 1997-2014. We observe that the purchase of theservices shows a clear upward trend over the period. It increased from $2,241 million CAD in
1997 to $8,919 million CAD in 2014, an annual growth rate of 8.47 per cent.

13

However, this individual category is not available in the input-output tables published by Statistics Canada.
This information was provided by an official at the Consumer and Business Services Surveys Division, Statistics
Canada.
1415

However, the upward trend may in part reflect a growing size of the economy over time.
Hence, we focus on the "intensity" of the intermediate purchase of data processing, hosting, andrelated services (defined as per cent of GDP). Here, we observe that the intensity has increased
over time. The intermediate purchase of the service accounted for 0.25 per cent of GDP in 1997.
The intensity had increased over time reaching 0.45 per cent in 2014.

Table 2: Intermediate purchase of data processing, hosting, and related services (I-O commodity
code MPS 518), basic price, Canada, millions of CAD, 1997-2014
Year

Total

Pvt

Govt

GDP

% GDP, total% GDP, pvt% GDP, govt

1997

2,244

2,035

206

0.25

0.23

0.02

1998

2,552

2,295

253

882,734
914,974

0.28

0.25

0.03

0.28

0.26

0.02

0.27

0.25

0.02

0.29

0.26

0.03

1999

2,735

2,550

180

982,444
1,076,577

2000

2,946

2,743

196

2001

3,180

2,865

307

2002

3,582

3,228

346

1,152,905

0.31

0.28

0.03

2003

4,150

3,820

322

1,213,175

0.34

0.31

0.03

2004

4,641

4,302

335

1,290,907

0.36

0.33

0.03

2005

4,835

4,470

361

1,373,853

0.35

0.33

0.03

2006

5,073

4,723

346

1,450,404

0.35

0.33

0.02

2007

5,875

5,501

369

1,529,589

0.38

0.36

0.02

2008

6,097

5,704

388

1,603,416

0.38

0.36

0.02

2009

6,034

5,377

650

1,567,007

0.39

0.34

0.04

2010

6,440

5,775

655

1,662,131

0.39

0.35

0.04

2011

7,124

6,435

674

1,769,922

0.40

0.36

0.04

2012

7,400

6,683

705

1,822,808

0.41

0.37

0.04

2013

8,110

7,280

811

1,897,532

0.43

0.38

0.04

1,108,047

2014
8,939
8,060
859
1,990,180
0.45
0.40
0.04
Note: The title of MPS 518 changes over time. We use the most recent title in this table.
Source: CANSIM Table 381-0033 and input-output tables published by Statistics Canada (Catalogue
15F0041X).

Table 3 reports the intermediate purchase of data processing, hosting, and related services for
the United States over the period 1997-2016. We observe a strong upward trend over the period
increasing from $43.7 billion USD in 1997 to $148.5 billion USD in 2016. Similarly, theintensity of the purchase of computing services increased over time. In 1997, the intermediatepurchase accounted for 0.51 per cent of GDP. As of 2016, it reached 0.80 per cent.
Interestingly, the share for the government sector is considerably higher in the United States.
Throughout 1997-2014, the average share for the government is 0.18 per cent in the UnitedStates while it stands at 0.02 per cent in Canada (see Table 4). This implies that nearly half of thedifference in the intensity between the United States and Canada is attributed to the difference inthe share of government.

16

Table 3: Intermediate purchase of data processing, hosting, and related services (BEA Input-Output
commodity Code 512), producers' price, the United States, billions of USD, 1997-2016
Year

Total

Pvt

Govt

GDP

% GDP, total% GDP, pvt% GDP, govt

1997

44.2

32.7

11.0

8,608.50

0.51

0.39

0.13

1998

48.4

37.3

10.6

9,089.20

0.53

0.42

0.12

1999

56.1

42.3

12.6

9,660.60

0.58

0.45

0.13

2000

63.6

48.2

13.8

10,284.80

0.62

0.48

0.13

2001

65.9

48.1

16.5

10,621.80

0.62

0.47

0.15

2002

66.4

46.3

19.3

10,977.50

0.60

0.43

0.18

2003

68.9

48

20.0

11,510.70

0.60

0.42

0.17

2004

75.6

52.7

22.0

12,274.90

0.62

0.44

0.18

2005

80.7

56.5

23.2

13,093.70

0.62

0.44

0.18

2006

92.1

65.1

25.7

13,855.90

0.66

0.48

0.19

2007

102.6

74.6

25.7

14,477.60

0.71

0.53

0.18

2008

109.8

78.5

28.8

14,718.60

0.75

0.55

0.20

2009

107.9

69.4

35.8

14,418.70

0.75

0.50

0.25

2010

112.7

72.6

37.5

14,964.40

0.75

0.50

0.25

2011

120.4

80.9

36.2

14,964.40

0.80

0.56

0.24

2012

127.2

85.5

37.1

16,155.30

0.79

0.56

0.23

2013

132.8

96.4

31.8

16,691.50

0.80

0.60

0.19

2014

138.8

102.4

31.7

17,427.60

0.80

0.61

0.18

2015

147.9

106.9

36

18,120.70

0.82

0.62

0.20

2016

153.8

111.1

37.4

18,624.50

0.83

0.62

0.20

Source: Input-output tables published by Bureau of Economic Analysis

Table 4: Average intensity of industries' purchase of data processing, hosting, and related services (as average %GDP), all industries, Canada and the United States, per centCanadaUnited States

PeriodTotal

Private Sector

Government

Total

Private Sector

Government

1997-2014

0.35

0.32

0.03

0.69

0.50

0.18

1997-1999

0.27

0.25

0.02

0.54

0.42

0.12

1997-2005

0.32

0.29

0.02

0.59

0.44

0.15

0.32

0.30

0.03

0.61

0.45

0.17

0.40

0.36

0.04

0.77

0.56

0.21

2006-2007

0.37

0.34

0.02

0.69

0.51

0.18

2008-2009

0.38

0.35

0.03

0.75

0.53

0.22

2000-2005
2006-20142010-2014
0.41
0.37
0.04
0.79
0.57
0.22
Note: Data processing, hosting, and related services is categorized under Input-Output Commodity Classification code
MPS518 for Canada and BEA Input-Output commodity Code 512 for the United States.
Source: Table 1 and Table 2

17

We pay particular attention to 2006, the year in which Amazon launched Elastic Compute
cloud (EC2), the first widely accessible cloud infrastructure services. Since the introduction ofEC2, cloud computing took off in the economy as Google and Microsoft subsequently launchedmore advanced cloud computing infrastructures. Thus, we suggest the structural break inaccessing computing resources occurred in 2006.
Table 4 shows the average intensity of the intermediate purchase in Canada and the UnitedStates over selected sub-periods. In general, the average intensity prior to 2006 is notably lower
than that observed during the period after 2006. Any sub-period before 2006 exhibits an averageintensity that is clearly lower than that observed during a sub-period after 2006.15
For example, in the United States, the average intensity ranges from 0.54 per cent to 0.59 percent during the sub-periods before 2006. The average intensity reaches as high as 0.77 per centduring the 2006-2014 period, the period associated with a wide diffusion of cloud computing. In
Canada, the average intensity stands at 0.27 per cent to 0.32 per cent during the sub-periods
before 2006. The average intensity reaches 0.40 per cent during the 2006-2014 period.
Although the average intensity tends to be higher during the period after 2006, the growth of
the intermediate purchase of data processing, hosting, and related services somewhat slows after
2006. Table 5 summarizes the annual growth rate observed during selected sub-periods. Over the
2000-2006 period, purchases grew at an annual rate of 9.48 per cent and 6.36 per cent in Canada
and the United States, respectively. However, the growth rate decreases to 7.34 per cent and 5.26
per cent in each country respectively over the 2006-2014 period.

Table 5: Annualized growth rates of the purchase of data processing, hosting, andrelated services, total economy, Canada and the United States
CanadaUnited States

Period

Total

Pvt

Govt

Total

Pvt

Govt

1997-2014

8.47

8.44

8.76

6.96

7.13

6.42

1997-2006

9.49

9.80

5.93

8.49

7.99

9.89

2000-2006

9.48

9.45

9.94

6.36

4.91

10.90

2006-2014

7.34

6.93

12.04

5.26

6.16

2.64

2006-2007

15.81

16.48

6.65

11.39

15.83

-0.07

2007-2009

1.34

-1.11

32.72

2.54

-3.20

18.05

2009-2014
8.18
8.46
5.73
5.17
8.25
-2.42
Note: Data processing, hosting, and related services is categorized under Input-Output
Commodity Classification code MPS518 for Canada and BEA Input-Output commodity
Code 512 for the United States.
Source: Author's calculation based on Table 1 and 2.

15

Obviously, this indicator is robust to cyclicality as it controls for GDP. As an example, one can see that the
average intensity continues to increase over the course of the recession following the financial crisis in 2007.

18

The growth rate annualized over the period 2006-2014 is affected by the substantial fall ingrowth during the period following the financial crisis in 2007 (i.e. 2007-2009).16 We see that thegrowth in the purchase of computing services was again robust after 2009 in Canada and theUnited States. For the United States, the annual growth in the private sector was actually higher
after 2009 than during any sub-period before 2006.
It is true that when one takes a growth rate, it fluctuates (i.e. goes up and down) over time as
we get to de-trend the time-series. However, it should be noted that a growth rate still tends tofall substantially during a recession. This affects the growth rate annualized over a period that
includes the recession. Hence, annual growth rates would pick up not only the potential effect ofcloud computing but also a cyclical component of the movement in the purchase of computing
services.
Note also that data processing, hosting and related services include not only cloud services
but also other types of computing service. Hence, the slower growth rate after 2006 may notnecessarily be related to cloud services. We actually find evidence that the importance of cloudservices in data processing, hosting, and related services has been increasing over time.
As we present in the following subsection in more detail, the share of “hosting andinformation technology infrastructure provisioning services” (e.g. SaaS, IaaS, and PaaS) in the
total sales in data processing, hosting, and related services had increased over time (see Table 6).
Over the same period, the shares of other service types had declined in general. Hence, theslower growth in the purchase of data processing, hosting, and related services might have been
driven by other types of computing services (e.g. firms migrating from conventional computing
to cloud computing).
The implication above suggests that a better indicator for the role of cloud computing is theaverage intensity of the purchase of computing services: it controls for GDP (see Table 4 for its
robustness to cyclicality); and it better captures a general trend of the increasing role of cloudcomputing that emerged after 2006. As a result, we compute counterfactuals based on the
average intensity in the following subsection.
C. Counterfactual Analysis
1. Methodology
In this subsection, we compute counterfactual levels of intermediate purchase that would haveoccurred had there been no wide spread of cloud computing. A key assumption is that any
increase in the average intensity of the purchase in computing services after 2005 is driven by adiffusion of cloud computing.

16

The fall in growth rate during the 2007-2009 period is the biggest drop observed in our sample period, 1997-2014.
We do see a fall in annual growth rate following the burst of the dot com bubble but the extent is much smaller.

19

The counterfactual is computed over the period after 2006 assuming the average intensity
observed during the period prior to 2006 (i.e. GDP multiplied by the average intensity):
𝑃𝑡𝑐 = 𝐺𝐷𝑃𝑡 ∙ 𝑠𝜏
where 𝑃𝑡𝑐 indicates a counterfactual purchase of data processing, hosting, and related services intime 𝑡 and 𝑠𝜏 is the average intensity observed over sub-period, 𝜏.
Here, we compute counterfactuals in two different scenarios: 1. counterfactuals assuming the
average intensity observed during 1997-2005; and 2.counterfactuals assuming the averageintensity observed during 2000-2005. Obviously, the counterfactual would be higher underscenario 2 which uses the average intensity observed during the period closest to 2006-2014. We
believe that counterfactual 2 is likely to present a more realistic estimate as it is based on the
period that covers a more relevant phase of the digitalization of the economy but without a wide
spread of cloud computing (i.e. 2000-2005).
Finally, we estimate the purchase of cloud services by taking the difference between theactual and counterfactual level of the purchase (𝑃𝑡 − 𝑃𝑡𝑐 ). Again, this implies that we assume
additional purchase of data processing, hosting, and related services after 2005 is completely
driven by a rise of cloud computing (net of the effect of a growing economy).
We argue that this is a plausible assumption since cloud computing is the most important IT
development during the mid 2000s. To support this, we refer to the Annual Survey of Software
Development and Computer Services conducted by Statistics Canada. The survey has
information for the breakdown of the total sales in the NAICS industry, data processing, hosting,and related services (NAICS 51821). The breakdown is by the type of computing services. Most
relevant to our analysis is the "hosting and information technology infrastructure provisioning
services" under which cloud services are classified (i.e. SaaS, PaaS, and IaaS).The category
consists of application service provisioning (NAPCS 751112) and other information technology
infrastructure provisioning services (NAPCS 751114). Hence, we believe that this category is avery close proxy for cloud services.
Table 6 reports the breakdown of the total sales in data processing, hosting, and related
services in terms of a share (per cent). We find that the share of “hosting and information
technology infrastructure provisioning services” increased over time while the aggregate share ofother types of service tended to decline. The “hosting and information technology infrastructure
provisioning services” accounted for 56.4 per cent of the total sales in 2008. It increased by 11.2
percentage points over the next 4 years to reach 67.6 per cent in 2012. Other types of service do
not exhibit a clear upward trend in their share.17Although it is not possible to further breakdown
17

It would be useful to compute the absolute level of sales in “hosting and information technology infrastructure
provisioning services” using the shares provided in Table 6, the total purchase of data processing, hosting andrelated service (I-O commodity code MPS 518) given in Table 2, and the share of the total MPS 518 produced by
the NAICS industry 51821 (data processing, hosting, and related services) in Canada. However, the two commodity
categories are not perfectly comparable. Therefore, we do not attempt to impute the absolute level of the sales forthe 2008-2012 period.

20

the category to cloud services, this trend supports our claim that the role of cloud computing in
ICT spending has grown since the introduction of the first widely accessible cloud services in the
mid 2000s.

Table 6: Breakdown of sales in Data processing, hosting, and related services (NAICS 51821) by type of services, per cent, 20082012
Computer
Information andHosting and information
Networksystems
document
Computer systems
technology infrastructure management
managementtransformation
design and related
Software
Other
provisioning services
services
services
services
services
publishing
sales
2008

56.4

7.8

3.8

15.3

9.5

F

7.3

2009

59.3

2.3

1.7

15.0

13.8

F

10.5

2010

68.6

1.2

1.7

15.1

8.7

F

4.5

2011

65.6

1.2

2.2

11.4

11.8

F

7.4

2012
67.6
1.5
1.7
12.1
12.1
1.0
4.0
Note: F indicates that statistics is too unreliable to be published. The shares may not add up to 100.0 due to rounding errors. Data arealso available for the 2013-2015 period (CANSIM Table 354-0012). Unfortunately, due to the changes made to the methods andprocesses used to compile statistics, the data for this period are not comparable to the data reported in Table 6 (This was part of theIntegrated Business Statistics Program (IBSP) launched in 2013. See http://www.statcan.gc.ca/eng/dai/btd/ibsp for details). We findthat, during 2013-2015 period, the share stabilizes: 43.2 per cent in 2013, 43.0 per cent in 2014, and 43.5 per cent in 2015. Again, thelower shares here do not mean that the share has decreased from the previous period. They are not comparable.
Source: Software Development and Computer Services published by Statistics Canada(Catalogue number 63-255-X).

Hence, it is reasonable to argue that cloud computing largely explains the increase in the
average intensity of the purchase of computing services in the economy. Although we do notpresent comparable evidence for the United States, we argue that a similar trend would be foundin that country since it has a cloud computing market of a size much bigger than that in
Canada.18 To check the extent our assumption is true, we also compare our estimates with cloud
spending/revenue data from external sources in the following subsection.
2. Results for Canada and the United States
Table 7 reports our counterfactual levels of intermediate purchase of computer and electronics
components in Canada over the 2006-2014. Had there been no wide diffusion of cloudcomputing in the economy, the upward trend in the purchase of computing services would havebeen much less pronounced after 2006 (see Appendix Chart A1). Instead of rising by $3,850
million CAD, the purchase would have increased by $1,703 million CAD under counterfactual 1
or $1,732 million CAD under counterfactual 2 over the 2006-2014 period. A similar trend isobserved for the United States (Table 8 and Appendix Chart A2).

18

For example, the United States accounts for over 60 per cent of the worldwide spending on the public cloud while
Canada accounts for less than 4 per cent. For example, according to IDC, the worldwide spending reached $70
billion USD. In 2015, the spending in Canada stood at $2.3 billion CAD. See IDC (2016) and "Public Cloud
Spending to Reach Nearly $70 Billion Worldwide in 2015, According to IDC" athttps://www.businesswire.com/news/home/20150721005355/en/Public-Cloud-Spending-Reach-70-BillionWorldwide.

21

Table 7: Counterfactual intermediate purchase of data processing, hosting, and related services (I-O commodity code
MPS 518), basic prices, all industries, Canada, millions of CAD, 2006-2014
Year

ActualCounterfactual 1

Counterfactual 2

Total

Private

Gov't

Total

Private

Gov't

Total

Private

Gov't

2006

5,073

4,727

346

4,576

4,217

359

4,653

4,279

374

2007

5,875

5,506

369

4,825

4,447

378

4,907

4,513

394

2008

6,097

5,709

388

5,058

4,662

396

5,144

4,731

413

2009

6,034

5,384

650

4,944

4,556

387

5,027

4,623

404

2010

6,440

5,785

655

5,244

4,833

411

5,332

4,904

429

2011

7,124

6,450

674

5,584

5,146

438

5,678

5,222

456

2012

7,400

6,695

705

5,750

5,300

451

5,848

5,378

470

2013

8,110

7,299

811

5,986

5,517

469

6,087

5,598

489

2014

8,939

8,080

859

6,279

5,786

492

6,385

5,872

513

Annualized growth rates, %2006-2014
7.34
6.93
12.04
4.03
4.03
4.03
4.03
4.03
4.03
Note: Counterfactual 1 is based on the average % GDP observed during 1997-2005. Counterfactual 2 is based on the
average % GDP observed during 2000-2005.
Source: Author's calculations based on CANSIM Table 381-0033 and input-output tables published by Statistics Canada(Catalogue 15F0041X).

Table 8: Counterfactual intermediate purchase of data processing, hosting, and related services (BEA Input-Output
commodity Code 512), all industries, United States, billions of USD, 2006-2016
Year

ActualCounterfactual 1

Counterfactual 2

Total

Private

Gov't

Total

Private

Gov't

Total

Private

Gov't

2006

92.1

66.4

25.7

81.6

60.5

21.1

84.8

61.8

23.0

2007

102.6

76.9

25.7

85.3

63.2

22.0

88.7

64.6

24.0

2008

109.8

81.0

28.8

86.7

64.3

22.4

90.1

65.7

24.4

2009

107.9

72.0

35.8

84.9

63.0

22.0

88.3

64.4

23.9

2010

112.7

75.3

37.5

88.1

65.3

22.8

91.6

66.8

24.8

2011

120.4

84.2

36.2

88.1

65.3

22.8

91.6

66.8

24.8

2012

127.2

90.1

37.1

95.1

70.5

24.6

98.9

72.1

26.8

2013

132.8

101.0

31.8

98.3

72.9

25.4

102.2

74.5

27.7

2014

138.8

107.1

31.7

102.6

76.1

26.5

106.7

77.8

28.9

2015

147.9

112.0

36.0

106.7

79.1

27.6

111.0

80.9

30.1

2016

153.8

116.4

37.4

109.7

81.3

28.4

114.0

83.1

30.9

Annualized growth rates, %2006-2014
5.26
5.78
3.81
3.00
3.00
3.00
3.00
3.00
3.00
Note: Counterfactual 1 is based on the average % GDP observed during 1997-2005. Counterfactual 2 is based on the average %GDP observed during 2000-2005.
Source: Author's calculations based on input-output tables from the Bureau of Economic Analysis.

22

Our estimates of the purchase of cloud services (difference between actual and counterfactual)in Canada and the United States are reported in Table 9 and Table 10, respectively. For Canada,
the estimated purchase of cloud services ranges from $420 million CAD (counterfactual 2) to$497 million CAD (counterfactual 1) in 2006 accounting for 8.3 per cent and 9.8 per cent of theactual purchase, respectively. The estimated purchase of cloud services increases over time interms of both absolute and relative terms. By 2014, it reaches as much as $2,660 million CAD
under counterfactual 1. This accounts for 29.8 per cent of the total purchase of computing
services in 2014. Under counterfactual 2, the purchase of cloud services is estimated to be $2,554
million CAD in 2014 accounting for 28.6 per cent of the total purchase of computing services
made in that year. This implies that, over the 2006-2014 period, the purchase of cloud services
had increased at an annual rate of 23.3 per cent under counterfactual 1 and 25.3 per cent undercounterfactual 2.

Table 9: Purchase of cloud computing proxied by the purchase of data processing, hosting, and related services(I-O commodity code MPS 518), Canada, 2006-2014
Difference (Actual - Counterfactual), millions of CAD
Counterfactual 1

Counterfactual 2

Year
2006

Total

Private

Gov't

Total

Private

Gov't

497

510

-

420

448

-

2007

1,050

1,059

-

968

993

-

2008

1,039

1,047

-

953

978

-

2009

1,090

828

263

1,007

761

246

2010

1,196

952

244

1,108

881

226

2011

1,540

1,304

236

1,446

1,228

218

2012

1,650

1,395

254

1,552

1,317

235

2013

2,124

1,782

342

2,023

1,701

322

2014

2,660

2,294

367

2,554

2,208

346

Ratio of difference to actual purchase, %Counterfactual 1
Year

Counterfactual 32

Total

Private

Gov't

Total

Private

Gov't

9.8

10.8

-

8.3

9.5

-

2007

17.9

19.2

-

16.5

18.0

-

2008

17.0

18.3

-

15.6

17.1

-

2009

18.1

15.4

40.4

16.7

14.1

37.8

2010

18.6

16.5

37.3

17.2

15.2

34.6

2011

21.6

20.2

35.1

20.3

19.0

32.3

2012

22.3

20.8

36.1

21.0

19.7

33.3

2013

26.2

24.4

42.1

24.9

23.3

39.7

2006

2014
29.8
28.4
42.7
28.6
27.3
40.3
Note: Counterfactual 1 is based on the average % GDP observed during 1997-2005. Counterfactual 2 is based on the
average % GDP observed during 2000-2005. Some negative values for the government sector are omitted(indicated by '-'). For 2006, 2007 and 2008, the intensity of the purchase of MPS 518 by government was smaller than the
average intensity used to compute counterfactuals. Hence, the difference between the actual and counterfactual is negative.
Source: Table 7

23

For the United States, the estimate ranges from $7.3 billion USD to $10.5 billion USD in2006 accounting for 7.9 per cent and 11.4 per cent of the total purchase of computing services,
respectively. Similarly, the estimated purchase of cloud services increases over time in terms ofboth absolute and relative term. Under counterfactual 1, it increases by $25.6 billion USD overthe 2006-2014 period to reach $36.1 billion USD in 2014.19 This accounts for 26.0 per cent of
the total purchase made in the country in 2014. Under a more conventional scenario(counterfactual 2), we estimate that the purchase of cloud services reaches $32.1 billion USD in2014 (an increase of $24.8 billion USD). This accounts for 23.1 per cent of the total purchases
made in 2014. This implies that, over the 2006-2014, the purchase of cloud services rose by 16.7
per cent and 20.4 per cent per year under counterfactual 1 and counterfactual 2, respectively.

Table 10: Purchase of cloud computing proxied by the use of data processing, hosting, and related services(BEA Input-Output commodity Code 512), United States, 2006-2014
Difference (Actual - Counterfactual), billions of USD
Counterfactual 1
Year

Total

2006
2007

Counterfactual 2

Private

Gov't

10.5

5.9

4.6

17.3

13.7

3.7

2008

23.1

16.8

6.4

2009

23.0

9.1

2010

24.6

2011

32.2

2012

32.1

2013
2014

Total

Private

Gov't

7.3

4.5

2.7

13.9

12.3

1.7

19.7

15.3

4.4

13.9

19.6

7.7

11.9

9.9

14.7

21.1

8.5

12.6

18.8

13.4

28.7

17.4

11.4

19.6

12.5

28.3

18.0

10.3

34.5

28.1

6.4

30.6

26.5

4.1

36.1

31.0

5.2

32.1

29.3

2.8

Ratio of difference to actual purchase, %Counterfactual 1
Year

Total

Counterfactual 2

Private

Gov't

Total

Private

Gov't

2006

11.4

8.8

18.0

7.9

6.8

10.6

2007

16.9

17.8

14.3

13.6

15.9

6.6

2008

21.1

20.7

22.1

17.9

18.9

15.1

2009

21.3

12.6

38.7

18.2

10.7

33.2

2010

21.8

13.2

39.2

18.7

11.3

33.7

2011

26.8

22.4

37.0

23.9

20.7

31.4

2012

25.2

21.7

33.6

22.2

20.0

27.7

2013

26.0

27.8

20.0

23.0

26.2

12.8

2014
26.0
28.9
16.3
23.1
27.3
8.8
Note: Counterfactual 1 is based on the average % GDP observed during 1997-2005. Counterfactual 2 is based on the
average % GDP observed during 2000-2005.
Source: Table 8

19Over the 2006-2016 period, it increases by $33.6 billion USD under scenario 1. We focus on the 2006-2014
period to be consistent with the Canadian data.

24

As part of the robustness test, we compare our estimates reported in Table 9 and 10 with thedata available from external sources. We expect to see a similar level of revenue or spending
associated with cloud services in each country. Most relevant data we found for Canada is from
IDC (2016). According to the source, spending on public cloud computing in Canada reached$2,295 million CAD in 2015.20 Given that this figure only includes public cloud, our estimate of$2,554 million CAD for 2014 under counterfactual 2 appears quite realistic.
For the United States, we refer to the World Semiannual Public Cloud Services Tracker
conducted by IDC. According to this source, the worldwide public services revenue reached$45.7 billion USD in 2013 and 68 per cent of the worldwide revenues was attributed to theUnited States.21 This implies that the revenue from public cloud services reached $31.1billion
USD in 2013. Our estimate for 2013 ranges from $30.6 billion to $34.5 billion USD. For 2014,
IDC reported that the worldwide public services revenue reached $56.6 billion USD implying$38.5 billion USD for the United States assuming the share of 68 per cent.22 For 2014, ourestimate suggests that it ranges from $32.1 billion to $36.1 billion USD. Although we tend tounderestimate relative to IDC in both years, our estimates are still reasonably similar to the IDC
estimates.
The key takeaway from this section is that organizations did respond to a rise of cloudcomputing by rapidly expanding their spending on cloud services. The annual growth of 20.4 percent to 25.3 per cent in spending on cloud services indeed reflects their increasing reliance on
cloud computing and more importantly, the extent to which the resources are being shifted tocurrent expenditure (e.g. purchasing SaaS, PaaS, and IaaS) from expenditure on ICT capital
goods.
This, in turn, has led to ICT investment by the cloud services industry (both own-account andpurchasing final outputs). Although the net effect on the total ICT investment is ambiguous, we
argue that the net effect is negative (i.e. lower ICT investment) since a cloud service provider'scomputing resources are pooled to serve many customers based on a multi-tenant model (refer to
Section II for detail). A given unit of ICT capital can serve more organizations. As a result, thetotal demand for ICT capital would be less than the level implied by conventional computing
systems (e.g. each organization setting up their own ICT infrastructure).

20

Data for the period prior to 2015 are not available.
See "IDC Expects Public Cloud Sales to Skyrocket through 2018" at http://www.channelfutures.com/idc-expectspublic-cloud-sales-skyrocket-through-2018
22
See "Public Cloud: Trends and Considerations for Business" at https://www.bcx.co.za/download/public-cloudwhitepaper/
21

25

IV.

Issue Two: Own-account investment in ICT by the IT service sector

We also account for the possibility that cloud service providers assemble ICT equipment on
an own-account basis, at least in part. We pay attention to the fact that a large increase in thecapital expenditure reflected in financial filings of cloud service providers does not seem totranslate into an equivalent increase in the official ICT equipment investment statistics (seeByrne et al., 2017 a, b).

$120

Chart 4: Capital expenditure of selected IT service providers in the
United States, based on financial filings, billions of USD, 1997-2015

100

80

60

40

20

0

Telecommunication service provider

Cloud service providers

Note: Included cloud service providers are U.S.-headquartered companies that meet Cisco's definition of "hyperscale" firms(refer to footnote 8 for detail). They include major cloud service providers such as Amazon Web Services, Rackspace,
Google, Salesforce, Facebook, Yahoo, ADP, Apple. Included telecommunication providers are AT&T, Verizon, Sprint, TMobile U.S., Century Link and related companies. Data are based on company's financial filings.
Source: Byrne et al. (2017b)

Based on capital expenditure reflected in financial filings, Byrne et al. (2017b) show thatmajor cloud providers have engaged in a large degree of capital investment since 2009 (Chart
4).23 However, this does not seem to translate into strong investment reflected in the official
statistics (Chart 5). Note that not all capital expenditure in Chart 4 occurred within the UnitedStates. However, it is likely that most of capital expenditure by cloud service providers would
23This seems to reflect a massive expenditure on cloud infrastructures to house cloud services and cloud-based
resources. For example, for cloud-hosting purpose, large cloud vendors have built multiple data centres of their own.

26

have occurred within the United States since most of their data centres were built in the country(e.g. Google's colocation centre located in New York and AWS's data centre located in Northern
Virginia and Ohio.).
Additionally, Byrne et al. (2017 a, b) show that IT service sectors in the United Statespurchased a large amount of computer and electronics components as intermediate goods
especially since the mid-2000s suggesting that they have assembled ICT equipment internally.
The use of intermediates to build their own ICT equipment is not accounted for by statistics
officials as ICT investment and hence leading ICT equipment investment to be underestimated tosome extent.
It is true that some non-market production is included in the official statistics such as ownaccount software production.24 However, it appears that official statistics do not include ICT
equipment produced within establishments for internal use. This is likely to be the case in
Canada as well. For example, the questionnaire for the business survey conducted by Statistics
Canada does not contain any question regarding own-account capital and infrastructure
investment.25

Chart 5: Investment in ICT equipment, total economy,
United States, billions of USD, 1997-2014
$

250
200
150
100
50

1997

1999

2001

2003

2005

2007

2009

2011

2013

Source: CSLS database for ICT investment. Available at http://www.csls.ca/data/ict.asp

24

Software produced within establishments for internal use is explicitly included as "own-account software
investment" in the United States and "Own-account software design and development services" in Canada.
25
This information was provided by an official at Consumer and Business Services Surveys Division, Statistics
Canada.

27

A. Trends in the intermediate purchase and output in IT service sectors
In this subsection, we examine the intermediate purchase made by IT services sectors in
Canada and the United States to estimate own-account investment in ICT equipment following
the method suggested by Byrne et al. (2017a, b). For the United States, we simply replicate thefindings in Byrne et al. (2017a, b) using the I-O tables from BEA. This is to compare thedevelopment observed in the United States with that observed in Canada.
Following Byrne et al. (2017b), we treat computer and electronic products (IOCC code
M334C for Canada and BEA I-O code 334 for the United States) as the most relevant input usedby cloud service providers to produce their own ICT equipment infrastructure (e.g. servers,
storage devices, and network components). For the BEA input-output tables, we do not haveenough details publicly available to differentiate the individual components in computer andelectronic product. However, we can in the input-output tables published by Statistics Canada. In
Canada, the inputs purchased by the sectors related to cloud services are concentrated in thefollowing sub-categories of computer and electronic product (IOCC M334C): telephoneapparatus and other communications equipment; computers and computer peripherals and parts;
printed and integrated circuits, semiconductors and printed circuit and assemblies; otherelectronic components.
These are essential parts for building cloud infrastructures such as servers, network switches,and data storage equipment. For example, a large amount of purchases of telecommunications
equipment is consistent with the fact that some major cloud service providers started to build
their own submarine cables to enhance the interconnectedness of their cloud data centres (e.g.
Google).
To capture the cloud services sector in a NAICS setting, we focus on a set of sectors called"IT service sectors".26 This is due to the fact that the primary activity of cloud service providers
is covered by more than one sector in NAICS.27 We believe that the IT service sectors we choose
are good representative sectors for the cloud service industry. The IT service sectors haveproduced over 80 per cent of the total data processing, hosting, and related services on average.
For example, in 2014, 84.1 per cent of the total data processing, hosting, and related services (IO commodity code MPS 518) was produced by the IT service sectors in Canada.28Among the IT
service sectors, data processing, hosting, and related services (NAICS 51821),
telecommunications (NAICS 517), and computer systems and design services (NAICS 5415)
accounted for most of the production.29
26

Following Byrne et al. (2017a), we define publishing industries, except internet (includes software) (NAICS 511),
broadcasting and telecommunications ((NAICS 515 and 517), data processing, hosting and related information
services (NAICS 518), other information services(NAICS 519), and computer systems and design services (NAICS
5415) as IT service sectors.
27
For example, the telecommunications sector is included in our IT service sectors. Note that some large
telecommunications firms have shifted a significant part of their business towards providing cloud computing
services using their existing infrastructures (e.g. AT&T, Telus, T-Mobile, Verizon/Terremark).
28
The rest of the production of MPS 518 is spread across a number of sectors.
29
This makes sense since the telecommunications sector now provides cloud services as explained in footnote 27
and the computer systems and design services sector provides services that are highly relevant for cloud computing(i.e. for firms that need migration from conventional computing systems to cloud-based systems).

28

Both in Canada and the United States, the IT service sectors have been purchasing a large
amount of computer and electronic products as intermediate. Table 11 and 12 report theintermediate purchase of computer and electronic products by the IT service sector in Canada
and the United States based on the input-output tables published by Statistics Canada and the
Bureau of Economic Analysis.
Table 11: Intermediate purchase of Computer and electronic products by the IT service sector and its subsectors, millions
of CAD, Canada, 1997-2014
Publishing industries ,data processing, internet
Computer
except internet
Broadcasting andpublishing and othersystems and(includes software)
telecommunication
information services
design services
Year(NAICS 511)
(NAICS 515 and 517)
(NAICS 51821)(NAICS 5415)
Total
1,084
1997
41
1,008
18
17
1998

14

1,046

15

20

1,095

1999

11

972

8

17

1,008

2000

8

1,131

13

19

1,171

2001

10

1,196

13

20

1,239

2002

8

1,287

15

20

1,330

2003

9

1,547

16

23

1,595

2004

11

1,518

19

25

1,573

2005

0

1,665

17

21

1,703

2006

8

1,677

15

20

1,720

2007

9

1,598

14

20

1,,641

2008

9

1,993

15

23

2,040

2009

124

3,065

45

108

3,342

2010

125

3,254

58

149

3,586

2011

162

3,486

73

181

3,903

2012

177

4,073

83

175

4,508

2013

171

4,263

131

234

4,798

2014

208

4,485

124

273

5,089

Annual Growth Rates, %1997-2008

-12.9

6.4

-1.6

2.8

5.9

1997-2006

-16.6

5.8

-2.0

1.8

5.3

2006-2014

50.2

13.1

30.2

38.6

14.5

2006-2008

6.1

9.0

0.00

7.24

8.9

2009-2014
10.9
7.9
22.4
20.4
8.8
Note: Computer and electronic products include: computers and computer peripheral equipment; telephone and othercommunications equipment; televisions and other audio and video equipment; navigational and guidance instruments; unrecorded
magnetic and optical recording media; printed and integrated circuits, semiconductors and printed circuit assemblies; and otherelectronic components. IT service sector includes: publishing industries, except internet (includes software), broadcasting andtelecommunication, data processing, hosting and related information services, other information services, and computer systems
and design services.
Source: CANSIM Table 381-0033 and input-output tables published by Statistics Canada (Catalogue 15F0041X).

29

Before we discuss the data, we present a caveat for the input-output tables for Canada. In
Canada, the change in the classification system in 2009 makes the statistics after 2008 notcomparable to those prior to 2009. After consulting officials at Statistics Canada on this issue,
we conclude that on the industry side, the change is not likely to affect our analysis greatly at theaggregated level (i.e. the IT service sector). However, on the product side, the changes in productdefinitions were significant, making the aggregate statistics (i.e. computer and electronic
products) potentially incomparable to the previous years. Hence, for Canada, we try to avoid
drawing implications without directly comparing the statistics before and after 2009.
In Canada, the total computer and electronic products purchased by the IT service sectors
continued to increase over the 1997-2014 period. It reached $5,089 million CAD by 2014.The
purchase of computer and electronic products as intermediates grew at 5.3 per cent per year overthe 1997-2006 period. However, during the next 8 years (i.e. 2006-2014), it grew at an annual
rate of 14.5 per cent. Even if we focus separately on the 2006-2008 and the 2009-2014 period
due to the 2009 change in the product/industry classification systems, the annualized growth
rates are still higher than that annualized over the 1997-2006 period: 8.9 per cent for 2006-2008
period and 8.8 per cent for the 2009-2014 period.
Note that broadcasting and telecommunications are responsible for most of the purchases of
the intermediate of computer and electronics components. Unlike the United States, we candifferentiate the two sectors in the I-O tables. The data suggest that the intermediate purchase ismainly driven by telecommunications. For example, of the total $4,485 million purchase bybroadcasting and telecommunications in 2014, telecommunications accounted for over 97 percent.
We see a similar trend in the United States. The intermediate purchase of computer andelectronics components by the IT service sector increased significantly over the 1997-2016
period. It reached $71.1 billion USD by 2016, up from $10.6 billion USD in 1997. The increase
accelerated since 2009. The IT service sectors increased its purchase by $40.0 billion USD overthe 2009-2016 period. We do not observe any increase of a comparable degree in the earlier
period. In terms of an annual growth rate, the purchase rose at 12.1 per cent per year during the
2006-2016 period. This is significantly higher than the annual growth rate of 8.8 per centobserved during the previous sub-period (i.e. 1997-2006).
As shown in Byrne et al. (2017b) , this is consistent with the trend we see in Chart 4. Since
2009, cloud service providers started to increase their capital investment significantly. Theircapital expenditures increased from $10.6 billion USD in 2009 to $51.6 billion USD by 2016, anincrease of $41.0 billion USD (Chart 4). This is very close to the $40.0 billion USD increase in
the purchase of computer and electronic components made by the IT service sectors (ascategorized based on NAICS) over the same period. Hence, Byrne et al. (2017b) suggest that thetwo data reflect the same underlying phenomenon.
In both countries, telecommunications sectors are largely driving the trend of the totalpurchase. Yet, as pointed by Byrne et al. (2017b), this is not consistent with Chart 4 in whichtelecommunications providers do not exhibit any strong upward trend. Here, it is important torealize that establishments of cloud services providers could be difficult to distinguish from30

telecommunications centers as they often engage in activities which, under NAICS, would be
categorized as the activity of the telecommunications sector. Note that NAICS used by Statistics
Canada and BEA defines industries as sets of establishments which share a common core activity.

Table 12: Intermediate purchase of Computer and electronic products by the IT service sector and its subsectors,
millions of USD, United States, 1997-2016
Publishing industries ,data processing, internet
except internet
Broadcasting andpublishing and other
Computer systems(includes software)
telecommunication
information services
and design services(NAICS 511)
(NAICS 515 and 517)
(NAICS 51821)(NAICS 5415)
Total
1997

1,847

6,594

422

1,739

10,602

1998

1,921

6,837

415

2,558

11,731

1999

1,768

9,909

783

3,585

16,045

2000

3,321

12,081

1,323

4,429

21,154

2001

2,962

9,709

1,164

3,477

17,312

2002

2,360

8,922

896

3,602

15,780

2003

2,483

10,427845

3,292

17,047

2004

2,562

12,392691

3,059

18,704

2005

2,613

13,529901

2,869

19,912

2006

3,180

15,694

938

2,825

22,637

2007

2,658

20,447

1,803

2,520

27,428

2008

3,003

18,915

2,393

3,278

27,589

2009

2,703

22,546

2,777

3,019

31,045

2010

2,642

30,230

2,959

4,397

40,228

2011

2,764

38,358

3,750

4,506

49,378

2012

2,425

39,861

5,267

4,739

52,292

2013

2,358

40,545

5,211

4,563

52,677

2014

2,567

41,569

5,595

4,216

53,947

2015

1,856

52,889

5,519

4,207

64,471

2016

1,929

59,290

5,469

4,374

71,0625.5

8.8

Annual Growth Rates, %1997-2006

6.2

10.1

9.3

2006-2016
-4.9
14.2
19.3
4.5
12.1
Note: Computer and electronic products include: computers and computer peripheral equipment; telephone and othercommunications equipment; televisions and other audio and video equipment; navigational and guidance instruments;
unrecorded magnetic and optical recording media; printed and integrated circuits, semiconductors and printed circuitassemblies; and other electronic components. IT service sector includes: publishing industries, except internet (includes
software), broadcasting and telecommunication, data processing, hosting and related information services, other information
services, and computer systems and design services.
Source: Input-output tables published by Bureau of Economic Analysis

Byrne et al. (2017b) provide some examples: Google's New York headquarters is a major
colocation centre (or "carrier hotel"). It is a physical location where data communications media
converge and are interconnected. To minimize overhead and optimize communications
efficiency, telecommunications firms use this facility to bridge their fiber networks. Anotherexample is that some cloud services firms have begun constructing submarine cables and other31

portions of the long-haul communications network. For example, Google announced in 2018 thatthey plan to invest in three new submarine cables of their own in order to increase the amount of
bandwidth on their global network interconnecting their cloud data centres.30 Hence, it appears
that the intermediate purchase of computers and electronics by telecommunications based on
input-output tables and capital expenditure by the cloud service providers in Chart 4 reflect thesame underlying investment activity.
Despite that the IT service sectors have purchased a substantial amount of computer andelectronic components, the output data suggest that they have produced essentially zero final
computer and electronic products over the 1997-2014. Especially, in both countries, the IT
service sectors produced zero output during the period when they substantially increase thepurchase of computer and electronic components (i.e. 2009-2014).
B. Estimates of own-account investment

Table 13: Estimates of own-account investment, Canada and the United States, 2006-2014
Canada, millions of CAD

United States, millions of USD

(1)

(2)

(1)

(2)

2006

1,720

3,440

22,63745,274

2007

1,641

3,282

27,42854,856

2008

2,040

4,080

27,58955,178

2009

3,342

6,684

31,04562,090

2010

3,586

7,172

40,22880,456

2011

3,903

7,805

49,37898,756

2012

4,508

9,017

52,292

104,584

2013

4,798

9,597

52,677

105,354

2014
5,089
10,17853,947
107,894
Note: Column (1) is based on the assumption that the value of the own-account production of final
computer/electronics is equal to the value of the computer/electronic intermediates used. Column (2)assumes that the value is equal to twice the value of intermediate used.
Source: Author's calculations based on the I-O tables published by Statistics Canada and the Bureau
of Economic Analysis.
Source: Table 11 and 12

Data from the input-output tables suggest that cloud service providers are engaging in ownaccount investment to a great extent. Table 13 reports our estimate of own-account investment
for Canada and the United States. The estimates are simply based on the intermediate purchaseof computing and electronics components adjusted for the value added from assembling andinstalling ICT equipment.
30

See "Three New Submarine Cables to Link Google Cloud Data Centers" and "Will the Submarine Cable Boom
Drive More Revenue to Colos?" available at: http://www.datacenterknowledge.com/google-alphabet/three-newsubmarine-cables-link-google-cloud-data-centers;http://www.datacenterknowledge.com/archives/2017/02/16/willnew-submarine-cables-boost-data-center-provider-revenue

32Expenditures by firms is treated either as intermediate expenditures or as investments. If thesector undertakes own-account investment in ICT equipment, then the costs associated with thisactivity (e.g. costs in purchasing components; costs in assembling and installing ICT equipment)
should be capitalized not expensed since these costs create a value that lasts into in the future.
However, it is difficult to precisely estimate the value own-account investment in ICT
equipment. Since both Statistics Canada and BEA do not include own-account investment inequipment in the accounts, there is no good template for us to follow. Instead, we refer to theirapproach in estimating the value of own-account software development.
Statistics Canada assess the value of own-account software development based on an
estimation of labour costs for computer programmers and system analysts and other costs (nonsalary) of in-house software production. Similarly, BEA estimates own-account investment insoftware using a "sum of costs" approach. Their estimates are based on production costs such as
worker compensation and intermediate expenses. Following this logic and Byrne et al. (2017a),
we adjust the value of own-account investment by making the following two assumptions: 1. thevalue of the own-account production of final computer and electronics is equal to the value of thecomputer and electronic intermediates used; and 2. the value is equal to twice the value ofintermediate used.31
Based on our conventional estimates (column 1 in Table 13), in Canada, own-accountinvestment in the IT service sectors amounted to $5,089 million CAD in 2014 up from $1,720
million CAD in 2006, an increase of $3,369 million CAD. In the United States, with an increaseof $31,310 million USD from 2006 to 2014, own-account investment reached $53,947 million
USD in 2014.
Again, the estimates for the United State is consistent with Chart 4 which shows the capital
expenditure of major IT service providers (U.S.-headquartered) based on financial filings. From2006 to 2014, capital expenditure rose by $34,100 million USD (or $31,300 million USD if we
consider only the cloud service providers).
We recognize that capital expenditure in Chart 4 also includes investment done outside theUnited States. However, we argue that a substantial part of the capital expenditure occurred
within the United States especially during the period when major cloud service providers firststarted to build their cloud infrastructures (e.g. AWS's data centre located in Northern Virginia
and Ohio). Hence, we believe that our estimate and the financial data are reasonably consistentand they represent the same underlying investment activities.

31

In Byrne et al. (2017), they note that the second assumption is still likely to be conservative citing Gartner, Inc's
finding that the market value of personal computers is roughly four times the value of electronic inputs.

33

V.

Augmented ICT investment in Canada and the United States

To provide a general idea of the impact of own-account investment on the ICT investment
statistics, we augment the official ICT investment measure with the value of own-account ICT
investment by the IT service sector. This alternative ICT investment measure would better reflect
how ICT investment has responded to the recent rise in the role of cloud computing in the ICT
market.
A. Augmented investment in ICT equipment
Chart 6 and 7 show the augmented investment in ICT equipment in Canada and the UnitedStates using our estimates from Table 13 (see also Appendix Table A1 and A2). Panel A in eachchart depicts the level of augmented investment in ICT equipment.
Panel A in Chart 6 shows the level of investment for Canada. Investment in ICT equipment
entered a slight downward trajectory following the financial crisis in 2007. Based on the official
statistics, investment in ICT equipment did not recover as of 2014. However, adding ownaccount investment greatly moderate this downward trend or even turns it into a slight upward
trend if we adopt a less conservative assumption (augmented series 2).
More importantly, adding own-account investment changes the "weak investment in ICT
equipment" story markedly. The augmented investment series implies that a slowdown in the
ICT equipment investment after 2000 was of a lesser degree. Appendix Table A1 reports annual
growth rates of investment in ICT equipment. Augmenting the statistics changes the annual
growth rate for 2006-2014 from -2.82 per cent to as high as 0.99 per cent (adding 3.81
percentage points). To account for the 2009 change in the classification system used in the inputoutput tables, we also annualize the growth rates separately over the 2006-2008 and 2009-2014
period. A general story holds the same. Adding own-account investment substantially raises theannual growth rates.
In terms of a share in nominal GDP, augmenting the official statistics moderates thedownward trend (Panel B in Chart 6). In general, investment in ICT equipment as a share of
GDP slowed from 2000. We observe that adding own-account investment on cloudinfrastructures from 2006 moderates the downward trend in the share. Instead of falling to 0.91
per cent in 2014 from 1.47 per cent in 2005, our estimate suggests that the share should be in therange of 1.17 per cent to 1.42 per cent in 2014.With the augmented series, the average shareranges from 1.38 per cent to 1.57 per cent during the period 2006-2014 instead of 1.18 per cent(see Appendix Table A2).

34

Chart 6: ICT equipment investment augmented by own-account ICT equipment
investment by the IT service sector, Canada, billions of CAD, 1997-2014
Panel A: Level, billions of CAD
30
28.1
25
23.0
20
17.9
15
10
5

Augmented series_1

Augmented series_2

ActualPanel B: A share of GDP, per cent
2.5
2.0
1.5

1.42
1.17

1.0

0.91

0.5
0.0

Augmented series_1

Augmented series_2

ActualNote: Augmented series_1 and Augmented series_2 correspond to column (1) and (2) in Appendix Table A1,
respectively.
Source: Author's calculation based on Table 13 and the CSLS database for ICT investment.

35

Chart 7: ICT equipment investment augmented by own-account ICT equipment
investment by the IT service sector, United States, 1997-2014
Panel A: Level, billions of USD, 1997-2014
350
300

294.0

250

240.0

200

186.1

150
100
50

Augmented series_1

Augmented series_2

ActualPanel B: As a share of GDP, per cent
2.5
2.0
1.69
1.5

1.38
1.07

1.0
0.5
0.0

Augmented series_1

Augmented series_2

ActualNote: Augmented series_1 and Augmented series_2 correspond to column (1) and (2) in Appendix Table A1,
respectively.
Source: Author's calculation based on Table 13 and the CSLS database for ICT investment.

36

Panel A in Chart 7 shows the level of ICT equipment investment for the United States.
Adding own-account ICT investment by the IT service sector changes the trend quite
significantly especially after 2009. The level of investment did not recover significantly after
reaching the lowest point during the recession after the financial crisis in 2007. However, ouraugmented series suggests that the investment in ICT equipment actually recovered and entered a
upward trajectory since 2009. In 2014, our estimates show that investment in IT equipment
should range from $240.0 to $294.0 billion USD (29.0 per cent to 58.0 per cent higher than theactual statistics).
As in Canada, the United States also experienced notably weak ICT equipment investment
especially after 2000. Again, augmenting the series with own-account ICT investment by the IT
service sector results in a quite different story. Relative to the official statistics, the annual
growth rate implied by the augmented series was much higher. The investment in ICT equipment
fell during the period 2006-2014 with an annual rate of -0.48 per cent. Augmenting the serieschanges the negative rate to a positive rate during this period: -0.48 per cent to 2.64 per cent.
This is additional 3.12 percentage points (see Appendix Table A1).
A stronger ICT investment is also found in terms of a share of GDP. The share continued to
decline from 2006 based on the official data. Adding own-account ICT investment by the IT
service sector again changes this trend. The augmented series suggests that investment in ICT
equipment as a share of GDP in 2014 should be in the range of 1.38 per cent to 1.69 per centinstead of 1.07 per cent (Panel B in Chart 7). This is the result of an increasing share from 2005:
the share stood at 1.34 per cent. Moreover, we find that during the 2006-2014 period, the average
share is higher than that suggested by the official statistics. During this period, our estimates
imply that the average share should range from 1.47 per cent to 1.73 per cent instead of 1.22 percent as suggested by the official statistics.
B. Augmented ICT investment
How would total ICT investment have evolved in the two countries if own-accountinvestment by the IT service sectors are taken into account? In Section I, we show that ICT
investment in both countries grew at a much slower rate and its share in GDP fell since the early
2000s (see Chart 1 and Table 1). Chart 12 and 13 depict official ICT investment series alongwith two sets of augmented series. Appendix Table A3 and A4 presents the data points in those
two charts from 2006 along with annualized growth rates and average shares in GDP.
Panel A in Chart 8 shows the level of ICT investment in Canada. ICT investment reachedthe highest in 2008 after recovering from a brief slump following the burst of the dot com bubble.
From 2008, ICT investment started to fall and it did not recover fully as of 2014. Adding ourestimates to the ICT investment changes the trend markedly. While the official series of ICT
investment fell by $1.7 billion CAD from 2008 to 2014, augmented series 2 suggests that it
actually increased by $4.3 billion CAD.

37

Chart 8: ICT investment (augmented and actual), Canada, billions of CAD, 1997-2014
Panel A: Level, billions of CAD
60
52.3
47.2
42.2

50
40
30
20
10

Augmented ICT investment series_2

Augmented ICT investment series_1

Actual ICT investment

Panel B: As a share of GDP, per cent
3.5
3.0
2.65
2.39
2.14

2.5
2.0
1.5
1.0
0.5
0.0

Augmented ICT invesment series_1

Augmented ICT investment series_2

Actual ICT investment
Note: Augmented series_1 and Augmented series_2 correspond to column (1) and (2) in Appendix Table A1,
respectively.
Source: Author's calculation based on Appendix Table A1 and the CSLS database for ICT investment. Available at
http://www.csls.ca/data/ict.asp

38

A more important result is that augmenting the official series implies stronger ICT
investment in terms of both an annual growth rate and a share of GDP. First, when we augment
the official series with the own-account investment, the annual growth rate during the 2006-2014
period is raised by as much as 1.71 percentage points: 0.48 per cent vs. 2.19 per cent (seeAppendix Table A3).32 This is a substantial addition.
Panel B shows ICT investment as a share of GDP. As we discussed, the share of ICT
investment has been on a downward trajectory since the early 2000s. Although this is still true
with our augmented series, the downward trend is much attenuated. Note that the downward
trend becomes more pronounced after 2006 according to the official statistics. With theaugmented series 2, the share stabilizes after 2006 instead of falling. The share reaches 2.65 per
cent, down from 2.70 per cent in 2005. This contrasts to the official statistics which shows a 0.66
percentage-points-decrease from 2005 to reach 2.14 per cent in 2014.33
Chart 9 shows the official and augmented ICT investment series for the United States. Again,
adding our estimates to the official series changes the picture quite considerably. After the troughin 2009, official ICT investment recovered to $539.8 billion USD by 2014 from $460.4 billion
USD in 2009, an increase of$79.4 billion USD. The estimates based on augmented series 2
suggest that ICT investment at the 2009 trough is $522.5 billion USD instead of $460.4 billion
USD. With an increase of $125.2 billion USD from 2009, the level of ICT investment reaches ashigh as $647.7 billion USD in 2014.
More important to us is that the annual growth rates tend to be higher with the augmented
series during the period 2006-2014 (see Appendix Table A3). The own-account investment incloud infrastructures boosts the annual growth rate by as much as 1.12 percentage points during
this period: 3.34 per cent instead of 2.22 per cent.
We also observe stronger ICT investment in terms of a share of GDP (Panel B in Chart 9).
Unlike Canada, the United States did not enter a clear downward trajectory in the share from2006. However, ICT investment still remained weak as the share stayed below the level observedin the early 2000s. Augmenting the series changes this trend significantly. Our augmented series
suggests that the share of ICT investment should have reached 3.42 per cent to 3.73per cent by
2014 instead of 3.11 per cent. This implies that ICT investment (as a share of GDP) had ameaningful recovery since the slump in the early 2000s. Our estimates indicate that the average
share during the 2006-2014 period should be in the range of 3.45 per cent to 3.70 per cent. This
compares to the average share of 3.19 per cent suggested by the official statistics during thisperiod (see Appendix Table A3).

32

The same pattern holds true if the growth rate annualized separately over the 2009-2014 period (accounting forthe change in the classification system in the input-output tables in 2009). The annual growth rate was as weak as
0.60 per cent during this period. However, the augmented series implies that the growth rate could have been as highas 1.91 per cent per year.
33
The average share stands at 2.82 per cent during the 2000-2005 period but it fall to 2.44 per cent during the 20062014 period (see Appendix Table A3). With the augmented series, the average share ranges from 2.63 per cent to2.82 per cent during the 2006-2014 period.

39

Chart 9: ICT investment (augmented and actual), billions of USD, United States,1980-2014
Panel A: Level, billions of USD
700

647.7

600

593.7
539.8

500
400
300
200
100

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014
Augmented ICT investment (upper bound)

Augmented ICT investment (lower bound)

ActualPanel B: As a shre of GDP, per cent
5.0
4.5
4.0

3.73
3.42
3.11

3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014
Augmented ICT investment series_1

Augmented ICT investment series_2

Actual ICT investment
Note: Augmented series_1 and Augmented series_2 correspond to column (1) and (2) in Appendix Table A1,
respectively.
Source: Author's calculation based on Appendix Table A1 and the CSLS database for ICT investment.

40

Although these augmented series are exploratory and should be assessed cautiously, the key
takeaway is that ICT investment in both Canada and the United States appears to have responded
significantly to the recent rise of cloud computing in their economies. For both countries, asignificant part of the “weak ICT investment story” discussed in Section I (with Chart 1 andTable 1) can be attributed to own-account equipment investment by cloud service providers.
We conclude this section by suggesting that there are other important measures potentiallybeing underestimated in the official statistics. For example, adding own-account investment by
the IT sector to ICT equipment would lead to a higher capital stock and labour productivity
growth. For example, Byrne and Corrado (2017) show that the contribution of ICT technologies
to labour productivity is substantial (1.4 percentage points per year). More importantly, they findthat about 25 per cent of the total ICT contribution is attributed to the diffusion of ICT
technology through purchases of cloud and related ICT services.
GDP is also a good example in this case. Appendix Table A4 present actual and augmented
nominal GDP for Canada and the United States. Accounting for own-account investment by the
IT service sectors would raise the 2014 GDP in Canada by 0.52 percent and add 0.04 percentage
point to the annual growth rate of GDP during the 2006-2014 period (based on the augmented
series 2). For the United States, it would raise the 2014 GDP by 0.62 per cent and add 0.04
percentage point to the growth rate from 2006 to 2014 (see Appendix Table A4).

VI.

Conclusion

This report explores the potential role of cloud computing in explaining the weak ICT
investment in Canada and the United States. Specifically, we hypothesize that the weak ICT
investment might be due in part to the shift of expense from capital to services. Cloud computing
allows organizations to access computing resources without having tangible and intangible
infrastructures on premises. Second, major cloud services providers now undertake own-accountinvestment (e.g. assembling servers and building cloud infrastructures internally). Suchinvestment is omitted from official statistics. For example, a discussion with some officials at
Statistics Canada revealed that own-account investment in ICT equipment is not included in theofficial ICT investment series in Canada.
We summarize our main findings as follows. Using the input-output tables, we estimate thatthe purchase of cloud services in Canada reached $2,554 million CAD in 2014, up from $420
million CAD in 2006, resulting in an annual growth rate of 25.3 per cent. In the United States,
our estimate suggests that the purchase of cloud services reached $32.1 billion USD, up from
$7.3 billion USD in 2006. This implies an annual growth rate of 20.4 per cent. These estimates
are consistent with the IDC estimates of spending on cloud services in Canada and the UnitedStates. In both countries, our results suggest that a substantial amount of resources has beenreallocated from purchasing ICT capital goods to purchasing cloud services.
Second, we estimate own-account ICT equipment investment in the "IT service sector" which
presumably cover core activities of cloud service providers. Based on our conventional estimates,
own-account ICT investment by the IT service sector in Canada reached $5.1 billion CAD by
2014. In the United States, it reached $53.9 billion USD in 2014, up from $22.6 billion USD in41

2006. This is an increase of $31.3 billion USD over the 8-year period. This is consistent with thetrend in capital expenditure (based on financial filings) worldwide by major cloud service
providers headquartered in the United States. From 2006 to 2014, their capital expenditure
increased by $31.3 billion USD. We argue that a substantial share of this increase occurred
within the United States as major cloud service providers had built their main data centres andcloud infrastructures across the country.
Adding our estimates of own-account ICT investment by the IT service sector to official ICT
investment statistics changes ICT investment performance markedly. With the augmented ICT
investment statistics, in Canada, ICT investment as a share of GDP stabilizes after 2006 insteadof falling. In terms of an average annual growth rate, ICT investment growth still slows down
after 2006 but the degree is lessened. Adding own-account investment results in an additional
1.71 percentage-points annual growth in the nominal ICT investment during the 2006-2014
period. In the United States, adding own-account investment results in a slight upward trend in
the ICT investment as a share of GDP. Also, it leads to an annual growth rate of 3.34 per centduring the 2006-2014 period, 1.12 percentage points higher than the actual annual rate.
This report is exploratory in nature in addressing the two important facets of the changing
ICT spending pattern driven by a rise of cloud computing. In this report, we propose a line ofresearch on the impact of cloud computing on ICT investment activities. We hope our researchleads to further debate on cloud computing and better data collection on the cloud services sector.
This would contribute not only to better measurement of ICT investment but also to a better
understanding of the changing ICT spending pattern in an increasingly digitalized economy.
We conclude our report by suggesting some future directions for data collection on the cloudservices sector as well as future research agendas. First, questions regarding own-accountinvestment in ICT equipment should be included in the survey for the computing services
industry done by Statistics Canada and the Bureau of Economic Analysis. This would resolve themeasurement issue we discuss in section IV.
Second, we suggest that the breakdown of sales in computing services sectors (as in Table 6)
includes a separate category for cloud services as cloud services are increasingly importantintermediate inputs purchased by the total economy in Canada and the United States. Better
estimates of the purchase of cloud services would help researchers shed more light on thechanging ICT spending pattern and its impact on the overall economy.
Finally, it would be useful to compile official data that indicate how much of cloud services
are provided by the firms based in the United States to organizations in Canada. This is related toa future research direction we present in the following.
Research on the market structure of cloud computing in North America would be important.
In this report, we estimate the purchase of cloud services made by organizations in Canada. Notethat it is likely that Canadian organizations purchase a substantial amount of cloud services fromthe U.S.-based firms with Canadian operations. There is enough anecdotal evidence to motivate
research on how much of the total cloud services purchased in Canada is from the firms in the
United States. For example, there are U.S.-based cloud service providers that have substantial
42Canadian operations but without main data centres located within Canada.34 The IDC report in2015 indicates that these two firms hold over 50 per cent of the total Canadian market share.35 If
this is indeed true, then the changing ICT spending pattern in Canada is largely supported or
facilitated by the cloud service providers in the United States. Moreover, most of capital
expenditure by major cloud service providers would have occurred within the United Statesrather than in Canada.
Due to the lack of official data on the cloud services sector, we currently do not have a full
picture on the cloud computing market in Canada. The cloud computing market in Canada ismost likely to be in the form of oligopoly with a few major cloud service providers dominating
the market. Examples are Google, Microsoft Azure, and Amazon Web Services. Although muchsmaller in size, we do have cloud service providers based in Canada such as Bell, Cogeco,
Rogers, Telus, and CenturyLink. These are the cloud service providers serving Canadianorganizations with their data centres located within Canada.36
There are a number of signs that these Canadian cloud service providers are expanding theircloud businesses within Canada. For example, Telus recently announced construction of a new$65 million data centre in Rimouski, Quebec to provide cloud services. In 2018, Bell alsoannounced that they are building a new data centre ($100 million) in Ottawa.37 However, withcurrent official data, we cannot assess the role of these Canadian firms in providing cloudservices to customers in Canada. A relevant statistic to construct would be a concentration ratioof major cloud service providers (U.S- and Canada-based, respectively) in the cloud computing
market in Canada. This would have implications for the market share of the U.S.-based cloudservice providers in the Canadian cloud computing market.
Another line of research can be on the relationship between a higher utilization rate of ICT
resources via cloud computing and the change in demand for ICT capital goods. Throughout thereport, we emphasize that cloud computing leads to a higher utilization rate of ICT
infrastructures within cloud service providers. However, we do not attempt to explicitly quantify
the effect of such efficiency gain on ICT investment in the report.
Before cloud computing, it was common for a firm to install servers and data storage devices
separately for each department. Such a deployment system of IT equipment inherently has alower capital utilization rate than cloud computing due to difficulty in server integration. The
difficulty is stemmed from differences between servers’ busy and idle periods and differences in
34

Amazon Web Service (AWS) does have a data centre in Canada. However, most of the infrastructure owned by
AWS and other major cloud service providers is located within the United States.
35
See "Top 10 Canadian cloud providers revealed: IDC Canada" at
https://www.computerdealernews.com/news/top-10-canadian-cloud-providers-revealed-idc-canada/39892
36
For example, Cogeco has data centres in Barrie, Toronto, and Montreal; CenturyLink in Vancouver, Toronto, andMontreal; Rogers in Vancouver, Edmonton, Calgary, Oakville, Toronto, London, Hamilton, Ottawa, and Halifax.
37
See "TELUS to build $65 million Intelligent Internet Data Centres in Rimouski, Quebec" athttps://www.newswire.ca/news-releases/telus-to-build-65-million-intelligent-internet-data-centre-in-rimouskiquebec-508253731.html. For Bell, see "New Bell Data Centre to Offer National Capital Region enhanced security,
availability, and energy efficiency" at https://www.newswire.ca/news-releases/new-bell-data-centre-to-offernational-capital-region-enhanced-security-availability-and-energy-efficiency-507481001.html

43system life cycles. Cloud computing solves these problems since a cloud service provider'scomputing resources are pooled to serve many organizations based on a multi-tenant model. A
given unit of ICT capital resource of cloud service providers can support more ICT operations
than the same unit of ICT resource of individual organizations without cloud computing.
Hence, we hypothesize that the net effect of cloud computing on the demand for ICT capital
goods is likely to be negative due in large part to the efficiency gain within cloud service
providers. This efficiency gain could more than offset the increase in demand for ICT capital
goods by cloud service providers as they meet the demand for their services. We believe that thisphenomenon could explain a large part of the "weak ICT investment" story in Canada and theUnited States.

References
Bain and Company (2017), The Changing Faces of the Cloud, available at
http://www.bain.de/Images/BAIN_BRIEF_The_Changing_Faces_of_the_Cloud.pdf
Byrne D., and Corrado, C. (2017), ICT Services and Their Prices: What Do They Tell Us About
Productivity and Technology?, International Productivity Monitor,No.33, pp.150-181
Byrne D., Corrado, C., and Sichel, D. (2017a), The Rise of Cloud Computing: Minding Your P’s
and Q’s, Paper presented at the NBER/CRIW conference, Measuring and Accounting forInnovation in the 21st century, held in Washington, D.C., March 10-11, 2017.
Byrne D., Corrado, C., and Sichel, D. (2017b), Own-Account IT Equipment Investment, Feds
Note, October 4t, 2017https://www.federalreserve.gov/econres/notes/feds-notes/own-account-it-equipment-investment20171004.htm
Canadian Channel Chiefs Council (2017), The Dynamics of the Canadian IT Market, Cloud
Adoption Rates, and the Status of the Channel
https://www.channelchiefs.ca/wp-content/uploads/2017/05/C4-Ryerson-IDC-Joint-ResearchStudy-v2.pdf
International Data Corporation (2015), IDC FutureScape: Worldwide Cloud 2016 Predictions Mastering the Raw Material of Digital Transformation, IDC report #259840
International Data Corporation (2016), How the Microsoft Ecosystem and Cloud Computing
Will Create 110,000 New Jobs in Canada from 2015 to 2020, IDC report #CA41566716
International Trade Administration (2016), 2016 Top Markets Report Cloud Computing,https://www.trade.gov/topmarkets/pdf/Cloud_Computing_Top_Markets_Report.pdf
Kuwazu, K. (2015), Increased Adoption of Cloud Services and Its Impact on the ICT Market,
Nomura Research Institute, No. 205
44

KPMG (2017), Journey to the Cloud,https://assets.kpmg.com/content/dam/kpmg/xx/pdf/2017/02/the-creative-cios-agenda-journey-tocloud.PDF
Mell Peter and Timothy Grance (2011), The NIST definition of Cloud Computing, NIST Special
Publication 800-145
Thomas, Jasmin (2015), An Analysis of the Canada-U.S. ICT Investment Gap: An Update to2013, CSLS research report 2015-01.
Thomas, Jasmin (2016), New Evidence on the Canada-U.S. ICT Investment Gap, 1976-2014,
CSLS research report 2016-17

45

VII.

Appendix: Additional Tables and Charts

A. Tables
Table A1: Augmented investment in ICT equipment, Canada and the United States, 2006-2016
Canada(billions of CAD)
ActualUnited States(billions of USD)

Augmented (billions of CAD)
(1)

(2)

ActualAugmented (billions of USD)
(1)

(2)

2006

22.5

24.2

26.0

193.4

216.0

238.6

2007

21.8

23.5

25.1

206.9

234.3

261.7

2008

22.9

25.0

27.0

193.8

221.4

249.0

2009

21.0

24.4

27.7

169.6

200.7

231.7

2010

18.9

22.5

26.1

183.0

223.2

263.4

2011

18.7

22.6

26.5

176.7

226.1

275.4

2012

18.2

22.7

27.2

179.2

231.5

283.8

2013

17.1

21.9

26.7

186.8

239.4

292.1

2014

17.9

23.0

28.1
186.1
Annual Growth Rate (%)

240.0

294.0

2006-2014

-2.82

-0.65

0.99

-0.48

1.33

2.64

2006-2008

0.94

1.53

2.03

-

-

-

2009-2014
-3.16
-1.16
0.26
Note: Column (1) is based on the assumption that the value of the own-account production of final
computer/electronics is equal to the value of the computer/electronic intermediates used. Column (2) assumes that thevalue is equal to twice the value of intermediate used. To account for the 2009 change in the classification system usedin the input-output tables, we annualize the growth rate separately over the 2006-2008 and 2009-2014 period for
Canada.
Source: Author's calculations based on the I-O tables published by Statistics Canada and the Bureau of Economic
Analysis.

46

Table A2: Augmented investment in ICT equipment as a share of nominal GDP, Canada and the United States,
per cent, 2006-2016
CanadaUnited States
ActualAugmented series
(1)

(2)

ActualAugmented series
(1)

(2)

2006

1.51

1.62

1.74

1.40

1.56

1.72

2007

1.39

1.49

1.60

1.43

1.62

1.81

2008

1.39

1.51

1.63

1.32

1.50

1.69

2009

1.34

1.56

1.77

1.18

1.39

1.61

2010

1.14

1.35

1.57

1.22

1.49

1.76

2011

1.06

1.28

1.50

1.14

1.46

1.77

2012

1.00

1.25

1.49

1.11

1.43

1.76

2013

0.90

1.16

1.41

1.12

1.44

1.75

2014

0.91

1.17

1.42

1.07
Average Share

1.38

1.69

2006-2014
1.18
1.38
1.57
1.22
1.47
1.73
Note: Column (1) is based on the assumption that the value of the own-account production of final
computer/electronics is equal to the value of the computer/electronic intermediates used. Column (2) assumes that thevalue is equal to twice the value of intermediate used.
Source: Author's calculations based on the I-O tables published by Statistics Canada and the Bureau of Economic
Analysis.

47

Table A3: Augmented ICT investment, Canada and the United States, 2006-2016
Canada (billions of CAD)
ActualUnited States (billions of USD)

Augmented (billions of CAD)
(1)

(2)

ActualAugmented (billions of USD)
(1)

(2)

2006

40.6

42.3

44.0

452.7

475.3

498.0

2007

42.2

43.8

45.5

483.4

510.8

538.3

2008

43.9

46.0

48.0

486.7

514.3

541.9

2009

40.9

44.3

47.6

460.4

491.5

522.5

2010

40.2

43.8

47.3

470.5

510.7

550.9

2011

40.3

44.2

48.1

484.0

533.4

582.8

2012

41.5

46.0

50.5

502.2

554.5

606.8

2013

40.5

45.3

50.1

521.2

573.9

626.6

2014

42.2

47.2

52.3
539.8
Annual Growth Rate (%)

593.7

647.7

2006-2014

0.48

1.40

2.19

2.22

2.82

3.34

2006-2008

4.06

4.26

7.82

-

-

-

2009-2014
0.60
1.31
1.91
Note: Augmented series_1 and Augmented series_2 correspond to column (1) and (2) in Appendix Table A1,
respectively. To account for the 2009 change in the classification system used in the input-output tables, we annualize
the growth rate separately over the 2006-2008 and 2009-2014 period for Canada.
Source: Author's calculation using the data in Appendix Table A1 and the CSLS database for ICT investment. Available
at http://www.csls.ca/data/ict.asp

48

Table A4: Augmented ICT investment as a share of nominal GDP, Canada and the United States,per cent,2006-2016
CanadaUnited States
ActualAugmented series
(1)

(2)

ActualAugmented series
(1)

(2)

2006

2.72

2.83

2.95

3.27

3.43

3.59

2007

2.68

2.79

2.89

3.34

3.53

3.72

2008

2.66

2.78

2.90

3.31

3.49

3.68

2009

2.61

2.82

3.04

3.19

3.41

3.62

2010

2.42

2.63

2.85

3.14

3.41

3.68

2011

2.28

2.50

2.72

3.12

3.44

3.76

2012

2.28

2.53

2.77

3.11

3.43

3.76

2013

2.14

2.39

2.65

3.13

3.44

3.76

2014

2.14

2.39

2.65

3.11
Average Share

3.42

3.73

2006-2014
2.44
2.63
2.82
3.19
3.45
3.70
Note: Column (1) is based on the assumption that the value of the own-account production of final
computer/electronics is equal to the value of the computer/electronic intermediates used. Column (2) assumes that thevalue is equal to twice the value of intermediate used.
Source: Author's calculations based on the I-O tables published by Statistics Canada and the Bureau of Economic
Analysis.

49

Table A5: Gross Domestic Product, Actual and Augmented, current prices, 2006-2014
Canada, millions of CAD
ActualAugmented 1

Augmented 2

2006

1,492.2

1,495.6

1,493.9

2007

1,573.5

1,576.8

1,575.2

2008

1,652.9

1,657.0

1,655.02009

1,567.4

1,574.0

1,570.7

2010

1,662.1

1,669.3

1,,665.7

2011

1,769.9

1,777.7

1,773.8

2012

1,822.8

1,831.8

1,827.3

2013

1,892.2

1,901.8

1,897.0

2014

1,973.0

1,983.2

1,978.1

Growth rates, %2006-2014

3.55

3.59

3.57

2006-2008

5.25

5.29

5.28

2009-2014

4.71

4.72

4.71

United States, millions of USD
ActualAugmented 1

Augmented 2

2006

13,855.9

13,901.2

13,878.5

2007

14,477.6

14,532.5

14,505.1

2008

14,718.6

14,773.8

14,746.2

2009

14,418.7

14,480.8

14,449.8

2010

14,964.4

15,044.8

15,004.6

2011

15,517.9

15,616.7

15,567.3

2012

16,155.3

16,259.8

16,207.5

2013

16,663.2

16,768.5

16,715.8

2014

17,348.1

17,456.0

17,402.0

2006-2014

2.85

2.89

2.87

2006-2008

3.07

3.09

3.08

Annualized growth rates, %2009-2014
3.77
3.81
Note: Augmented 1 and 2 are based on column (1) and (2) respectively in Table A1.
Source: Author's calculation based on Table A1 and the CSLS database for ICT investment. Available at
http://www.csls.ca/data/ict.asp

50

3.79

B. Charts

Appendix Chart A1: Actual and Counterfactual Intermediate purchase of
Data processing, hosting and related services, millions of
CAD, Canada, 1997-2014
10,000
9,000
8,000
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0

Counterfactual 1

Counterfactual 2

ActualSource: Author's calculations based on CANSIM Table 381-0033 and input-output tables published by Statistics
Canada (Catalogue 15F0041X).

51

Appendix Chart A2: Actual and Counterfactual Intermediate purchase of
Data processing, hosting and related services, billions of USD, the UnitedStates, 1997-2016
180
160
140
120
100
80
60
40
20

Counterfactual 1

Counterfactual 2

ActualSource: Author's calculations based on input-output tables from the Bureau of Economic Analysis.

52