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Impacts of Crude Oil Production from Alberta Oil Sands on the Canadian Economy
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G. R. Timilsina , J.P. Prince, D. Czamanski and N. LeBlanc
Canadian Energy Research Institute, #150, 3512, 33 Street NW, Calgary, AB, T2L 2A6, Canada
ABSTRACT
Canada has the largest hydrocarbon resource potential after Saudi Arabia in the world. Most of the proven
reserves of crude bitumen (≅ 28 billion cubic meters) are located in Alberta in the form of oil sands. At present,
oil sands accounts for about 40% of the total Canadian crude oil production. This share is expected to exceed
70% by 2015. It is projected that the industry would invest about 87 billion dollars in the development of
mining, in-situ and upgrading projects and produce 371 billion dollars of crude bitumen and synthetic crude oil
during the 2000-2015 period. Using an input-output model, this study estimates the overall economic impacts
on Canada due to the development and production activities in the oil sands industry. The study finds that the
oil sands industry would contribute 954 billion dollars of gross output, 541 billion dollars of gross domestic
product, 93 billion dollars of government revenues and about 293 thousands jobs to the Canadian economy
during the 2000-2015 period.
Key Words: Economic Impact analysis, Input-Output Model, Oil Sands industry.
1. INTRODUCTION
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Oil sands located in Canada are one of the largest hydrocarbon deposits in the world.
These are primarily found in carbonate sedimentary formations in three areas in the province
of Alberta: Athabasca, Cold Lake, and Peace River. Oil sands deposits are also located in
Venezuela’s Orinoco Belt, but these are generally referred to as heavy and extra-heavy crude
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oil . The ultimate potential, a value representing the volume expected to ultimately be found
by the time all exploratory and development activity has ceased, of Canadian bitumen
resources is estimated to be 400 billion cubic meters. Of which, 6% is characterized as
amenable to surface mining and the rest is available through in situ recovery or underground
mining methods (NEB, 2000). It is estimated that initial volume in place of crude bitumen in
Alberta oil sands is approximately 260 billion cubic meters, of which 28.3 billion cubic
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Corresponding author, Fax: 1 403 284 4181, E-mail: gtimilsina@ceri.ca
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The oil sands deposits are composed primarily of quartz sand, silt and clay, water and bitumen, along with minor amounts
of other minerals such as titanium, zirconium. The oil sands bitumen is characterized by high density, very high viscosity,
high metal concentration and high carbon to hydrogen ratio as compared to conventional crude oils (NEB, 2000).
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The crude bitumen from the oil sands deposits in Alberta has an API gravity of around 8 to 12° whereas the shallow sands
in Venezuela has API 8 to 9.5° (Dusseault, 2001). The bitumen and extra heavy crude oil produced are upgraded to about
35° API for Canadian synthetic and about 32° API for the Zuata Orinoco project.
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meters can be recovered using existing technologies. This established reserve of 28.3 billion
cubic meters would be sufficient to meet Canada’s oil demand for about 200 years, at current
rates (NEB, 2000). With this reserve, Canada is now placed second after Saudi Arabia (43
billion cubic meters) in world oil reserves (Radler, 2002).
Although production of oil from oil sands is much more expensive as compared to
conventional oil, Alberta’s oil sands have attracted the world’s attention. This is because the
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oil price is skyrocketing and the world oil demand is rapidly increasing. Moreover,
continental energy security is one of the key items of the contemporary energy policies in
North America. Global oil demand is forecasted to grow by 1.6% per year, reaching 121
million barrels per day in 2030 of which OPEC could supply about a half (IEA, 2004). The
rest needs to be supplied from Non-OPEC countries including Canada. Conventional oil
reserves are continuously declining in Canada. This implies that increasing production from
Alberta’s oil sands is inevitable. At present, oil sands accounts for 53% of Alberta’s total
crude oil production (or 40% of Canada’s total crude oil production), this share is projected
to be 80% (70% at the national level) by 2015. Increasing US demand for Canadian oil is
another factor to push up the production from Alberta oil sands. Total US oil imports is
projected to be 15.5 million barrels per day by 2015, 47% higher as compared to 2002(NEB,
2004).
In order to deliver Alberta’s blended bitumen and synthetic crude oil (SCO) to
various refineries in Canada and the US, a large number of new pipelines as well as
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expansion of existing pipelines have been proposed (Petro. Econ., Jan. 2005) . Development
of oil sands projects, production from those projects, pipelines and other infrastructure to
support the production require a huge investment. The Alberta Economic Development
(AED) estimates, based on the recent inventory of existing and planned oil sands projects, a
spending of CN$61 billion on new oil sands projects in the 2004-2013 period (AED, 2005).
Another CN$11 billion may be spent on sustaining capital during the same period. Moreover,
an additional $CN1.1 billion may be spent on co-generation, pipeline and other
infrastructure. During the 1996-2003 period, the industry spent an estimated CN$28 billion
on new projects and sustaining capital (AED, 2004).
Development and production activities in the oil sands industry does not only impact
the oil industry alone but also other industries supplying the oil industry and eventually the
entire provincial and national economies. It is of interest to government and industry to
understand the size of such economic impact. Using an economic model based on input-
output tables, this study estimates the impacts on the Canadian economy of the development
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Recently, spot crude oil prices have reached US$57 per barrel for WTI at Cushing, Oklahoma. In the long term, the
Alberta Energy and Utilities Board projects oil price below US$31 per barrel until 2013 (AEUB, 2004a).
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The crude bitumen extracted from surface mining is upgraded by reducing the hydrogen to carbon ratio and the product is
called synthetic crude oil (SCO). The bitumen produced through in-situ method is blended with some diluent (e.g.,
pentane). The SCO and blended bitumen is transported through pipelines to refineries.
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and production activities in the oil sands industry. The paper is organized as follows. Section
2 highlights the model and input data prepared for the model. This is followed by discussions
on economic impacts or the model results. Finally key conclusions are drawn.
2. MODEL AND DATA
An Input-output model of Canada has been developed for the purpose of this study.
The model is based on national I-O tables produced by the Statistics Canada for year 2000
(Statistics Canada, 2004). The Statistics Canada I-O structure consists of three tables (or
matrices): (i) Make or Output matrix, (ii) Use or Input matrix and (iii) Final Demand matrix.
The Make matrix presents production of commodities (row) by various industries (column).
The Use matrix presents consumption or use of commodities (row) by various industries
(column). The Final Demand matrix presents consumption or use of commodities (row) by
various final demand sectors (column), such as household, government, investment, trade,
and inventory. A social accounting matrix (SAM) has been prepared combining these three
matrices and data from national income and expenditure accounts (Statistics Canada, 2003).
The Statistics Canada I-O tables presented in Catalogue No. 15-201 have 47 commodities
(goods and services) and 25 industries. One of the key limitations of these tables is that no
detailed breakdown is available for the oil and gas sector. All energy commodities (e.g., coal,
crude oil, natural gas) are lumped together as a single ‘mineral fuel’ and all energy industries
(e.g., coal production, coal mining, gas production) are embedded into a single ‘mining and
oil & gas extraction’ industry.
One of the key features of this I-O model is that the mineral fuel commodity in the
Statistics Canada I-O table is split into coal, natural gas and crude oil (including crude
bitumen and SCO from oil sands industry). Similarly the ‘mining and oil & gas industry’ is
broken down to four industries: (i) coal mining, (ii) oil production, (iii) natural gas
production and (iv) other mining (i.e., metal and non-metal mining except coal and bitumen
mining). Services incidental to mining is also allocated to these individual energy sectors and
the other mining sector. Moreover, the utility sector was diaggregated into electric, gas and
water utility. While electric and gas utilities are separately presented, water utility is lumped
together with other services. A wide range of data such as production, consumption and
prices of energy commodities, sectoral GDP, gross outputs (or total sales value) are needed to
split the aggregated energy commodities (i.e., mineral fuels and utility services) and
industries (i.e., mining, oil & gas industry and utility industry). These data were collected
from various sources such as Statistics Canada (Statistics Canada, 2001), Canadian
Association of Petroleum Producers (CAPP, 2001), Alberta Energy and Utilities Board
(AEUB, various issues of monthly statistics) and Natural Resources Canada (NRCan, 2003).
The Statistics Canada I-O table presents a very detailed disaggregation of some
sectors such as service sectors. Such a detailed disaggregation of this sector is not necessary
for energy and environmental policy analysis, as this sector is a less energy intensive sector.
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Hence, the I-O model represents the service activities through a few sectors such as business
services, other services etc.
One of the limitations in the I-O model used in this study is that it has a single
manufacturing sector. This is because our primary data source Statistics Canada (2004) has a
single manufacturing sector. Representing all manufacturing activities through a single
manufacturing industry greatly limits the capability of the model in dealing with industry
sector demand side policy analysis. Nevertheless, this limitation does not affect assessing the
economic impacts of oil sands industry being pursued in the current study.
After incorporating the aggregation and disaggregation as mentioned above, the I-O
model has 19 sectors, as presented in Table 1.
Table 1. Sectors/Commodities in CERI I-O Model
Serial No. Sector or Commodity
1 Agriculture
2 Forestry
3 Other Mining
4 Crude Oil
5 Natural Gas
6 Coal
7 Manufacturing
8 Construction
9 Transportation & Communication
10 Electricity Utility
11 Gas Utility
12 Wholesale
13 Retail
14 FIRE
15 Business Services
16 Education
17 Health
18 Food and Accommodation Service
19 Other Services
The oil sands industry has two series of impacts. First, impacts of development
activities (e.g., construction) and impacts due to production activities. Studies focussing on
short-term impact of development or construction activities only capture the first series of
impacts. For example, impacts of construction of roads or any other infrastructure on the
economy (e.g., final demands for various types of goods due to the construction activities;
employment generated by the construction activities etc.) are included in the first series of
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impacts. On the other hand, construction or development in the oil sands sector results in
productive capacities or assets (bitumen mines, upgrading plants, in-situ wells etc.) which
starts to produce commodities (i.e., mined bitumen, in-situ bitumen and SCO) once their
construction is over and operation begins. This study captures both effects (i.e., impacts of
construction and impacts of production). Note, however, that both construction and
production activities will continue as long as the resource basins have enough reserves
attractive for investment and production. Note that investment is defined as purely
construction expenditure in this study. Sustaining capital is defined as expenditure on repair
and maintenance to maintain the production and hence its impacts are included in the impacts
of production.
The first step in the modelling exercise is to find investment (i.e., construction
expenditure) and production projections, which are taken from CERI (2004). Investment
projections are available for three categories of oil sands activity: (i) mining, (ii) In-Situ and
(iii) upgrading. The total investment in each type of activity is then split into purchases of
various goods and services (e.g., manufacturing, fuel, business service, etc.) and labour using
expenditure shares. The expenditure shares are compiled from a large number of
environmental impact assessment reports submitted by oil sands projects to the Alberta
Energy and Utilities Board.
Like investment, total production, in value, (or output or sales) from each type of
activity (i.e., mining, in-situ and upgrading) is allocated to purchase of goods and services,
payment to labour, payment to government (e.g., royalty and taxes) and other operating
surplus (profits, depreciation etc.). Note that expenditure shares, which are used to allocate
value of production (or sales) to purchase of goods/services, labour etc., are different from
those for investment, as demands for goods/ services and labour in production are different
from those in construction.
Investments and value of productions together with their allocation across goods and
services and labour are thus used to estimate demand for various goods/services and labour in
construction and production. These demands are met through two sources: domestic
production and imports. The imported portion is stripped off using the import share, which is
the share of imports to the total demand for a good/service. Ideally, import shares should be
estimated through a survey of the oil sands industry. Such a survey was not undertaken in
this study. An alternative approach to the survey is to use import share calculated using the I-
O table constructed by Statistics Canada. The main drawback of this alternative approach is
that the import share of an aggregated good/service is used instead of that particular good or
service. For example, oil sands mining requires large trucks and shovels which are
manufactured outside Alberta and hence the import share for this equipment is 100%, but the
alternative approach considers all trucks and shovels in a single category irrespective of their
size and use. Some of these trucks and shovels might be manufactured in Alberta implying
that the import share of the ‘truck and shovels category’ is smaller than 100%.
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The portion of the total demand that is domestically produced is used as input to the I-
O model. The I-O model estimates economy-wide impacts in terms of gross output, GDP,
household or labour income, employment and government revenues. Like in a standard I-O
model, the output impact of oil sands industry is calculated using the following relationship:
∆GO = [ I − DNB] −1 × DN ∆F (1)
Where:
∆GO Change (or increase) in gross output due to construction and operation
of oil sands projects.
B The input coefficient matrix, an element of this matrix is derived
dividing use of a commodity in a sector by the total output of that
sector. The element represents requirements of a commodity in a
sector to produce one unit of output from that sector.
N Matrix of domestic shares in the total supply of a commodity. This
matrix converts the input coefficient matrix [B] to input coefficient
matrix of domestically produced goods and services [NB].
D Matrix of sectoral shares in the total commodity production; an
element of this matrix is derived by dividing production of a
commodity from a sector to the total production of that commodity in
the economy. It represents the fraction of a commodity produced by a
sector. This matrix is used to convert delivery of commodity to
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delivery of a sectoral output .
∆F Change (or increase) in final demand for commodities directly
demanded (or purchased) for the construction of and production from
oil sands projects.
Once the output impact (i.e., change in output) is calculated using the relationship
mentioned above, calculation of impacts on GDP, household income and employment are
straightforward. These impacts are estimated at the industry level using the ratio of each (i.e.,
GDP, household) to gross output.
Key input data used in the study are projections of investment for development of
mining, in-situ and upgrading projects during the 2000-2015 period and production of crude
bitumen and SCO during the same period. The data are presented in Table 2. While the
historical data (i.e., data for 2000-2003 period) are taken from CAPP (2004), forecasted data
are taken from CERI (2004). Actual crude oil prices (2004 constant price) were taken for the
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Since the objective of the study is to assess economic impacts at the sectoral (or industry) level, an industry by industry
requirement matrix is needed. An element of DNBij matrix represents demand for a good/service domestically produced
by an industry i in order to produce one unit of output from industry j.
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historical period (i.e., 2000-2004) and a constant price of US$32 per barrel is considered for
the future period.
Table 2. Investment and Production Data (Million dollars, 2004 price)
Year Investment Production
Mining In-Situ Upgrading Total Mining In-Situ Upgrading Total
2000 3,491 659 162 4,312 3,717 2,808 1,934 8,459
2001 3,762 1,119 1,151 6,032 2,322 1,708 2,627 6,657
2002 4,258 1,488 1,148 6,894 4,359 2,434 2,137 8,930
2003 3,610 1,205 340 5,155 5,587 3,257 3,001 11,846
2004 708 1,004 857 2,568 8,631 4,474 4,743 17,848
2005 1,074 1,173 1,425 3,672 6,858 4,082 4,497 15,437
2006 1,494 1,691 2,019 5,204 7,303 4,681 5,152 17,136
2007 1,904 1,642 2,366 5,912 8,273 6,340 5,476 20,089
2008 1,893 1,462 2,163 5,518 9,125 7,599 6,418 23,142
2009 1,659 1,471 1,678 4,809 10,131 8,493 7,380 26,004
2010 1,952 1,482 1,490 4,924 10,851 9,518 8,001 28,370
2011 3,391 1,151 1,982 6,523 11,598 10,687 8,427 30,711
2012 4,709 585 2,691 7,985 12,941 11,780 8,931 33,652
2013 4,358 218 2,755 7,330 15,393 12,235 9,918 37,547
2014 3,056 285 2,289 5,630 17,976 12,269 11,070 41,316
2015 1,995 539 1,724 4,259 19,431 12,246 11,888 43,565
Total 43,314 17,173 26,240 86,727 154,497 114,610 101,601 370,709
Source: CERI (2004) and CAPP (2004)
As can be seen from Table 2, about 87 billion dollars would be invested in the oil sands
industry during the 2000-2015 period and about 371 billion dollars crude bitumen and SCO
would be produced during the same period.
3. MAIN RESULTS AND DISCUSSIONS
This section discusses the main results of the study including impacts on gross
outputs, GDP, labor income, employment and government revenue. Overall (or total) impacts
are presented first followed by sectoral details.
3.1 Overall Impacts
Table 3 presents impacts on gross output, GDP, labor income and employment by
type of activities (i.e., mining, in-situ and upgrading) due to the development and production
separately as well as combined. As can be seen from the table, the cumulative impact of
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production activity during the 2000-2015 period is much higher than that of development
activity. This is because production expenditure is higher than construction during the period.
For example, about 17 billion dollars is expected to be invested in the development of oil
sands in-situ projects during the 2000-2015 period; at the same time, about 115 billion
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dollars value of outputs (i.e., bitumen) would be produced from oil sands projects . Like in
the case of conventional oil industry, about 48% of the total sales value is expended as
production costs such as payments to labor, purchase of fuel and purchase of other goods and
services for repair and maintenance. The rest 52% is used for operating surplus (e.g., profits)
and payments to governments (i.e., taxes and royalties).
Table 3. Economic Impacts – Overall Results (2000-2015)
Mining In-Situ Upgrading Total
Investment
Gross Output (million CN$) 117,698 49,335 74,025 241,059
GDP (million CN$) 52,600 22,289 33,708 108,597
Labor Income (million CN$) 29,886 12,777 19,123 61,786
Employment (thousand person year) 782 344 512 1,639
Production
Gross Output (million CN$) 302,190 212,193 198,470 712,853
GDP (million CN$) 179,864 135,839 116,878 432,582
Labor Income (million CN$) 48,981 29,639 32,264 110,885
Employment (thousand person year) 1,250 682 822 2,755
Investment and Production
Gross Output (million CN$) 419,889 261,528 272,495 953,912
GDP (million CN$) 232,464 158,128 150,586 541,178
Labor Income (million CN$) 78,868 42,416 51,388 172,672
Employment (thousand person year) 2,032 1,026 1,334 4,393
As demonstrated in Table 3, the oil sands industry will generate about 541 billion
dollars of GDP in Canada during the 2000-2015 period. This amount is about a half of
Canada’s GDP in year 2004. Of the total GDP, 29% would be generated through in-situ
projects and the remaining 71% through mining and upgrading projects. The industry will
generate about 4.4 millions person-year employment or about 293 thousand jobs during the
2000-2015 period. This employment would generate about 173 billion dollars of household
income.
Table 4 presents proportions at which development and production activities in the oil
sands industry would impact to the entire Canadian economy. For example, a dollar
investment in development (i.e., construction) of oil sands industry would produce 2.78
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Note that the production accounts both existing projects as well as those developed during the 2000-2015 period .
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dollars of gross output, 3.35 dollars of GDP, 2.83 person years of employment and 2.85
dollars of labor income from the entire economy. Similarly, a dollar expenditure for
producing crude bitumen and SCO from the oil sands industry would produce 1.92 dollars of
gross output, 1.74 dollars of GDP, 4.78 person years of employment and 2.28 dollars of labor
income from the entire economy. The difference between development and production in
these multipliers (i.e., output multiplier, GDP multiplier etc.) reflects the different
proportionate need for labor, goods and services for these activities. For example, of the total
development expenditure (i.e., construction investment) in mining, most (72%) is spent to
purchase manufacturing goods and the rest for labor (20%) and business services (8%). On
the other hand, almost half of the total production expenditure in mining (43%) is spent for
labor and the remaining is used to purchase manufacturing goods (40%) and fuel (17%).
Table 4. The Multipliers
Mining In-Situ Upgrading Total
Investment
Gross Output 2.72 2.87 2.82 2.78
GDP 3.59 3.45 3.01 3.35
Labor Income 3.22 2.95 2.44 2.85
Employment 2.71 3.01 2.92 2.83
Production
Gross Output 1.96 1.85 1.95 1.92
GDP 1.69 1.91 1.68 1.74
Labor Income 2.06 4.03 2.11 2.28
Employment 5.21 3.83 5.21 4.78
Investment and Production
Gross Output 2.12 1.98 2.13 2.09
GDP 1.89 2.04 1.85 1.91
Labor Income 2.28 3.61 2.20 2.43
Employment 3.84 3.51 4.01 3.80
The total impact is also split into direct, indirect and induced impacts. Figure 1
presents the share of direct, indirect and induced impacts on the total gross output. Of the
total 954 billion dollars of gross output, 48% is direct impact -- development expenditure for
the oil sands industry and value of crude bitumen and SCO produced--. Indirect impacts (i.e.,
increase in outputs from other sectors to support development and production activities in the
oil sands sector) accounts for 23% of the total impact. The remaining 29% is the induced
impact (i.e., output needed to meet the increased demand for household consumption
resulting from the increased household income due to the development and production
activities).
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29%
48%
23%
Direct Impacts Indirect Impacts Induced Impacts
Figure 1. Share of Direct, Indirect and Induced Impacts in the Total Impact (Gross Output)
Another important impact of the development and production activities in the oil
sands industry is government revenues. Revenue sources included here are: royalties; indirect
taxes such as general sales tax (GST) and provincial sales tax (PST); corporate income tax
and personal income tax. These revenues can also be categorized in two groups:
(i) Revenues directly generated by the oil sands industry (e.g., royalty, indirect
taxes and corporate taxes directly paid by the oil sands industry) and personal
income tax paid by employee of the oil sands industry;
(ii) Revenues generated indirectly such as personal income tax paid by employee
of other industries, indirect and corporate income tax on other industries.
Table 5 presents government revenues through various sources as a result of
development and production activities in the oil sands industry. The development and
production activities in the oil sands industry would generate about 93 billion dollars to
governments, of which about a half (53%) is directly contributed by the oil sands industry
through royalties (27%), indirect tax (7%), corporate tax (9%) and personal income tax
(10%). It is very important to note that the other half of this total revenue is generated
indirectly (i.e., through other industries).
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Table 5. Impacts on Government Revenues (2000-2015)
Million CN$ %
Direct revenues
Royalties (oil sands industry) 24,613 27
Indirect tax (oil sands industry) 6,294 7
Corporate tax (oil sands industry) 8,477 9
Personal income tax (oil sands industry) 9,442 10
Indirect revenues
Personal income tax (other industries) 16,570 18
Indirect tax (other industries) 15,800 17
Corporate tax (other industries) 11,353 12
Total revenues 92,548 100
3.2 Sectoral Results
Impacts on sectoral gross output and sectoral value added due to the development and
production activities in the oil sands industry are presented in Figure 2. As can be seen in the
figure, the highest level increase in gross output and value added is, as expected, in the oil
sector, which includes oil sands. This is followed by the manufacturing and construction
sectors. Manufacturing goods are the main items required for both development and
production activities. For example, more than 85% of the total goods and services required
for crude bitumen production and upgrading are manufacturing goods. Similarly, more than
70% of the goods and services required for development of mining and upgrading plants are
also manufacturing goods. Since entire development expenditure is paid to the construction
sector, sectoral output as well as value added of this sector would obviously be high. Other
sectors with significant increase in gross output and value added are gas utility, FIRE
(finance, insurance and real estate), business service and other services.
The pattern of impacts on sectoral labor income and employment are similar to those
of gross output and GDP (please see Figure 3). The oil sector would enjoy the highest level
of increment in labor income, whereas the construction sector would do the same for
employment. The highest increment in labor income but not the employment in the oil sector
clearly suggests higher level of average wage rate in this sector. In some of the sectors,
particularly the education, increase in employment is higher as compared to labor income
thereby suggesting lower average wage rate in this sector.
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Other Services
Food and Accommodation
Health
Education
Business Services
FIRE
Retail
Wholesale
Gas Utility
Electricity Utility
Transportation & Communication
Construction
Manufacturing
Coal
Natural Gas
Crude Oil
Mining
Forestry
Agriculture
0 50 100 150 200 250 300 350 400
Billion Canadian Dollar (2004 Price)
Gross Output Value Added
Figure 2. Impacts of Oil Sands Project Development and Production on Sectoral Outputs
during 2000-2015 Period
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40
Labour Income --Billion Canadian Dollar (2004 Price)
35
Employment -- 100 thousand person year
30
25
20
15
10
5
0
Coal
Gas Utility
Mining
Electricity Utility
Crude Oil
Retail
Forestry
Health
Natural Gas
Construction
Education
Transportation & Communication
Food and Accommodation
Manufacturing
Business Services
Other Services
FIRE
Agriculture
Wholesale
Labour Income Employment
Figure 3. Impacts of Oil Sands Project Development and Production on Sectoral Employment
and Labor Income during 2000-2015 Period
4. CONCLUSIONS AND FINAL REMARKS
The oil sands industry is expected to contribute to the Canadian economy
significantly for a long period of time. The industry is estimated to invest about 87 billion
dollars during the 2000-2015 period and would produce 371 billion dollars crude bitumen
and synthetic crude oil in this period. Using an input-output model, this study estimates that
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the development and production activities in the oil sands industry would produce about one
trillion dollar of gross output, about half a trillion dollar of GDP, 173 billion dollars of labor
income and 293 thousands jobs during the 2000-2015 period. The total GDP impact during
the 2000-2015 period is about a half of the size of Canada’s GDP in year 2004.
The study also shows that a dollar expenditure on development and production
activities in the oil sands industry would produce more than two dollar’s value of output from
the entire economy. Of the total impacts, 48% is produced directly by the oil and
construction sectors, 23% indirectly by other sectors and the other 29% is induced by
employment resulting from the oil sands development and production activities.
The study also estimates that the development and production activities in the oil
sands industry would generate about 93 billion dollars in government revenues. The revenues
are generated through royalties, corporate and indirect taxes in oil sands as well as other
industries and personal income taxes on new jobs created in the oil sands and other
industries.
The main industries experiencing the highest increment in gross output, value added
and employment are the oil sands industry itself, manufacturing and construction industries.
Other industries such as, gas utility, FIRE (Finance, insurance and real estate) and business
services, would also experience significant impacts.
This study analyzes impacts of development and production activities for a 15 years
period. Such a period is brief as compared to the span of time over which the development
and production activities could continue to exploit the established resource in place (28
million cubic meters). Moreover, the model used in the study is a static model incapable of
capturing the complete and dynamic picture of the economy. Assessment of the economic
impacts of the oil sands industry for a longer period of time using a dynamic macroeconomic
model could be an interesting further extension.
REFERENCES
Alberta Economic Development (AED, 2005) Oil Sands Industry Update, February 2005
Edition, http://www.alberta-canada.com/statpub/mpindex.cfm downloaded on 7 March 2005.
Alberta Economic Development (AED, 2004) Oil Sands Industry Update, September 2004
Edition, http://www.alberta-canada.com/oandg/pdf/oilsands_sept04_revised.pdf, downloaded
on 15 December 2004.
Alberta Energy and Utilities Board (AEUB), Alberta Energy Resource Industries Monthly
Statistics (ST3), Various Issues, AEUB, Calgary, Canada.
14
Alberta Energy and Utilities Board (AEUB, 2004a), Alberta’s Reserves 2003 and
Supply/Demand Outlook 2004 – 2013. Revised Edition, June 2004.
Canadian Association of Petroleum Producers (CAPP, 2001), 2000 Statistical Handbook,
CAPP, Calgary, Canada.
Canadian Association of Petroleum Producers (CAPP, 2004), 2003 Statistical Handbook,
CAPP, Calgary, Canada.
Canadian Energy Research Institute (CERI, 2004), Oil Sands Supply Outlook: Potential
Supply and Costs of Crude Bitumen and Synthetic Crude Oil in Canada 2003-2017, CERI,
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