DRAFT
The Contributions of Trade, Technology, and Consumption
to Canadian Jobs and Output, 1986 to 2004
Ziad Ghanem
Anick Johnson
Industry Accounts Division
Statistics Canada
April, 2008
Table of Contents
1
Introduction........................................................................................................................... 3
2
Methodology ......................................................................................................................... 4
3
The sources of changes in employment.................................................................................. 9
4
The sources of changes in output ......................................................................................... 16
5
Trade by geographic area..................................................................................................... 16
6
Conclusion .......................................................................................................................... 19
Appendix 1: Data sources............................................................................................................ 22
2
1
Introduction
The growing liberalization of trade, the emergence of the newly industrialising economies, and the
continuing rapid pace of technological change are raising questions about the evolving role of the
Canadian economy in the globalization of production processes. Two major manifestations of
these developments within Canada are the continuing shifts in production and employment from
the goods-producing to the services industries and an important growth in the education level of
the employed workforce. The purpose of this paper is to examine these structural changes through
an empirical measure of the distinct impacts of changes in trade, technology, and domestic
consumption expenditures on industrial growth and employment in Canada.
Our analysis is guided by separate theoretical frameworks that provide some overlapping if not
completely integrated explanations. Ricardo’s comparative advantage and the Heckscher-Ohlin
theorem provide the foundations of the analysis of international trade. Generally speaking, these
theories postulate that countries trade in order to benefit from the international division of labour
and that they should be net exporters of the commodities that embody their relatively abundant
factors and net importers of the commodities that embody their relatively scarce factors.
A second explanation of developments relates to the changing nature of demand for labour due to
the inherent skill bias of technological change. Many authors believe that new technologies are
intrinsically linked to an upgrading of skills. Bound and Johnson (1992) find such evidence for the
U.S. Berman, Bound, and Machin (1998) find similar evidence across several advanced
economies, thereby allowing them to generalize their finding that technological change has
favoured the more skilled workers at the expense of the less skilled.
The final argument is provided by Clark (1940) who has contended that with growing income
levels, consumer demand will shift to services. He based his analysis on the hierarchy of needs
hypothesis, which states that services satisfy higher needs than goods, and that, as income grows, a
higher share of incomes will be used for the purchase of services. Clark also recognized that the
resulting shift in employment will be compounded by the higher rates of productivity growth in
the manufacturing sector as compared to the services sector.
While recognizing that, in reality, the Canadian economy presents a complex web of interactions
between these three different phenomena, this paper, nonetheless, adopts a framework that aims to
assign a distinct empirical measure to each source of change in production and employment. The
foundations of this method are anchored in the open Leontief input-output model. The specific
model is based on the work of Gregory, Zissimos, and Greenhalgh (2001) which combines the
methods developed by Chenery, Shishido, and Watanbe (1962) for the study of structural change
and economic growth and the pioneering work by Leontief (1951) on the factor content of trade.
Our analysis relies on several Statistics Canada data sources. The latter include the annual
Canadian current and constant price input-output (IO) tables1 and the labour input data from the
1
The constant price input-output tables in year t are expressed in terms of the prices of year t-1 and weighted by the
current price values of year t-1.
3
KLEMS database 2 produced by the Canadian Productivity Accounts. The study covers the years
from 1986 to 2004. For the period from 1997 to 2004, primary source data from the International
Merchandise Trade and the Balance of Payments programs are used to supplement the
international trade vectors of the IO tables with the information required for analyzing the
geographic patterns of trade.
The major structural changes that we seek to explain are the following. According to the KLEMS
database, 4.1 million full-time equivalent net jobs were added to the Canadian economy over the
period from 1986 to 2004. Of these, the services industries accounted for an increase of 3.9 million
while the goods-producing industries accounted for a mere 202 thousand jobs. At the same time,
the share of high-education employment increased from 49% to 66% of the total employed
workforce. The IO tables also show that over this same period, the services industries continued
their historical ascendancy, increasing their share of GDP from 64% to 67%.
Our main findings are that over the period under study, growth in employment in Canada has been
led by a relatively constant growth in domestic consumption expenditures, especially of services.
International exports played a growing role in job creation, reaching 25% of total employment by
2004 thereby overshadowing growing import intensities, which contributed to the loss of 751
thousand jobs. The most important factor in job shedding, however, was labour-saving
technological change, which displaced over 3 million jobs.
In general, domestic consumption and net trade have favoured skilled labour. Technological
change, however, was the most important force in displacing low-skill employment both in the
goods and services industries. Nonetheless, technological change was also a significant factor in
job creation, promoting the addition of a large number of high skill jobs in the services industries.
Exports contributed relatively more to GDP than to employment and the trend appears to be
reinforced by the growing share of primary commodities in exports. An examination of the
geographic nature of Canadian trade over the period from 1997 to 2004 confirms the continued
dominant role of the U.S. export market for Canadian jobs, but an emerging trend points toward a
switch in offshoring activities away from the U.S. toward all other major trading regions.
The paper is organized in the following manner. The next section develops the model used in
explaining the sources of output and employment change. Sections 3 and 4 present the results of
the model in terms of employment and output respectively. Section 5 presents the results by
geographic area for the period covering 1997-2004. Section 6 provides concluding remarks.
2
Methodology
The model draws on the work of Gregory et al. (2001) for measuring the contributions of changes
in domestic demand, technology, and trade on industrial output and employment. The starting
point of the model is the basic input-output identity, which defines domestic production as equal to
demand due to inter-industry transactions and final expenditures net of international imports.
2
The acronym KLEMS stands for “capital, labour, energy, materials, and services”. It is an experimental database of
industry statistics for multifactor productivity analysis published by Statistics Canada.
4
Following the approach taken by Gregory et al. (2001), this basic identity is slightly modified in
equation (1) to show capital expenditures as a function of industry gross outputs3.
(1)
g = (Dhˆ B)g + (Dhˆ J)g + Dhˆ f + Dx
where g is the vector of total gross outputs by industry; B and J are the commodity by industry
matrices of intermediate input and capital input coefficients per unit of gross output; f is a
commodity vector of final domestic expenditures of households, non-profit institutions, and
government; D is the industry by commodity market share matrix; x is a commodity vector of
international exports; and h is a vector of home shares by commodity, where the symbol ^
indicates the conversion of a vector into a diagonal matrix.
Defining capital expenditures as a function of gross outputs allows the model to endogenize capital
expenditures as a function of all other final expenditures, in a sense, treating them similarly to
intermediate inputs. This allows the model to better delineate the impact of exports on economic
activity. Even though investment expenditures have an economic life that exceeds the one year
accounting cycle of other expenditures in the IO tables and a direct link between investment
expenditures and production for final consumption expenditures or exports cannot be established
within a given year, it is nonetheless a reasonable allocation method given the relatively long
period of analysis and the large number of industries covered by this paper. While recognizing its
limitations, this method remains preferable to the alternative approach of treating investment
expenditures as domestic expenditures thereby underestimating the true contribution of trade to
domestic production.
Solving equation (1) for gross outputs:
(2)
[
g = I − Dhˆ B − Dhˆ J
]
−1
D(hˆ f + x)
Equation (2) can be differenced to decompose variations from one year to the next
(3)
(
g = R 0 hˆ 0 f + hˆ f1 + x + hˆ B1g 1 + hˆ 0 Bg1 + hˆ J 1g 1 + hˆ 0 Jg 1
)
where the subscript 0 represents the starting period and the subscript 1 represents the subsequent
−1
period, both valued in constant prices, and R = I − Dhˆ B − Dhˆ J D .
[
]
Equation (3) expresses total changes in industry gross outputs as a function of changes in demand
and technology. The impact of final domestic consumption is expressed in R 0 hˆ 0 f ; exports in
R 0 x ; the impact of the changing share of imports related to final consumption, intermediate
inputs, and capital expenditures are expressed in R 0 hˆ f1 + hˆ B1g 1 + hˆ J 1g1 ; and finally the impact
of technological change is captured in R hˆ Bg + hˆ Jg . Technological change in this
0
(
[
0
1
0
1
)
]
context has a very broad meaning—it refers to changes in industry demand that are due to changes
3
This equation is adapted from the standard industry by industry formulation to the Canadian industry by commodity
Supply and Use tables.
5
in the intermediate input and capital expenditure coefficients, regardless of what may be at the root
of such changes, whether they be due to changes in relative prices, economies of scale, firm entry
or exit from the industry, changes in organization, technological innovation, change in output
product mix, outsourcing of activities, etc.
Impacts on employment can be derived from the employment by industry coefficients
(4)
L = Lr • g
where L is an industry by skill level matrix of employment, Lr is a matrix of similar dimensions
of ratios of employment to gross output by industry, and the operator • indicates an element-byelement multiplication.
Yearly variations in employment can be decomposed into variations that are due to changes in the
levels of industry output and to variations that are due to the labour input coefficient:
(5)
∆L = Lr0 • ∆g + ∆Lr • g 1
By substitution of equation (3) into (5)
(6)
[
]
∆L = Lr0 • R 0 hˆ 0 f + hˆ f1 + x + hˆ B 1 g 1 + hˆ J 1 g 1 + hˆ 0 Bg 1 + hˆ 0 Jg 1 + Lr • g 1
The last term in equation (6) adds a new element to the measure of technological change expressed
in equation (3). Changes in employment that are due to changes in the demand for labour
embodied in intermediate and capital inputs are complemented by changes in the direct
employment coefficient of each industry.
From the perspective of empirical analysis, the formulation in equation (6), as developed in
Gregory (2001), is extremely rich and can be further extended in several ways to examine the
sources of variations in GDP, the impacts of the geographic nature of trade, and the causality links
between exports and domestic demand on the one hand and imports and technological change on
the other.
A further decomposition of the impact of domestic and export demand on imports and
technological change is possible from an expansion of the gross output term g 1 in equation (6) by
substitution from equation (2):
(7)
(
)
∆L = Lr0 • R 0 hˆ 0 ∆f + ∆x
+ Lr0 • R 0 ∆hˆ f1 + ∆hˆ B1 R 1 + ∆hˆ J 1 R 1
+ Lr • R hˆ R ( B + J ) + Lr • R
[
[
0
0
0
(
1
1
)(hˆ f
](hˆ f
1 1
1 1
)]
+x )
+ x1
1
The first line in equation (7) again defines the impacts of changes in the levels of consumption
expenditures and exports on employment; the second line regroups the impacts on imports of
changes in the home shares of final domestic expenditures (in the first term) as well as the home
shares of intermediate and capital expenditures used in the production for domestic consumption
6
and exports; the third line expresses the impacts of technological changes reflected in the changes
in intermediate, capital, and direct employment coefficients related to production for domestic
demand and exports.
A study of impacts on GDP variations similar to the impact on employment can be operated based
on three equations that are symmetric to equations (4)-(6), where the GDP coefficients by industry
replace the employment coefficients.
(8)
gdp = gdp r • g
where gdp is a vector of GDP levels by industry and gdpr is a vector of ratios of GDP to gross
output by industry.
gdp = gdp r0 • g + gdp r • g 1
(9)
(10) ∆gdp = gdp r0 • R 0 hˆ 0 f + hˆ f1 + x + hˆ B1g 1 + hˆ J 1g 1 + hˆ 0 Bg1 + hˆ 0 Jg 1 + (gdp r ) • g 1
A further decomposition of international trade by geography is also possible. Thus, exports can be
decomposed by geographic destination, so that we can express
[
(11)
x=
xn ,
]
for n = 1,...N .
n
where x n is a commodity vector of international exports to the country n and N is the total number
of countries.
By substitution of equation (11) into the exports-related term in the first line of equation (7), it is
possible to isolate the impact of changes in exports by geography on employment by industry and
education level:
(12)
∆L Xn = Lr0 • R 0 x n ,
for n = 1,...N .
where LXn is an industry by education matrix of employment levels related to exports and N is the
number of regions.
Home shares can be related to the changes in import shares by country of origin
(13)
hˆ n = (I − ˆ n ),
for n = 1,..., N .
where ĥ n is a commodity vector of supply shares that exclude country n and
vector of import shares from the country n.
n
is a commodity
Similarly to exports, from equations (13) and the terms related to changes in import shares in
equation (6), it is possible to isolate the impact of changes in imports by geography on
employment by industry by education level.
(14)
[
(
)]
∆LMn = Lr0 • R 0 ∆ (I − ˆ n )f1 + (∆ (I − ˆ n )B1 R 1 + ∆ (I − ˆ n )J 1 R 1 ) hˆ 1f1 + x1 ,
for n = 1,...N .
7
where LMn are industry by education by region matrices of employment levels for each region n.
Up to this point, the presentation of the model has proceeded with the assumption that the
comparison between the base and end periods will be in constant prices. This is because in the
present context, price variations can distort the measurement of the relationship between industry
gross outputs and employment. In the short term, this relationship can be expected to exhibit
relative stability in relation to volumes but certainly not to values of output.
However, removing the distortions caused by price variations creates a contradiction between a
static measurement of the most current information and the dynamic analysis of the changes that
have brought about these results. Removing price variations creates a problem of non-additivity
between the levels measured in the base period, the cumulative effect of yearly changes reflected
in the analysis of the sources of the variations, both of which are measured for example, in base
year prices, and the observed levels at the end period, if the latter are measured in the prices of the
end period. The assumption that in a given year the best way to define a volume-based Leontief
production function is by normalizing prices to one, will inevitably lead to a loss of additivity if
those measures are to be integrated with an analysis of the sources of change that are net of price
variations.
It is therefore necessary to remove the role of prices in distorting the measurement of the sources
of change in the short term but at the same time account for their role in reallocating inputs over
the longer term. This role of prices in re-weighting costs can be measured through an application
of equation (2) to the differences between the current and constant price IO tables for the same
year and by explicitly introducing the role of prices:
(15)
(
)
(
∆g KC = R C PtF • hˆ f + PtX • x − R K PtF−1 • hˆ f + Pt X−1 • x
)
where R C and R K are respectively the current and constant price versions of the R matrix; P F
and P X are commodity vectors of the prices of domestic final consumption and exports with the
subscripts t and t-1 representing respectively current and base-year prices; and the f and x
commodity vectors, in this context, are measured in volumes. The term ∆g KC represents the
differences by industry between current and constant price values of gross output. (The difference
between the ending year and the sum of the starting year and the cumulated changes due to
changes in the levels of demand, technology, and import propensity will reflect the impact of price
variations.)
Distinguishing impacts on industry inputs, such as employment by type of demand can be obtained
from equations (15) and (5)
(16)
[ (
)
(
)]
(
∆L KC = LrK • R K ∆P F • f + ∆P X x + ∆R PtF • hˆ f + PtX • x + ∆Lr • R C ∆P F • f + ∆P X x
)
Equation (16) measures the impact of changes in relative prices on the allocation of employment
by industry. As with equation (5), it reflects the embedded and direct within-industry impacts. It
also reflects the changes in prices of domestic demand or exports. The total effect of this term
8
across demand categories must sum to zero as it can only act to re-allocate employment numbers
between domestic demand and exports.
Overall, the main advantage of the model is its capacity to explain the net changes in output and
employment for each industry, from one period to the next, as a function of the distinct impacts of
changes in the levels of domestic final demand, exports, import propensities, technology, and
relative prices. One of its main weaknesses, however, is its incapacity to explain any changes in
behaviour linking the different sources of change. For example, a decline in the price of an
imported commodity may lead to a substitution effect in consumption expenditures; the model,
however, would only attribute this change to two independent developments: an increase in the
import propensity of the product and a change in expenditure levels, thereby shedding no light on
any causality links between the two related developments.
Two clarifications are necessary before proceeding to an analysis of the empirical results of the
model. First, it has been assumed that short term price fluctuations do not impact production
functions but that once they occur they become the new basis of allocations in the subsequent
accounting period. The variations between 1986 and 2004 that are reported in this paper represent
the sum of annual variations from base year current price to subsequent year constant price IO
tables. This method of cumulating annual changes avoids the problem of large shifts in the relative
weights of detailed components between the base and current years that would be associated with
deflating and directly comparing the 2004 and 1986 tables. The added benefit is that the detailed
annual data also allow a closer examination of the evolution of these variations over time.
The second issue is that while one of the main objectives of this paper is the study of the skill
content of employment, the only readily available pertinent data source, which is consistent with
the industrial classification of the IO tables, the KLEMS database, contains information solely on
formal education levels and not overall skills related to the job. The education level is therefore
used as a proxy for the analysis of qualifications required to fulfill a job despite recognizing its
limitations as a measure due to on the one hand the roles of on the job training and experience in
enhancing purely formal qualifications and on the other hand the inherent ambiguity of the
relevance of formal education to the accomplishment of job-related tasks. Furthermore, while the
KLEMS database contains up to six education levels, for ease of analysis, they are grouped in this
study into the two categories of lower education for all those that have at most completed their
secondary education and higher education for those with some or completed post-secondary
education.
3
The sources of changes in employment
The sources of employment by educational attainment in 1986 and 2004 as well as the cumulative
changes between the two periods, as formulated in the model, are presented in Table 1. The levels
of employment for 1986 and 2004 are derived from the combination of equations (2) and (4). The
sum of annual variations due to changes in demand, import shares, and technology are derived
from equation (7) and those that are due to the impact of re-weighting are calculated from equation
(16).
9
Table 1 Sources of changes in employment, by education, 1986 and 2004
Source
Education
1986
Demand
Import shares
Technology
Re-weighting
2004
Consumption expenditures
Low
High
thousands of jobs
4,809
1,839
-320
-2,558
150
3,920
4,943
2,816
-300
662
115
8,235
Exports
Low
1,320
1,456
-68
-1,111
-84
1,513
Total
High
1,022
1,779
-63
-32
-180
2,525
12,094
7,889
-751
-3,039
0
16,193
An overview of Table 1 shows that the job market is dominated by the needs of consumption
expenditures and that job creation, due to growth in the levels of demand by both the domestic and
export sectors has largely outpaced job displacement by technological change and imports. At 4.7
million new jobs, the increase in the level of consumption expenditures has been the highest
contributor to job creation, but despite the relatively smaller size of the export sector, growing
export demand nonetheless generated an additional 3.2 million jobs. Thus, the 138% growth rate
related to export demand substantially outpaced the 48% growth rate of employment linked to
domestic consumption expenditures, pushing up the share of exports in total employment from
19% in 1986 to 25% by 2004.
The impact of changing import propensities displaces 751 thousand jobs and does very little to
counteract the overall role of export growth. Consequently, the overall contribution of net trade to
job creation remains substantial with job creation due to international exports exceeding by almost
four fold the total job losses due to growing import shares.
Labour-saving technological change was the most important factor in counteracting the stimulative
role of the growth in demand. It also appears to play a bigger role in the export sector. As a share
of the gross demand for jobs by sector, that is, as a share of the sum of the 1986 level and the
changes due to growth in demand, it represented 21% in the export sector as compared to 13% in
the domestic sector.
The yearly re-weighting of the constant price IO tables shows relatively minor effects. It
contributes to the reallocation of 265 thousand jobs from the export to the domestic sector. This
shift indicates that between 1986 and 2004, changes in relative prices appear to have generally
favoured the domestic sector.
The period under study witnessed the ascendance of high-skill employment to a position of
dominance in the labour market. In 1986, low-skill jobs exceeded high-skill jobs by a small
margin. This relationship was reversed by 2004 when there were almost twice as many high-skill
jobs as compared to low-skill jobs. A closer examination of the origin of these jobs by type of
demand shows that even though skilled labour only slightly exceeded non-skilled labour in the
domestic sector and was lower than non-skilled labour for the export sector in 1986, it shifted to a
solid supremacy in both sectors by 2004. The share of skilled labour grew to represent 68% in the
domestic sector and 63% in the export sector.
10
In general, demand favoured growth in high-skill employment while technological change focused
on the elimination of low-skill jobs even as it simultaneously promoted the creation of high-skill
jobs. Imports had a relatively small effect but nonetheless still favoured by a small amount the
displacement of low-education as compared to high-education jobs.
Changes in the levels of demand led to the creation of almost 4.6 million high education jobs as
compared to 3.3 million low education jobs. A breakdown by sector shows that in the domestic
sector, the creation of high-education jobs outstripped low-education jobs by 53%, while in the
export sector the same relationship persisted but at a more moderated level of 22%.
Technological change was a very destructive force for low-education jobs. For the domestic
sector, technological change brought about the elimination of approximately 2.6 million loweducation jobs, at the same time as it promoted the creation of 662 thousand high-education jobs.
In the export sector, over 1.1 million low-education jobs were lost to technological change while
the high-education jobs were barely touched with a loss of only 32 thousand.
Decomposing these variations into their yearly elements highlights the role of two factors: the
importance of the business cycle for all sources of change and the appearance of a structural break
in the mid-1990s related to the demand for skilled labour. The main sources of yearly changes in
employment by education level, covering 1986 to 2004 and as formulated in equation (6), are
presented in Table 2. The variations sum to the aggregates presented in Table 1, however, for ease
of presentation, changes in imports and technology are aggregated across types of demand.
Table 2 Sources of employment change by education, 1986 to 2004
Source
Education
Consumption
expenditures
Low
High
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Total change
174
241
189
-22
-187
126
96
137
21
87
103
126
122
169
92
127
135
102
1,839
176
246
174
28
-82
137
87
147
36
105
112
219
229
268
194
249
268
225
2,816
Exports
Import shares
Low
High
Low
High
thousands of jobs
54
63
2
50
22
94
135
164
125
93
133
173
155
141
-6
20
-44
83
1,456
45
71
5
41
18
85
128
171
151
117
168
233
229
219
-27
30
-38
132
1,779
-2
-30
-10
-25
-59
-49
-57
-13
-26
-18
-47
-64
-9
50
22
-3
2
-48
-388
7
-28
0
-22
-41
-46
-56
-21
-23
-22
-46
-80
-15
66
43
-5
-3
-73
-363
Technological
change
Low
High
Total
employment
change
Low
High
-132
-139
-118
-49
-54
-374
-374
-396
-221
-202
-385
-211
-119
-307
-222
-60
-202
-106
-3,669
95
136
63
-46
-278
-204
-199
-108
-100
-40
-196
24
149
54
-115
83
-109
30
-763
61
28
77
83
149
-69
177
69
160
-33
239
-80
-213
-273
57
22
211
-34
630
289
317
256
131
43
107
335
367
324
167
472
291
230
280
267
296
439
250
4,861
11
Over the period under coverage, growth in employment levels has been led by a relatively constant
growth in domestic demand, which showed serious weaknesses only in 1990 and 1991. Net trade
made most of its impact on job creation from 1992 to 2000, coinciding both with the introduction
of the Canada-U.S. Free Trade Agreement and the growth period of the U.S. business cycle.
Yearly variations for the domestic demand and trade categories are heavily influenced by the
business cycle. The slowdowns in job creation around the North American recession in 1991 and
the US recession in 2001 are clearly evident. However, while both domestic consumption and net
trade were contributing to job losses around 1991, the same was not the case for the years
following 2001 when the domestic economy continued to generate a large number of jobs even as
the export sector faltered.
Starting in 1988 and up to 1999, increasing import intensity mildly but consistently contributes to
job losses. This trend in job displacement slows down in 1999 and reverses directions in 2000 and
2001. It is worth noting that this reversal is not generalized in its character and is mostly
attributable to the declining import intensity of intermediate inputs and not due to any major shifts
in the trend related to final expenditures. Of the 181 thousand net jobs created over those two
years, 198 thousand were in fact due to the decline in the import intensity of intermediate inputs
while direct imports by final expenditures continued its contribution to job shedding even if at the
mild difference of 17 thousand jobs.
Until recently at least, the impact of net trade was also highly correlated with the movements of
the Canadian exchange rate. Figure 1 shows that over the period from 1987 to 2000 the two
variables show a high level of correlation. The year 2001, however, marks a decoupling of this
relationship. The continued depreciation of the Canadian dollar in 2001 and 2002 did not stem the
tide of the decline in the demand for exports. While the beginning of the ascent of the currency in
tandem with the growing prices of primary commodities evidently did not hold back real growth in
demand in 2004. Nonetheless, two factors are at play during this period: the Canada-U.S. Free
Trade Agreement which boosted trade with the U.S. and the pull-back in export demand
accompanying the U.S. economic slowdowns in 1991, 1995-1996, and 2001.
12
Figure 1 Employment change due to net trade and the Canada-US exchange rate, 1986-2004
1.6
600
500
400
300
1.4
200
1.3
100
Jobs (1000s)
C$ per $US
1.5
0
1.2
-100
-200
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
1.1
Can-US exchange rate
Employment change, net trade
The biggest contributions by labour-saving technological change appear centered around the
period of highest economic growth, from 1992 to 2001. This would be a reasonable development
during periods of growing demand for labour. Conversely, the moderation in its impacts on labourshedding around the periods of economic slowdown may be partially related to the phenomenon of
labour hoarding by firms during the troughs of the business cycle.
While the overall growth in both domestic consumption and exports has favoured high-skill
employment, the year 1994 appears to be a watershed in the evolution of this bias. Relatively small
differences prior to 1994 evolve into large diverging trends. Up to 1993, domestic consumption
created 766,000 high-skilled relative to 617,000 low-skilled jobs. In comparison, after 1993, this
increases to 2.1 million high-skilled as compared to 1.2 million low-skilled jobs. This represents a
growth in the share of the high skilled from to 55% to 63% between the two periods. For the
export sector, which created an almost equivalent number for both categories at 393,000 for the
high-skilled and 420,000 for the low-skilled during the first period, the relationship also shifts in
the second period to 1.4 million high-skilled and one million low-skilled, to reach a share of 57%
for the highly-skilled in job creation.
Imports similarly evolve in two distinct phases. Up to 1993, imports favoured the displacement of
low education jobs. Beginning in 1994, imports switch to competing more heavily with higheducation jobs. Not all years show a negative impact from increasing import shares. Most notably
in 2000 and 2001, a reversal in offshoring activities actually favours job creation instead of job
shedding, especially of relatively more skilled jobs.
Overall net trade favours the higher relative to the less skilled jobs. Even if the focus is switched to
the post-1993 period, the share of embodied skilled labour still maintains an overall superiority in
exports, at 57% as compared to 54% for imports.
13
Technological change consistently contributes to the displacement of low-education jobs over the
entire period. For most years, it also simultaneously favours the creation of high-education jobs;
the most notable exception being from 1998 to 2000, at the height of the high-tech boom, when it
actually contributed to the displacement of 566 thousand high-education jobs. A possible
explanation could be that technological change reacted to the growing demand for skilled labour
with the introduction of labour-saving transformations aimed at promoting substitution away from
the growing relative scarcity of the factor.
Table 3 basically shows the same information as Table 1 but presented by industry. The 1986 and
2004 levels as well as the sources of employment change between these two periods are
categorized by industry4 and education level.
Table 3 The sources of employment change by industry and education level, 1986 to 2004
Industry
Primary
Secondary
Services
Total
Education
Low
High
Low
High
Low
High
1986
474
214
1,647
1,134
4,009
4,617
12,094
consumption
expenditures
41
25
289
301
1,509
2,490
4,654
exports
import
shares
thousands of jobs
148
-33
102
-23
675
-274
705
-247
633
-81
971
-94
3,235
-751
technology
Reweighting
2004
-304
-48
-1,017
-17
-2,348
695
-3,039
-17
-2
-26
-75
109
11
0
308
268
1,293
1,802
3,831
8,690
16,193
Most benefits from the growing levels of demand accrued to the services industries which gained 4
million new jobs. Services accounted for 86% of the total new jobs related to domestic
consumption and 50% of new jobs related to exports. Job losses due to imports had a much larger
impact on the goods industries at 577 thousand and 77% of the overall impact by this source of
change. Technological change slightly favours net job losses in the services industries at 1.65
million and 54% of the sector total.
For both education categories, the biggest level increases have been in the services sector and
associated with the growth in domestic consumption. The large job losses for low-skill
employment associated with technological change were centered in services at 2.3 million and
secondary industries at 1 million.
A comparison of the beginning and end period levels shows the share of skilled employment
increasing for all three industrial sectors. Between 1986 and 2004, it increased from 31% to 47%
in the primary industries, from 41% to 58% in the secondary industries, and from 54% to 69% in
services.
4
Primary industry includes agriculture, forestry, mining, and oil and gas extraction; secondary industry includes
manufacturing, construction, and utilities; and services includes all other industries, including the non-profit and
government sectors.
14
In the case of the primary goods industries, low-skilled employment benefited the most from the
growth in export demand at 148 thousand jobs created, but this was more than offset by a drop of
304 thousand jobs brought about by technological change. In general, despite the larger level
increases for low-skill jobs, growth rates favoured the higher skilled jobs and technological change
disproportionately targeted the elimination of lower-skill jobs.
High-skilled employment in the secondary industries benefited both from higher level increases
and growth rates in demand. Imports were slightly biased against low-skill employment in terms
of levels but this order is reversed if the data are examined in terms of growth rates. Over a million
low-skill jobs were displaced by technological change, while high-skill jobs were barely touched
with a loss of 17 thousand jobs. Together, imports and technological change displaced more lowskill jobs than was added by growth in the demand levels whereas it was the opposite case for
high-skill jobs.
In the services sector, high-skill jobs due to growing demand significantly outpaced the growing
demand for low-skill jobs. The largest factor in shifting the sector’s skill distributions, however,
was due to technological change. The latter had a substantial impact on reducing low-skill jobs by
displacing 2.3 million at the same time as it actually increased the demand for high skill jobs by a
non-negligible 695 thousand. Imports played a minor role in displacing jobs with only a slight bias
against higher skill jobs.
A more differentiated view emerges from an analysis of the industrial breakout of the skill content
of Canadian trade. For the primary industries, the embodiment of high vs. low skill jobs shows an
equivalent proportion for exports as compared to imports. Secondary industry shows a slightly
higher relative proportion for skilled labour in exports. While services show the highest relative
proportion for skilled labour embodied in exports as compared to imports.
Other studies of the Canadian economy, using different methods, have found no links between
imports and employment levels. Baldwin and Gu (2007) report no impact on employment from
goods or services offshoring over the period from 1961 to 2003. In a similar vein, Morissette and
Johnson (2007) also find no evidence of a correlation between services offshoring and the
evolution of employment rates over the period from 1987 to 2006. These results are not very
surprising since our model shows that due to their small relative weight the impacts of changes in
imports have been swamped by other factors.
Contradicting some of our findings though, Baldwin and Gu (2007) do find a relationship between
the decrease in the share of university-educated workers and the increase in the material offshoring
of the manufacturing sector. But they find no relationship between the offshoring of services
activities across all industries and the share of university-educated workers.
Researchers are also not unanimous when it comes to assessing the reasons for the growing role of
skilled labour. Lee (1996) finds that over the period from 1970 to 1990, the relative employment
of non-production to production workers in the manufacturing sector is negatively related to
technical progress. Gera, Gu, and Lin (2001), however, contradict Lee’s findings. Basing their
analysis on the share of skilled workers in the total wage bill, they find that in the 1980s and early
1990s technological change was biased toward the use of skilled workers in Canadian industries.
15
More in line with our results that both technological change and offshoring have exhibited a skill
bias, Yan (2006) finds that in the manufacturing sector, over 1981 to 1996, both expenditures on
information and communication technologies and offshoring have had an impact on the use of
more skilled workers.
4
The sources of changes in output
Table 4 shows the sources of average annual growth rates of real GDP by industry based on
equation (10)5. The yearly averages demonstrate that, as with employment, the largest contribution
is from domestic final consumption. Exports play a secondary but substantial role which, as with
employment, significantly outpaces the impact of imports. The contribution of technical change to
GDP growth is negative but very small. This visibly contrasts with its important impact on job
displacement. However, in this context, the technology term is not very meaningful as it basically
reflects the impact of shifts in the ratios of industries’ GDP to total inputs (current, primary, and
capital). Since these ratios tend to decrease mildly over the long term, their impact will be
manifested in equivalently small negative values.
Table 4 Sources of GDP growth by industry, average annual rates, 1987 to 2004
Domestic Final
Consumption
Primary
Secondary
Services
Total
0.02
0.27
1.50
1.78
Exports
Percent
0.21
0.70
0.59
1.50
Import
shares
Technological
change
Total GDP
growth
-0.05
-0.24
-0.08
-0.37
-0.05
-0.12
0.06
-0.11
0.14
0.61
2.06
2.80
The relative order of industries in total GDP growth shows the dominant role of services in overall
growth, followed by secondary, and finally by primary industry. Increasing domestic consumption
levels make their biggest contribution to growth in the services industries, with a much smaller
impact on secondary industry and an almost negligible role for primary industry. The export
sector, however, reverses roles, with most of its impact being attributed to the goods producing
industries. Nonetheless, services still benefit substantially from the export sector, even if a large
portion of the activity is in fact attributable to the distribution and transportation of goods. Imports
are heavily tilted towards secondary industry, which accounts for two-thirds of the total drag on
GDP growth by imports.
5
Trade by geographic area
The total impacts of changes in trade by geographic area on employment as expressed in equations
(12) for exports and (14) for imports, are reported in Table 5. The analysis is restricted to the
5
The “Total GDP growth” rate is based on the growth rate between the constant price IO table in year t and the
current price IO table in year t-1.
16
period covering 1997 to 2004 due to limitations on data availability6. We organize the trade data
by OECD and non-OECD membership as a proxy for the categorization of less vs. more
developed economies. We also break out the detail for the most important trading partner in each
grouping, the U.S. and China.
Table 5 Employment effects due to changes in trade, by geography, 1998-2004
1998 1999 2000 2001 2002 2003
thousands of jobs
Exports
5
4
8
5
-4
6
China
Import
-11
-6
-15
-16
-30
-29
Net
-7
-2
-7
-11
-34
-23
Exports
-5
3
23
-5
-2
27
Other non-OECD
Imports
-14
6
8
-6
-9
-23
Net
-19
9
31
-10
-11
3
Exports
32
25
79
3
-3
12
Other OECD
Imports
-37
-22
-3
-21
-3
6
Net
-5
3
76
-18
-6
19
Exports
373
352
250
-36
59
-127
United States
Imports
-81
-2
126
108
34
45
Net
292
350
376
72
93
-82
Exports
405
384
360
-33
50
-81
Total
Imports
-144
-24
116
65
-8
-1
Net
261
360
476
32
42
-83
2004
Total
23
-54
-31
24
-34
-10
29
-18
11
138
-15
123
214
-121
93
47
-162
-115
65
-73
-7
177
-99
78
1,010
215
1,225
1,299
-118
1,181
From 1998 to 2004, net trade is job creating with the exception of 2003, the unique occurrence of a
negative net employment effect, mostly due to the impact of the slowdown in U.S. exports. As
expected, table 5 shows that the U.S. is the main driving force behind changes in the trade-related
component of the job market. Over this period, the U.S. represented 78% of total jobs created by
exports and a smaller but still important component of the impact of imports on jobs.
The trend points to the growing role of trade with all non-OECD relative to trade with other
OECD countries, excluding the U.S. Overall, net trade shows that job creation is outpacing job
losses with OECD countries while job losses are increasingly dominating job creation in trade
with China and to a much lesser extent with the other non-OECD countries.
Table 6 shows the impacts on employment of the changes in import intensities by geography and
by type of demand as derived from equation (14). The results are summed over the period from
1998 to 2004.
Table 6 Employment effects due to changes in import shares by geography and type of demand, 1998 to 2004
Domestic
Export
Total
Source
6
Consumption
Intermediate
inputs
Capital
Intermediate
inputs
Capital
Domestic
Exports
Appendix 1 provides an explanation of the data sources.
17
thousands of jobs
China
Other non-OECD
Other OECD
US
Total
-66
-26
-33
34
-91
-29
-13
-18
73
13
-23
-4
-19
16
-29
-34
-29
-16
82
3
-10
-1
-12
10
-14
-118
-43
-70
123
-108
-44
-30
-28
92
-10
Over this period, domestic final expenditures are the main source of the growing impact of
increasing import intensities. Altogether, they contribute to the loss of 134 thousand jobs. While
consumption expenditures are the most important factor, capital imports also make a noticeable
contribution. Total imports into intermediate inputs show little impact, masking some changes in
the geographic structure of offshoring activities.
An examination of the geographic detail brings to light a growing dichotomy between the relative
roles of the U.S. and all other countries. It appears that offshoring activities are shifting from the
U.S. to all the other regions.
Table 7 shows the impact of exports by geographic region7 on the level of Canadian employment
and income-based GDP at basic prices for 1997 and 2004.
Table 7 Sources of GDP and employment, total and by export region, 1997 and 2004
GDP
Employment
1997
2004
1997
2004
billions of current dollars
Thousands of jobs
2
6
34
71
China
21
25
334
330
Other non-OECD
39
52
622
655
Other OECD
180
280
2,568
2,983
United States
242
363
3,559
4,038
Total exports
817
1,201
14,025
16,193
Total economy
This comparative static analysis shows total exports contributing $363 billion or 30.2% of
Canada’s GDP in 2004. This is slightly up from its share of 29.6% in 1997. The data again
confirm the importance of the U.S. export market for the Canadian economy. In 2004, 23% of
Canada’s GDP was attributable to U.S. exports. The other OECD countries accounted for most of
the remainder, at around 4%, with the ‘Other’ category representing around 2%. China’s negligible
contribution at .5%, visibly contrasts with the previously noted growing impact of Chinese imports
on the Canadian labour market. Over this period, the U.S. increases its share by a percentage point
and China also makes a slight gain while both ‘other’ categories show a slight decline.
7
A measure of the levels of GDP by export country can be obtained from a substitution of equations (8) and (11) into
the export component of equation (2) to obtain: GDPn = gdp • Rx n ,
equations (4) and (11) into equation (2) for the employment levels.
X
for n = 1,...N. And similarly for
18
Interestingly, the contribution of exports to employment shows both a lower level and a different
evolution than its contribution to GDP. While exports initially accounted for 25.4% of total
employment in 1997, at 4.2 percentage points lower than their share in GDP, that share was down
to 24.9% by 2004, just as the share in GDP was increasing. The U.S. and China increasing their
weight at the expense of the other regions.
The higher share in GDP as compared to employment may be partially due to a superior level of
productivity in the export sector relative to production for the domestic economy. This would be in
line with other findings. For example, Baldwin and Gu (2004) report that export-market
participants demonstrated a higher productivity growth among Canadian manufacturing plants
from 1984 to 1996, during the lead up period to the estimates reported in Table 7. They attribute
this superior productivity performance to increases in product specialization, access to foreign
technology, and the greater intensity of competition.
While differing productivities may explain some of the differences in the initial 1997 relative
shares, the continued growth in the divergence is mostly due to the changing mix of exported
commodities. The continuing spread is mostly due to the growing share in exports of the mining
and oil and gas extraction industries, since the latter have, in general, much higher GDP to
employment ratios than other exporting industries.
6
Conclusion
The paper applied an input-output approach to measuring the links between trade, technology, and
domestic final consumption and the observed changes in industry GDP and employment by skill
level. The model lacks certain behavioural links and incorporates certain basic weaknesses that
that are characteristic of input output modelling in general. Yearly variations are based on
snapshots that do not fully articulate the inter-relationships and feedbacks that characterize the
dynamic transition process. In a sense, the model ascribes independence and additivity to
phenomena that are clearly subject to more complex relationships. Nonetheless, despite its
simplifying assumptions, the model likely provides a reasonable approximation of the most
important aspects of these relationships.
We find that in Canada, over 1986 to 2004, employment in general, and skilled employment in
particular, has benefited the most from growth in consumption expenditures on services.
International exports have increased their share in employment and have substantially
overshadowed the impact of growing import intensities. The most important factor in job
shedding, however, was labour-saving technological change, which displaced over 3 million jobs.
Domestic consumption, net trade, and technological change have all favoured skilled labour.
Technological change, however, displaced a large number of low-skill jobs across all industries
even as it simultaneously promoted the creation of a large number of high skill jobs in the services
industries.
Exports contributed relatively more to GDP than to employment. An examination of the more
recent period from 1997 to 2004 shows that among export regions, the U.S. market continues to
19
play a dominant role. For imports, though, an emerging trend points toward a switch in offshoring
activities away from the U.S. toward all other major trading regions.
While much of this paper has concentrated on the sources of the large structural changes in the
Canadian economy, the role of services employment would benefit from further exploration. The
classification of industries according to primary, secondary, and tertiary is very limited and does
not fully elaborate the dependent role of services in the distribution of goods (e.g., transportation,
wholesale, and retail services), in the production of goods (e.g., financial and engineering services)
or in the direct provision of services to final demand. Furthermore, an analysis based on
occupations may also be useful as a means of avoiding some of the problems of classifying
activities by industry as well as provide a more precise measure of the skill content of employment
as compared to the education level criterion.
20
References
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Growth and Innovation, Economic Analysis Research Paper Series, catalogue no. 11F0027MIE,
Ottawa, Statistics Canada.
Baldwin, J. R. and W. Gu (2007) Outsourcing and Offshoring in Canada: Trends, Causes and
Economic Impact, Micro-Economic Analysis Division, Ottawa, Statistics Canada, Forthcoming.
Berman, Eli, John Bound, and Stephen Machin (1998) “Implications of skill-biased technological
change: international evidence,” Quarterly Journal of Economics, 113, 1245-79.
Bound, Johnson and George Johnson (1992) “Changes in the structure of wages in the 1980s: an
evaluation of alternative explanations,” American Economic Review, 82, 371-92.
Chenery, Hollis B., Shuntaro Shishido, and Tsunehiko Watanbe (1962) “The Pattern of Japanese
Growth, 1914-1954,” Econometrica, vol. 30 no. 1, 98-131.
Clark, Colin (1940) The Conditions of Economic Progress. MacMillan & Co. Ltd. London.
Gera, Surendra, Wulong Gu, and Zengxi Lin (2001) “Technology and the Demand for Skills in
Canada: An industry-level Analysis,” Canadian Journal of Economics, vol. 34, no. 1, 132-148.
Gregory, M., B. Zissimos, and C. Greenhalgh (2001) Jobs for the skilled: how technology, trade,
and domestic demand changed the structure of UK employment, 1979-90, Oxford Economic
Papers, 53, 20-46.
Lee, Frank C. (1996) Implications of technology and imports on employment and wages in
Canada. Working paper no. 12. Industry Canada.
Leontief, Wassily (1951) The Structure of the American Economy 1919-1939: An Empirical
Application of Equilibrium Analysis. Oxford University Press, New York.
Morissette, René and Anick Johnson (2007) Offshoring and Employment in Canada: Some Basic
Facts, Analytical Studies Branch Research Paper Series, catalogue no. 11F0019MIE, Ottawa,
Statistics Canada.
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21
Appendix 1: Data sources
All data used in this paper are from Statistics Canada sources. The IO tables and KLEMS database
are published by Statistics Canada. The geographic detail of trade consistent with the IO tables,
however, is not a published product. It had to be constructed from source data on merchandise
trade published by the International Trade Division and on services trade published by the Balance
of Payments Division.
Input-Output tables
The Industry Accounts Division publishes annual IO tables both in current and constant prices.
The constant price table for a given year is expressed in terms of the weights and prices of its
preceding year. From 1986 to 1996, the IO tables are organized in 243 industries by 679
commodities. The industrial classification is according the 1980 Standard Industrial Classification
(SIC). Beginning in 1997, the IO tables are organized in approximately 300 industries, based on
the North American Industrial Classification System (NAICS), by 727 commodities. The two
industrial classification systems are bridged by a 1997 table cross-classified to both systems.
In the IO tables, capital expenditures are available at a higher aggregation level of approximately
50 industries for both classification systems. Since the model requires a consistent industrial
classification for both current and capital expenditures in a given year, capital expenditures by
industry are allocated to the lower level of detail based on industry gross outputs.
Trade by geographic area
International trade by geographic area was constructed based on source data on trade in
merchandise and services. Due to difficulties in constructing this series, we limited our focus to
the most recent period covering 1997 to 2003.
The International Trade Division publishes the complete geographical detail for all merchandise
trade. This information was used to generate the estimates of exports and imports of goods by
geography that are consistent with the IO framework.
The Balance of Payments (BOP) Division publishes adjustments to merchandise trade and trade in
services between Canada and all other countries for the travel, commercial, transportation, and
government services accounts. Commodity detail for these accounts is only published for six
geographical areas: the United States, United Kingdom, Other European Union, Japan, Other
OECD, and Other Countries. Given the growing importance of trade with China, we split out the
geographic area of China based on the totals in the major accounts and the commodity detail from
the category Other Countries. Since trade with China is dominated by goods and services represent
a small value, this method is unlikely to have any serious consequences on the quality of the
overall estimates of trade with China.
Due to a difference in coverage, the IO estimates of total trade are higher than the BOP estimates
of total trade in merchandise and services by the value of ‘financial intermediation’ services. The
22
value of ‘financial intermediation’ services was allocated to geographic regions based on the
closest proxy, the BOP estimate of the value of the item 'financial services other than insurance'.
Finally, the RAS method was used to ensure that the data on geographic areas match both the
commodity dimension of the IO tables and the total trade by geographic area reported by the
primary source data. The implicit price indices from the current and constant price IO tables were
used to deflate the trade by geographic area.
Employment
The Canadian Productivity Accounts publish the KLEMS database, which provides estimates of
capital, labour, energy, materials, and services that are consistent with the industrial classifications
of the IO tables. Labour inputs by industry are classified by education level in terms of hours
worked. Prior to their use in the model, the data are converted to full-time equivalent jobs based on
average hours worked. The database, however, is only available at a higher level aggregation of
124 SIC industries and 89 NAICS industries. The results of the model were therefore summed to
these higher aggregation levels prior to the application of the education coefficients by industry.
23