December 2021

170 Laurier Avenue West
Suite 604
Ottawa, Ontario K1P 5V5
613-233-8891
csls@csls.ca

CENTRE FOR THE
STUDY OF LIVING
STANDARDS

A Strengthening Position at the Bargaining Table?
Understanding the Productivity-Median Wage Gap in
Canada, 1976-2019

James Ashwell
CSLS Research Report 2021-09
Report Prepared for Employment and Social Development Canada
December 2021

A Strengthening Position at the Bargaining Table?
Understanding the Productivity-Median Wage Gap in
Canada, 1976-2019
Table of Contents
List of Tables............................................................................................................. 4
List of Charts ............................................................................................................ 4
Executive Summary .................................................................................................. 5
Motivation .................................................................................................... 5
Framework ................................................................................................... 5
Key findings: ................................................................................................ 6
Explanations of the Gap and Future Research............................................... 6
Introduction .............................................................................................................. 8
I. Review of Empirical Estimates ............................................................................. 9
Findings for Canada ..................................................................................... 9
Findings for the United States .................................................................... 10
Findings for Other Developed Countries .................................................... 11
II. Theoretical Approach ........................................................................................ 12
Intuitive Explanation .................................................................................. 12
Mathematical Decomposition ..................................................................... 14
III. Empirical Approach......................................................................................... 16
Data Sources .............................................................................................. 16
Variables .................................................................................................... 17
Nominal Output ...................................................................................... 17
Total Nominal Labour Compensation ..................................................... 17
Labour Share .......................................................................................... 18
Real Total Output ................................................................................... 19
Labour Productivity ................................................................................ 19
Real Average Hourly Compensation ....................................................... 19
Real Average Hourly Wages ................................................................... 20
Real Median Hourly Wages .................................................................... 20
Possible Improvements in Data Availability ............................................... 21
2

Linking series ......................................................................................... 21
Self-employment .................................................................................... 21
Median wages and hours ......................................................................... 22
Price measures ........................................................................................ 22
IV. Results ............................................................................................................... 23
Tables of Key Results................................................................................. 23
The Productivity-Wage Gap, 1976-2019 .................................................... 26
Developments Since 2008 .......................................................................... 28
The 2000-2008 Period ................................................................................ 29
Trends in Productivity, 1976-2019 ............................................................. 29
Trends in Labour Share, 1976-2019 ........................................................... 30
Trends in Compensation and Wages, 1976-2019 ........................................ 32
Inequality ................................................................................................... 35
V. Explanations of the Gap and Avenues for Future Research ............................ 41
Unionization ............................................................................................... 41
Business Practices and Labour Abuses ....................................................... 42
Globalization, Firm Size and Executive Compensation .............................. 43
Top Income Shares ..................................................................................... 44
Automation, Depreciation and Capital Accumulation ................................. 45
Unemployment ........................................................................................... 45
Final Note .................................................................................................. 46
VI. Conclusion ........................................................................................................ 46
Appendix 1: Comparison of Results from CSLS (2021) with Uguccioni et al.
(2016) ....................................................................................................................... 47
Appendix 2: Comparison of Results from CSLS (2021) with Williams (2021) .... 50
Appendix 3: Comparison of Results from CSLS (2021) with Mishel and Bivens(2021) ....................................................................................................................... 55
Bibliography ........................................................................................................... 58

3

List of Tables
Table 1: Basic Trends (per cent annual growth) ........................................................ 23
Table 2: Explanatory Factors for Productivity Gap (percentage points) .................... 24
Table 3: Explanatory Factors For Productivity Gap (percentages) ............................ 25
Table 4: GDP Shares in Key Years ........................................................................... 32
Table 5: Percentage Shares of Total Nominal Compensation, SLI and Imputed selfEmployment Labour Income, Key Years .................................................................. 34
Table 6: Average Income Growth in Canada by Decile, 1976-2019 .......................... 35
Table 7: Real Earnings vs Real Wage Growth, SLID ................................................ 47
Table 8: Comparison of Results of this Report to Uguccioni et al. (2016), 1976-2014................................................................................................................................. 48
Table 9: Comparison of Results of this Report to Uguccioni et al. (2016), Sub-periods................................................................................................................................. 49
Table 10: Comparison of Results of this Report to Williams (2021), 1976-2019....... 50
Table 11: Comparison of Results of this Report to Williams (2021), 1976-2019....... 51
Table 12: Difference in Growth Rates for Sub-periods (percentage points, Williams
rates minus our rates) ................................................................................................ 51
Table 13: Growth Rates for Periods with Differing Sources ...................................... 52
Table 14: Differences in Sourcing and Growth Rates, Williams (2021) vs CSLS 2021
report ........................................................................................................................ 53
Table 15: Growth Rate of Key Variables, United States ........................................... 56
Table 16: Comparison of Results of this Report to Mishel and Bivens (2021), 19762019 ......................................................................................................................... 56
Table 17: Difference in Rates, Canada and United States.......................................... 57

List of Charts
Chart 1: Productivity-median Hourly Wage Gap, 1976-2019 and Sub-periods.......... 26
Chart 2: Indexed Productivity, Wages and Compensation, 1976=100 ....................... 27
Chart 3: Annual Growth in Productivity and Median Wages, 1976-2019 .................. 27
Chart 4: Productivity Growth by Cyclical Period, 1976-2019 ................................... 29
Chart 5: Labour shares from PA and SNA Data, Indexed to 1976 ............................. 30
Chart 6: Shares of GDP, 1976-2019 .......................................................................... 31
Chart 7: Real Hourly Compensation Growth, 1976-2019 .......................................... 32
Chart 8: Real Average Hourly Compensation and Wage Growth, 1976-2019 ........... 33
Chart 9: Real Median and Average Hourly Wage Growth, 1976-2019 ...................... 34
Chart 10: Distribution of Growth in Incomes Among Earner Deciles, Various Time
Periods...................................................................................................................... 38

4

A Strengthening Position at the Bargaining Table?
Understanding the Productivity-Median Wage Gap in
Canada, 1976-2019
Executive Summary
Motivation
Ensuring that the benefits of economic growth are fairly shared is an increasingly
important policy goal. One useful metric for understanding progress on this issue is thegap between the growth rates of productivity and median wages. As productivity grows,
workers should be able to demand higher wages for their work and benefit from thatgrowth.
While productivity growth has been well-studied for decades, the transmissionof productivity gains to workers has more recently become an important topic forresearchers and policymakers, as median wage growth has grown more slowly than
productivity for extended periods over the past half-century (Sharpe, Arsenault, &Harrison, 2008b). Some hypothesize that the failure to pass on gains to workers is moreof an artifact of the data than it is a reflection of reality, while others believe it represents
a fundamental break in how the economy functions. This report examines productivity
growth and real wage growth and breaks down the gap between the two to better
understand how and why productivity growth is or is not passed on to workers in
Canada.

Framework
The productivity-wage gap we specify in this report is the difference in growth
rates (if any) between output per hour worked and the real median hourly wage. We
decompose that gap into four components which help us to understand the underlying
forces which affect it.
The first component represents changes in how much of the economic value
generated by productivity growth goes to labour as opposed to capital and other sources.
The second component of the decomposition represents the difference between pricechanges in the economy as a whole and the prices of consumer goods. The third
component evaluates the difference between a comprehensive labour compensation
series and a more narrowly defined wage series to understand how much of the
productivity-wage gap is attributable to changes in supplementary labour income (suchas employer pension contributions) and self-employment income. The fourthcomponent measures the effect that inequality has on reducing the benefits the medianworker receives from productivity growth. Median wages can remain static while
average wages grow if, for instance, growth is concentrated among those at the top of5the wage distribution. Therefore, we measure the difference in growth rates between
mean and median wages as a proxy for overall inequality.
We use data from the Survey of Labour and Income Dynamics, the Labour Force
Survey, Canada’s Productivity Accounts and Canada’s System of National Accounts,
going back to 1976 for data availability reasons. We link series where necessary andcompare the growth rates of variables between peak-to-peak years over the businesscycle.

Key findings:• From 1976-2019 median wages grew about 1 percentage point per year more
slowly than productivity. However, the gap between the growth rates of the twovariables was smaller in 2008-2019 than in any other period since 1976. The
second-smallest gap was observed in 2000-2008, while the largest wasobserved in 1989-2000, indicating a “slowdown” of sorts in the productivitymedian wage gap since 2000.
• Faster growth in median wages is largely responsible for this slowdown, as they
grew faster in 2008-2019 than in any other period, and 2000-2008 was thesecond-fastest.
• Growing inequality between median and average wage levels accounts for justunder 50 per cent of the overall gap, while worsening labour terms of trade andlabour share of GDP each account for roughly 25 per cent. Supplementarylabour income and changes in the labour income of the self-employed have onlya small overall effect.
• The labour share of income has declined slightly since 1976. It declined fairly
consistently from 1976 to 2005, then recovered slightly in the recession and has
fluctuated around the same level since then.
• Depreciation costs as a share of GDP have risen, especially since 2005. It
appears not to be the cause of lower labour share, as both labour share anddepreciation share declined and rose in similar periods. Removing output-basedtaxes or housing does not change this story.
• After unusually strong growth in the 1989-2000 period, productivity growth
has returned to the level at which it has stood in most periods since 1976 at
around 1 per cent per year.

Explanations of the Gap and Future Research
Several explanations have been put forward to explain the persistence of this gap,
most of which relate to workers’ declining bargaining power in labour markets since
the mid-1970s. Rising top wage income shares, globalization, automation, declining
costs of investment goods, and changing welfare and labour market policies all relate
to the capacity of workers, particularly workers in the middle and bottom of the wage
distribution, to obtain higher wages. Policy approaches to address the gap must address
rising wage inequality if they are to be successful, and this can be done by empowering
6

workers at the bargaining table. However, the extent to which these trends have eachindividually affected the productivity-wage gap requires further research.

7

A Strengthening Position at the Bargaining Table?
Understanding the Productivity-Median Wage Gap in
Canada, 1976-20191
Introduction
Despite relatively consistent GDP growth, many Canadians do not perceive theireconomic situation to be improving (Russell, 2016). Productivity growth, which helped
drive the large and consistent increases in living standards in the 1950s and 1960s, hasslowed down across the developed world since the mid-1970s (OECD, 2018). Of equal
concern has been the apparent “decoupling” of median wages from the productivity
growth that has occurred. As The Economist (April 10-16, 2021) put it, “It is right tojudge economic progress by the purchasing power of median wages, not profits or shareprices.”
The apparent failure in recent decades of productivity gains to be passed on toworkers has inspired much discussion among economists. Some have hypothesized thatthe observed failure to pass on gains to workers is an artifact of the data more than it isa reflection of reality (Williams, 2021; Strain, 2019), while others believe it represents
a fundamental break in how the economy functions (Stansbury & Summers, 2020;
Mishel & Bivens, 2015). This report examines the trends in labour productivity, wages
and related variables in Canada to demonstrate to what extent typical workers havebenefitted from productivity growth and describe how policy affects the transmissionof productivity growth to median wages.
To shed light on this issue, we use an accounting identity first laid out by Sharpe
et al. (2008a) to decompose the difference between productivity growth and median
wage growth into four components. In doing so, we show the relative importance ofmeasurement and methodological choices, labour share changes and mean-median
wage inequality in explaining the productivity-wage gap.
This report continues in section one with a review of empirical estimates of the
productivity-wage gap in Canada and peer countries. In section two we present thetheoretical approach which guides the empirical inquiry of this report. Section three
details the measurement challenges associated with this project and how we address
them through the construction of our variables. In section four we present our results.
In section five we discuss possible explanations for the trends and identify key avenues
for future research. In Appendixes 1 and 2 we compare our results with Uguccioni etal. (2016) and Williams (2021), who also study Canada. Appendix 3 compares thetrends identified in this report with those of the United States identified by Mishel and
1This paper was written by James Ashwell, while a summer student at the Centre for the Study of Living ofStandards (CSLS), under the supervision of CSLS Executive Director Andrew Sharpe. The CSLS would like tothank Employment and Social Development Canada (ESDC) for financial assistance.

8

Bivens (2021). The Data Appendix contains all the data used in this report along withsome supplemental series pertaining to wages and productivity.

I. Review of Empirical Estimates
Findings for Canada
The productivity-wage gap has become an important object of study ineconomics and estimates of its magnitude have been conducted all over the world. For
Canada, Sharpe et al. (2008a) quantify this gap and develop the decomposition
accounting approach used in this paper. This report uses earnings rather than wages as
the central metric for workers' income, which includes imputed labour income of theself-employed. Median earnings barely grew from 1980-2005, increasing 0.01 per centper year, average earnings grew 0.36 per cent per year, while productivity grew 1.27
per cent per year. Mean-median inequality explained 28 per cent of the gap and thedecline of the labour share explained 20 per cent. Measurement of supplementary
income explained a further 20 per cent and the loss in labour’s terms of trade explained
33 per cent.
Uguccioni et al. (2016) use the same methodology to update the numbers for
productivity and wages to 2014. They find that productivity grows from 1976-2014 by
1.12 per cent per year while median earnings grew at 0.09 per cent per year, for a
productivity-wage gap of 1.03. Fifty per cent of the gap can be explained by increased
mean-median earnings inequality, 30 per cent by the decreasing labour share, and 20
per cent by labour’s terms of trade. The overall contributions of supplementary labour
income and the imputed labour income of the self-employed accounts for less than one
per cent of the overall gap. The 2008-2014 period displays the highest gap of any period
studied at 1.26 as median wages shrank 0.14 per cent per year while productivity grew
1.12.
Williams (2021) investigates the same essential question as the previous authors
but modifies the approach slightly to account for recent debates about measurement andvariable selection. Williams argues that depreciation and taxation costs must be
accounted for when considering productivity and wage trends, and he develops
measures of net productivity and net labour share to integrate these considerations into
his analysis. Williams finds that before accounting for taxes and depreciation, labour
productivity rises from 1961-2019 by 1.65 per cent per year, whereas it rises 1.47 percent per year after including them.
Instead of median wages, Williams prefers average compensation measures toevaluate the transmission of productivity gains to workers. This allows a clearer pictureof how labour overall is faring, but does not provide insight as to the distribution of
those gains among workers. Deflated using the CPI, average wages grew 1.60 per centper year, and using Williams’ preferred implicit consumption deflator they grew 1.73.
The labour share of GDP before accounting for depreciation and taxes decreases over9the same period by 0.19 per cent per year, but after accounting for those factors andcalculating labour’s share of NDP it decreases just 0.01 per cent per year. For the 20082019 period, Williams finds that productivity grows 0.99 per cent per year andcompensation deflated with CPI grew 0.75 per cent per year.

Findings for the United States
Harrison (2009) applies the methodology from Sharpe et al. (2008a) to theUnited States to compare the situations across the two countries. He finds that from1980-2005 productivity in the United States grew 1.73 per cent per year while medianwages grew 0.33 per cent per year, for an overall gap of 1.40 points per year. This gap
is 45 per cent attributable to mean-median inequality, 23 per cent attributable to labour’sterms of trade, 17 per cent attributable to labour’s declining share of GDP, and 12 percent attributable to the measurement of supplementary and self-employment labour
income.2
Mishel and Gee (2012) find that from 1973-2011 productivity in the UnitedStates rises 1.56 per cent per year while median wages rise 0.10 per year, for an overall
gap of 1.46 points per year. They attribute 41 per cent of the gap to mean-medianinequality, 20 per cent to labour’s terms of trade, 17 per cent to the labour share and 11
per cent to supplementary and self-employment labour income.
Stansbury and Summers (2018) use an econometric approach to bring new
insights into the discussion of productivity and pay. They regress compensation on
productivity in a number of different specifications and find that the link between thetwo variables is strong. For the 1973-2016 period, the authors find that 1 percentage
point higher productivity growth was associated with between 0.7 and 1 percentage
point higher median and average compensation growth and with between 0.4 and 0.7
percentage points higher production/non-supervisory compensation. Overall, theauthors estimate that the failure of productivity transmission accounts for 38 per cent of
the observed productivity-median compensation gap, while other factors “orthogonal toproductivity” account for the other 62 per cent. Stansbury and Summers (2018) also run
regressions for other countries, including Canada. They find that 1 percentage point
higher productivity growth is associated with a 0.95 percentage point increase inaverage pay in Canada for 1972-2015, higher than any country surveyed except the UK.
Stansbury and Summers (2018) also test the hypothesis that technologicalchange is responsible for the productivity-wage breakdown. They find that unlike that
hypothesis would suggest, periods of higher productivity growth are not associated witha higher divergence between productivity and pay. They find that higher productivity
growth is also not correlated with mean-median inequality growth, further undermining
technological explanations for the overall productivity-wage gap.

2

Components do not sum to 100 per cent because of data availability and measurement issues, see Harrison (2009)p. 10 footnote on Summary Table 5 for more detail.

10Mishel and Bivens (2021) give further evidence against technologicalexplanations and present a case attributing labour’s lost compensation to policy-related
decreases in their bargaining power. These authors find that from 1979-2019,
productivity grew 1.35 per cent per year and the median wage grew at 0.31 per cent per
year, for an overall gap of 1.03 percentage points per year. Mean-median inequality
accounted for 65 per cent of the gap, labour’s terms of trade accounted for 33 per centand labour’s share of income accounted for 2 per cent. They argue that this gap is best
explained by institutional changes such as macroeconomic austerity and deregulation
which have empowered employers at workers’ expense, reducing the latter’s bargaining
power. Stansbury and Summers (2020) argue that declining worker power also explains
higher profitability rates, lower labour share of income, and lower unemployment andinflation.

Findings for Other Developed Countries
Pessoa and Van Reenen (2013) examine both the United States and the United
Kingdom using a similar methodology to Sharpe et al. (2008a). They define “grossdecoupling” as the difference between the growth of productivity and averagecompensation deflated using the GDP deflator, and define “net decoupling” as thedifference between the growth of productivity and median wages deflated using a
consumption deflator. They find that in the United States from 1972 to 2010, the growthrate of productivity was 63 per cent higher than the median wage growth rate. Twentyone percentage points of this wage decoupling are attributable to mean-medianinequality, while 14 points are due to labour’s terms of trade and 13 per cent are due tonon-wage benefits (p. 25). Putting aside other measurement issues comprising not morethan a few per cent, the remaining 13 per cent of the gap constitutes a “net decoupling”
of average compensation and productivity.
In the UK, gross decoupling is 43 per cent from 1972 to 2010, of which 17
percentage points are explained by inequality, 16 points are explained by non-wage
benefits, 3 points are explained by labour’s terms of trade, 6 points are explained by
self-employed labour income (p. 4). Net decoupling is slightly less than zero, indicatingthat average compensation has grown more quickly than productivity over this period.
Other results have been obtained for a broad cross-section of countries. Sharpe
et al. (2008b) find that across 18 countries, an unweighted measure of average
productivity grew at 2.33 per cent per year for 1970-2006, while average wages deflatedwith consumer price indexes grew at 2.22 per cent per year. This broad co-movement
supports the hypothesis that wages track productivity on some important level, butparticularities of time and place may greatly affect these trends. Four countries
experienced faster average wage growth than productivity, while 9 experienced fasterproductivity than wage growth (some countries were dropped for lack of data). The
labour shares declined on an unweighted average basis across all 20 countries from 51.2
per cent to 50.2 per cent from 1970 to 2006.
11

Uguccioni et al. (2016) find that, in most of the 11 OECD countries studied, fromthe mid-nineteen eighties to around 2010, inequality tends to rise and the labour sharesdecline, contributing to productivity-wage gaps. Ireland, Norway and Spain are the only
countries in which wage growth exceeded productivity growth, and the United States
displays the highest gap of those studied at 1.47 percentage points per year
Schwellnus et al. (2017) find that across 24 OECD countries for 1995-2013
where a decoupling generally takes place: productivity across the countries rose at 1.57
per cent per year while median compensation grew at 1.17 per cent per year, for an
overall gap of 0.40 percentage points per year. Price changes were not examined in thisstudy as the authors simply used GDP deflators for all numbers; compensation was usedrather than wages, so SLI and self-employment labour income were already included intheir wage measures. At the overall level, mean-median inequality therefore accounts
for 55 per cent of the observed gap, while the decline in labour share accounts for theother 45 per cent. Among the G7 countries, productivity and median compensation grew
0.69 and 0.48 per cent per year respectively, much more slowly than for the OECDoverall.

II. Theoretical Approach
Intuitive Explanation
Basic models of the labour market predict that workers overall will be paid anamount roughly equal to the marginal economic value that they provide to employers.
As workers generate more value, their compensation should therefore rise accordingly.
“Productivity” measures the amount of value that workers provide their employers, interms of dollars per hour worked. Workers are generally paid on a per hour basis, so
growth in productivity should be equal to growth in hourly pay. We measure the growthof productivity in per cent change per year for a given period and measure the growthin hourly pay over the same period. Subtracting the rate of growth in wages from therate of growth in productivity, we obtain the gap between the two variables inpercentage points. To understand this gap, we break it down into four components, also
given in percentage points, which add up to the overall productivity-wage gap.
The first component is the labour share. When productivity goes up, part of thebenefits of that increase goes to workers, but part of it goes to capital. Roughly speaking,capital is anything used in production other than the labour of workers. Examples ofcapital may include equipment, technology, or financial capital (i.e. money which wasloaned to the business to allow it to grow). The proportion of economic benefits goingto labour has historically remained steadily around 50-60 per cent in Canada, with theother 40-50 per cent going to capital. These proportions are referred to as the labour
share and the capital share, and while they have historically remained at similar levels,
these shares do change over time. If a higher proportion of the benefits of productivity
growth go to capital, then the labour share becomes smaller, and workers get less thanthey normally would from the increased productivity, generating a productivity-pay
12gap. In the empirical section below, we describe how each variable and measure isconstructed in detail.
The second component of the gap is called “labour’s terms of trade”, and it
relates to price changes. Because of inflation, “real wages” and productivity must be
calculated using constant dollar amounts which account for the differences in pricechanges over time. However, the prices of goods and services consumed by workers
may not rise at the same speed as the prices of goods and services produced by workers.
The adjustment of nominal wages must therefore be done either on the basis ofconsumer prices or producer prices.
The factor by which we multiply the nominal wage series in order to adjust for
price changes is called a deflator. The deflator can be derived from the price levels in
the economy as a whole, or from the price levels of goods and services consumed byworkers. The first type of deflator is called a GDP deflator, and the second is called a
consumer price deflator, the most widely used example of which is the Consumer Price
Index (CPI).3 To understand how workers’ living standards are changing, we deflate
their wages using the CPI since that deflator reflects the costs of living as experienced
by workers. To deflate the output of the economy as a whole, we use the GDP deflator,
because that deflator includes the prices of everything that is produced, rather than justthe prices of things that are consumed domestically. If the prices of consumer goods
change at a different rate than prices overall, there will be a gap between the growth ofreal wages from the point of view of workers and the point of view of their employers.
This difference can contribute to the overall gap between productivity and median real
wages. The term we use for this component of the gap is “labour’s terms of trade”.
The third contributor to the productivity-wage gap is called the SLI/Selfemployment component. This component is essentially the difference between the rates
of growth of average compensation and average wages. The compensation measure ismore exhaustive, as it includes supplementary labour income (SLI) and an estimate oflabour income for the self-employed, in addition to wages. SLI refers to compensationthat employees receive from their employers beyond their regular wages, salaries andcommissions, such as contributions to pension plans and employment insurance. The
labour component of self-employment income is estimated (“imputed”) because there
is no way of directly measuring how much of the income of the self-employed can becharacterized as labour income as opposed to capital income since these workers tend
to invest both their time and their capital into their endeavours. We discuss this
imputation in detail in the “Empirical approach” section.
The final component is wage inequality, as proxied by the difference in growth
rates of average and median wages. The average hourly wage is obtained by adding up
the wage income of all workers and dividing it by the number of total hours(8)
3

There are alternative measures of consumer prices, which we discuss in the Empirical Approach- Variables
section.

13

worked in a year. The median hourly wage is the wage received by the worker in thevery middle of the wage distribution. Put another way, the median wage is the wage of
the worker for whom the number of people who earn more is equal to the number ofworkers who earn less. If workers at the top of the distribution enjoy faster wage growththan everyone else, then the average wage will rise faster than the median wage.4 The
inequality component measures the difference between the rates of growth between
median and average wages. With this fourth component in place, we can fully explain
the gap between productivity and median hourly wages, as the reproduced equation (8)shows below:∆% 𝐺𝑎𝑝 = ∆% 𝑆𝐿𝐼(𝑖𝑛𝑐𝑙. 𝑠𝑒𝑙𝑓𝑒𝑚𝑝𝑙𝑜𝑦𝑚𝑒𝑛𝑡) − ∆% 𝐼𝑛𝑒𝑞𝑢𝑎𝑙𝑖𝑡𝑦− ∆% 𝐿𝑎𝑏𝑜𝑢𝑟 ′ 𝑠 𝑆ℎ𝑎𝑟𝑒 − ∆% 𝐿𝑎𝑏𝑜𝑢𝑟′𝑠 𝑇𝑒𝑟𝑚𝑠 𝑜𝑓 𝑇𝑟𝑎𝑑𝑒
The technical details of how these variables relate to one another and how they
are put together from Statistics Canada data are explained in the Mathematical
Decomposition and Variables sections below.

Mathematical Decomposition
Following Sharpe et al. (2008), our theoretical model starts from the following
accounting identity:
𝑌𝐿
𝑌
𝑌𝐿 𝑃𝑌
=
× ×
𝑃𝐶 × 𝐿 𝑃𝑌 × 𝐿 𝑌 𝑃𝐶
𝑌𝐿 represents the total nominal income of labour, 𝑃𝐶 is the price level ofconsumer goods as measured by CPI, and 𝐿 is labour input as measured by total hours
worked. 𝑌 represents the nominal income of the total economy, 𝑃𝑌 is the price level ofthe total economy, as measured by the GDP deflator.
The left side of the equation is therefore the real hourly compensation of workers
when calculated using consumer prices:

𝑌𝐿
𝑃𝐶 × 𝐿. On the right-hand side,

𝑌

𝑃𝑌

𝑌

𝑃𝐶

labour productivity, 𝐿 is labour’s share of income, and

𝑌
𝑃𝑌 ×𝐿

represents

is the ratio of total prices to

consumer prices, known as “labour’s terms of trade”.
We next differentiate logarithmically with respect to time to derive the following
statement:∆% 𝐻𝑜𝑢𝑟𝑙𝑦 𝑅𝑒𝑎𝑙 𝐶𝑜𝑚𝑝𝑒𝑛𝑠𝑎𝑡𝑖𝑜𝑛 =∆% 𝐿𝑎𝑏𝑜𝑢𝑟 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 + ∆% 𝐿𝑎𝑏𝑜𝑢𝑟 ′ 𝑠 𝑆ℎ𝑎𝑟𝑒+ ∆% 𝐿𝑎𝑏𝑜𝑢𝑟 ′ 𝑠 𝑇𝑒𝑟𝑚𝑠 𝑜𝑓 𝑇𝑟𝑎𝑑𝑒

4

(1) (

1)

It is worth noting that if the poorest workers benefit faster than everyone else, then the same phenomenon isobserved: faster growth in the average than in the median. For this reason it is important to dig deeper into how
the benefits of productivity are distributed among workers, as we do in the “Inequality” sub-section of our results

14This equation shows the relationship between the percentage changes in eachvariable over time.
Our goal is to understand the gap between median real wages and productivity,
not merely the gap between average compensation and productivity. Formally, wewant to find:(2) (2)∆% 𝐺𝑎𝑝 = ∆% 𝐿𝑎𝑏𝑜𝑢𝑟 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦− ∆% 𝑀𝑒𝑑𝑖𝑎𝑛 𝑅𝑒𝑎𝑙 𝐴𝑛𝑛𝑢𝑎𝑙 𝑊𝑎𝑔𝑒 𝐼𝑛𝑐𝑜𝑚𝑒
Rearranging (2) to isolate labour productivity and substituting into (1) we
obtain:∆% 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝐻𝑜𝑢𝑟𝑙𝑦 𝑅𝑒𝑎𝑙 𝐶𝑜𝑚𝑝𝑒𝑛𝑠𝑎𝑡𝑖𝑜𝑛 = ∆% 𝐺𝑎𝑝 +∆% 𝑀𝑒𝑑𝑖𝑎𝑛 𝑅𝑒𝑎𝑙 𝐴𝑛𝑛𝑢𝑎𝑙 𝑊𝑎𝑔𝑒 𝐼𝑛𝑐𝑜𝑚𝑒 +∆% 𝐿𝑎𝑏𝑜𝑢𝑟 ′ 𝑠 𝑆ℎ𝑎𝑟𝑒 + ∆% 𝐿𝑎𝑏𝑜𝑢𝑟 ′ 𝑠 𝑇𝑒𝑟𝑚𝑠 𝑜𝑓 𝑇𝑟𝑎𝑑𝑒

(3) (

3)

Rearranging (3) to isolate the ∆% 𝐺𝑎𝑝 we obtain:∆% 𝐺𝑎𝑝 = ∆% 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝐻𝑜𝑢𝑟𝑙𝑦 𝑅𝑒𝑎𝑙 𝐶𝑜𝑚𝑝𝑒𝑛𝑠𝑎𝑡𝑖𝑜𝑛 −∆% 𝑀𝑒𝑑𝑖𝑎𝑛 𝑅𝑒𝑎𝑙 𝐴𝑛𝑛𝑢𝑎𝑙 𝑊𝑎𝑔𝑒 𝐼𝑛𝑐𝑜𝑚𝑒 −∆% 𝐿𝑎𝑏𝑜𝑢𝑟 ′ 𝑠 𝑆ℎ𝑎𝑟𝑒 − ∆% 𝐿𝑎𝑏𝑜𝑢𝑟′𝑠 𝑇𝑒𝑟𝑚𝑠 𝑜𝑓 𝑇𝑟𝑎𝑑𝑒

)

(4)

4

To understand the importance of employer social contributions and selfemployed labour income in explaining the gap, we evaluate how average compensation(including employer contributions and labour income of self-employed) differs fromaverage wages (excluding employer contributions and labour income of self-employed).
∆% 𝐸𝑚𝑝𝑙𝑜𝑦𝑒𝑟 𝐶𝑜𝑛𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛𝑠= ∆% 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝐻𝑜𝑢𝑟𝑙𝑦 𝑅𝑒𝑎𝑙 𝐶𝑜𝑚𝑝𝑒𝑛𝑠𝑎𝑡𝑖𝑜𝑛− ∆% 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝐴𝑛𝑛𝑢𝑎𝑙 𝑅𝑒𝑎𝑙 𝑊𝑎𝑔𝑒 𝐼𝑛𝑐𝑜𝑚𝑒

(
5)
(5)

Rearranging (5) to isolate average hourly real compensation, and substituting into (4) we obtain:∆% 𝐺𝑎𝑝 = ∆% 𝐸𝑚𝑝𝑙𝑜𝑦𝑒𝑟 𝐶𝑜𝑛𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛𝑠− ∆% 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝐴𝑛𝑛𝑢𝑎𝑙 𝑅𝑒𝑎𝑙 𝑊𝑎𝑔𝑒 𝐼𝑛𝑐𝑜𝑚𝑒− ∆% 𝑀𝑒𝑑𝑖𝑎𝑛 𝐴𝑛𝑛𝑢𝑎𝑙 𝑅𝑒𝑎𝑙 𝑊𝑎𝑔𝑒 𝐼𝑛𝑐𝑜𝑚𝑒− ∆% 𝐿𝑎𝑏𝑜𝑢𝑟 ′ 𝑠 𝑆ℎ𝑎𝑟𝑒 − ∆% 𝐿𝑎𝑏𝑜𝑢𝑟′𝑠 𝑇𝑒𝑟𝑚𝑠 𝑜𝑓 𝑇𝑟𝑎𝑑𝑒(6)

To understand the role that inequality plays in contributing to the gap, we use
the difference between average and median wage income:∆% 𝐼𝑛𝑒𝑞𝑢𝑎𝑙𝑖𝑡𝑦= ∆% 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝐴𝑛𝑛𝑢𝑎𝑙 𝑅𝑒𝑎𝑙 𝑊𝑎𝑔𝑒 𝐼𝑛𝑐𝑜𝑚𝑒− ∆% 𝑀𝑒𝑑𝑖𝑎𝑛 𝐴𝑛𝑛𝑢𝑎𝑙 𝑅𝑒𝑎𝑙 𝑊𝑎𝑔𝑒 𝐼𝑛𝑐𝑜𝑚𝑒(7) (7)

15

Substituting (7) into (6) we obtain:∆% 𝐺𝑎𝑝 = ∆% 𝑆𝐿𝐼 − ∆% 𝐼𝑛𝑒𝑞𝑢𝑎𝑙𝑖𝑡𝑦 − ∆% 𝐿𝑎𝑏𝑜𝑢𝑟 ′ 𝑠 𝑆ℎ𝑎𝑟𝑒 −∆% 𝐿𝑎𝑏𝑜𝑢𝑟′𝑠 𝑇𝑒𝑟𝑚𝑠 𝑜𝑓 𝑇𝑟𝑎𝑑𝑒

(8) (

8)
Therefore, in our empirical section, we will construct variables for the growth
rates of each component outlined in (8), which will show the origins of the gap between
the growth in productivity and the growth rate in median hourly wages.

III. Empirical Approach
Data Sources
All data used in this report are freely available on the Statistics Canada website.
Most of our data come from the Productivity Accounts, which we supplement with datafrom the Survey of Labour and Income Dynamics, the Labour Force Survey, andCanada’s National Accounts. Not all sources provide wage or earnings series which
cover all sectors, or which include supplementary labour income and self-employedlabour income. The table below (from Williams, 2021) summarizes these data sources
and the Variables section below it explains how each variable that we use in thedecomposition is constructed.
Data source

Includescompensation ofself-employed?

Productivity accounts (PA)

Includessupplementarylabourincome?
Yes

Yes

Includesbusiness andnon-businesssectors?
Yes

National accounts (NA)

Yes

No

Yes

Survey of labour and income
dynamics (SLID)5
Labour force survey (LFS)

No

Yes

Yes

No

No6

Yes

Source: Williams, 2021, information from Statistics Canada
A deeper discussion of measurement and variable choice issues aroundproductivity has been well documented by Stigler (1961), Baily and Gordon (1988),
Ahmad and Schreyer (2016), and others.7 Ross and Murray (2010) outline aggregate
income and output measures and discuss their implications for the study of productivity,
while Mućk et al. (2018) outline the issues associated with measuring the labour share.
Not infrequently, Statistics Canada will discontinue and replace statisticalsurveys or will update definitions of variables to conform with new international
5

SLID data is supplemented by Statistics Canada with earlier data from the Survey of Consumer Finance (SCF),
and in 2011 SLID was replaced by the Canadian Income Survey (CIS)6In March 2020, Statistics Canada (2020, p26) added questions to the LFS about compensation for the selfemployed. The data is not yet public, however.
7
For an accessible introduction to these issues, see Sharpe (2002) “Productivity Concepts, Trends and Prospects:
An Overview”

16

standards and emerging best practices. In these cases, we sometimes observe a
difference in levels of a variable across surveys. To link these series, we use the longer
or most recent series available and apply the growth rates of the older or shorter series
to a base year value from the main series. We refer to this approach as “backcasting”
for the remainder of this report.
For example, our nominal GDP series links two series in the year 1981. The mainseries used is from Table 36-10-0221-01 for 1981-2019, and growth rates for the pre1981 period are taken from Table 36-10-02550-01. The value of the main series in 1981
in millions of dollars is 368,358. The values of the older series are 360,471 in 1981 and
314,390 in 1980. Therefore, the growth rate for 1980-1981 is 14.7 per cent. We multiply
the value of the base year of our main series (368,358) by a factor expressing the growthrate of the earlier series for 1980-1981 (314,390/360,471) yielding a value for 1980 in
the linked series of 321,269. The resulting value is then multiplied by a factor
expressing the growth rate from the earlier series.

Variables
Nominal Output
Our measures of nominal output at market prices come from two tables from
Statistics Canada’s Productivity Accounts. Table 36-10-0220-01 is used for 1981-2019,and Table 36-10-0225-01 is used to backcast to 1976. Output in our main analysis ismeasured as real gross value added (GVA), which we multiply by the GDP deflator to
obtain a measure of nominal GVA. A direct measure of nominal value added is provided
by Statistics Canada only for 1997 to 2017, so to ensure consistency over the entire
1976-2019 period we use the deflated real value series for our main analysis. The SNA
nominal GDP annual growth rate for 1976-2019 is 5.80 and the deflated GVA series
growth rate for the same period is 5.82. GVA is denominated in basic prices andexcludes intermediate output.8
We opt to study the total economy rather than just the business sector. Workers
can and do switch between public and private sector employment, so wages are
determined at an equilibrium level reflective of the productivity of both sectors.
Excluding the public sector from our calculations would therefore skew our results.
Total Nominal Labour Compensation
Total labour compensation for our main analysis is taken from Table 36-100480-01 for 1981-2019 and Table 36-10-0303-01 for 1976-1981. Total compensation
includes supplementary labour income (SLI) as well as the imputed labour income ofthe self-employed. SLI, also known as employer social contributions, is defined by
Statistics Canada (2016) as:

8

For more information, see https://www150.statcan.gc.ca/n1/pub/13-606-g/2016001/article/14619-eng.htm.

17

… actual or imputed contributions that employers make on behalf of theiremployees to both government-sponsored social security schemes […] andemployer-sponsored health and disability insurance, pensions, maternity, dental,
life insurance and other benefit schemes (p. 127)
Self-employed workers input their labour and capital into their enterprises. To
avoid counting capital income when adding self-employed income to a worker
compensation measure, it is necessary to impute their labour income distinctly fromtheir capital income. To do this, Statistics Canada assumes that before 1990 “the selfemployed essentially earned incomes similar to the employed” (Baldwin, Gu, & Yan,
2007, p. 26). After 1990, census data indicated that self-employed workers generally
earned less than their paid employee counterparts. Statistics Canada now assumes that:… the hourly earnings of self-employed workers is proportional to that of paid
workers with the same level of education and experience. The proportional or
scaling factor is based on the relative hourly earnings of paid and self-employedworkers from the Census of Population. (Baldwin, Gu, & Yan, 2007, p. 26)
To break down GDP shares in more detail as described below, we supplement thiscompensation series with one from the SNA which excludes self-employed labour
incomes. This series is sourced from Statistics Canada Table 36-10-0221-01 for 19812019 and Table 36-10-0254-01 for 1976-1981.
The wage measure used later in the decomposition excludes both self-employedlabour income and SLI, making it a simpler, though a less comprehensive measure ofworker pay.
Labour Share
Several conceptual issues have been raised with regard to calculating labour
shares effectively. Williams (2021), Pessoa and Van Reenen (2013) and others haveargued that a better measure of the labour share excludes depreciation and output-basedtaxes from the output, generating a “net labour share” measure. However, in this paper,
our primary interest is in understanding the change in workers’ incomes, whether thatbe attributable to depreciation, taxes, higher profits or any other factor. Therefore, wefirst report the labour share using Productivity Accounts data and then in a second step
examine the extent to which different factors such as taxes and depreciation explain thetrends over time using SNA data. We calculate the depreciation as nominal
consumption of fixed capital among corporations, unincorporated businesses,
governments, and non-profit institutions serving households, divided by total nominal
GDP. The tax share consists of taxes less subsidies on production, products and imports,
divided by nominal GDP. The capital share is then calculated as the remaining GDP not
going to labour, depreciation costs, or taxes.
Rognlie (2015) and Gutierrez and Piton (2020) argue that the inclusion of
housing in productivity and labour share calculations is problematic, because the growth18

in value of owner-occupied housing accrues solely or primarily to capital. But this is
only a problem in so far as housing’s share of GDP increases significantly. By our
calculations, rents from owner-occupied dwellings as imputed by Statistics Canada
accounted for 8.03 per cent of Canada’s GDP in 1997 and 8.14 per cent in 2017.9 This
increase of just 0.11 percentage points is small enough that we can confidently set aside
this component in our analysis.
Labour share is calculated by dividing total nominal labour compensation bynominal gross value added (GVA) or nominal GDP. GDP and GVA measures differ
slightly, as do the corresponding measure of labour compensation from the productivity
accounts and SNA. We use GVA for productivity because that is the approach used by
Statistics Canada productivity accounts. In order to avoid introducing discrepancies inour decomposition which would arise from switching to GDP, we also calculate thelabour share using GVA in our main analysis. To remain consistent, we therefore also
use the measure of labour compensation from the productivity accounts, which includes
an imputed measure of labour income for the self-employed.
Nominal GDP, depreciation, output-based taxes, and compensation excluding
self-employed, are taken from SNA Table 36-10-0221-01 for 1981-2019 and Table 3610-0254-01 to backcast to 1976. Nominal GVA and compensation including imputed
self-employment labour income are taken from Table 36-10-0480-01 for 1997-2019
and backcast to 1976 using Table 36-10-0303-01. These series are provided inAppendix Table 9.
Real Total Output
Real output comes from the same two tables as nominal output and isdenominated in chained 2012 dollars. Table 36-10-0220-01 is used for 1981-2019, andTable 36-10-0225-01 is used to backcast to 1976. The conversion from current dollars
to chained dollars is done by Statistics Canada and is based on prices in the total
economy, and the ratio between the two is expressed as the GDP deflator.
Labour Productivity
Labour productivity is calculated as real output divided by total hours worked.
The hours worked series uses Table 36-10-0480-01 for 1997-2019, and growth rates
from Table 36-10-0303-01 to backcast the series for 1976-1996. As mentioned above,
the productivity series is deflated using chained dollars which represent price changes
across the total economy. Our productivity series is denominated in real output per hour
worked.
Real Average Hourly Compensation
To compute real hourly compensation, we divide our nominal totalcompensation series by our average hours worked, which are taken from Table 36-100480-01 for 1997-2019, and Table 36-0303-01 for 1976-1997, the same tables used to9Data are from Statistics Canada GDP estimates by industry from Table 36-10-0402-01

19

calculate productivity. We then deflate our hourly nominal compensation series using
the GDP deflator from Table 36-10-0130-01 and the CPI from Table 18-10-0005-01 to
obtain our two compensation series, which can be referred to as producer wage andconsumer wage. The difference in growth rates of these two series constitutes our“labour terms of trade” gap component.
Although there are some biases in the CPI, it remains the standard measure of
the cost of living in Canada, used by the Government of Canada, Bank of Canada andwidely in the private sector.10 Williams (2021) prefers the consumption expendituredeflator, which weights items differently and has a slightly different scope, but whichbroadly tracks the CPI measure. We do deflate by the consumption expenditure deflator
recommended by Williams (2021) as a robustness check and can confirm that realcompensation grows slightly faster when deflated in that manner (0.71 per cent per year
for 1976-2019 versus 0.61 per year for CPI and 0.85 for GDP-deflated compensation).
Real Average Hourly Wages
Wages, as mentioned above, are distinct from compensation because theyexclude both SLI and imputed self-employment labour income. The series does
however include salaries and commissions. Wage income on an annual basis is takenfrom Statistics Canada Table 11-10-0159-01 which combines Survey of Labour andIncome Dynamics (SLID), Survey of Consumer Finance (SCF), and Consumer Income
Survey (CIS) data for the years 1976 to 2019. We then divide this annual series (whichis already denominated in constant 2019 dollars) by average hours worked as
documented in the Productivity Accounts Table 36-10-0480-01 for 1997-2019, andTable 36-0303-01 for 1976-1996, to obtain an hourly wage income series for each of
those years.
Real Median Hourly Wages
Annual median wage income, denominated in 2019 constant dollars, is takenfrom Table 11-10-0159-01, which combines data from SLID, SCF and CIS. We assume
the median hours worked is 40 hours per week, 50 weeks per year, for an annual median
hours count of 2000. Although Stansbury et al. (forthcoming) show that median hours
may drop below the 2000 mark starting in 2012, we prefer to maintain a constant hours
assumption because the median number of hours worked may not reflect the hours
worked by the earner of the median annual wage income. If we were to use the series
from Stansbury, our post-2011 trend of faster median wage growth becomes stronger,
supporting the overall narrative that our data show. For the years in which LFS andSLID median wage series overlap, the LFS series grows at 0.53 per cent per year while
the SLID series grew at 0.66 per cent per year.11
10

See Sabourin (2012) for a discussion of the potential issues with CPIMedian and average wages are both lower in the LFS series, but the difference between the average wage
measures is much greater than that between median measures. If we use the LFS series for 1997-2019 and backcast
using the growth rates from the SLID series for 1976-1997, then we find that the productivity-wage gap is 0.04
points smaller for 1976-2019, the inequality component is 0.14 points smaller, and the SLI/Self-employment
1120Possible Improvements in Data Availability
Numerous data challenges arise in studying productivity and wages over thistimescale. Some of these challenges have been resolved and others have been worked
around in this paper, but it is worth identifying several ways in which the data can be
improved.
Linking series• Virtually all the important data series used in this report combined data fromboth current and archived Statistics Canada tables. If Statistics Canada provided
linked series for longer-term periods, researchers would have a common
foundation of data to build upon. The SLID/SCF/CIS series is exemplary in thisregard. Unfortunately, it is the exception, as basic series such as totalcompensation, nominal GDP, and labour share must be linked by researchers.
• Current series and archived for the same variables often overlap for a period ofa few years, during which we observe level differences and differences in growth
rates for variables which are ostensibly the same. We have sought to explainthese differences where possible based on Statistics Canada User Guides andliterature, but clear explanations for these differences should be more easily
available.
• Some series are only available as quarterly or monthly series prior to a certain
point in time. Some historical series were only made available to researchers
upon request and have not been published on the Statistics Canada website(Williams, 2021). Compiling annual series and ensuring that historical data iseasily accessible to the public on the Statistics Canada website should be apriority.
Self-employment• The imputation of self-employed income is not clearly described in the
Productivity Accounts documentation. We include a quote from the User Guide
explaining the general procedure, but this explanation lacks detail and makes it
difficult to know exactly how the imputation is done.
• While the SLID/SCF/CIS series breaks down self-employment income explicitly
apart from paid employee income, Productivity Accounts and SNA data do notprovide such a breakdown, so we must infer the magnitude of self-employedincome• Greater transparency and clarity in this area would allow us to better understandwhether self-employed workers increase or decrease productivity, how theyaffect the labour share of GDP, and what impact they have on wage inequality.

component is 0.23 points larger. As for the sub-periods, the productivity-wage gap is 0.40 points smaller for 19892000, 0.27 points larger for 2000-2008 and 0.05 points larger for 2008-2019. Mean-median inequality is lower
for 1989-2000, 2000-2008 and slightly higher in 2008-2019, while the SLI/Self-employment component is larger
for all relevant periods. Labour’s share of income and terms of trade are of course unaffected.

21

As non-traditional work arrangements become more common (Jeon, Liu, &Ostrovsky, 2019) monitoring the changing nature of self-employment will only
become more important.
Median wages and hours• Median hours worked are not available from Statistics Canada unless one canaccess and program public-use microdata files.
• The median and average hourly wage series provided in the LFS is only available
calculated for an employee’s “main job” and therefore fails to capture wage
trends in workers’ secondary jobs.
• Income inequality data are not disaggregated into wage income and capitalincome, so distributional changes within wage income are difficult to discern.
Price measures• Implicit price deflators are not available for GVA, for GDP excluding taxes orfor GDP net of depreciation. Access to these deflators would allow more precise
calculation of the labour share.
• Some series are made available only in constant dollars, while others are only
posted in current dollars. Enabling users of online Statistics Canada tables toselect the denomination of the series would allow quicker and more reliable
comparisons across data sets.
In the next section, we lay out the main results of our decomposition.

22

IV. Results
Tables of Key Results
Table 1: Basic Trends (per cent annual growth)
1976-1981

1981-1989

1989-2000

2000-2008

2008-2019

1976-2000

2000-20192008-20132013-2019

1976-2019

0.51

1.07

1.58

0.92

1.04

1.19

0.99

1.05

1.03

1.10

-0.31

-0.32

-0.50

-0.25

0.08

-0.40

-0.06

0.22

-0.04

-0.25

C. Average realhourly compensation(GDP deflator)

0.20

0.75

1.08

0.67

1.12

0.78

0.93

1.27

0.99

0.85

D. Average realhourly compensation(CPI deflator)

-0.69

0.28

0.82

1.20

0.81

0.32

0.98

1.10

0.57

0.61

E. Average realhourly wages

-0.24

0.30

0.73

0.94

0.75

0.39

0.83

1.10

0.46

0.58

F. Median real hourly
wages

-0.66

0.18

-0.20

0.35

0.66

-0.17

0.53

0.55

0.75

0.14

G. Productivity–
median wage gap

1.18

0.90

1.79

0.57

0.38

1.36

0.46

0.50

0.28

0.96

A. Labour
productivity
B. Labour share of
nominal GDP

A. Real output per hour worked, constant 2012 dollars. Source: Statistics Canada, see Data Appendix T1 for details
B. Total nominal labour compensation divided by total nominal GDP. Growth rate here shows changes in that fraction. Total labour compensation includes imputed labour
income for the self-employed. Source: Statistics Canada, see Data Appendix T5 for details
C. Total labour compensation (including imputed labour income of self-employed and SLI) divided by total hours worked, deflated with implicit GDP deflator. Source:
Statistics Canada, see Data Appendix T6 for details

23

D. Total labour compensation (including imputed labour income of self-employed and SLI) divided by total hours worked, deflated with CPI. Source: Statistics Canada,
see Data Appendix T6 for details
E. Average annual income from wages, salaries and commissions (excl. self-employed), divided by average hours worked (PA, incl. self-employed), deflated with CPI.
Source: Statistics Canada, see Data Appendix T10 for details
F. Median annual income from wages, salaries and commissions (excl. self-employed), divided by median hours worked, deflated with CPI. Source: Statistics Canada, see
Data Appendix T10 for details
G. Labour productivity (A) minus median hourly wages (E)Table 2: Explanatory Factors for Productivity Gap (percentage points)
1976-1981

1981-1989

1989-2000

2000-2008

2008-2019

1976-2000

2000-20192008-20132013-2019

1976-2019

A. Inequality

0.42

0.13

0.94

0.59

0.09

0.56

0.30

0.55

-0.29

0.45

B. Labour's share ofincome

0.31

0.32

0.50

0.25

-0.08

0.40

0.06

-0.22

0.04

0.25

C. Labour's terms of
trade

0.90

0.46

0.26

-0.53

0.30

0.46

-0.05

0.17

0.41

0.24

D. SLI/Selfemployment

-0.45

-0.02

0.09

0.26

0.06

-0.06

0.14

0.00

0.11

0.03

E. Sum of positive
factors

1.63

0.92

1.69

1.10

0.40

1.02

0.25

0.73

0.13

0.93

F. Sum of negative
factors

0.45

0.02

-0.09

0.53

0.02

-0.34

-0.20

0.22

-0.15

-0.03

G. Sum of factors
1.17
0.89
1.78
0.57
0.38
1.36
0.46
0.50
A. Average real hourly wages (E) minus Median real hourly wages (F)B. Total nominal labour compensation divided by total nominal GDP (C)C. Average real hourly compensation deflated with GDP deflator (C) minus Average real hourly compensation deflated using CPI (D)

0.28

0.96

24

D. Average real hourly compensation (D) minus average real hourly wage (E)E. Sum of factors which worsen the productivity-wage gap
F. Sum of factors which make the gap smaller
G Sum of all factors

Table 3: Explanatory Factors for Productivity Gap (percentages)

1976-1981

1981-1989

1989-2000

2000-2008

2008-2019

1976-2000

2000-20192008-20132013-2019

1976-2019

Inequality

35.9

14.5

52.7

103.9

24.7

41.3

65.9

110.1

-102.7

46.5

Labour's share ofincome

26.1

36.1

28.1

44.0

-20.3

29.5

13.2

-44.0

15.1

26.0

Labour's terms of
trade

76.5

52.0

14.4

-93.6

79.6

33.9

-10.4

34.2

147.4

24.6

SLI/Self-employment

-38.5

-2.6

4.8

45.7

16.0

-4.7

31.4

-0.3

40.2

2.9

Contributions to the overall gap from Table 2 rows A-D are divided by the overall productivity-wage gap, listed in row G. The percentages in this table sum to 100 per
cent in each column.

25

The Productivity-Wage Gap, 1976-2019
For the 1976-2019 period, we observe a gap between growth in productivity andgrowth in median wages of 0.96 percentage points. Growing inequality between
average and median worker wages accounts for 48 per cent of this gap, while a decreasein labour’s terms of trade and the labour share of GDP each account for roughly 25 percent. Measurement differences accounting for supplementary labour income and selfemployed workers account for the remaining per cent overall.
Chart 1: Productivity-median Hourly Wage Gap, 1976-2019 and Sub-periods
2.00
1.80
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00

1.79

1.18
0.96

0.90
0.57
0.38

1976-1981

1981-1989

1989-2000

2000-2008

2008-2019

1976-2019

Source: Statistics Canada, see Data Appendix T3 for details

As shown in Table 1, productivity and wages have diverged in Canada since
1976, although the divergence has slowed in each of the most recent periods since 2000.
The factors driving divergence have differed greatly across periods, as shown in Table
2. In the late 1970s and throughout the 1980s, deteriorating terms of trade were mostimportant in driving divergence. In the 1990s, labour terms of trade were less important
than inequality and labour share, with the former taking on nearly twice the importanceof the latter in explaining the gap. Inequality continued to grow significantly in the
2000s, while the labour share continued to shrink, albeit less dramatically. In this periodlabour’s terms of trade made a large contribution to improving workers’ wages for the
first time on record. Since 2008 that component has returned to its previous trend andhas contributed to the continued widening of the productivity-wage gap. However,slower increases in inequality and improvements in the labour share of income madethe growth of the productivity-wage gap smaller since 2008 than in any previous period.
Chart 2 shows that the average wage has tracked productivity much more closelythan the median wage, reflecting the fact that the mean-median inequality component
in the productivity-wage gap is responsible for roughly half of the overall productivitywage gap. The closeness of the average compensation and average wage series reflects
how small an effect the addition of SLI and self-employed workers has on the overall
story. In contrast, the gap between the two series for average compensation, as deflatedby the CPI and GDP deflator, reflects the importance of labour’s terms of trade, whichmakes up roughly 25 per cent of the gap. The gap between average compensation and26

productivity reflects labour’s lost share of GDP over time, amounting to about a quarterof the overall gap.
Chart 2: Indexed Productivity, Wages and Compensation, 1976=100
170.0
160.1
160.0

Indexed productivity (1976=100)

150.0

143.7

140.0
129.9
130.0
128.4

120.0

106.0

110.0

Indexed average hourlycompensation, GDP-deflator
deflated (1976=100)
Indexed average hourlycompensation, CPI-deflated(1976=100)
Indexed average hourly wage
(1976=100)

100.0
Indexed median hourly wage
(1976=100)

90.0

1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018

80.0

Source: Statistics Canada, see Data Appendix for details

The trend in the median wage can be divided into two main periods. From 19762004, the median wage grew and shrank over time, without ever surpassing its starting
value of 18.3 constant 2019 dollars. Beginning in 2004, median wages trend
consistently upward, surpassing the 1976 level in 2011, and remaining above it sincethen.
Chart 3: Annual Growth in Productivity and Median Wages, 1976-2019
2.00
1.58
1.50
1.07
1.00

1.10

1.04

0.92

0.66

0.51
0.50

0.35

0.18

0.14

0.00
-0.20

-0.50
-1.00

-0.66
1976-1981

1981-1989

1989-2000

A. Labour productivity

2000-2008

2008-2019

1976-2000

F. Median real hourly wages

Source: Statistics Canada, see Data Appendix for details

27

Detailed descriptions of the trends in the two most recent time periods areprovided below, followed by descriptions of the long-term trends in our fundamental
variables: productivity, compensation and wages, and the labour share.

Developments Since 2008
While the productivity-wage gap continues to grow, the 2008-2019 gap was just
0.38 percentage points, the lowest of any period since 1976. Productivity growth, at
1.04 per cent per year, was slightly below the 1976-2019 overall trend of 1.10 points
per year, but on par with the growth in 1976-1981 (0.51) and 2000-2008 (0.92). Median
wage growth was well above the 1976-2019 average of 0.14 per cent per year during
this period, as it grew 0.66 per cent annually.
The smaller divergence between these variables can primarily be explained by aslowing of mean-median wage inequality growth and an exceptional improvement in
the labour share of GDP. Inequality grew by 0.09 percentage points per year over thisperiod, down from 0.94 and 0.59 percentage points per year in the preceding two
periods, and well below the long term (1976-2019) rate of 0.45 percentage points per
year.
The labour share of GDP increased from 2008 to 2019 by 0.08 percentage points
per year, rising from 61.9 per cent to 62.4 per cent. However, a closer look shows thatthe labour share has fluctuated significantly year to year, and had already risen to 64.9
per cent of GDP in 2009, before falling immediately to 62.0 by 2011, the level aroundwhich the share fluctuates for the remainder of the period. The slight increase in thelabour’s share between the first and last years of the period is therefore not indicativeof a significant trend towards higher labour share, but a reflection of the annual volatilityof the variable.
The SLI/self-employment component contributed to the worsening of the gap,
albeit only by 0.06 percentage points per year in this period. This represents acontinuation of the post-1989 trend reversing the contribution that this component
makes to the productivity-pay gap, as it had reduced the gap in pre-1989 periods. This
indicates that the decline in self-employment income has been greater than the increase
in SLI which has continued to take place, a trend we discuss in the “Trends inCompensation and Wages” section below.
Upon breaking down the period even further, we see similar trends occurring
across the 2008-2013 and 2013-2019 sub-periods. Mean-median inequality in 20082013 is closer to its 2000-2008 level as it contributes 0.55 points per year to the
productivity-wage gap. For 2013-2019 however, inequality actually decreases as
median wage growth outstrips the average measure, and the gap for that period is
reduced by the inequality component by 0.29 points per year. In contrast, labour’s shareof income increases by 0.22 points per year from 2008-2013 and decreases by 0.04
28

points per year thereafter. Labour’s terms of trade continue to worsen, worsening by
0.17 points per year in 2008-2014 and by 0.41 points per year in 2013-2019. The
SLI/Self-employment component remains small, as it grew 0.11 points per year from2013-2019 and not at all in 2008-2013

The 2000-2008 Period
The 2000-2008 period was unusual because during those years labour’s terms oftrade reduced the size of the productivity-wage gap, the only period in which it did so.
Its contribution to the gap amounted to -0.53 percentage points per year.
In contrast, a declining labour share of income increased the size of the gap by
0.25 percentage points per year in the 2008-2019 period, exactly equal to the long-term
contribution of that component to the gap. Inequality grew during this period at 0.59
points per year, down from 0.94 points in 1989-2000, but above the 1976-2019 rate of
0.45 points. SLI and self-employment contributed 0.09 percentage points per year,
worsening the gap for the first time since 1976.

Trends in Productivity, 1976-2019
Productivity growth in Canada peaked in the 1989-2000 period when it grew at
1.54 per cent per year. The lowest period of growth in our dataset is the 1976-1981
period, in which growth was at 0.51 per cent per year. The growth rate hovers around 1
per cent per year in the other periods, reaching 1.07 in 1981-1989, 0.92 in 2000-2008,
and 1.04 in 2008-2019. We characterize the finding for 2008-2019 as largely acontinuation of the post-1970s norm, rather than an exacerbation of the productivity
slowdown.
Chart 4: Productivity Growth by Cyclical Period, 1976-2019
1.80
1.58

1.60
1.40
1.20

1.07

1.04

1.03

2008-2019

1976-2019

0.92

1.00
0.80
0.60

0.51

0.40
0.20
0.00
1976-1981

1981-1989

1989-2000

2000-2008

Source: Source: Statistics Canada, see Data Appendix T3 for details

29

Trends in Labour Share, 1976-2019
From 1976 to 2019, the Productivity Accounts show that labour’s share of grossvalue added (which includes imputed labour income of the self-employed) declined
annually by 0.25 per cent per year, from 63.2 per cent to 56.8 per cent. The labour shareof GDP based on SNA data (which excludes self-employed labour income) declined at
an annual rate of 0.16 per cent per year, dropping from 54.5 to 50.9 per cent of GDP.
From 1976 to 2000, the labour share of GVA decreased from 63.2 per cent to57.4 per cent, comprising the vast majority of the overall decline. After 2000, the labour
share dropped further to its nadir of 55.6 per cent in 2005. It rebounded quickly to 59.1
per cent in 2009, before largely stabilizing around the 56 per cent mark for the remainderof the post-recession period. The 2008-2019 period is the only one to demonstrate
growth in the labour share of GDP, but this fact conceals the reality that the 2019 levelof 56.8 per cent is lower than its levels in years 2009 (59.1) and 2015 (57.8), indicating
no clear trend of growth or decline since the recession. As chart 5 shows, the trends inlabour share as measured using the two datasets track quite closely, although the PAdata shows a greater overall decline.
Chart 5: Labour shares from PA and SNA Data, Indexed to 1976
105.0
100.0
95.0
90.0
85.0
80.0

Indexed labour share of GVA (from PA) 100=1976
Indexed labour share of GDP (from SNA) 100=1976

Source: Statistics Canada, see Data Appendix T9 for details

Depreciation has been identified as a possible culprit for the declining labour
share (Manyika, et al., 2019; Williams, 2021). Since the GVA and GDP series differ,and no depreciation data is available from the Productivity accounts which contain
GVA, we exclusively refer to the labour share as a percentage of GDP from SNA data
throughout the following discussion.
The depreciation share was 14.8 per cent in 1976 and reached its pre-2000 peakin 1982 at 16.7 per cent of GDP. The share then underwent a secular decline, reaching30

a nadir of 14.4 per cent in 2005. Since then, it rose rapidly to reach its all-time high of
17.4 per cent in 2016, before levelling out at 16.6 per cent in 2019.
This evidence unambiguously supports the thesis that depreciation costs haverisen. However, those costs were declining for many years during which the labour
share also declined and rising in the years when labour share was rising. In fact, boththe labour share and the depreciation share reached their lowest points in the same year,
2005. The hypothesis that depreciation is to blame for declining labour shares would
predict that periods of rising depreciation would correspond with periods of decreasing
labour shares, and we observe the opposite.
Williams (2021) also argues that taxes should be accounted for when calculating
the labour share. The taxation share of GDP was 10.6 per cent in 1976 and rose to its
peak of 13.0 per cent in 1993, before declining to 10.2 per cent in 2008 and then risingslightly to 11.1 per cent in 2019. Although there are some fluctuations in the tax shareof GDP, they do not appear to correspond with changes in the labour share.
We calculate a capital share based on the GDP not accounted for by labour
compensation, depreciation, and output-based taxes. This capital share decreased from
22.0 per cent of GDP in 1976 to its nadir of 17.4 per cent in 1992, and then grew to its
peak of 25.8 per cent in 2005. Since then, it has declined to a 2019 share of 21.4 per
cent.
Overall, the picture of GDP shares is similar to our picture of the productivitypay gap: workers have lost ground over time, but different factors appear to be at playin different periods. Moreover, the labour share after 2000 appears unchanged despite
short-term fluctuations and has even gained some ground since 2008.
Chart 6: Shares of GDP, 1976-2019

Changing income shares
60.00
50.00
40.00

Labour share of GDP (per cent)

30.00

Depreciation share of GDP (per
cent)

20.00

Capital share excluding
depreciation and taxes (per cent)

10.00

1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018

0.00

Source: Statistics Canada, see Data Appendix T9 for details

31

Table 4: GDP Shares in Key Years
1976

1981

1989

2000

2008

2019

69.5

68.4

66.7

63.1

61.9

62.4

30.5

31.6

33.3

36.9

38.1

37.6

54.5

53.4

52.2

49.9

49.5

50.9

14.7

15.7

14.9

14.9

15.5

16.5

Tax share

10.6

10.4

12.1

11.7

10.2

11.1

Capital ShareExcludingDepreciation and
taxes

20.1

20.5

20.8

23.4

24.8

21.4

Labour share of
GVA (PA)
Non-labour shareof GVA
Labour share of
GDP (SNA)
Depreciation
Share

Definitions
Total
compensation/GVA
100-labour share
Total
compensation/GDP
Capitalconsumption/GDP
Taxes less subsidies
on products, imports
and production/GDP
100-labour sharedepreciation sharetax share

Source: Statistics Canada, see Data Appendix T9 for details

Trends in Compensation and Wages, 1976-2019
Compensation has grown in real terms at an annual rate of 0.61 per cent per year
from 1976-2019 when using the CPI to deflate the nominal series. When the GDP
deflator is used, the series grows much faster at 0.85 points per year, thus 0.24 pointsof the productivity-wage gap are attributable to the divergence of prices, which is shownin Chart 3 below. As previously noted, the only period in which the CPI grew more
quickly than did the GDP deflator was for the 2000-2008 period, and the 2008-2019
period appears to show a return to normal for this component.
Chart 7: Real Hourly Compensation Growth, 1976-2019
1.50

1.20

1.08
1.00
0.50

0.82

0.75

1.12
0.81

0.67

0.85
0.61

0.28

0.20

0.00
-0.50
-1.00

-0.69
1976-1981

1981-1989

1989-2000

2000-2008

2008-2019

1976-2019

Average per hour compensation for all jobs (2012 dollars, GDP deflator)

Average per hour compensation for all jobs (2012 dollars CPI)

Source: Statistics Canada, see Data Appendix T5, T6 and T10 for details

32

Average real hourly compensation has grown at 0.61 per cent per year, while
average real hourly wages have grown at a similar pace, 0.58 per cent per year. Wages
have therefore grown slightly more slowly than overall compensation, meaning that thecontribution of the “SLI/Self-employment” component contributes to widening the gap
between productivity and median wages, although its contribution is very small. The
small magnitude of this contribution is somewhat puzzling given that, as Table 5 makes
clear, SLI has grown much more quickly than compensation overall. However, thiscomponent also contains the imputed labour income of the self-employed. We cantherefore conclude that the imputed real hourly incomes of the self-employed havedeclined. Baldwin, Gu and Yan (2007) confirm this trend occurred at least in the 1990s(p. 26).
Chart 8: Real Average Hourly Compensation and Wage Growth, 1976-2019
1.50

1.20

1.00

0.82

0.50

0.94
0.73

0.81 0.75

0.61 0.58

0.28 0.30

0.00
-0.24

-0.50
-1.00

-0.69
1976-1981

1981-1989

1989-2000

2000-2008

2008-2019

1976-2019

Average per hour compensation for all jobs (2019 dollars CPI)
Average real hourly wage (2019 dollars, SLID/SCF/CIS)

Source: Statistics Canada, see Data Appendix T5, T6 and T10 for details

As shown in Table 5, SLI increased significantly as a share of compensation,
reaching 13.7 per cent in 2019 after beginning at 8.7 per cent in 1981.12 In contrast, selfemployment income shrank as a share of compensation starting after 1989, reaching its
lowest level of 4.8 per cent in 2019. Data from SLID/SCF/CIS further confirms thistrend, as the average annual income of a self-employed worker drops in real terms from$39,800 in 1976 to $17,500 in 2019 and the median drops from $18,100 to $7,000 (Data
Appendix 7). This indicates that the decline in self-employment incomes is a real
phenomenon and not a mere artifice of the imputation process.

12

SLI data are only available starting in 1981. The SLI/Self-employment component for 1976-2019 is calculated
as the difference between compensation and wages, but the component cannot be further disaggregated into SLI
and self-employment.

33

Table 5: Percentage Shares of Total Nominal Compensation, SLI and Imputed Selfemployment Labour Income, Key Years

1981
1989
2000
2008
2019

SLI

Self-employment

8.7
9.1
12.0
12.6
13.7

6.3
7.0
6.5
5.6
4.8

Source: Statistics Canada, see Data Appendix T7, T8 for details

When comparing mean wage growth and median wage growth, the importantrole of inequality in producing the productivity-wage gap becomes clear, as was shownin Chart 2.
Chart 9: Real Median and Average Hourly Wage Growth, 1976-2019
1.50
0.94

1.00

0.75

0.73

0.50

0.30

0.66

0.58

0.35
0.18

0.14

0.00
-0.50

-0.20

-0.24
-0.66

-1.00
1976-1981

1981-1989

1989-2000

2000-2008

2008-2019

1976-2019

Average real hourly wage (2019 dollars, SLID/SCF/CIS)Median real hourly wage, 2000 hours worked per year (2019 dollars, SLID/SCF/CIS)

Source: Statistics Canada, see Data Appendix T10 for details

Average wages have grown in all periods except 1976-1981, and between 1989
and 2008 growth outstripped that of median wages by a significant margin (see Table1). The period in which the gap between median and mean wages was the highest was
1989-2000, when the difference in growth rates reached 0.94 percentage points. The
gap in 2000-2008 is lower but still relatively large at 0.59 points. This component
decreases dramatically in the 2008-2019 period, mostly due to the historically high levelof median wage growth at 0.66 per cent per year.

34

Inequality
The mean-median inequality metric only provides a narrow conception of how
the wage distribution has changed in the past decades. In Table 5 below, we show thegrowth rates in different periods of average market income for each income decile.
Market income includes investment and retirement income and is therefore not perfectly
analogous to our wage series. Breakdowns of wage income by decile are only available
through analysis of LFS microdata. Nonetheless, the table shows some stark differences
across time and deciles, showing a clear overarching trend in the long term.
Table 6: Average Income Growth in Canada by Decile, 1976-2019

19761981
19811989
19892000
20002008
20082019
19762019

1st

2nd

3rd

4th

5th

6th

7th

8th

9th

10th

3.13

1.19

0.80

0.89

0.86

0.83

0.96

0.99

0.97

-1.02

-1.91

-0.74

0.05

0.45

0.68

0.83

0.79

0.75

0.88

1.55

-4.38

-2.08

-1.26

-0.70

-0.24

-0.06

0.19

0.33

0.46

1.81

7.07

2.53

1.59

1.45

1.36

1.36

1.35

1.52

1.64

1.00

0.00

1.34

1.09

0.87

0.81

0.84

0.84

0.86

0.77

0.48

0.13

0.27

0.35

0.50

0.62

0.70

0.77

0.84

0.89

0.94

Source: Statistics Canada, see Data Appendix T11 for details

From 1976 to 2019, every decile grows positively but more slowly than thedecile above it, meaning inequality increased across the board. The top decile grows
fastest at 0.94 per cent per year while the bottom decile grows slowest at 0.13 per centper year. Average income growth was 0.83 per cent per year for those at the top of the
distribution, and 0.37 per cent for the bottom half.
The late 1970s are a good time for the bottom decile which grows 3.13 per centper year, and a poor period for the top decile which actually shrinks for the only period
we observe. Deciles 3 to 9 all enjoy comparable modest growth of around 0.85 per centper year. Growth in the 1980s and 1990s have very similar distributional shapes, in thatthe bottom deciles shrank, the upper half of deciles grew, and the top decile grew much
faster than any other. This trend reverses very abruptly in the 2000-2008 period, inwhich the bottom decile grows much faster than any other, deciles 3 to 9 enjoy similar
modest growth rates, and the top decile grows more slowly than any other.
The post-recession period is perhaps the most puzzling. Growth rates are lower
on average than in the preceding periods, although no decile sees negative growth. The
lowest decile’s income is the same at the start and the end of the periods, so its growthrate is zero. In contrast, the second decile grows faster than any other in the period at35

1.34 per cent per year. Deciles 4 to 10 grow at modest rates, with the 9th and 10th deciles
having the third- and second-lowest growth of all deciles.
The story these numbers tell is largely in line with that told by other researchers
studying the topic in more depth. Beach (2017) examines the income distribution tounderstand the extent to which concerns about the “declining middle-class” are reflectedin data. Beach defines the middle class as those workers earning between 50 and 150
per cent of median annual earnings. Beach finds that the number of workers within thatsegment has declined from 74.3 per cent in 1970 to 62.8 per cent in 2005 for full-timefull-year (FTFY) male workers, and from 76.5 to 63.0 per cent of FTFY female workers.
A higher proportion of those exiting this middle-class bracket entered the lower-earning
bracket than entered the higher-earning bracket, as the former bracket grew by 5.1
percentage points for men and 5.7 points for women, while the latter bracket grew 3.4
points for men and 4.9 points for women.
The declines in the share of wage income going to middle-class earners havebeen even starker than the declines in the share of workers in the category. Among male
FTFY workers, the earnings share going to middle-class workers declined from 64.1
per cent in 1970 to 47.3 per cent in 2005, and from 69.3 to 51.5 per cent among women.
Those losses went predominantly to higher earners, who saw their share of wage income
grow 13.5 percentage points among FTFY male and female workers.
These findings are supported by similar findings from Green and Sand (2015),
who examine the “labour polarization” hypothesis put forward by Autor et al. (2006) ina Canadian context. This hypothesis proposes that wages have grown faster at both the
top and the bottom of the wage distribution and that the slowest increases have accrued
to those in the middle of the distribution. Green and Sand show that labour polarization
does not occur in Canada in the long term, although in certain sub-periods a degree ofpolarization does take place. Across all periods the upper percentiles of earners enjoy
the highest gains, while workers at the bottom of the distribution tend to benefit theleast. Among male workers, those at the 90th percentile enjoyed wage growth of 15 percent from 1981-2006, while those at the 10th percentile saw their wages shrink byroughly 10 per cent. Similar patterns are observed for female workers, although thoseat the bottom of the distribution enjoyed positive wage growth. Inequality has therefore
grown since 1981, although it is worth noting that this growth appears to be
decelerating, as inequality grows most in the 1980s and least in the 2000s. In fact, from
2000-2006 all workers below the median wage level enjoyed growth at roughly thesame pace, although the upper half of the distribution continued to grow faster. From2006 to 2011, the bottom percentile grows faster than all others and the top of the
distribution grows at a similar pace to that of the middle percentiles. This pattern ofslowing inequality growth is also observed in the United States for the 1990s, and theauthors point out that Canada’s slowdown could reflect a lagged technology effectdiffusing into Canada. However, they note that research by Fortin and Lemieux (2015)
indicates other forces at work.
36Fortin and Lemieux (2015) break down patterns in wages across provinces andfind that minimum wage laws and resource booms have been driving forces affecting
wage distributions in Canada. They find that the bottom percentile of earners tended to
grow faster than the other percentiles in the 2006-2010 period, especially in provinces
that raised the minimum wage. At the same time, the gap between the 100th percentile
and 50th percentile also grew significantly, as upper-end wage dispersion grewsignificantly. The authors also note that between-group inequality declined over time in
the provinces, even as overall inequality grew or remained constant. This means thatthe inequalities driven by formal education, age, and gender were reduced, even as
inequalities among those with the same characteristics increased. This pattern wasespecially notable in the resource-boom provinces of Alberta, Saskatchewan and
Newfoundland and Labrador.
Further insight into the trends affecting resource provinces is provided byMarchand (2012), who breaks down Western provinces by census division according
to the proportion of economic activity attributable to energy extraction and compares
the wage trends among them. He finds that in those divisions with the most energy
extraction, the growth at the bottom of the distribution is differentially greater than in
the divisions with less extraction, yet at the top of the distribution he also finds higher
dispersion as the very top of the distribution grows even faster than the other deciles.
Overall, Marchand finds slightly higher differential growth of the Gini coefficient inresource-heavy census divisions than in control divisions, and that measures whichweight higher-end inequality more grow more quickly, while those which weight lowerend inequality more grow more slowly.
To understand inequality, we must understand the changes that have taken placeat the top of the income distribution. The incomes of “the 1 percent” or the top percentileof earners have attracted much media attention in recent years (Healing, 2020;
Belmonte, 2020). Veall (2012) uses tax data to understand how top incomes have
evolved and what policy options may be used to address their surging share of income.
Chart 10 plots income growth (y-axis) by income decile (x-axis), to show which deciles
have grown more quickly in which periods. “Wage polarization” would appear as a Ushaped curve, while a linear curve from the bottom left to top right corner would display
a straightforward increase in inequality all along the distribution.

37

Chart 10: Distribution of Growth in Incomes Among Earner Deciles, Various Time Periods
Panel A: 1976-1981
4.00
3.00
2.00
1.00
0.00
-1.00
-2.00
1st

2nd

3rd

4th

5th

6th

7th

8th

9th

10th

3rd

4th

5th

6th

7th

8th

9th

10th

3rd

4th

5th

6th

7th

8th

9th

10th

3rd

4th

5th

6th

7th

8th

9th

10th

Panel B: 1981-1989
2.00
1.50
1.00
0.50
0.00
-0.50
-1.00
-1.50
-2.00
-2.50
1st

2nd

Panel C: 1981-1989
3.00
2.00
1.00
0.00
-1.00
-2.00
-3.00
-4.00
-5.00
1st

2nd

Panel D: 2000-2008
8.00
7.00
6.00
5.00
4.00
3.00
2.00
1.00
0.00
1st

2nd

38

Panel E: 2008-2019
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
1st

2nd

3rd

4th

5th

6th

7th

8th

9th

10th

3rd

4th

5th

6th

7th

8th

9th

10th

Panel F: 1976-2019
1.00
0.80
0.60
0.40
0.20
0.00
1st

2nd

Source: Statistics Canada, See Data Appendix T11 for more details

The income share of the top 1 per cent, 0.1 per cent and 0.01 per cent of earners
declined in Canada from the mid-1930s until the mid-1970s, then increased
significantly through to its peak in 2007. Veall’s data, which ends in 2009 shows a slightdecline in these groups’ income shares for 2007-2009 as it had in previous recessions.
The growth of these high earners’ income shares reflects increases in their wage andsalary income rather than capital income or business income (from self-employment
and partnerships), which grow more slowly and make up a shrinking share of highearners’ total income.
Using Statistics Canada Table 11-10-0055-01, we confirm Veall’s findings forthe pre-2009 period, and also examine trends for 2009-2018. Somewhat surprisingly,
the top income shares did not recover after the 2008 recession and have shrunk as apercentage of total income since that time. The income share of the 1 per cent was 12.0
per cent in 2007 and 10.0 per cent in 2018, the top 0.1 percenters claimed 4.7 per centin 2007 and 3.4 in 2018 and the 0.01 percenters earned 1.6 per cent in 2007 and 1.1 percent in 201813. However, Wolfson et al. (2016) show that this apparent flattening of top
income shares excludes income from Canadian-controlled private corporations
13

There is a large spike in income listed for 2015 and a subsequent large drop in 2016. However, this is likely anaberration attributable to the tax planning measures taken in advance of higher top marginal income tax rates
introduced for 2016. Since 2016 income shares have increased slightly, but it is unclear if this has merely been atax planning rebound or a return to the broader trend of growing top income shares.

39

(CCPCs) and that their inclusion shows that top income shares rebound as of 2010.
They find that when CCPC income is included, the income share of the top percentile
in 2011 is 3.3 percentage points higher, that of the top 0.1 per cent is 1.5 points higher
and that of the 0.01 per cent is 0.8 points higher. Top incomes earners appear to continue
to grow their share of total income in the economy.

40

V. Explanations of the Gap and Avenues for Future Research
The results of this decomposition show that, measurement issues aside, a real
productivity-wage gap persists in Canada and that inequality, the slightly lower labour
share of GDP, and changing labour terms of trade can explain it. In order to ensure thegains of future productivity growth are transmitted to workers, these underlying issues
which cause these trends must be addressed. We outline possible explanations for theseunderlying phenomena in the following section and identify where more detailed
research is needed to ensure policy responses are well-informed.
Before addressing specific policies, it is important to understand how workers’
wages are determined. Essentially, the classical theory holds that workers earn in wages
the amount of value that they provide to the firm. However, every wage-setting decision
made by a firm is shaped both by the supply and demand of labour, and by market
imperfections which prevent the theoretically efficient allocation of resources.
All firms and workers must negotiate in setting wages.14 Workers want to obtain
the best terms of employment, while profit-maximizing employers seek to minimize
their labour costs. The ability of employers or workers to dictate terms to the other party
constitutes their bargaining power (Dufour & Russell, 2015), and policy changes may
affect that bargaining power either directly by altering the balance of power among theparties or indirectly by supporting economic, social, or technological phenomena which
affect that balance. We expect changes in bargaining power to impact both the labour
share of GDP and inequality, though these effects may differ across time, geography,
and industry.

Unionization
Mishel and Bivens (2021) argue that policy-driven erosions of bargaining power
are the primary causes of workers’ inability to capture the full gains of productivity.
The decline in unionization is chief among the issues they identify. When workers
bargain collectively, they are generally able to extract better terms from their employers,and employers are more likely to provide better salaries to their workers as a means toprevent them from forming a union. Dufour and Russell (2015) find union membershipto be positively correlated with the productivity-wage transmission in Canada at the 10
per cent significance level, and Card et al. (2004) show evidence that the decline inunionization in the United States and the UK has contributed to higher income
inequality in those countries.
Unionization rates appear to have declined fairly consistently over time,
dropping from around 38 per cent in 1981 to 30 per cent in 2000 (Morissette,
14

When wages for a particular position are set in advance, it may seem false to claim negotiation occurs. However,in determining what level of compensation to set for that position, the firm has already engaged in an implicit
cost-benefit analysis which it accounts for workers’ alternative uses of time, including choosing to leave thelabour force or remain unemployed. In this way, we can say that at a high level, all wages are determined to an
extent by bargaining power exercised through this mechanism.

41

Schellenberg, & Johnson, 2005) and down to 28 per cent in 2019 (See Data Appendix
T12). Data on this issue are difficult to compare across long time periods, but if we takethe growth rates of these numbers, we can see that from 1981-2001 unionization rates
shrink 1.09 per cent per year, whereas they shrink 0.32 per cent per year from 20002019, indicating there may be a link between the slowing decline in unionization andthe reduction in the productivity-wage gap.
A more in-depth assessment of the various data sources on unionization rates
and union coverage could be coupled with regression analysis such as thatcompleted by Dufour and Russell (2015), to determine more precisely theimportance in of unions in passing down productivity gains to workers.

Business Practices and Labour Abuses
Minimum wage levels may also contribute to workers’ bargaining positions, byincreasing the wages of workers in such positions and pushing employers to makehigher offers to those just above the minimum level. Dufour and Russell (2015) find acorrelation at the 10 per cent level for minimum wage levels and productivity
transmission, and Mishel and Bivens (2021) recommend higher minimum wages toclose the gap in the United States.
Mishel and Bivens (2021) also find the weakening of labour protections and thefailure to properly enforce existing standards have put American workers in worse
positions. When instances of wage theft, uncompensated overtime, underpayment of
undocumented workers, and misclassification of employees go unchecked byregulators, workers become increasingly vulnerable to exploitation by their employers
and less able to exert bargaining power over them.
Other changes in how businesses are run have also changed worker-employer
power dynamics. Non-compete clauses, no-poaching agreements, and forced arbitration
clauses have all become commonplace and reduced workers' ability to turn down bad
employer offers in favour of alternatives (Mishel & Bivens, 2021). Businesses haveincreasingly contracted out much of the work that was formerly done in-house, reducing
employers’ accountability to the workforce employed in their supply chain (Weil,
2014). Increasing shareholder pressure and the rise of shareholder activism have likely
encouraged such practices, as businesses seek to cut costs and focus on high-profit corecompetencies (Stansbury & Summers, 2020; Weil, 2014).

42

The proper enforcement of labour standards and implementation of regulations
against certain emerging business practices will likely improve labour’s bargaining
power and push up median wages in Canada, if these problems are widespread.
However, the extent to which these problems are present in Canada has not beenclosely studied. Future research should identify the extent to which these businesspractices and abuses are occurring in Canada, and determine how best to reducethem.

Globalization, Firm Size and Executive Compensation
These transformations have taken place alongside globalization and rapid
technological change. As Autor et al. (2020) and Schwellnus et al. (2017) havedocumented, globalization has allowed successful firms to become dominant at apreviously impossible scale and become so-called “superstar firms”. This dominancecan translate into monopsony power, meaning that large firms responsible for
employing large shares of employees in a particular market have disproportionate
power in that market. The scale of these firms can also translate into monopoly powerin the product market, meaning they can raise consumer prices and obtain higher profits
for capital in the form of monopoly rents, and thus reduce the labour share in thatindustry (Autor, Katz, & Kearney, 2006). Bivens, Mishel and Schmitt (2018) review
the relevant literature on these issues and find that market power tends to reduce average
wages, as this theory predicts. Superstar effects can also occur on an individual level,
meaning that those in charge of large companies can demand higher compensation
because they exert a greater influence over the performance of the company overall(Rosen, 1981; Giaricano & Rossi-Hansberg, 2006).
Autor et al. (2006) and Goldin and Katz (2007) propose variations of the “skillsbiased technological change” theory. This theory holds that technological changes andautomation have led to higher demand for highly skilled labour and lower demand forworkers in the middle and bottom of the earnings distribution, thus increasing
inequality. The increasing globalization of production in general and manufacturing inparticular has also been proposed as a contributor to rising within-country inequality(Katz & Murphy, 1992). Helpman (2016) summarizes the relevant literature on thishypothesis and finds that globalization and trade have had a “significant, yet modest”(p. 34) impact on wage inequality.
Merchandise imports have grown as a share of total GDP in Canada from 17.9
per cent in 1976 to 26.5 per cent in 2019. They grew most rapidly from 1989 to 2000,
when their share increased from 20.7 per cent to 32.8 per cent. The share then decreased
2.5 per cent per year to its 2008 level of 26.8. These trends indicate that faster tradeintegration may correspond with lower bargaining power for workers.

43More research is needed to understand whether or not monopsony effects play
any role in Canada, and the extent to which superstar effects apply to Canadiancompanies. A preliminary look at import penetration indicates that
globalization may play an important role in determining the productivity-wage
relationship, but a closer look at the many variables which relate to globalizationis necessary to guide an informed policy agenda.

Top Income Shares
These globalization and technological trends have been proposed as explanations
for the contentious issue of executive compensation. Bebchuk et al. (2002) and Bivens
and Mishel (2013) argue that corporate structures create inefficiencies which are
exploited by CEOs to secure compensation levels above optimal levels. However,Kaplan and Rauh (2013) and Lemieux and Riddell (2015) note that top incomes havegrown across professions, indicating broader trends at play. Both of these latter studies
draw attention to the increasing representation of finance industry actors among top
earners, indicating that finance’s increased role in the economy may also be helping
drive up the top incomes. Macdonald (2021) provides a critical overview of CEO
compensation in Canada, while Geloso (2020) provides a more favourable
interpretation.
Veall (2012) finds some support for the theory that globalization and worker
mobility have allowed top talent to find higher compensation by using data regarding
top income tax filers in Quebec. Top Quebecois earners who file income taxes inEnglish have increased their income shares more than those who file in French,
indicating that links with the broader English-speaking corporate world may increase
the level of top earner compensation. Piketty and Saez (2006) also note the largest
increases specifically occur in English-speaking countries, although they leave open thequestion of why this has occurred.15 Veall also notes that large differences in top income
share growth across countries indicate that technological explanations such as the skillsbiased technical change hypothesis put forward by Katz and Murphy (1992) can at best
provide a partial explanation of these trends.
Policies which reduce income inequality by fostering growth in the middle andbottom of the wage distribution will by definition reduce the gap between
productivity growth and that of median wages. However, more research isneeded to determine the extent to which top incomes are the result of market
inefficiencies or a necessary part of operating in a globally integrated economy.

15

See Atkinson and Piketty (2007) for an extensive international comparison of top income shares

44

Automation, Depreciation and Capital Accumulation
Other theories for understanding labour share’s decline and inequality’s rise havebeen put forward. Acemoglu and Restrepo (2018) argue that automation reduces thecomparative advantage of labour, while Karabarbounis and Neiman (2014) similarly
argue that the declining relative cost of investment goods has improved theattractiveness of capital investment and eroded labour’s share of GDP. Piketty and
Zucman (2014) argue that capital accumulation is a driving force of the declining labour
share, and theorize that continued low growth and moderate savings level among thewealthy will continue to erode the labour share, although Rognlie (2015) argues thistheory requires an unrealistic level of labour-capital substitution elasticity.
While depreciation costs are not likely responsive to policy action, policies
which affect the speed and shape of automation may be actionable. However,these markets are complex, and automation has historically been a driver ofhigher productivity (Autor D. , 2015), so policy interventions must be
approached with caution. To address the accumulation theory, Piketty and
Zucman (2014) argue that wealth taxation will be crucial.

Unemployment
A final key component of bargaining power which has not yet been mentioned
is the unemployment rate. The unemployment rate reflects a worker’s capacity to turndown unfavourable offers and find alternatives. The average unemployment rates were
9.6 per cent and 9.2 per cent for the 1981-1989 and 1989-2000 periods respectively,
whereas they were 6.9 and 7.0 for the 2000-2008 and 2008-2019 periods. Stansbury andSummers (2018) and Dufour and Russell (2015) use a regression approach to show clear
correlations between the unemployment rate and the productivity-pay gap.
Unemployment is a central determinant of worker bargaining power. These findings
indicate that an employment-oriented growth strategy may be most effective at ensuring
the transmission of productivity gains to workers. This is especially relevant in the areaof monetary policy. In periods of tighter monetary policy such as the early 1980s in the
United States and the early 1990s in Canada, we observe much higher unemployment
rates, which puts workers in a worse bargaining position. Mishel and Bivens (2021)
argue that macroeconomic policy has been too focused on avoiding inflation risks, andhas pushed unemployment rates too high and harmed workers.

45

The low interest rates and relatively low rates of unemployment which havepersisted throughout most of the 2000s may have significantly improved
workers’ capacity to harness the benefits of productivity gains. More researchwhich looks more comprehensively at the labour market is needed to reveal theextent to which monetary policy and jobs growth affects median wages, but it
appears based on current evidence that enhancing job-creation and ensuring
unemployment remains low may be the most straightforward way of ensuring
workers benefit from productivity in the years to come.

Final Note
As Stansbury and Summers (2018), Williams (2021) point out, the link between
productivity and wages remains significant, despite the transmission issues outlined inthis report and elsewhere. When devising solutions, it therefore remains important tofind policies which increase productivity while also supporting the transmission of
productivity gains to the workforce.

VI. Conclusion
Despite the continued growth of productivity in Canada, median workers havenot enjoyed the full benefit of those gains. Worsening labour terms of trade and a
declining labour share have been partly to blame, but rising mean-median inequality is
the most important factor. Recent decades have shown promise, as the median worker
has benefitted more in the last two business cycles than those before 2000. However,
the gap persists, and policy responses can still improve workers’ situations.
Globalization, automation, tight monetary policy and a significant recession may
have all contributed to making the 1990s the period in which we observe the largest
productivity-wage gap. However, more research is needed in order to understand how
these factors contribute to the growth or suppression of median wages, and how theyshould be managed to benefit workers going forward.

46

Appendix 1: Comparison of Results from CSLS (2021) with
Uguccioni et al. (2016)
Two key differences in methodology create differences in the final results in thisreport vis à vis previous Uguccioni et al. (2016) and Sharpe et al. (2008). Firstly, selfemployment income is treated slightly differently in this study, and secondly, we use a
different hours series for calculating the median hourly wage.
The self-employed are excluded from the median and average hourly wage series
used in our main analysis, whereas they were included in the hourly earnings series usedin 2016. The series is otherwise the same. We replace median earnings with median
wage for two reasons. Firstly, because the measurement issues associated with the
imputation of labour income among the self-employed risk biasing our main results in
unforeseen ways, and secondly because the self-employed often have very different
characteristics than the median paid worker, such as longer average hours worked.
Table 7 shows that earnings grow slightly slower than wages do for all periods
except 1981-1989. This tells us that the incomes of the self-employed grew more slowly
on an annual basis than the incomes of salaried and wage workers. Inequality, as
measured by the gap between median and average measures, is slightly lower for wages
than for earnings for all periods except 1989, implying that inequality among the selfemployed grew faster than among the salaried and wage workers. The component ofour decomposition previously labelled as “Employer social contributions” is now
labelled “SLI/Self-Employment” to reflect the inclusion of these two effects in thatcomponent.
Another implication of exchanging wages for earnings is that we can extend our
SLID series beyond 2011 without access to microdata files. Statistics Canada publishes
median hourly wage statistics from the LFS starting in 1997, whereas the “earnings”
variable has not been collected since the end of SLID. Uguccioni et al. (2016) construct
a median earnings series from microdata to resolve this problem, whereas we can simply
apply the growth rates in median hourly wages to our series.
Table 7: Real Earnings vs Real Wage Growth, SLID

19761981
19811989
19892000
20002011
19762011

Averageearnings

Average
wages

Medianearnings

Medianwages

Earnings
inequality

Wages
inequality

-1.31

-0.89

-0.90

-0.57

-0.41

-0.32

0.32

0.32

0.16

0.16

0.15

0.16

0.56

0.71

-0.36

-0.06

0.92

0.77

0.49

0.55

0.15

0.29

0.33

0.26

0.21

0.34

-0.16

0.03

0.37

0.31

47

The second methodological change pertains to the measures of hours worked.
Previous editions of this decomposition divided annual median earnings by average
hours worked to create an hourly median earnings measure. However, the median hours
worked per worker likely corresponds better with the median per worker earnings thanan overall average. Average hours worked have declined steadily since 1976, but
median hours worked remained constant for all years up to 2011, when we switch to the
LFS median wage series (Stansbury, Summers and Greenspon, forthcoming).16
The consequence of these changes is our new median per hour wage measure
grows faster than the old measure. This is because the old measure’s denominator was
decreasing with time, whereas the new denominator remains constant.
The results of these methodological changes lead to changes in the inequality
and the SLI/Self-employment components. Inequality rises faster in the new series forthe 1976-1981 and 2000-2008 periods, but rises more slowly for 2008-2014. The
SLI/Self-employment component (formerly “employer social contributions”) grows
more slowly or at the same pace in the first three periods and then rises more quickly inthe last two periods. Labour’s terms of trade and the labour share measures are
essentially unchanged, and the inequality adjustments have a much greater impact on
the overall productivity-wage gap than the SLI adjustments. As a result, the overall gap
is larger in 1976-1981 and 2000-2008 periods, smaller in the 1989-2000 and 2008-2014
periods, and unchanged in 1981-1989.
Table 8: Comparison of Results of this Report to Uguccioni et al. (2016), 1976-2014
This report
Inequality
Labour's share ofincomeLabour's terms of
trade
SLI/SelfEmployment
Total gap

16

Difference

0.56
0.31

Uguccioni et al.
2016
0.53
0.31

0.20

0.20

0.00

0.04

0.00

0.04

1.11

1.03

0.08

0.03
0.00

The implication of this trend is that more people are working part time and fewer hours, but at the same time
more people are working longer hours. The number of people working more has been close to the number
working less, but the degree to which those who work less have decreased their hours is stronger than the degree
to which those who work more have increased their hours.

48

Table 9: Comparison of Results of this Report to Uguccioni et al. (2016), Sub-periods
Factors contributions to productivity-wage gap, calculated in this report(percentage points per year)
1976-1981 1981-1989 1989-2000 2000-2008 2008-2014
Inequality
0.27
0.15
0.88
0.83
0.39
Labour's share of
0.76
0.19
0.46
0.23
-0.08
incomeLabour's termsof trade
SLI/Selfemployment
Productivitywage gap

0.90

0.46

0.26

-0.53

0.14

-0.39

-0.03

0.00

0.09

0.52

1.53

0.78

1.60

0.62

0.98

Component contributions to productivity-wage gap, calculated in Uguccioni et al(percentage points per year)
1976-1981 1981-1989 1989-2000 2000-2008 2008-2014
Inequality
-0.41
0.15
0.92
0.20
1.52
Labour
0.76
0.19
0.48
0.29
-0.20
Share
Labour’s
0.92
0.48
0.24
-0.55
0.18
Terms of
Trade
SLI
0.03
-0.03
0.14
0.01
-0.24
Productivitywage gap

1.21

0.78

1.79

-0.05

1.26

Differences between component contributions (this report minus Uguccioni
numbers, percentage points per year)
1976-1981 1981-1989 1989-2000 2000-2008 2008-2014
Inequality
LabourShare
Labour’s
Terms ofTrade
SLI/Selfemployment
Productivitywage gap

0.68
0.00

0.00
0.00

-0.04
-0.02

0.63
-0.06

-1.13
0.12

-0.02

-0.02

0.02

0.02

-0.04

-0.42

0.00

-0.14

0.08

0.76

0.32

0.00

-0.19

0.67

-0.28

49

Appendix 2: Comparison of Results from CSLS (2021) with
Williams (2021)
Williams (2021) uses a similar methodology to study these issues and comes toslightly different conclusions. Williams’ main conclusion is that average compensation
has kept up with net productivity. Net productivity is defined as net domestic productat basic prices divided by hours worked, meaning it removes taxes and depreciationfrom GDP. Several data differences lead our two studies to come up with different
results. See Table 14 for a detailed description and comparison of sources.
Williams uses average compensation as the measure for his main analyses rather
than median wage, because his central aim is to investigate the transmission of
productivity gains by firms to workers in general. Our study aims to understand theoverall transmission of productivity to the median worker while taking note of trends in
SLI and self-employment which might affect the perception of the transmission.
Williams also studies a longer time range, 1961-2019, and uses historical dataobtained by special request from Statistics Canada to study the pre-1997 periods.
Consequently, results for those periods differ slightly between our studies, as laid out
in Tables 10 and 11 below.
Table 10: Comparison of Results of this Report to Williams (2021), 1976-2019
Gross
Productivity
Net productivity
Avg comp (GDP)Avg comp(consumer)
Labour sharechangeCSLS 2021
1.08

Williams (2021)
1.18

Differences
-0.10

1.02
0.85
0.61

0.98
0.90
0.92

0.03
-0.05
-0.31

-0.24

-0.28

0.04

Williams’ “hours worked” series for 1961-1997 is obtained by special requestfrom Statistics Canada and grows more slowly than ours. This means both of his
productivity series (net and gross) grow more quickly than ours do for the pre-1997
periods. It is also one reason his pre-1997 per hour compensation series grows more
slowly, the other reason being that he uses a total compensation series from a special
request that grows more quickly than ours does.
Williams uses the same tables for total and average labour compensation as we
do for the 1997-2019 periods so those results are mostly the same. However, the datain these tables for 2016-2019 were revised after Williams accessed them such that his
average compensation series grow more slowly than ours in the last years of the 20082019 period. This is not enough to offset the faster growth in the pre-1997 series, which50

is why our long-term compensation growth remains smaller. Deflators used throughout
are identical.
Returning to productivity, Williams uses CPA tables for calculating GDP andgross productivity, while we use SNA tables for those calculations. Output grows fasterin the CPA than in the SNA for all periods, so Williams’ gross productivity series grows
more quickly than ours in all periods, even when we use the same “hours worked” series
for the post-1997 period.
Interestingly, Williams doesn’t use CPA tables to calculate NDP, but rather uses
SNA tables, consistent with our approach. The only differences in our net productivity
series are those which occur in the pre-1997 series and can be attributed to the use ofdifferent “hours worked” series.
In short, we have very similar results for the post-1997 period, but before thenWilliams uses different sources which make our results differ.
Table 11: Comparison of Results of this Report to Williams (2021), 1976-2019

Gross Productivity
Net productivity
Avg comp (GDP)Avg comp(consumer)
Labour sharechangeThis report
1.08
1.02
0.85
0.61

Williams (2021)
1.18
0.98
0.90
0.92

Difference
-0.10
0.03
-0.05
-0.31

-0.24

-0.28

0.04

Table 12: Difference in Growth Rates for Sub-periods (percentage points, Williams rates
minus our rates)
19811989

19892000

20002008

20082019

0.15

0.02

0.01

0.07

0.07

0.07

-0.01

0.00

0.08

0.15

0.00

-0.06

0.09

0.15

-0.01

-0.06

Labour share -0.06

0.13

-0.02

-0.12

Gross
Productivity
Net
productivity
Avg comp(GDP)
Avg comp(CPI)

Legend:Orange= CPA output series usedby Williams instead of SNA
outputBold= Different hours series(pre-97)
Green= Revised 2016-2019 datafor compensation and hours from
CPA
Purple= Different compensation
series (pre-97)

51

Table 13: Growth Rates for Periods with Differing Sources
Nominal output
Real output
Total nominal labour
compensation
Net domestic product (nominal)
Hours worked
Productivity
Net productivity

Period1961-1981
1961-2019
1961-1997

CSLS 2021
11.46
3.11
8.70

Williams 2021
11.40
3.21
8.81

1961-1981
1961-1997
1961-2019
1961-2019

11.56
1.79
1.52
1.51

11.32
1.71
1.65
1.47

52

Table 14: Differences in Sourcing and Growth Rates, Williams (2021) vs CSLS 2021 report
Williams

CSLS 2021
For 1981-2019, data is from SNA,
For 1981-2019 is from SNA
Table 36-10-0221-01 (formerly 384Table 36-10-0221-01 (formerly0037). Series is backcast for 1961-1981
CANSIM 384-0037) anddata using data from SNA, Table 36-10Nominal
backcast using annualized0254-01 (formerly 380-0016). Series
Outputgrowth rates from quarterly SNA overlap from 1981-2011, the CAGR ofseries in table: 36-10-0103-01
Table 36-10-0221-01 in that time is(formerly CANSIM 380-0063)
5.38 and the CAGR of Table 36-100254-01 is 5.35
For 1981-2019, data is from SNA,
For 1997-2019, chained 2012
Table 36-10-0222-01 (formerly 384dollar amounts CPA Table: 360038). Series is backcast for 1961-1981
10-0480-01 (formerly CANSIM data using data from SNA, Table 36-10Real output
383-0033). Series is then02550-01 (formerly 380-0017). Series
backcast to 1961 using a real
overlap from 1981-2011, the CAGR of
GDP index from special request Table 36-10-0222-01 in that time is
to Statistics Canada
2.44 and Table 36-10-02550-01 series
CAGR is 2.50
For 1997-2019, data is from CPA, Table
For 1997-2019, data is from36-10-0480-01 (formerly 383-0033).
CPA Table 36-10-0480-01
Total
Series is backcast to 1961 using data
(formerly CANSIM 383-0033).
nominalfrom CPA, Table 36-10-0303-01
Series is backcast to 1961 using
labour(formerly 383-0003). Series overlap
labour compensation series fromcompensationfrom 1997-2001, the CAGR of Table
special request to Statistics
36-10-0480 in that time is 5.61 and theCanadaCAGR of Table 36-10-0303-01 is 5.76
Net domestic Series is constructed by
Series is constructed by removing
product
removing capital consumption
capital consumption and output taxes(nominal)
and output taxes from GDP. For from GDP. For 1981-2019 data is from

Comparison

Growth rates

Same series used
for 1981-2019,different series
are used prior

Williams CAGR 1961-1981: 11.40
CSLS 2021 CAGR 1961-1981: 11.46

We use SNA andWilliams uses
CPA for real
outputWilliams CAGR 1961-1997: 3.71("PA_historical" tab)
CSLS 2021 CAGR 1961-1997: 3.57
Williams CAGR 1997-2019: 2.40("PA_annual" tab)
CSLS 2021 CAGR 1997-2019: 2.36
Williams CAGR 1961-2019: 3.21("PA_historical" tab)
CSLS 2021 CAGR 1961-2019: 3.11

We use the same
CPA series for
1997-2019,different series
are used prior

Williams CAGR 1961-1997: 8.81
CSLS 2021 CAGR 1961-1997: 8.70

Same series for
1981-2019,

Williams CAGR 1961-1981: 11.32
CSLS 2021 CAGR 1961-1981: 11.56

53

1981-2019 is from SNA Table
36-10-0221-01 (formerly
CANSIM 384-0037) andbackcast using annualized
growth rates from quarterly SNA
series in table: 36-10-0103-01(formerly CANSIM 380-0063)

SNA Table 36-10-0221-01 (formerly
different series
CANSIM 384-0037). Series is backcast are used priorfor 1961-1981 using Table: 36-10-025401 (formerly CANSIM 380-0016)

For 1997-2019 data is from CPA, Table
36-10-0480-01 (formerly 383-0033).
Series is backcast to 1961 using growth
rates from CPA, Table 36-10-0303-01(formerly 383-0003). Series overlap
from 1997-2001, the CAGR of Table
36-10-0480 in that time is 1.68 and theTable 36-10-0303-01 series CAGR is
1.95

Hours
workedFor 1997-2019 is from CPA
Table: 36-10-0480-01 (formerly
CANSIM 383-0033) andbackcast to 1961 using growth
rates from a specially requested
series from Statistics Canada

Productivity"Gross" productivity is chained
dollar output (CPA) divided byhours worked (CPA, including
specially requested series)"Gross" productivity is chained dollar
output (SNA) divided by hours worked(CPA).

Net
productivity

Net productivity is nominal
NDP (using CPA output)
deflated using the GDP deflator
divided by hours worked (CPA,
including specially requested
series)Net productivity is nominal NDP (using
Differences due
SNA output and CPA hours) deflated
to hours andusing the GDP deflator divided by hours
output differences
worked (CPA)

Same series for
1997-2019,different series
are used priorDifferences due
to hours andoutput differences

Williams CAGR 1961-1997: 1.71
CSLS 2021 CAGR 1961-1997: 1.79

Williams CAGR 1961-1997: 1.97
CSLS 2021 CAGR 1961-1997: 1.75
Williams CAGR 1997-2019: 1.18
CSLS 2021 CAGR 1997-2019: 1.13
Williams CAGR 1961-2019: 1.65
CSLS 2021 CAGR, 1961-2019: 1.52
Williams CAGR 1961-1981: 2.24
CSLS 2021 CAGR 1961-1981: 2.39
Williams CAGR 1981-2019: 1.09
CSLS 2021 CAGR 1981-2019: 1.05
Williams CAGR 1961-2019: 1.47
CSLS 2021 CAGR 1961-2019: 1.51

54

Average compensation in his study grows at 0.09 percentage points per year
faster from 1981-1989 than in our report, and 0.15 points per year faster in 1989-2000.
Labour productivity (“gross” or not net of depreciation and taxes) is also higher by 0.15
points per year for 1981-1989 and 0.02 points per year for 1989-2000. Net productivity
grows 0.07 percentage points faster in Williams’ data than in ours for each of the pre2000 periods.
Gross and net labour productivity and compensation grow at effectively identicalrates for 2000-2008, but the results for 2008-2016 differ slightly. Gross productivity
grows 0.07 points faster while compensation grows 0.06 points slower, while net
productivity grows equally fast in both data sets. The reason for these post-2008
differences is that hours and compensation data from Table 36-10-0480-01 were
updated for the years 2016-2019 after being accessed by Williams in 2020. Hours
worked were revised upwards in 2016, 2017, and 2018, and revised slightly downwards
in 2019. Total compensation was revised downwards for all four years. Consequently,
our labour share growth rate for the post-recession period is lower, as are our averagecompensation growth rates.
While we don’t calculate net labour share or net productivity growth for ourcentral analyses, we have the data to do so. We find that net productivity from 19762019 grew 1.02 per cent per year, while average real hourly compensation deflated with
CPI grew 0.61 per cent per year. Williams finds that for 1961-2019 net productivity
grows 1.47 per cent while CPI-deflated average real hourly compensation grows at 1.59
per cent. This difference mostly reflects the difference in time scales, since the pre-1976
period saw much higher growth in both wages and productivity.

Appendix 3: Comparison of Results from CSLS (2021) with Misheland Bivens (2021)
Mishel and Bivens (2021) analyze wages and productivity in the United Stateswith a methodology similar to this report. Although different dates are used to break uptime periods, we can report on analogous periods, as indicated in Table 6. Other
methodological and data collection differences mean that these results should beinterpreted with a significant degree of wariness.
Productivity growth and all measures of compensation and wages have grown
more slowly in Canada than in the United States over the long term. The gap between
productivity and wages has grown only slightly more slowly in Canada based on thesefigures. Mean-median inequality accounts for 65 per cent of the gap measured in the
United States from the late 1970s to 2019, whereas in Canada it accounts for 50 per
cent. Labour’s terms of trade account for 32 per cent of the gap in the United States but
only 25 per cent of the gap in Canada. Meanwhile, the decline in labour share only
accounts for 2 per cent of the gap in the United States compared to 25 per cent in
Canada. Measurement differences between compensation measures and wage measures55

make a small but positive contribution to the gap in the United States, whereas it makes
a small but negative contribution to it in Canada.
Table 15: Growth Rate of Key Variables, United States

Productivity
Average compensation- GDP
Deflator
Average compensation- CPI
Median hourly wages
Productivity-wage gap

1979–
1995
1.06
0.88

1995–
2000
1.38
1.21

2000–
2007
2.32
2.93

2007–
2019
2.19
1.48

1979–
2019
1.49
1.05

0.68
-0.47
1.33

0.82
-0.04
1.22

2.26
1.41
1.57

1.24
0.46
0.75

0.86
0.41
1.03

Table 16: Comparison of Results of this Report to Mishel and Bivens (2021), 1976-2019
This report
Gross productivity
Net productivity

1.08
1.02

Mishel andBivens (2021)
1.35
1.18

Difference

Average compensation(GDP)
Average compensation(CPI)
Labour share change
Median real hourly wages

0.85

1.17

-0.32

0.61

0.89

-0.28

-0.24
0.15

0.01
0.31

-0.25
-0.16

Productivity-wage gap

0.93

1.03

-0.10

-0.27
-0.16

56

Table 17: Difference in Rates, Canada and United States

Mishel & Bivens startand end dates"The
Eighties"
19791995"The
Nineties"
19952000“Early2000s”
20002007

Current report start andend dates

19811989

19892000

20002008“Post“Mainrecession” analysis”
200719792019
2019
20082019

19762019

Difference in annual growth rates, key variables, (percentage points, Canada less
United States)
Productivity
-0.44
-0.78
-1.29
-0.16
-0.26
Average compensation-0.46
-1.85
-0.81
0.32
-0.32
GDP Deflator
Average compensation-0.54
-1.44
-0.04
0.17
-0.28
CPI
Median hourly wages
0.20
-1.47
-0.18
0.22
-0.16
Productivity-wage gap

-0.55

0.38

-0.95

-0.42

-0.09

Difference in explanatory factors' contribution (percentage points, Canada less
United States)
Inequality
-0.63
-0.28
0.2
-0.16
-0.1
Labour share
0.21
1.26
-0.23
-0.32
0.23
Labour's terms of trade
0.07
-0.41
-0.77
0.15
-0.04

57

Bibliography
Acemoglu, D. a. (2018, May). Modeling Automation. AEA Papers and Proceedings,
108, 2018.
Ahmad, N., & Schreyer, P. (2016). Are GDP and Productivity Measures Up to the
Challenges of the Digital Economy? International Productivity Monitor, 30, 427.
Alberta. (2021). Oil Prices. Retrieved 06 15, 2021, from Alberta Economic Dashboard:
https://economicdashboard.alberta.ca/oilpriceAtkinson, A., & Piketty, T. (Eds.). (2007). Top Incomes Over the Twentieth Century: A
Contrast Between Continental European and English-Speaking Countries.
Oxford: Oxford University Press.
Autor, D. (2015). Why are there still so many jobs? The history and future of workplace
automation. Journal of Economic Perspectives, 29(3), 3-30.
Autor, D. H., Katz, L. F., & Kearney, M. F. (2006). The Polarization of the US LabourMarket.
AmericanEconomic
Review,
96(2),
198-194.
doi:10.1257/000282806777212620
Autor, D., Dorn, D., Katz, L. F., Patterson, C., & Van Reenen, J. (2020, May). The Fallof the Labor Share and the Rise of Superstar Firms. The Quarterly Journal of
Economics,
135(2),
645-709.
Retrievedfromhttps://doi.org/10.1093/qje/qjaa004
Baily, M. N., & Gordon, R. J. (1988). The Productivity Slowdown, Measurement
Issues, and the Explosion of Computer Power. Brookings Papers on Economic
Activity, 2, 347-431.
Baldwin, J. R., Gu, W., & Yan, B. (2007). User Guide for Statistics Canada's Annual
Multifactor Productivity Program. Statistics Canada. Retrieved fromhttps://www150.statcan.gc.ca/n1/en/pub/15-206-x/15-206-x2007014eng.pdf?st=6vqR5tZY
Baldwin, J., Gu, W., & Yan, B. (2007). User Guide for Statistics Canada's annual
Multifactor Productivity Program. Statistics Canada. Retrieved fromhttps://www150.statcan.gc.ca/n1/en/pub/15-206-x/15-206-x2007014eng.pdf?st=6vqR5tZYBank of Canada. (2021). Commodity Price Index. Retrieved 06 15, 2021, from Bank of
Canada Price Indexes: https://www.bankofcanada.ca/rates/price-indexes/bcpi/
Beach, C. M. (2017). What Happened to Middle-Class Earnings in Canada. In D. A.
Green, W. C. Riddell, & F. St-Hilaire (Eds.), Income Inequality: The Canadian
Story (pp. 83-102).
58

Bebchuk, L. A., Fried, J. M., & Walker, D. I. (2002). Managerial power and rent
extraction in the design of executive compensation. The University of Chicago
Law Review, 69, 751-846.
Belmonte, L. (2020, September 17). Canada's Billionaires Have Actually Gotten Richer
Throughout
thePandemic.
Retrievedfrom
Narcity:https://www.narcity.com/richest-canadians-actually-saw-their-wealth-increasethroughout-the-pandemic
Bivens, J., & Mishel, L. (2013). The pay of corporate executives and financial
professionals as evidence of rents in top 1 percent incomes. Journal of Economic
Perspectives, 27(3), 57-78. doi:DOI: 10.1257/jep.27.3.57
Bivens, J., Mishel, L., & Schmitt, J. (2018). It's not just monopoly and monopsony: How
market power has affected American wages. Economic Policy Institute.
Retrieved from https://files.epi.org/pdf/145564.pdf
Bowlus, A., Gouin-Bonenfant, É., Liu, H., Lochner, L., & Park, Y. (2021, April). Four
Decades of Canadian Earnings Inequality and Dynamics Across Workers andFirms. Bank of Canada Working Paper.
Card, D., Lemieux, T., & Riddell, W. C. (2004). Unions and Wage Inequality. Journalof Labour Research, 25(4), 519-562. doi:10.1007/s12122-004-1011-z
Dufour, M., & Russell, E. (2015). Why isn't Productivity More Popular? A Bargaining
Power Approach to the Pay/Productivity Linkage in Canada. International
Productivity Monitor, 28(Spring), 47-62.
Eavis, P. (2021, June 11). Meager rewards for workers, exceptionally rich pay for
CEOs.
Retrieved
from
The
New
York
Times:
https://www.nytimes.com/2021/06/11/business/ceo-pay-compensationstock.html?smid=em-share
Eisfeldt, A., Falato, A., & Xioalan, M. (2021). Human Capitalists. Cambridge, MA:
National Bureau of Economic Research. doi:DOI 10.3386/w28815
Elsby, M. W., Hobijn, B., & Şahi, A. (2013). The Decline of the US Labor Share. In D.
H. Romer, & J. Wolfers (Eds.), Brookings Papers on Economic Activity: Fall2013 (pp. 1-63). Brookings Institution Press. Retrieved fromhttps://www.brookings.edu/wpcontent/uploads/2016/07/2013b_elsby_labor_share.pdf
Feldstein, M. S. (2008). Did wages reflect growth in productivity. National Bureau of
Economic Research. Retrieved from http://www.nber.org/papers/w13953
Fortin, N. M., & Lemieux, T. (2015, May). Changes in wage inequality in Canada: Aninterprovincial perspective. The Canadian Journal of Economics, 48(2), 682713.
59Geloso, V. (2020). The Truth About CEO and Worker Compensation. Fraser Institute.
Giaricano, L., & Rossi-Hansberg, E. (2006). Organization and inequality in aknowledge economy. Quarterly Journal of Economics, 121, 1383-1435.
Goldin, C., & Katz, L. (2007). The Race Between Education and Technology: The
Evolution of US Educational Wage Differentials,1890 to 2005. National Bureau
for Economic Research. Retrieved from https://www.nber.org/papers/w12984
Green, D. A., & Sand, B. M. (2015, May). Has the Canadian Labour Market Polarized?
The Canadian Journal of Economics, 48(2), 612-646.
Gutiérrez, G., & Piton, S. (2020). Revisiting the Global Decline of the (Non-Housing)Labor Share. American Economic Review: Insights, 2(3), 321-338.
doi:10.1257/aeri.20190285
Harrison, P. (2009). Median Wages and Productivity Growth in Canada and the UnitedStates. Centre for the Study of Living Standards.
Healing, D. (2020, June 17). Canada’s wealthiest one per cent hold 25.6% of riches,new
PBO
reportsays.
Retrieved
from
TorontoStar:
https://www.thestar.com/business/2020/06/17/canadas-wealthiest-one-per-centhold-256-of-riches-new-pbo-report-says.html
Helpmann, E. (2016). Globalization and Wage Inequality. National Bureau of
Economic Research. Retrieved from http://www.nber.org/papers/w22944
ILO. (2013). Global Wage Report 2012/2013. Geneva: International Labour Office.
Retrieved from https://www.ilo.org/wcmsp5/groups/public/---dgreports/--dcomm/---publ/documents/publication/wcms_194843.pdf
Irwin, N. (2021, May 5). Can the Biden Agenda Fix Middle America's Deepest
Problem?
Retrieved
from
The
New
York
TImes:
https://www.nytimes.com/2021/05/05/upshot/biden-agenda-middleamerica.html
Jeon, S.-H., Liu, H., & Ostrovsky, Y. (2019, December). Measuring the Gig Economy
in Canada Using Administrative Data. Analytical Studies Branch Research
Paper Series, Catalogue no. 11F0019M, no. 437.
Johnson, S. (2002). Canadian Union Density 1980 to 1998 and Prospects for the Future:
An Empirical Investigation. Canadian Public Policy, 333-349.
Kaldor, N. (1957). A Model of Economic Growth. Economic Journal, 67(268), 591624.
Kaplan, S. N., & Rauh, J. (2013). It's the market: The broad-based rise in the return to
top talent. Journal of Economic Perspectives, 27(3), 35-56. doi:DOI:
10.1257/jep.27.3.35
60

Karabarbounis, L., & Neiman, B. (2014). The Global Decline in the Labour Share.
Quarterly Journal of Economics, 129(1), 61-104.
Katz, L. F., & Murphy, K. M. (1992). Changes in Relative Wages, 1963–1987: Supply
and Demand Factors. Quarterly Journal of Economics, 107, 35-78.
Lemieux, T., & Riddell, W. C. (2015). Who Are Canada’s Top 1 Percent? In D. A.
Green, W. C. Riddell, & F. St-Hilaire (Eds.), Income Inequality: The Canadian
Story (pp. 103-157). Institute for Research on Public Policy. Retrieved fromhttps://irpp.org/wp-content/uploads/2016/01/aots5-riddell-lemieux.pdf
Macdonald, D. (2021). The golden cushion: CEO compensation in Canada. CanadianCentrefor
PolicyAlternatives.
Retrievedfromhttps://www.policyalternatives.ca/sites/default/files/uploads/publications/Natio
nal%20Office/2021/01/Golden%20cushion.pdf
Manyika, J., Mischke, J., Bughin, J., Woetzel, J., Krishnan, M., & Cudre, S. (2019). A
New Look at the Declining Labor Share of Income in the United States.
McKinsey
GlobalInstitute.
Retrievedfromhttps://www.mckinsey.com/featured-insights/employment-and-growth/a-newlook-at-the-declining-labor-share-of-income-in-the-united-states#
Mishel, L., & Bivens, J. (2015). Understanding the Historic Divergence Between
Productivity and a Typical Worker’s Pay: Why It Matters and Why It’s Real.
Economic
PolicyInstitute.
Retrievedfromhttps://files.epi.org/2015/understanding-productivity-pay-divergence-final.pdf
Mishel, L., & Bivens, J. (2021). Identifying the Policy Levers Generating Wage
Suppression and Wage Inequality. Washington, D.C.: Economic Policy Institute.
Mishel, L., & Gee, K.-F. (2012). Why Aren't Workers Benefiting from Labour
Productivity Growth in the United States? International Productivity Monitor,
23(Spring), 31-43.
Morissette, R., Schellenberg, G., & Johnson, A. (2005, April). Diverging Trends inUnionization. Statistics Canada Perspectives, Catalogue no. 75-001-XIE.
Mućk, J., McAdam, P., & Growiec, J. (2018). Will the True Labor Share Stand Up? An
Applied Survey on Labor Share Measures. Journal of Economic Surveys, 32(4),961-984. Retrieved from https://doi.org/10.1111/joes.12252
OECD. (2015). The Future of Productivity.
doi:https://doi.org/10.1787/9789264248533-en.

Paris:

OECD

Publishing.

OECD. (2018). Decoupling of Wages from Productivity: What Implications for Public
Policies? OECD Economic Outlook, 2018(2), 51-65. Retrieved fromhttps://www.oecd.org/economy/outlook/Decoupling-of-wages-fromproductivity-november-2018-OECD-economic-outlook-chapter.pdf
61

Pessoa, J. P., & Van Reenen, J. (2013). Decoupling of Wage Growth and Productivity
Growth? Myth and Reality. Centre for Economic Performance. Retrieved fromhttps://cep.lse.ac.uk/pubs/download/dp1246.pdf
Piketty, T., & Saez, E. (2006). The evolution of top incomes: A historical andinternational perspective. American Economic Review, 96, 200-205.
Piketty, T., & Zucman, G. (2014, August). Capital is Back: Wealth-Income Ratios inRich Countries 1700-2010. The Quarterly Journal of Economics, 129(3), 12551310.
Riddell, C. (1993). Unionization in Canada and the United States: A Tale of Two
Countries. In D. Card, & R. B. Freeman, Small Differences That Matter: Labor
Markets and Income Maintenance in Canada and the United States (pp. 109148).
UniversityofChicagoPress.
Retrievedfrom
http://www.nber.org/chapters/c11147
Rognlie, M. (2015). Deciphering the fall and rise in the net capital share: Accumulationor scarcity. In D. H. Romer, & J. Wolfers (Eds.), Brookings Papers on Economic
Activity, Spring 2015 (pp. 1-69).
Rosen, S. (1981). The economics of superstars. American Economic Review, 71, 845858.
Ross, C., & Murray, A. (2010). Aggregate Measures of Income and Output in Canada
and the United States: Implications for Productivity and Living Standards.
International Productivity Monitor, 19(Spring), 20-39.
Russell, A. (2016, January 13). 4 in 10 Canadians believe they are ‘worse off’ than theirparents:
Ipsos
poll.
Retrieved
from
GlobalNews:
https://globalnews.ca/news/2451943/4-in-10-canadians-believe-they-areworse-off-than-their-parents-ipsos-poll/
Saez, E., & Veall, M. R. (2005). The Evolution of High Incomes in Northern America:
Lessons from Canadian Evidence. American Economic Review, 95(3), 831-849.
Schwellnus, C., Kappeler, A., & Pionnier, P.-A. (2017). The Decoupling of Median
Wages from Productivity in OECD Countries. International Productivity
Monitor, 32(Spring), 44-60.
Schwellnus, C., Pak, M., Pionnier, P.-A., & Crivellaro, E. (2018). Labour Share
Developments Over the Last Two Decades: The Role of Technological Progress,
Globalisation and "Winner-Takes-Most" Dynamics. OECD. Retrieved fromhttps://dx.doi.org/10.1787/3eb9f9ed-en
Sharpe, A. (2002). Productivity Concepts, Trends And Prospects: An Overview. In K.
Banting, F. St.-Hilaire, & A. Sharpe (Eds.), The Review of Economic
Performance and Social Progress (Vol. 2, pp. 31-56). Centre for the Study of62

Living Standards and the Institute for Research on Public Policy. Retrieved fromhttp://www.csls.ca/repsp/2/andrewsharpe.pdf
Sharpe, A., Arsenault, J.-F., & Harrison, P. (2008a). Why Have Real Wages Lagged
Labour Productivity Growth in Canada? International Productivity Monitor,
17(Fall), 16-27.
Sharpe, A., Arsenault, J.-F., & Harrison, P. (2008b). The Relationship Between Labour
Productivity and Real Wage Growth in Canada and OECD Countries. Centre
for
the
Study
of
LivingStandards.
Retrievedfrom
http://www.csls.ca/reports/csls2008-8.pdf
Stansbury, A., & Summers, L. (2018). Productivity and Pay: Is the Link Broken?
Washington, DC: Peterson Institute for International Economics. Retrieved fromhttps://www.piie.com/system/files/documents/wp18-5.pdf
Stansbury, A., & Summers, L. H. (2020). The Declining Worker Power Hypothesis: An
Explanation for the Recent Evolution of the American Economy. Cambridge,
MA: National Bureau of Economic Research. doi:10.3386/w27193
Statistics Canada. (2016). User Guide: Canadian System of Macroeconomic Accounts.
Retrievedfromhttps://www150.statcan.gc.ca/n1/pub/13-606-g/13-606g2016001-eng.pdf
Stigler, G. (1961). Economic Problems in Measuring Changes in Productivity. In T. C.
Wealth, Output, Input, and Productivity Measurement (pp. 47-78). Princeton
University Press. Retrieved from http://www.nber.org/chapters/c2219
Strain, M. R. (2019). The link between wages and productivity is strong. Expanding
Economic
OpportunityforMore
Americans.
Retrievedfromhttps://www.aspeninstitute.org/longform/expanding-economic-opportunity-formore-americans/the-link-between-wages-and-productivity-is-strong/
Trudeau, J. (2013, 04 13). Why It's Vital We Support the Middle Class. Retrieved fromThe Globe and Mail: https://www.theglobeandmail.com/news/politics/justintrudeau-why-its-vital-we-support-the-middle-class/article11209063/
Uguccioni, J., & Sharpe, A. (2016). Decomposing the Productivity-Wage Nexus in
Selected OECD Countries, 1986-2013. Centre for the Study of Living Standards.
Retrieved from http://www.csls.ca/reports/csls2016-16.pdf
Uguccioni, J., Sharpe, A., & Murray, A. (2016). Labour Productivity and theDistribution of Real Earnings in Canada, 1976-2014. Centre for the Study of
Living Standard. Retrieved from http://www.csls.ca/reports/csls2016-15.pdf
Veall, M. R. (2012). Top income shares in Canada: Recent trends and policy
implications. Canadian Hournal of Economics, 45(4), 1247-1272. Retrieved
from https://doi.org/10.1111/j.1540-5982.2012.01744.x
63

Weil, D. (2014). The Fissured Workplace: Why Work Became So Bad for So Many andWhat Can Be Done to Improve It. Cambridge, MA: Harvard University Press.
Williams, D. M. (2021). Pay and Productivity in Canada: Growing Together Only
Slower Than Ever. International Productivity Monitor.
Wolfson, M., Veall, M., Brooks, N., & Murphy, B. (2016). Piercing the veil: Private
corporations and the income of the affluent. Canadian Tax Journal, 64(1), 1-30.

64