Many blame globalisation for growing wage inequality in the UK. But according to research by Giulia Faggio, Kjell Salvanes and John Van Reenen, the rise in inequality is better explained by increasing dispersion in the productivity of firms related to their use of new technology. Their study finds that much of the rise in wage inequality is driven by increasing differences in wages among firms in the same industry. A major driver of such differences is firms’ varying ability to make use of new technology. This is particularly felt in the service sector.

Faggio, Giulia

Salvanes, Kjell G.

Van Reenen, John

English

Research Papers in Economics

CentrePiece Winter 2007/08
18
W
age inequality has
increased substantially in
both the United States
and the UK in the last 
30 years. This fact, which is now firmly
established, has fuelled debate about
appropriate policy responses, including
more progressive taxation, education and
training, tougher corporate governance to
control the remuneration of top
management, strengthening unions and
minimum wages, curtailing trade and
beefing up social security. Some critics of
pro-market reforms claim that rising
inequality is evidence that liberalisation
helps the rich at the expense of the
average worker. For others, rising
inequality is used to argue for
programmes to upgrade skills.
But a proper policy response requires
an understanding of what has caused
wage inequality. Much research shows
(see, for example, the summary in Machin
and Van Reenen, 2007) that an important
part of the rise in inequality comes from
increases in inequality among similar
workers – what economists call ‘within-
group’ inequality. This means that workers
with a similar age, gender, skill and
industry group tend to be paid increasingly
dissimilar wages.
Within-group inequality may be driven
by the same factors explaining the broader
distribution of wages between workers.
For example, if technology increases the
payoff to a university education it is also
more likely to increase the wages of more
able graduates more than those of less
able graduates. But the increase in within-
group inequality may be driven by other
factors – such as declining union
membership and the minimum wage
(Goldin and Katz, 2007).
Technology-based theories of within-
group wage inequality share a common
prediction: since workers’ pay is linked to
their productivity, increases in wage
inequality should be accompanied by
increases in ‘productivity dispersion’. In
other words, the productivity distribution
for firms should have widened. 
Our new study looks first at
individuals’ earnings and firms’ average
wages and shows that the increase in
wage dispersion between people is mainly
due to an increase in wage inequality
between firms. In other words, the
internal structure of wages within firms
has not widened as much as the
difference in average wages between firms
(in the same industries). This is an
important finding when looking for the
causes of wage inequality. It suggests that
little of the growth in inequality is the
result of changes in the way firms treat
their own workers.
Hundreds of papers have documented
a close correlation between firms’ average
wages and firms’ average productivity
Many blame globalisation for growing wage
inequality in the UK. But according to 
research by Giulia Faggio, Kjell Salvanes and
John Van Reenen, the rise in inequality is
better explained by increasing dispersion in 
the productivity of firms related to their use of
new technology.
Inequality of
individual wages
and the dispersion 
of firm productivitybeginning with the pioneering work 
of ex-Monetary Policy Committee
members Sushil Wadhwani and Steve
Nickell in the 1980s at the CEP (see, for
example, the summary in Layard et al,
2005). We also find that this relationship
persists and has grown stronger,
suggesting that firms’ characteristics are
important in understanding the evolution
of wage inequality. 
To test the link between productivity
and inequality, our research looks at
changes in firm productivity, mainly
measured by value added per worker, over
time. We focus on the differences
between high- and low-productivity firms
among representative samples of
hundreds of thousands of British firms.
Previous research has studied the
manufacturing sector (Dunne et al, 2004;
Haskel and Martin, 2002), but we analyse
both the manufacturing and service
sectors of the UK economy since the two
sectors have experienced very different
trends. In particular, the manufacturing
sector has been in rapid decline, which
means that the least productive firms 
are disappearing from view, compressing
the observed distribution. Consistent 
with this fact, productivity inequality has
risen much faster in services than in 
the manufacturing sector since the 
early 1980s.
It is well-known and entirely
understandable that different firms have
CentrePiece Winter 2007/08
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Figure 1:
Productivity dispersion in the UK economy, 1984-2001
Much of the rise in wage
inequality is driven by
increasing differences in
wages among firms in the
same industry 
0.8
1
1.2
1.4
1.6
1.8
1990 1992 1994 1996 1998 2000 1988 1986 1984
Bottom tenth
Top tenth
Median
P
r
o
d
u
c
t
i
v
i
t
y
 
(
1
9
8
4
=
1
)
Year
Note: Productivity is defined as the log of value added per worker.Values are indexed to be 
1 in 1984, so the lines show the growth in productivity at different parts of the distribution.
The upper line is at the 90th percentile, the middle line is the median and the bottom line is at
the 10th percentile.CentrePiece Winter 2007/08
20
comparisons are useful because when
‘general-purpose technologies’ such as ICT
become ubiquitous, the impact on firms is
felt worldwide. Cross-country comparisons
make it possible to distinguish general
effects from changes specific to the UK. 
In terms of policy, our findings suggest
that the causes of rising inequality are
primarily structural and related to new
technology rather than to trade or
institutions. Thus, contrary to what some
have argued, greater trade protectionism
or the re-energising of unions may do
relatively little to reverse the increase 
in inequality.
A better strategy would be to
concentrate on raising the skill and
education levels of the workforce,
particularly of those at the bottom 
of the ability distribution. This means 
not just improving the quantity of
schooling for disadvantaged groups, 
but increasing the quality of school and
pre-school education.
different productivity levels. Some firms
are better managed and use better
technology than other firms. But an
original finding of our work is that this
productivity gap between firms has
widened. We look at two groups of firms
from opposite ends of the productivity
distribution: one at the top (90th
percentile) and one at the bottom 
(10th percentile).
So productivity inequality rose
substantially over the period (see Figure 1).
Between 1984 and 2001, productivity in
our sample rose by about 49% (40 log
points) for the median firm. But for firms
near the bottom (the 10th percentile)
there was a rise in productivity of only
22% (20 log points) whereas for firms
near the top (90th percentile) productivity
has risen by about 82% (60 log points). 
Our research shows that changes in
labour productivity are mainly driven by
changes in ‘total factor productivity’,
rather than changes in the amount of
buildings or old capital equipment used.
These results suggest that technological
differences among firms may be the
underlying cause of increasing dispersion.
Using data on the use of information and
communication technologies (ICT), we
show that productivity dispersion rose
most strongly in sectors where ICT use
grew most rapidly and intensively. 
The rise in productivity dispersion did 
not seem closely related to imports or to
trade unions.
Finally, we also document a rise in
productivity dispersion in France and
Norway in the 1990s, although the rise
was smaller than in the UK. Such
This article summarises ‘The Evolution 
of Inequality in Productivity and Wages:
Panel Data Evidence’ by Giulia Faggio,
Kjell Salvanes and John Van Reenen,
CEP Discussion Paper No. 821
(http://cep.lse.ac.uk/pubs/download/
dp0821.pdf).
Giulia Faggio is an economist at Citigroup
Inc. in London and a CEP research associate.
Kjell Salvanes is at the Norwegian School of
Economics and Business Administration.
John Van Reenen is director of CEP .
Further reading
Timothy Dunne, Lucia Foster, John
Haltiwanger and Kenneth Troske (2004),
‘Wage and Productivity Dispersion in US
Manufacturing:The Role of Computer
Investments’, Journal of Labor Economics
22(2): 397-429.
Claudia Goldin and Lawrence Katz (2007),
‘Long-run Changes in the US Wage Structure:
Narrowing,Widening, Polarizing’, National
Bureau of Economic Research Working 
Paper No. 13568.
Jonathan Haskel and Ralf Martin (2002),
‘The UK Manufacturing Productivity Spread’,
Ceriba Working Paper
(http://www.ceriba.org.uk).
Richard Layard, Stephen Nickell and Richard
Jackman (2005), Unemployment:
Macroeconomic Performance and the Labour
Market, Oxford University Press.
Stephen Machin and John Van Reenen (2007),
‘Changes in Wage Inequality’, CEP Special
Paper No. 18, forthcoming in The New
Palgrave Dictionary of Economics
(http://cep.lse.ac.uk/pubs/download/special/
cepsp18.pdf).
The increase in
the productivity
dispersion of firms
is mainly in
services, especially
in sectors where
ICT use grew 
most rapidly 
and intensively
A major source of
rising inequality is
greater dispersion in
firms’ productivity
related to their use
of new technology

Inequality of individual wages and the dispersion of firm productivity.

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