The UK Productivity Puzzle
and
Its Policy Implications
A Working Paper by Caroline Margiotta
Fall 2015
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I. Introduction
Since the financial crisis began, affected countries have recovered slowly in employment
and output, and several economies have failed to return to pre-crisis conditions. While
Britain’s labour productivity was fairly strong prior to the crisis, in part owing to its
strength in business services, real GDP fell by more than 6%, employment by 2%, and
labour hours by 4% as a result of the crisis.i Employment, real output, and total weekly
labour hours have grown—to 6%, 5%, and 4% above their 2008 Q1 levels, respectively–
, yet labour productivity has failed to follow its pre-crisis growth trend and has largely
stagnated since 2008 (Figure 1, Figure 2).
To take into account as many explanations for this fall in labour productivity as
possible, I focus in this paper on nonfinancial corporate loans, R&D expenditures,
private nonfinancial net corporate lending, and the prevalence of part-time labour in
the workforce—all of which should have positive effects on output per worker,
especially the latter given its implications for labour flexibility. Out of these factors,
Corporate Loans and Net Lending should have the largest effects on productivity, as
they provide a clue as to how innovation and other productivity-boosting activities are
funded. To test this hypothesis, this paper proceeds as follows: Section II begins with a
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brief discussion of the most pertinent theory topics to the productivity puzzle and
reviews the work of other scholars who have investigated it. Section III analyses data on
output, employment, and corporate loans in an attempt to determine the validity of
other scholars’ arguments, and discusses the political implications. Section IV
concludes.
II. Theory and Analysis
A discussion of the productivity puzzle is incomplete without mention of the
natural, or structural, rate of unemployment, a key metric from which we can determine
the real wage from the relation between unemployment, worker power, and a firm’s
market power. The Natural Rate of Unemployment occurs at the intersection of labour
supply and labour demand, where inflation will neither accelerate nor decelerate, and at
which prices are as expected (Weiner, 1986). More rigorously, it occurs at the real-wage
level where the wage-setting and price-setting relations intersect at
.ii
Within the wage-setting relation, u has a negative effect on the natural rate of
unemployment, while z has a positive effect. We can see that a decrease in worker
power leads to an outward shift of the wage-setting relation, leading to a higher natural
rate of unemployment; the opposite phenomenon leads to a lower natural rate of
unemployment (Possibility 1).
Alternatively, an increase in mark-ups
enabled by weaker anti-competition
legislation, stricter patent enforcement, or
import restrictions can cause the natural
rate of unemployment to increase in
conjunction with a downward shift of the
price-setting relation and a fall in the real
wage (Possibility 2). For example, Blundell et al (2013) note a 4% decrease in average
real hourly wages since 2008, highlighting a possible increase in mark-ups and the
natural rate of unemployment (pp. 4).
Inherently linked to the wage-setting and price-setting relations, the price level,
and the natural rate of unemployment is the Aggregate Supply (AS)–Aggregate Demand
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(AD) model. We assume that expected and actual prices differ in the short-run, and so
the wage-setting and price-setting relations come together as
use the fact that
. We
to transform the above relation into the AS
relation:
.iii By the AS relation, an increase in output will lead
to an increase in employment, an increase in the nominal wage, and thus an increase in
the expected and actual price levels through wages. AS contracts due to this price
increase, leading to a further increase in price for consumers. This affects the LM
relation (
) through a decrease in the real money supply, an increase in
interest rates, and a decrease in quantity demanded. On the AD curve, represented by
the relation
,iv this coincides with a rise in prices and a decrease in
output. In the medium run, equilibrium between AD and AS occurs where the actual and
expected prices are equal and the reservation wage of workers equals the wage offered
by firms.
The UK Productivity Puzzle has arisen from significant shortfalls in labour
productivity in comparison to both pre-crisis trends and the pre-recession peak in Q1 of
2008. Peter Patterson of the ONS (2012) notes that the 6.3% fall in real GDP between
the 2008 peak and the 2009 trough led to a 4.3% decrease in labour productivity over
that period (p. 3). Blanchard (2015) corroborates this and notes that labour
productivity, measured as output per hour, has remained approximately 16% below the
level predicted by the pre-crisis trend.v It is a highly important current issue to
consider in making monetary policy decisions and estimates on the British economy’s
growth potential, as failing to consider this low productivity might generate large
inflationary pressure.
Barnett et al suggest two possible sources of this productivity shortfall (2014).
The first supposes that the shortfall can be explained by short-term cyclical factors,
such as excess capacity in firms and thin market externalities.vi The second supposes
that the productivity shortfall is caused by long-term factors such as insufficient
tangible, intangible, and working capital investment, poor allocation of capital, and
higher firm survival rates due to financial institutions and regulators’ relative relaxation
of their stances towards firms making financial losses.vii Given Barnett et al’s
uncertainty as to the impact of short-term factors on the shortfall in unemployment, it is
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more likely that the productivity shortfall is best explained by the second hypothesis,
which they estimate to predict between 6-9% of the shortfall in productivity (pp. 114).
Those who believe the productivity shortfall has been caused by long-term factors also
believe that any monetary policy attempts to increase output and stimulate productivity
will simply increase inflation (Pessoa and Van Reenen, 2013).
One key outcome of the present productivity gap is a decline in the real wage, which has
exacerbated the shortfall in affecting the use of capital. Within the framework of the
second hypothesis, Blundell et al (2013) note that the reduction in the capital-labour
ratio, which has resulted from an increase in the effective cost of capital and the
misallocation of capital to less efficient uses, has coincided with a reduction in the real
wage, labour costs and, ultimately, productivity (p. 7). As a result of decreased worker
power and increased wage flexibility, real wages have fallen, and there has been
surprisingly low unemployment in Britain.viii This has occurred because the fall in
nominal and real wages has made labour an effectively cheaper factor of production
than capital, leading firms to use more labour-intensive production methods rather than
investing in physical and intangible capital. Over time, insufficient investment in
physical and intangible capital, such as product innovation and process innovation,
leads to a deterioration of the capital stock per worker, output per worker, and
productive efficiency. This phenomenon leads to a growth in low-productivity sectors
relative to high-productivity sectors and thus a decrease in the average level of
productivity in the economy.
Several other factors, including the financial crisis and improper resource allocation,
have exacerbated the fall in productivity. The financial crisis made it more difficult for
firms to obtain credit and thus decreased firms’ ability to meet regular expenses
through their stores of working capital (Barnett et al, 2014). Barnett et al speculate that
improper resource reallocation has resulted from (i) caution on the part of firms in
investing in capital and labour due to uncertainty about the economic situation and (ii)
the financial crisis’s impairment of the movement of resources across the economy
through poor capital allocation and higher firm survival rates (pp. 124). As a result,
there have been significant delays in the replacement of the capital stock, a reduction in
the frequency of innovation, and a loss of human capital as firms have decreased
training expenditures. Perhaps unsurprisingly, this has led to substantial decreases in
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total output within construction (17.8%), manufacturing (12.5%), and transport
(7.8%)—three capital-intensive sectors with a particular need for funding—, as well as
substantial decreases in output per hour in financial and insurance activities,
information and communication, manufacturing, and transportation and storage since
the pre-recession period (Patterson, 2012).
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III. An Empirical Examination of the Productivity Gap and its Policy Implications
In an attempt to determine which factor best explains the productivity gap, I construct a
simple OLS model based upon the arguments made in Patterson (2012). Patterson
notes that the role of the financial sector, the behaviour of supply and of firms, and the
flexibility of labour markets are of key importance in understanding the productivity
puzzle, so my model uses proxies for each of these explanations as well as a composite
variable, YearQuarter, to control for the effects of time.ix
The model is constructed as follows:
By the null hypothesis, none of the proxies I have selected for the role of the financial
sector, the behaviour of supply and firms, and labour market flexibility can explain the
loss in output per hour. To test the null and to get a general sense of the relationships
between variables, I collected data from the ONS and Eurostat for 28 quarters,x and ran
the regression as follows.
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The regression indicates that the part-time worker ratio has a strong positive effect on
whole-economy output per hour, while private nonfinancial corporate lending, R&D
expenditures, and nonfinancial corporate loans have very weak positive effects.
However, non-financial corporate loans are the only statistically significant factor
contributing to the percent change in output per hour since the 2008 peak and
therefore the only factor for which we can reject the null hypothesis at the 10% level
and conclude that non-financial corporate loans and other factors relating to the
financial sector best explain the change in output per hour from 2008. This OLS model,
of course, explains only 50.8 percent of the variation in the change in output per hour,
so another specification might yield different and more powerful results.
Assuming Barnett et al’s second hypothesisxi holds, we can view non-financial corporate
loans as a potential source of funding for capital investment and for business
operations. The policy implications of this are crucial to fiscal and monetary policy and
the regulation of the banking sector. Because the coefficient on nonfinancial corporate
loans is positive, we know that an increase in available nonfinancial corporate loans
contributes to growth in output per hour. Expansionary monetary policy can help this
growth through a decrease in the price of borrowing for banks and firms through a fall
in the nominal interest rate or a decrease in reserve requirements, allowing banks to
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issue more loans. Expansionary fiscal policy, such as a reduction in corporate taxes, or
pro-business policies, such as tax breaks to firms engaging in R&D and innovation have
a similar impact.xii These policy instruments, with those that promote a flexible labour
market and efficient workers and firms while discouraging labour hoarding, are highly
important to improving labour productivity in Britain.
IV. Conclusion
Among the possible factors that have accompanied the fall in the natural rate of
unemployment and average real hourly wages and have contributed to the UK’s
productivity puzzle, insufficient access to non-financial corporate loans seems the most
likely explanation for disappointing labour productivity. My OLS model reveals that this
is the only variable which has a positive and statistically significant effect on
productivity, as loans can help firms fund improvements to the production process and
worker training as well as help them manage day-to-day expenses. To harness the
positive effects of loan availability on productivity, the UK Government could engage in
expansionary fiscal or monetary policy, though doing so could increase inflation
through increases in consumption and investment demand. The effectiveness of any
policy action in improving productivity depends upon firms’ proper allocation of
resources, so the source of the productivity puzzle must therefore be a combination of
insufficient availability of capital funding and inefficient business practices.
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Appendix I: Notes on the Model
I chose my regressors based on a number of explanatory factors (as laid out in
Patterson, 2012). Data sources and my rationale for choosing these particular variables
as proxies are laid out below.
Explanatory
Factor
Proxy
Variable
Role of the
Financial
Sector
Nonfinancial
Corporate
Loans (£)
Behaviour of
Supply
Research &
Development
Expenditures,
Seasonally
Adjusted (£)
Behaviour of
Firms
Private
Nonfinancial
Corporation
Net Lending
(+) and
Borrowing (), Seasonally
Adjusted (£)
Labour
Market
Flexibility
Ratio of Part
Time
Employees to
Total
Employed
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Data Source
Rationale
EuroStat Loans
Nonfinancial Corporate
Loan volumes are an
indicator of the availability
of funds to firms for the
financing of capital.
ONS
Research & Development
is an indicator of
intangible capital
investment.
ONS: Publication:
QNA Quarterly
National
Accounts
As a result of labour
hoarding, costs to firms of
dismissing and re-hiring
employees are diminished.
The combination of labour
hoarding and firms’ net
surplus has made it easier
to withstand the economic
downturn.
Publication: LMS
Labour Market
Statistics Integrated FR
The proportion of parttime workers in the labour
force provides some
indication of worker
power. The lower is
worker power, the greater
is the likelihood of having
to take part-time work.
10
Blundell, R., Crawford, C., and Jin, W. (2014). ‘What can wages and employment tell us about the UK’s
productivity puzzle?‘ The Economic Journal, 124 (May), 377–407.
i
ii
In this relation,
is the real wage, u is the unemployment rate, z represents the factors
(including unemployment benefits, trade union strength and membership, and employment
protection) that affect worker power, and µ represents firms’ price mark-up, which is determined
by the degree of competition in product markets.
iii
Here, P is the actual price, Pe is the expected price, µ is the mark-up, Y is output, and L
represents the size of the labour force.
iv
In the Aggregate Demand Relation, G represents government spending and T represents taxes.
v
See Lecture 6, Slide 59 for further details.
vi
Whereby companies may have been forced to work harder to attract business during the Great
Recession.
vii
They define tangible capital as physical capital and intangible capital as knowledge-based or
sales-based capital (such as IP rights, brand names), product and process innovation (especially
their implementation), and Research & Development.
viii
5.2% as of August 2015, according to Eurostat: http://appsso.eurostat.ec.europa.eu/nui/show.do .
ix
See Appendix 1 for further details.
x
These 28 quarters include Q1 of 2008 to Q4 of 2014.
xi
Long term factors best explain the productivity puzzle.
xii
For example, the HMRC has provided tax relief to SMEs and large corporations engaging in
R&D since 2007 through the Research and Development Expenditure Scheme.
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Bibliography
Blanchard, O., Amighini, A., and Giavazzi, F. (2013). Macroeconomics A European Perspective, 2nd
Edition, Chapter 8.
Barnett, A., Batten, S., Chiu, A., Franklin, J. and Sebastia-Barriel, M. (2014), ‘The UK
productivity puzzle’, Bank of England Quarterly Bulletin, Vol. 54, No. 2, 114-128.
Paulo Pessoa, J. and Van Reenen, J. (2014). ‘The UK Productivity and Jobs Puzzle: Does the
Answer Lie in Wage Flexibility?’ The Economic Journal, 124 (May), 433–452.
Blundell, R., Crawford, C., and Jin, W. (2014). ‘What can wages and employment tell us about
the UK’s productivity puzzle?‘ The Economic Journal, 124 (May), 377–407.
Patterson, P. (2012). ‘The Productivity Conundrum, Explanations and Preliminary Analysis’
Deputy Chief Economist, Office for National Statistics (ONS), 16 October 2012.
Weiner, S (1986). "The Natural Rate of Unemployment: Concepts and Issues." Economic Review
(Federal Reserve Bank of Kansas City), January. pp. 12.
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