Fast-growing firms, product
strategies and skills development
Geoff Mason*+, Catherine Robinson** and Chiara Rosazza Bondibene*+
*National Institute of Economic and Social Research, London
**University of Kent
+ Centre for Learning and Life Chances in Knowledge Economies and
Societies (LLAKES)
Paper prepared for Productivity and Firm Growth Workshop,
NIESR, 2 July 2014
Order of presentation
• Firm growth, skills and training: background
issues
• Theory and hypotheses
• Data sources and measurement issues
• Empirical specification
• Impact of training on firm growth
• Lack of persistence in rapid firm growth
• Summary and assessment
Rapidly-growing firms:
what do we know about them?
• Fast-growing firms tend to be younger than other firms
(Henrekson and Johansson, 2010)
• No clear relationship between firm growth and size
• Mixed evidence on links between firm growth and
innovation (Hőlzl and Friesenbichler, 2010; Coad and Rao,
2008; Mason et al, 2009)
• Many fast-growing firms do not maintain their rapid
growth into subsequent time periods (Parker et al, 2010;
Daunfeldt and Halvarsson, 2012)
• Coad et al, 2014: Little knowledge to date about the
‘internal features’ of fast-growing firms (eg, business
strategy, investment, work organisation, skills and training)
Research questions
• Lack of persistence in rapid firm growth probably reflects
pressures and challenges of such growth
(eg, different skills required as operations are scaled up)
• Fast-growing firms may find it difficult to maintain and
improve the quality of key assets which helped drive
their initial rapid growth
• Focus here on role of skills and training:
– How much does rapid firm growth depend on prior
training of employees?
– Do firms’ commitments to employee training survive
the challenges of coping with rapid growth?
Explaining heterogeneity in firm
performance
• Resource- and knowledge-based theories of the firm suggest
that superior performance requires firms to develop products
that are superior and/or cheaper than those of rivals and hard
for others to duplicate or imitate (Teece et al, 1997; Phelan and
Lewin, 2000; Teece, 2007)
• Emphasis on development of ‘dynamic capabilities’: eg, skills
and knowledge required for new product development,
improvement of production processes and organisational
routines and ability to identify and make effective use of
relevant new knowledge (Teece et al, 1997; Eisenhardt and
Martin, 2001)
• Strong correlation at firm level between skills and indices of
product strategy which capture innovation leadership,
involvement in ‘premium quality’ production and ability to
command above-average prices (Mason, 2011)
Firm growth and skills development:
hypotheses
• At high levels of capacity utilisation, opportunity costs of providing
training for existing employees during working hours are high 
pressures to rely more on external recruitment of skilled workers
than on staff training
• But firm-specific nature of the superior products and/or production
techniques required for firms to achieve rapid growth may make it
essential to commit resources to staff training and development
• H1: All else being equal, firm growth is positively related to prior
investments in workforce training
• Concerns about the opportunity costs involved in training may
intensify for firms which find themselves experiencing rapid growth -could help explain why rapid firm growth tends not to persist into
future time periods
• H2: All else being equal, the level of training provided by fastgrowing firms tends to decline in later stages of rapid-growth
periods
Data sources
• National Employers Skill Survey (NESS) 2007 and 2009:
nationally representative telephone surveys of
establishments in England with at least two people working
in them -- 79,012 establishments surveyed in 2007; 79,152
establishments in 2009
• Both NESS 2007 and NESS 2009 contain extensive data on
training provision – but data on innovation leadership and
other components of product strategy measure are only
found in NESS 2009 as are data on workforce qualifications
(which can be used to construct a proxy measure of skill
levels)
• Business Structure Database (BSD): contains employment
and sales data for firms since 1998 as well as information
on the years of firm births and deaths
Matched NESS-BSD samples
• Private sector establishments in NESS 2007 and NESS
2009 matched to firms in the BSD which had ten or more
employees in 2007 and continued to be classified as
‘active’ by the ONS in 2010
• In total some 19.3% (15250) of NESS 2007 establishments
and 22.3% (17489) of NESS 2009 establishments were
matched to BSD firms
• Compared with full NESS samples, the two matched NESSBSD samples have lower shares of establishments in the
under 10 employees size group and in business services
and community, social and personal services
• Conversely, the two matched samples have slightly larger
shares of establishments in retail/wholesale and hotels
Product strategy and skill measures
• Summary measure of product strategy derived from factor analysis of NESS
2009 respondents’ answers to questions which invited them to rate
themselves against other establishments in the same industries in respect
of:
– product quality
– innovation leadership
– dependence on non-price factors for competitive success
• Certified skill levels defined on the basis of a wage-weighted qualifications
index in which ‘effective units of labour’ are calculated relative to the
unskilled category as follows:
3
skills =
[ wi qi ] / N
i 1
where three different qualification groups are identified; wi = mean hourly
earnings of qualifications group i (indexed to unity in the case of the ‘low
qualifications’ group); qi= numbers employed in qualifications group i and N
= total employment in each establishment.
Training measures
• Summary measure of overall training provision derived through a factor
analysis of four indicators:
– Whether establishments arrange or fund either on- or off-the-job
training (Yes/No)
– Whether establishments arrange or fund both on- and off-the-job
training (Yes/No)
– Proportion of staff receiving training of some kind
– Training intensity: average number of days training per employee
arranged or funded by establishment
• Since NESS respondents were asked to estimate the proportion of
training that was devoted solely to health, safety and induction
training, a second summary measure of training which excludes those
three types of routine training can also be estimated
Figure 3.1: Mean product strategy score, 2009, analysed by quantiles of firm
growth rate distributions, 2007-2010
0.20
Mean product strategy score
0.15
0.10
0.05
Employment growth
Sales growth
0.00
-0.05
-0.10
-0.15
-0.20
1-24
25-49
50-74
75-94
Firm growth rate distributions (percentiles)
Source: NESS 2009, BSD 2007-10
95-100
Figure 3.2: Mean skills score, 2009, analysed by quantiles of firm growth
distributions, 2007-2010
1.24
Mean skills score
1.22
1.20
Employment growth
Sales growth
1.18
1.16
1.14
1.12
1-24
25-49
50-74
75-94
Firm growth rate distributions (percentiles)
Source: NESS 2009, BSD 2007-10
95-100
Figure 3.3: Mean training summary score, 2007, analysed by quantiles of firm
growth distributions, 2007-2010
0.15
Mean training summary score
0.10
0.05
0.00
Employment growth
Sales growth
-0.05
-0.10
-0.15
-0.20
-0.25
1-24
25-49
50-74
75-94
Firm growth rate distributions (percentiles)
Source: NESS 2007, BSD 2007-10
95-100
Empirical specification: combining
time series and cross-sectional data
• First, following Coad (2010) we explore the relationship
between employment (sales) growth and lagged sales
(employment) growth between 2008-2010 by estimating
reduced-form vector auto-regression (VAR) models:
Em pGrowthit  0  1Em pGrowthi ,t 1   2 SalesGrowthi ,t 1
 1Em pGrowthi ,t  2   2 SalesGrowthi ,t  2  1
• Second, following Black and Lynch (2001), the residuals
from the first-stage equation are regressed against
measures of training and other firm-level characteristics
which are only available for a single year:
Re siduals( EmpGrowthit )  0  1Trainingi ,t 1  2  X ki,t 1   2
k
Other methodological issues
• Assume NESS establishments are representative of BSD firms to which
they belong
• Establishments which are part of multi-site firms with two or more
establishments in the sample are weighted by their shares of total firm
employment in the sample
• Establishments which are part of multi-site firms but are the only
establishment from their organisation in the sample are given a weight
of one as are single-site firms
• Address simultaneity issues by regressing 2008-10 firm growth on 2007
training levels
• Address endogeneity concerns by use of instrumental variables in
second-stage equation
• Training summary measures instrumented by measure of barriers to
training and by rank order versions of themselves
• Check sensitivity of overall training measure to use of alternative
measures which (1) omit routine health, safety and induction training
(2) capture training intensity alone (average number of days training per
employee)
Table 5.4: Vector autoregression estimates of firm growth, 2008-2010
Employment
growth rate
Sales
growth rate
-0.0287***
0.1778***
[0.005]
[0.007]
0.0675***
-0.1735***
[0.004]
[0.005]
-0.0224***
0.1022***
[0.004]
[0.006]
0.0447***
-0.0879***
[0.003]
[0.004]
Observations
44297
44297
Adj R2
0.0106
0.0405
SEE
0.3154
0.4334
Dependent variable:
Employment growth (t-1)
Sales growth (t-1)
Employment growth (t-2)
Sales growth (t-2)
Sources: BSD 2008-2010
Notes:
*** p<0.01, ** p<0.05, * p<0.1
Firm-weighted vector autoregression estimates. The dependent variables are annual rates of growth.
Robust standard errors in brackets are corrected for clustering on firm. All models include controls for
single-site enterprises, employment size, firm age, sector and region.
Table 5.5: OLS regressions of 2008-10 employment growth residuals from VAR
equations on 2007 training variables and firm-level controls
Dependent variable:
Training (summary measure)
Employment
growth
(residuals)
Employment
growth
(residuals)
Employment
growth
(residuals)
Employment
growth
(residuals)
0.0074***
[0.002]
Training, excluding HSI training (summary
measure)
0.0065***
[0.002]
Training intensity - 2nd quartile
0.0104**
[0.005]
Training intensity - 3rd quartile
0.0111**
[0.005]
Training intensity - upper quartile
0.0151***
[0.005]
Training intensity (excl. HSI) - 2nd quartile
0.0117**
[0.005]
Training intensity (excl. HSI) - 3rd quartile
0.0115**
[0.005]
Training intensity (excl. HSI) - upper
quartile
0.0128**
[0.006]
Observations
40492
39500
40492
39500
Adj R2
0.0071
0.0071
0.0068
0.0069
SEE
0.3094
0.3107
0.3095
0.3107
Sources: NESS 2007, BSD 2008-10
Table 5.6: OLS regressions of 2008-10 sales growth residuals from VAR
equations on 2007 training variables and firm-level controls
Dependent variable:
Training (summary measure)
Sales
growth
(residuals)
Sales
growth
(residuals)
Sales
growth
(residuals)
Sales
growth
(residuals)
0.0061**
[0.002]
Training, excluding HSI training (summary
measure)
0.004
[0.003]
Training intensity - 2nd quartile
0.0078
[0.007]
Training intensity - 3rd quartile
0.0055
[0.007]
Training intensity - upper quartile
0.0158**
[0.007]
Training intensity (excl. HSI) - 2nd quartile
0.0093
[0.007]
Training intensity (excl. HSI) - 3rd quartile
0.0086
[0.007]
Training intensity (excl. HSI) - upper
quartile
0.0176**
[0.007]
Observations
40491
39499
40491
39499
Adj R2
0.0112
0.0113
0.0111
0.0113
SEE
0.4307
0.4328
0.4307
0.4328
Sources: NESS 2007, BSD 2008-10
Table 5.7: Instrumental variables (IV) regressions of 2008-10 employment and
sales growth residuals from VAR equations on 2007 training variables and firmlevel controls
Dependent variable:
Training (summary measure)
Employment
growth
(residuals)
Sales
growth
(residuals)
0.0085***
0.0061**
[0.002]
[0.003]
Training, excluding HSI training
(summary measure)
Employment
growth
(residuals)
Sales
growth
(residuals)
0.0075***
0.0057**
[0.002]
[0.003]
Observations
38748
38747
37804
37803
Hansen J test
0.8485
1.1043
1.0381
1.0203
Hansen P value
0.3570
0.2933
0.3083
0.3124
C statistic
0.0689
1.9002
0.0534
0.0834
C statistic P value
0.7929
0.1681
0.8172
0.7727
Kleibergen-Paap LM statistic
3977.10
3976.83
4132.50
4132.38
Kleibergen-Paap P value
<0.000
<0.000
<0.000
<0.000
Sources: NESS 2007, BSD 2008-10
Interim assessment
• Opportunity costs of providing training versus skill
requirements associated with development of superior
products and production/delivery processes
• In case of employment growth, strong support for
H1: firm growth positively related to prior investments in
training
• Robust to use of different measures of training and tests
for potential endogeneity of training measures
• More limited support for H1 in case of sales growth
• May reflect greater opportunity costs of training when
sales are growing rapidly
• Does this help explain lack of persistence in firm growth
in later time periods?
Figure 5.1: Mean training summary score, 2009, analysed by quantiles of firm
growth distributions, 2007-2010
0.15
Mean training summary score, 2009
0.10
0.05
0.00
Employment growth
Sales growth
-0.05
-0.10
-0.15
-0.20
-0.25
1-24
25-49
50-74
75-94
Firm growth rate distributions (percentiles)
Source: NESS 2009, BSD 2007-10
95-100
Figure 5.2: Incidence of skill updating needs, 2009, analysed by quantiles of firm
growth distributions, 2007-2010
Proportion of firms reporting skill uodating needs
0.82
0.80
0.78
0.76
0.74
Employment growth
Sales growth
0.72
0.70
0.68
0.66
0.64
1-24
25-49
50-74
75-94
95-100
Firm growth rate distributions (percentiles)
Source: Matched NESS 2009-BSD dataset
Notes:
Firm-weighted estimates. Survey respondents were deemed to have skill updating needs if they
expected that, over the next 12 months, any of their employees would need to acquire new skills or
knowledge as a result of factors such as new products, new work practices and/or competitive market
pressures.
Table 5.8A: Determinants of training provision, 2009
Dependent variable:
Employment growth –
25th to 49th percentiles
Training
(summary
measure)
Training,
excluding HSI
training
(summary
measure)
-0.0806***
-0.0531**
[0.022]
[0.022]
0.028
0.0169
[0.025]
[0.025]
0.0732***
0.0680***
[0.025]
[0.025]
0.0601
0.0558
[0.037]
[0.038]
Observations
14453
14072
Adj R2
0.0838
0.0735
SEE
0.9513
0.96
Employment growth –
50th to 74th percentiles
Employment growth –
75th to 94th percentiles
Employment growth –
95th to 100th
percentiles
Sources: NESS 2009, BSD 2007-10
Notes:
*** p<0.01, ** p<0.05, * p<0.1
Firm-weighted OLS estimates. Robust standard errors in brackets are corrected for clustering on firm.
All models include controls for single-site enterprises, employment size, firm age, sector and region.
The reference categories for the employment and size growth variables are the lower quartiles of the
growth distributions in each case. HSI training refers to health, safety and induction training.
Table 5.8B: Determinants of training provision, 2009
Training
(summary
measure)
Training,
excluding HSI
training
(summary
measure)
0.0972***
0.0984***
[0.023]
[0.024]
0.1075***
0.1013***
[0.023]
[0.024]
0.1527***
0.1393***
[0.024]
[0.025]
0.1112***
0.0918**
[0.037]
[0.038]
Observations
14442
14062
Adj R2
0.0835
0.0743
SEE
0.9509
0.9592
Dependent variable:
Sales growth – 25th to
49th percentiles
Sales growth – 50th to
74th percentiles
Sales growth – 75th to
94th percentiles
Sales growth – 95th to
100th percentiles
Sources: NESS 2009, BSD 2007-10
Main findings
• Rapidly-growing firms benefit from prior investments in training
and also maintain high levels of training at late stage of growth
period
• Opportunity costs of training apparently outweighed by pressing
need for fast-growing firms to develop new skills and
competences to try and deal with challenges of rapid growth
• Need to look elsewhere to help explain lack of persistence in
firm growth in later time periods
• Other possible causes include:
– limited access to finance to support continued rapid growth
– difficulty in predicting future skill requirements in rapidly
growing firms
– inherent riskiness of all forms of firm investment, including
investments in workforce training
ACKNOWLEDGEMENT
We are grateful to NESTA for financial support of this project
DISCLAIMER
This work was based on data from the Business Structure Database, produced by the
Office for National Statistics (ONS) and the National Employers Skill Survey which
were supplied by the Secure Data Service at the UK Data Archive. The data are
Crown Copyright and reproduced with the permission of the controller of HMSO and
Queen's Printer for Scotland. The use of the data in this work does not imply the
endorsement of ONS or the Secure Data Service at the UK Data Archive in relation to
the interpretation or analysis of the data. This work uses research datasets which may
not exactly reproduce National Statistics aggregates.