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Professor Mark Hart
Deputy Director, Enterprise Research Centre and Aston Business
School
TEN Workshop 10th March 2021
Levelling Up - Key Components?
• Business Dynamism – it’s not all about start-ups!!! – nor
indeed scale-ups!!
• Local Productivity Distributions – long tails, whales and
frontier firms!
• Innovation – dismantling the ‘arc of innovation’?
• Finance – do equity investors recognise life outside the M25?
Venture Creation
• Clear connection between ‘business
dynamism’ and growth in productivity –
at local and national level
• Business start-up and growth metrics
crucial to understand the nature and
trajectory of business dynamism in a
region
Start-ups in a year of Crisis!
• Self-employment significantly reduced1 –
decline of 500k over the year
• GEM TEA rate (nascent and new business
owners) – fell significantly from 10% to
7.8%
• But……record numbers of start-ups
registering at Companies House – 772k+ -
increase of 13% since 2019 – even the
ONS struggling to understand this!
Start-ups per 10k Adult Population
2019
(OECD definition)
Job Reallocation Rates (JRR)
• The sum of the job creation rate and the job destruction rate is
referred to as the job reallocation rate (JRR). JRR summarises the
overall volume of change and in essence represents the ‘reshuffling
of job opportunities across locations’ (Davis et al., 1996).
• Tracking the job reallocation rate allows us to arrive at a measure of
business dynamism for the economy:
– Little variation in these rates of job creation and destruction over the period
1998-2018
– JRR averaging around 20-28% over 20 years – but slight decline leading up to
2018
– There are regional variations – Midlands Engine and Y&H performing well
below UK average – NW (Greater Manchester) and Greater London above
– Sectoral variations – weak business dynamism in the manufacturing sector as
well as wholesale and retailing
Start-ups £1m+ T/O in
3 years
• 55.1% so almost half of all start-ups
do not make it to their third year.
• Proportion, if they survive, that go
on and generate at least £1m in
revenues after 3 years?
• This threshold reflects the ambitions
of many entrepreneurs as they strive
to grow their businesses – getting to
the ‘first million’ is frequently cited
as an important milestone.
• proportion of UK-owned start-ups
that achieve this early indication of
‘scale’ is very small indeed (2%
nationally)
UK’s Productivity: Long Tail to ‘the Whale’
The UK faces a productivity crisis, remaining 23% behind the US and 15% behind the
G7 average.
Productivity - Dispersion and
Persistence
• ERC analysis using the ONS firm-level data (2008-2015)
suggests that, in a population of survivor firms, firms at the
top 10% mark of the productivity distribution are ten times
more productive than those at the bottom 10% mark.
• And, just as important, this dispersion is persistent: about a
decade later the 90/10 ratio was still around ten.
• No significant distributional differences between LEPs - So we
can rule out overall productivity distribution differences as a
possible explanation to local (LEP-level) disparities in
productivity.
Local Productivity Distributions
Firm Size
• Larger firms (250+) exhibit
different productivity
distributions in high
performing compared with low
performing LEPs.
• Micro-firms (1-9 employees)
have no statistical difference in
productivity distribution
between LEPs
• However, there are statistically
significant differences when
looking at firms with 50-249
employees where productivity
is much more dispersed
between the high and low
performing LEPs.
GFC - What happened to firms at Top
and Bottom of Productivity Distribution?
• Top 25% of productivity distribution appear to be better insulated and
more resilient face to the crisis compared to Bottom 25% as they
demonstrate higher survival rates.
• They also appear to have retained employees even when turnover was
stagnating or decreasing. This came at a price of a fall in real wages and
productivity.
• Bottom 25% group, on the contrary, experienced an increase in labour
productivity across the UK => an exit of more productive firms from the
market could provide some space for lower performers to improve their
productivity.
Distribution of Innovating Firms
(UKIS)
Arc of Innovation
“Knowledge to money: assessing the
business performance effects of publicly-
funded research and innovation grants”
• Impact is larger for firms in high-tech
manufacturing and knowledge
intensive services.
• Growth effects are larger for small
firms and those with lower pre-
project productivity.
• Growth effects on firms in the top
quartile of the productivity
distribution are relatively small.
• However, bulk of spend ………. In
London and the SE!!
Equity Finance: do they know where the
Midlands is never mind the North?
London accounts for the largest share of equity deals – 47% of deals
and 66% of investment in SMEs in the 12 months to Q3 2019.
Equity Deals (2019) - top 10 LADS
Hunting the Snark!
• Start-ups rates one small part of the business dynamism narrative which
drives productivity – it’s about the dynamism of the whole private sector
• Local productivity distributions set out the scale of the challenge in
addressing variations in aggregate productivity for local economic areas.
• Public sector funded innovation to business (Innovate UK primarily) needs
to focus on non-frontier firms and re-balance the regional spend
• Equity finance has a similar problem to innovation funding – NPIF and
MEIF seeking to redress but………………. long way to go!!
• Levelling up? – the above perhaps illustrates why after ~75 years of
public policy in the post-ward period nothing much has changed – we
need to get real about what we mean by ‘levelling up’
Thank you
More information at http://enterpriseresearch.ac.uk/
Contact us:
Mark Hart mark.hart@aston.ac.uk
This work contains statistical data from ONS which is Crown Copyright. The use of these data does not imply the
endorsement of the data owner or the UK 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.

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Levelling UP_ an impossible task?

  • 1. Professor Mark Hart Deputy Director, Enterprise Research Centre and Aston Business School TEN Workshop 10th March 2021
  • 2. Levelling Up - Key Components? • Business Dynamism – it’s not all about start-ups!!! – nor indeed scale-ups!! • Local Productivity Distributions – long tails, whales and frontier firms! • Innovation – dismantling the ‘arc of innovation’? • Finance – do equity investors recognise life outside the M25?
  • 3. Venture Creation • Clear connection between ‘business dynamism’ and growth in productivity – at local and national level • Business start-up and growth metrics crucial to understand the nature and trajectory of business dynamism in a region Start-ups in a year of Crisis! • Self-employment significantly reduced1 – decline of 500k over the year • GEM TEA rate (nascent and new business owners) – fell significantly from 10% to 7.8% • But……record numbers of start-ups registering at Companies House – 772k+ - increase of 13% since 2019 – even the ONS struggling to understand this! Start-ups per 10k Adult Population 2019 (OECD definition)
  • 4. Job Reallocation Rates (JRR) • The sum of the job creation rate and the job destruction rate is referred to as the job reallocation rate (JRR). JRR summarises the overall volume of change and in essence represents the ‘reshuffling of job opportunities across locations’ (Davis et al., 1996). • Tracking the job reallocation rate allows us to arrive at a measure of business dynamism for the economy: – Little variation in these rates of job creation and destruction over the period 1998-2018 – JRR averaging around 20-28% over 20 years – but slight decline leading up to 2018 – There are regional variations – Midlands Engine and Y&H performing well below UK average – NW (Greater Manchester) and Greater London above – Sectoral variations – weak business dynamism in the manufacturing sector as well as wholesale and retailing
  • 5. Start-ups £1m+ T/O in 3 years • 55.1% so almost half of all start-ups do not make it to their third year. • Proportion, if they survive, that go on and generate at least £1m in revenues after 3 years? • This threshold reflects the ambitions of many entrepreneurs as they strive to grow their businesses – getting to the ‘first million’ is frequently cited as an important milestone. • proportion of UK-owned start-ups that achieve this early indication of ‘scale’ is very small indeed (2% nationally)
  • 6. UK’s Productivity: Long Tail to ‘the Whale’ The UK faces a productivity crisis, remaining 23% behind the US and 15% behind the G7 average.
  • 7. Productivity - Dispersion and Persistence • ERC analysis using the ONS firm-level data (2008-2015) suggests that, in a population of survivor firms, firms at the top 10% mark of the productivity distribution are ten times more productive than those at the bottom 10% mark. • And, just as important, this dispersion is persistent: about a decade later the 90/10 ratio was still around ten. • No significant distributional differences between LEPs - So we can rule out overall productivity distribution differences as a possible explanation to local (LEP-level) disparities in productivity.
  • 8. Local Productivity Distributions Firm Size • Larger firms (250+) exhibit different productivity distributions in high performing compared with low performing LEPs. • Micro-firms (1-9 employees) have no statistical difference in productivity distribution between LEPs • However, there are statistically significant differences when looking at firms with 50-249 employees where productivity is much more dispersed between the high and low performing LEPs.
  • 9. GFC - What happened to firms at Top and Bottom of Productivity Distribution? • Top 25% of productivity distribution appear to be better insulated and more resilient face to the crisis compared to Bottom 25% as they demonstrate higher survival rates. • They also appear to have retained employees even when turnover was stagnating or decreasing. This came at a price of a fall in real wages and productivity. • Bottom 25% group, on the contrary, experienced an increase in labour productivity across the UK => an exit of more productive firms from the market could provide some space for lower performers to improve their productivity.
  • 11. Arc of Innovation “Knowledge to money: assessing the business performance effects of publicly- funded research and innovation grants” • Impact is larger for firms in high-tech manufacturing and knowledge intensive services. • Growth effects are larger for small firms and those with lower pre- project productivity. • Growth effects on firms in the top quartile of the productivity distribution are relatively small. • However, bulk of spend ………. In London and the SE!!
  • 12. Equity Finance: do they know where the Midlands is never mind the North? London accounts for the largest share of equity deals – 47% of deals and 66% of investment in SMEs in the 12 months to Q3 2019.
  • 13. Equity Deals (2019) - top 10 LADS
  • 14. Hunting the Snark! • Start-ups rates one small part of the business dynamism narrative which drives productivity – it’s about the dynamism of the whole private sector • Local productivity distributions set out the scale of the challenge in addressing variations in aggregate productivity for local economic areas. • Public sector funded innovation to business (Innovate UK primarily) needs to focus on non-frontier firms and re-balance the regional spend • Equity finance has a similar problem to innovation funding – NPIF and MEIF seeking to redress but………………. long way to go!! • Levelling up? – the above perhaps illustrates why after ~75 years of public policy in the post-ward period nothing much has changed – we need to get real about what we mean by ‘levelling up’
  • 15. Thank you More information at http://enterpriseresearch.ac.uk/ Contact us: Mark Hart mark.hart@aston.ac.uk This work contains statistical data from ONS which is Crown Copyright. The use of these data does not imply the endorsement of the data owner or the UK 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.