This document discusses a new OECD project called DYNEMP that aims to analyze business dynamics and job creation using firm-level data from over 20 countries. It finds that most jobs are concentrated in medium and large firms despite most firms being small. However, young small firms contribute disproportionately to net job creation across countries. While the majority of micro start-ups do not grow, the few that do account for a large share of total job creation. The growth dynamics of startups vary significantly between countries. Young firms were more impacted by the crisis but recovered more quickly. The document outlines how the DYNEMP database and analyses can provide new insights into how policies impact startups versus incumbents.

1. NEW TOOLS AND
NEW EVIDENCE ON
BUSINESS
DYNAMICS: THE
ROLE OF (MICRO)
STARTUPS.
WHAT’S IN THERE FOR
REGIONS AND CITIES?
Chiara Criscuolo
Science Technology and Innovation Directorate,
OECD
RSA-ERC DG Regio Open Day Session
Dynamics of job creation and role of micro-enterprises
Tuesday 13 October 2015, European Commission

2. • Where are jobs created?
• How are new jobs created?
• What has been the impact of the crisis on
jobs?
• How does my area fare relative to other in
my country and in Europe?
• What has been the impact of
European/National Regional policies?
• Etc….
Regional Questions on job
creation

3. • Will not be able to answer these questions
across regions nor cities but
• Will present a new OECD project DYNEMP:
– Answer similar policy relevant questions at
national level
– New tool for comparative analysis of business
dynamics
• flexible
• Modular
Even though…

4. • Motivation
• Dynemp: a new tool
• Data
• Policy questions
• Some answers
• Summary, ongoing work and next steps
Outline
4

5. • Increasing academic & policy interest in:
– job creation/destruction; creative destruction and
productivity growth; allocative efficiency; new
sources of growth
• Upsurge in the interest in firm dynamics and in
heterogeneous impact of policies:
– KBC, ICT and globalization may have increased the
gap between “losers” and “winners”
• Cross-country evidence on the growth
dynamics of start-ups is extremely limited
Motivation I

6. DYNEMP:
A NEW TOOL TO EXPLOIT
EXISTING DATA

7. • Ongoing Project :
- Micro-aggregated harmonized database via
distributed microdata approach
– 20+ countries
• Aim:
– To provide cross-country evidence on
employment dynamics from confidential
national business registers
What is DynEmp

8. • Based on firm level data; cross-country;
longitudinal; representative; sector, age and size
dimensions
• Challenges:
• Commercial data with well known shortcomings
• National surveys and Business Registers: access /
confidentiality
• Solution: metadata collection and common Stata
routine run locally by a network of experts on
national firm-level data
• Outputs: Dynemp express database and
Dynemp v.2 database
Data: needs, challenges, solution,
outputs

9. • Job flows for cells jointly defined along 18 countries;
– 3 macrosectors; 5 age classes; 6 size classes; 11
years (2001-2011)
• Transition matrices reporting the number of firms
moving across size classes over a 3-year period
– starting in 2001; 2004 and 2007
– across 16 country
– 6 size classes: 1-9; 10-49; 50-249; 250-499; 500+
– 4 age classes: 0-2; 3-5; 6-10; 11+
– US excluded; ES not available
Dynemp express: The database

10. The DynEmp v. 2 database: an
overview
1) Annual flow datasets: yearly flow (from t-1 to t) collecting
statistics on gross job flows and mean growth by incumbents,
entrants, exiting
2) Transition matrices: statistics on growth patterns of
cohorts of firms over 3, 5, and 7 years; focus on entrants.
3) Distributed regressions: firm size distribution, threshold
of size contingent policies
4) Data for 15 countries validated thus far. More received and
to be added once checked

11. 1. Where are most jobs?
2. But Where are new jobs coming from?
3. Can we deconstruct job creation?
4. How is the dynamics of (micro) startups?
5. How much can micro start-up up-scale
across countries?
6. What has been the impact of the crisis on
job creation and growth for startups and
others?
Policy Questions

12. QUESTION 1:
WHERE ARE EXISTING
JOBS?

13. Most firms are small
Share of firms by size class

14. But more than half of the employment
is in medium and large firms
Share of employment by firm size class

15. Role of small firms across
countries: two polar cases
Magnified
0
10
20
30
40
50
60
70
80
90
100
ITA USA ITA USA ITA USA ITA USA
Micro (1-9) Small (10-49) Medium (50-249) Large (250+)
% Firms Employment
0.0
0.2
0.4
0.6
0.8
1.0
ITA USA ITA USA
Medium (50-249) Large (250+)
% 3.8
Source: OECD, Dynemp project. Preliminary results.

16. The age profile of small firms
vary across countries
Average over time, firms below 50 employees

17. QUESTION 2:
WHERE ARE NEW JOBS
COMING FROM?

18. • Evidence - mainly from the US - suggests:
– Young (which are small) rather than (all) small
firms create jobs (Kane, 2010; Haltiwanger, 2011;
Haltiwanger, Jarmin and Miranda, 2013)
• To what extent can this be generalized across
countries?
Existing evidence

19. No matter their size, young firms are
the ones which create jobs
Source: OECD, Dynemp Express project
0%
10%
20%
30%
40%
50%
60%
Young (1-5) Old (>5) Young (1-5) Old (>5)
Small (1-249) Large (250+)
Percentageshareintotalemployment,totaljob
destructionandtotaljobcreation
Contribution to employment Contribution to job destruction Contribution to job creation
Employment
Jobcreation
Jobdestruction

20. Young firms are job creators in all
countries
Contribution to employment, job destruction and job creation by small young firms

21. The share of start-up is
declining in most countries
Share of start-ups among all firms
Note: As a percent of all firms in the total private business sector. Startups are firms aged from
0 to 2. Data for Japan refers to establishment in the manufacturing sector.

22. QUESTION 3:
CAN WE DECONSTRUCT
JOB CREATION?

23. 23
Net job creation by surviving entrants
relative to total employment
Source: Calvino, Criscuolo and Menon (2015)
Shareofemployment(%)

24. Net job creation by entrants is a
combination of 4 elements
Net job
creation
by
surviving
entrants
Start-up
ratio
Post-
entry
growth
Survival
share
Average
size at
entry

25. 25
Net job creation by surviving entrants
is a combination of four elements
Start-up ratio Survival rate (after 3 years)
Average size at entry Average post-entry growth
Source: Calvino, Criscuolo and Menon (2015)
EmployeesUnitsper1000Employees
Final/initialempl.(%)Shareofsurvivingunits(%)

26. Start-up ratio vary widely across
countries
Start-up ratio (new firms per 1,000 employees); average 2001, 2004, 2007.

27. Survival share
Share of surviving entrants on total number of entrants over a 3 year period;
average over 2001, 2004, and 2007

28. Exit probability peaks around the age of
2 / 3 – more so during the recession
Relative probability of exit at different ages in recession and no-recession periods in
Belgium (coefficients from distributed regressions)

29. Different mix across economies
Measures are divided by the maximum value across included countries

30. QUESTION 4:
WHAT IS THE GROWTH
DYNAMICS OF THESE
YOUNG FIRMS?

31. The majority of micro start-ups do not
grow
Share of units in all micro (0-9 employees) entrants by final size class 5 years later

32. But those who do create a lot of jobs
Share of units in all micro (0-9 employees) entrants by final size class 5 years
later and their contribution to total net job creation

33. GROWTH POTENTIAL OF
YOUNG FIRMS

34. 0
50
100
150
200
250
300
3 5 7 3 5 7 3 5 7 3 5 7 3 5 7 3 5 7 3 5 7 3 5 7 3 5 7 3 5 7 3 5 7
AUT BEL DNK FIN HUN ITA NLD NOR NZL PRT SWE
Final/initialemployment(%)
Cross-country differences in start-up
growth beyond the 3rd year
Final over initial employment after 3, 5, and 7 years; country average of starting year
2001 and 2004, surviving entrants

35. Growth of young firms is a challenge
Average firm size of young and old firms
Manufacturing Services
0
10
20
30
40
50
60
70
80
USA
LUX
CAN
BEL
FRA
HUN
GBR
AUT
SWE
NOR
BRA
FIN
NLD
PRT
ESP
NZL
ITA
JPN
Emplyoees
Startups (0-2) Old (>10)
0
10
20
30
40
50
60
70
80
USA
GBR
BEL
CAN
LUX
FRA
NOR
BRA
AUT
HUN
PRT
SWE
NLD
NZL
FIN
ESP
ITA
JPN
Employees
Startups (0-2) Old (>10)

36. HETEROGENEOUS IMPACT OF
GREAT RECESSION

37. Young firms suffered more from the crisis, but
recovered more quickly
Average net growth rate over participating countries, total private sector

38. During the financial crisis young firms are
still net job creators
-8%
-6%
-4%
-2%
0%
2%
4%
6%
By young (0-5) By old (>5) Net growth rate
Contributions to aggregate net job creation

39. Adjustment via lower entry and growth of
young firms and job shedding
-8%
-6%
-4%
-2%
0%
2%
4%
6%
Young (entry-exit) Young (incumbents) Old (exits)
Old (incumbents) Total
Contributions to aggregate net job creation

40. • One size does not fit all: country heterogeneity in
start-up patterns
– E.g., wide differences in entrepreneurship (start-up ratio)
– Differences in upscaling of start-ups
• But there are also some important regularities
– In all countries most firms are small
• But their employment share and age profile vary greatly
– Young – rather than small – firms disproportionally
contribute to job creation in all countries
– First 3 years of activity are characterized by much higher
growth rate; more volatility; higher probability of exit.
– Large majority of start-ups do not growth…
– …but the few that do contribute hugely to job creation
Summing up

41. • Policies shape the environment in which start-
ups experiment, innovate, and grow
• Improving on previous analyses, the DynEmp
v.2 database
– enables disentangling the role of policies for entrants
vs. incumbents
– at detailed sector and country level
• Which policies support/hamper young firms?
– How does the effect on young firms differ from that
on older incumbents?
Pushing the policy evidence forward

42. • Access to finance
– widely recognized as one of the most critical assets for
start-ups growth
• Bankruptcy regulation: tight laws…
– May hamper risky investments as they pose a greater
burden on entrepreneurs in case of failure
– But can reinforce investors’ rights, making access to
credit easier
• Contract enforcement
– improve the predictability of business relationships
– is associated with high relationship-specific investments
Example of policies of interest

43. THANK YOU!
For any additional information on DynEmp
please email: dynemp@oecd.org
and visit oe.cd/dynemp