Transcript Dias nummer 1

Expert Group on Business Registers
12th Session – Paris, 14-15 September 2011
Linking business registers
across statistical domains:
An application to entrepreneurship data
Dorte Høeg Koch
Mariarosa Lunati
Plan of the presentation
• OECD-Eurostat Entrepreneurship Indicators
Programme
• Linking data in Denmark
• Entrepreneurship Database
– Structure & linking
– Results
– Data relevance for policy Implications
• Conclusions
The Entrepreneurship Indicators Programme
• Rising interest from policy makers in
entrepreneurship – no reliable data available
• The OECD-Eurostat Entrepreneurship Indicator
Programme was launched in 2007, to develop
policy-relevant and internationally comparable
indicators of entrepreneurship and its
determinants.
• Constructed entirely from business register
data
• But there are still unanswered questions...
Administrative Registers in Denmark
Person
Building
Three unique identifiers
+ a visionary law
Business
-Occupation
-Education
-Nationality
-Parents
-Income
-Experience
-Marital
status/
children
Person
Statistics
(Gender
&Age)
-Industry
-Employees
-Legal form
-Geography
Business
Register
-Turnover &
Exports
Person
Statistics
Business
Register
Entrepreneurship
Database
New enterprises, surviving enterprises and gazelles
Entrepreneurs and employees
Less than 30 % of the entrepreneurs are women,
2001-2008
There is a higher share of young women than men
with high education. Among entrepreneurs, there
is a higher share of women with higher education
– at any age
There is no difference between the share of male and
female entrepreneurs that become gazelles (i.e. highgrowth enterprises), 2008
%
Women
Men
11,9
11,9
Pct.
- 50 % of Danish women are employed in the public sector
- Most of the female entrepreneurs come from the private sector
100
90
80
70
60
50
40
30
20
10
0
Men
Public sector
Women
Private sector
Unknown
More women than men start a new business
in an industry where they have no prior
experience. This is a problem, because survival
and growth are generally correlated with
previous industry experience.
Percentage
Men
Women
Industry experience
37,8
33,4
No industry experience
51,2
50,2
Unknown prior industry
11
16,3
100
100
Total
Many women start up in industries that have no
or low entry requirements which make them very
competitive sectors with low survival rates
Top 1
Top 2
Top 3
Business
Women consultancy
activities
Hairdressing
saloons
Takeaway
restaurants
Men
Business
Construction &
consultancy civil
activities
engineering
Carpentry
Pct. survival after 5 yrs.
Women establish their businesses when they are in
their most fertile age. For female entrepreneurs with
small children, the survival rates in retail trade is
lower than in knowledge-intensive activities
50
40
30
20
10
0
With small
children
No children
Retail
With small
children
No children
Knowledge-intensive services
Additional insights from
the linked data
Having parents with experience of self-employment increases
the probability of becoming self-employed. In particular:
- The effect of a self-employed father is significantly
higher for males
- The effect of a self-employed mother is significantly
higher for females
The historical lack of female entrepreneurs can therefore
explain why less women become entrepreneurs today
Some policy implications drawn by Denmark
based on analysis of the linked data
• A role model focus – especially around the
Global Entrepreneurship Week
• Awareness of female entrepreneurs – yearly
statistics
• Improvement of the maternity leave and
payment
• Information information information –
about DOs and DON’Ts
Concluding remarks
• Linking of registers can enrich the statistics
and give more answers
– Less costly
– High quality
– Includes all
– Lower burden on the enterprises
• But we lack of timeliness and the possibility
of benchmarking with other countries