advancing methodology to measure entrepreneurship from a ... · definition of entrepreneurship: ......

Workshop on Developing Entrepreneurship Statistics by Gender in Armenia, 16-17 December 2014, Yerevan, Armenia

United Nations Statistics Division

Advancing Methodology to Measure Entrepreneurship from a Gender

Perspective: an EDGE-OECD Collaboration

Social and Housing Statistics Section - UNSD



Outline • Why measure entrepreneurship from a gender

perspective?

• Summary of main items discussed at 1st EDGE technical meeting on measuring entrepreneurship

• EDGE methodology – Definition – Conceptual framework – Key indicators



Why measure entrepreneurship from a gender perspective?

Existing research finds that gender is relevant to: • Determinants of entrepreneurship

– Women are less likely to start an enterprise and more likely to be “pushed” into entrepreneurship

• Characteristics of enterprises – Women’s enterprises tend to be smaller, operate with less

capital and be more embedded in the family • Performance of enterprises

– Women’s enterprises tend to be • less profitable • have smaller life-spans



Why measure entrepreneurship from a gender perspective (cont’d.)?

Policy relevance: • Better understanding of how women contribute to

the economy and of how to foster women’s entrepreneurial activity – Sustained creation of new jobs – Poverty-reducing economic growth – Spillover effects on women’s empowerment



1st EDGE technical meeting on measuring entrepreneurship

• 5-6 December 2013, New York • Attended by NSOs of Georgia, Ghana, India, Mexico,

Philippines, USA, as well as UNECLAC, UNECA, FAO, OECD, World Bank, African and Asian Development Banks and researchers

• Objectives: – To take stock of existing data and research on gender and

entrepreneurship – To identify EDGE’s methodological contribution to

measuring entrepreneurship from a gender perspective



Main items discussed at EDGE meeting

Defining entrepreneurship: • Who is an entrepreneur? • Little convergence on definitions among researchers • While there is agreement on the typical traits of

‘entrepreneurs’- willingness to take risk, innovate, problem solve, value addition - these concepts are difficult to operationalise



Main items discussed (cont’d.)

Classifications for facilitating gender analyses of entrepreneurship: • Necessity-based and opportunity-based entrepreneurs • Formal and informal enterprises • Own-account and employer enterprises • Nascent, new, and established enterprises • Type of economic activity enterprise is engaged in



Main items discussed (cont’d). Data sources: Labour Force Surveys • Advantages

– Standardized questions on characteristics of working population – Self-employment data on # of employers/own account workers – High quality, timely, good int’l coverage

• Limitations – Not all self-employed are entrepreneurs – Usually no info on enterprise other than size/type of activity – Sample size

• The number of female employers is generally limited, even in relatively large surveys, so it is often not possible to cross-tabulate gender and other detailed business or individual characteristics



Main items discussed (cont’d). Data sources: Surveys on owners of micro and small businesses (mixed surveys) • Use existing household-level data collection as sampling frame

– E.g. Mexico’s quarterly labour force survey for ENAMIN or Brazil’s demographic census for ECINF

– Enables more reliable estimates than small-sample household surveys

• Collect information on both the entrepreneur and the enterprise – Reasons for starting enterprise, employment history, time spent

on enterprise – Estimates of the size and economic performance of micro-

businesses, registered or not



Main items discussed (cont’d.)

Data sources: Enterprise Surveys • Advantages

– More suitable than household surveys to analysis of performance differentials of women-owned and men-owned enterprises

• Limitations – Limited availability of comparable business surveys with

information on owners – Very small businesses may not be covered



Main items discussed (cont’d.) Data sources: Business Registers • Advantage:

– Less costly to produce entrepreneurship statistics from business registers than from sample surveys

• Limitations: – Limited availability of linked business and population registers – May be problematic to assign meaningful ownership based on

the name of the owner listed in business register – Non-registered businesses excluded



Implications for EDGE initiative

• Definition of entrepreneurship: – must strike a good balance between:

• broad definitions that include people without entrepreneurial skills and traits, and

• narrow definitions that exclude individuals within target group for women’s empowerment (e.g. home-based entrepreneurs with no paid employees)

– must be easily implementable with standard data collection instruments

– should be statistically measureable by NSOs as a part of official statistics



Implications for EDGE initiative (cont’d.)

• Proposed methodology should build on existing instruments to ensure sustainability of data collection – Expand existing household and enterprise surveys to cover

additional data items – Explore feasibility of using administrative data sources

• Start with population-based data – Most women entrepreneurs are concentrated in micro/small

home-based enterprises – Opportunity to pilot full survey module on entrepreneurship

with modules on asset ownership



EDGE methodology on measuring entrepreneurship from a gender

perspective: Definition, conceptual framework

and key indicators



EDGE operational definition of an entrepreneur

Those persons who have direct control over the activities of an enterprise they own alone or with other individuals. The owners of economic units producing goods and services intended for own final use are not considered entrepreneurs.

(Entrepreneurs as business owners)



Operational definition (cont’d.) Main intention • Under 19th ICLS Resolution, the main intended

destination of production determines employment status

• Those producing mainly for own final use but selling surplus in the market are not considered self-employed and hence, are not entrepreneurs



Operational definition (cont’d.) EDGE definition excludes: • Dependent self-employed

– those self-employed whose functions are close to those of wage employees and who are economically dependent on a single purchaser of their services

• Pure own-account workers – those whose work cannot be generally delegated to a third

person and who do not employ others even if they can afford to (e.g. baby sitters, domestic helpers etc.)



Open questions Main occupation? • EDGE definition implicitly restricts entrepreneurs to

those working for their own enterprise as their main occupation

• Restriction meant to minimize type II error • But does it exclude too many others?

– US Census Bureau reports that up to ½ of all people who begin start-ups keep their “day job” as a source of financing or safety net

• Gender bias if women are more likely than men not to perceive themselves as entrepreneurs?



Open questions (cont’d.) Ownership size threshold? • No ownership size threshold or upper bound is

established in EDGE definition

• But defining the ‘gender’ of enterprises owned by a large number of people with complex ownership structures is problematic and may not be meaningful from a gender perspective.



EDGE conceptual framework Determinants Outcomes Impact Entrepreneurial

participation Motivations

and aspirations

Entrepreneurial resources

and constraints

Enterprise performance

Employment creation

Growth with poverty

reduction

Women’s empowerment

Analysis EDGE indicators on entrepreneurship



Motivations and aspirations

• EDGE focus on how “entrepreneurial culture” shapes gender gaps in entrepreneurship – Motivations for starting an enterprise – Mode of acquisition of enterprise – Growth aspirations



Proposed indicators: motivations and aspirations, by sex

Indicator Data Source Current Availability A1. Percentage of necessity entrepreneurs

Household survey (primary); enterprise survey (supplemental)

In unofficial data (GEM) and micro-enterprise surveys for a few countries

A2. Percentage of entrepreneurs who were unemployed before starting enterprise


Household surveys can provide information on previous economic activity.

A3. Percentage of enterprise founders

Household survey or Enterprise-level data

Few countries, in surveys of owners (US SBO, Mexico ENAMIN)

A4. Percentage of entrepreneurs satisfied with size of enterprise


Few countries in micro-enterprise surveys



Entrepreneurial resources and constraints • EDGE focus on self-reported “soft” and “hard” resources for

starting/growing enterprise and constraints faced during start-up/management process: – Skills and management experience of entrepreneur – Income available to invest in enterprise – Access to credit – Time available to invest in enterprise – Support networks



Proposed indicators: entrepreneurial resources and constraints, by sex Indicator Data Source Current Availability B1. Percentage of entrepreneurs who completed secondary or higher education

HH survey (primary), Enterprise-level data (supplemental)

Yes, in household and labour force surveys and population censuses

B2. Percentage of entrepreneurs who received training or education on starting an enterprise

HH survey Few microenterprise surveys (Mexico ENAMIN)

B3. Percentage of founders who used credit from banks to start enterprise

Enterprise-level data or HH surveys

WB Enterprise Survey, few firm-level, microenterprise surveys

B4. Percentage of entrepreneurs who used credit from banks to finance operating investments

Enterprise-level data or HH surveys

WB Enterprise Survey



Proposed indicators: entrepreneurial resources and constraints, by sex (cont’d.) Indicator Data Source Current Availability

B5. Percentage of entrepreneurs identifying access to finance as major constraint for enterprise growth


Few microenterprise surveys and firm-level surveys (France SINE)

B6. Percentage of entrepreneurs identifying lack of time as major constraint for enterprise growth


In few micro-enterprise surveys

B7. Average hours spent working on business per week


Yes, in household and labour force surveys

B8. Percentage of entrepreneurs who regularly receive managerial advice, by source of advice

Household survey Not available



Entrepreneurial participation

• Most important objective of international data collection on women’s entrepreneurship is to produce a reliable and comparable measure of the number of men and women entrepreneurs.

• EDGE focus on identifying a metric that is: – easily and similarly understood across different

development contexts – easy to produce via light modifications to extant

data collection instruments



Proposed indicators: entrepreneurial participation, by sex

Indicator Data Source Current Availability C1. Percentage of adult population who are entrepreneurs

Household survey or population census (primary), Enterprise-level data (supplemental)


C2. Percentage of entrepreneurs, by size of enterprise and economic activity

Household survey or population census (primary), Enterprise-level data (supplemental)


C3. Percentage of women who are main owners and managers of enterprise, by size of enterprise

Household survey and Enterprise-level data

Not available, with limited exceptions (US SBO)



Proposed indicators: entrepreneurial participation, by sex (cont’d.)

Indicator Data Source Current Availability

C4. Percentage of enterprises owned by women/men, by size of enterprise and activity

Enterprise-level data (primary), household survey (supplemental)

WB Enterprise Survey for most countries

C5. Percentage of women/men among owners of unregistered enterprises

Household survey From household, labour force and micro-enterprise surveys but only for a few countries

C6. Percentage of enterprises registered by women/men

Administrative data Not available, with limited exceptions (Germany)



Enterprise performance

• Performance is traditionally proxied by longitudinal indicators measuring growth path of enterprise – Requires highly developed infrastructure of longitudinal

data • EDGE focus is on performance indicators that can be more

easily produced via cross-sectional surveys • Challenges include:

– Identifying a single concept of business earnings – Assessing best approach for measuring earnings – Apportioning share of profits in multi-owner enterprises



Proposed indicators: enterprise performance, by sex of owner

Indicator Data Source Current Availability D1. Gender gap in earnings from enterprise


Often only for unincorporated self-employed in household surveys, and in few micro-enterprise surveys

D2. Gender gap in enterprise turnover


WB Enterprise Survey and a few micro-enterprise surveys

D3. Percentage of enterprises with employment growth


Not available



Proposed indicators: enterprise performance, by sex of owner (cont’d.)

Indicator Data Source Current Availability

D4. Percentage of innovating enterprises, by type of innovation

Enterprise-level survey

Available only in few Enterprise-level surveys (France SINE)

D5. Percentage of exporting enterprises

Enterprise-level survey Non-official data (GEM), few micro-enterprise surveys, WB Enterprise Survey

D6. Average age of enterprise


Enterprise surveys

D7. Job satisfaction of entrepreneur

Household survey Not available



Thank you!

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