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Pushed into necessity?
Labor market inequality and entreprenurship of disadvantaged group
Joanna Tyrowicz Magdalena Smyk
GRAPE |FAME, IAAEU, IZA, University of Warsaw GRAPE |FAME, Warsaw School of Economics
Motivation
Pushed or pulled?
What is a main reason for becoming self-
employed? Are entrepreneurs pushed from wage-
employment market? Or rather pulled by new op-
portunities? Is the labor market inequality pushing
factor for self-employment?
These questions remain mostly unanswered, espe-
cially due to lack of data with discirminated work-
ers observed JUST before decision of becoming
self-employed.
Our contribution and hypotheses
⇒ The analysis considers separetely self-employed due to necessity and aspirations.
⇒ We exploit cross-country & time variation of labor market gaps.
Intuition:
• Inequality is a push factor for necessity self-employment, but should not matter for aspirational one.
• Wage inequality may operate weaker than employment inequality (employee agrees to lower wage
instead of becoming self-employed, there is no such alternative in the context of employement
inequality).
Theoretical model
We extend the model by Fonseca et al (2001):
- V - self-employment payo, U - work payo, K - start-up cost and α - distribution of enterpreneurial skill
- individuals may have a gender ⇒ women are disadvantaged in employment / wages (but not productivity): U(1 − gap).
- m and f - costs of being self-employed are also gender-specic.
For becoming self-employed:
M: (α − m)V − K  U ⇒ Sm =
U + K
V
+ m,
W: (α − f)V − K  U(1 − gap) ⇒ Sw =
U + K − gap ∗ U
V
+ w
This yields a gap in
1
1 − F(Sw)
−
1
1 − F(Sm)
= −
gap ∗ U
V
+ (w − m)
- it is negative so long as m is suciently smaller than w.
- (w − m) is likely to be a country specic eect.
Data
Gender wage gaps
• Nopo et al. (2011) for 64 countires (cross-
section) and Tyrowicz  van der Velde
(2016) for app. 500 data points (time and
cross-section)
Gender employment gaps
• Goraus, Tyrowicz  van der Velde (2016)
for app. 1200 data points (time and cross-
section)
Measures of necessity and aspirational SE
• Global Entrepreneurship Monitor -
entrepreneurs report whether their self-
employment is driven by aspiration or due
to necessity.
Matching
- 25 countries matched for GEG and 21 for GWG
in exact matching (the same year in GEM and
GEG/GWG data)
- 26 countries for GEG  GWG in inexact matching
(+/- 5 years of GEM data relative to GEG/GWG
data)
Results
Table 1. Necessity self-employment for women (Multi-Level Regression)
Necessity SE (1) (2) (3) (4)
for women
Country-year groups 185 53 191 175
Observations 339 702 101 616 344 308 326 663
GEG exact match 0.0060***
(0.0018)
GWG exact match 0.0021
(0.0030)
GEG inexact match 0.0064***
(0.0014)
GWG inexact match 0.0046*
(0.0025)
Necessity SE - men 0.6242*** 0.6315*** 0.6237*** 0.9931***
(0.0375) (0.0597) (0.0363) (0.0488)
Age -0.0001*** -0.0001*** -0.0001*** -0.0001***
Tertiary education 0.0004 0.0000 0.0004 0.0003
Knows entrepreneur 0.0071*** 0.0079*** 0.0072*** 0.0072***
Knows business angel 0.0118*** 0.0103*** 0.0116*** 0.0111***
Constant 0.0010 0.0049*** 0.0011 -0.0021
• Multi-level regression conrmed positive link between GEG/GWG and necessity self-employment.
• No such link was found for aspirational entreprenuers.
Conclusions
• Link between ajusted gender employment gap or gender wage gap and necessity self-employment is
positive and robust.
• Eect of GEG is stonger than eect of GWG.
• No evidence on link between GEG/GWG and aspirational self-employment was found.
Acknowledgements
We are grateful for long and clarifying discussions
on the topic to Tomasz Mickiewicz, Saul Estrin,
Irene van Staveren, Yona Rubinstein, Marcin Bi-
elecki and Lucas van der Velde. Remaining errors
are ours. Authors gratefully acknowledge the fund-
ing support from INNOGEND project co-funded
from Norway Grants in the Polish-Norwegian Re-
search Programme operated by the National Cen-
tre for Research and Development.

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Pushed into necessity? ASSA 2018 poster

  • 1. Pushed into necessity? Labor market inequality and entreprenurship of disadvantaged group Joanna Tyrowicz Magdalena Smyk GRAPE |FAME, IAAEU, IZA, University of Warsaw GRAPE |FAME, Warsaw School of Economics Motivation Pushed or pulled? What is a main reason for becoming self- employed? Are entrepreneurs pushed from wage- employment market? Or rather pulled by new op- portunities? Is the labor market inequality pushing factor for self-employment? These questions remain mostly unanswered, espe- cially due to lack of data with discirminated work- ers observed JUST before decision of becoming self-employed. Our contribution and hypotheses ⇒ The analysis considers separetely self-employed due to necessity and aspirations. ⇒ We exploit cross-country & time variation of labor market gaps. Intuition: • Inequality is a push factor for necessity self-employment, but should not matter for aspirational one. • Wage inequality may operate weaker than employment inequality (employee agrees to lower wage instead of becoming self-employed, there is no such alternative in the context of employement inequality). Theoretical model We extend the model by Fonseca et al (2001): - V - self-employment payo, U - work payo, K - start-up cost and α - distribution of enterpreneurial skill - individuals may have a gender ⇒ women are disadvantaged in employment / wages (but not productivity): U(1 − gap). - m and f - costs of being self-employed are also gender-specic. For becoming self-employed: M: (α − m)V − K U ⇒ Sm = U + K V + m, W: (α − f)V − K U(1 − gap) ⇒ Sw = U + K − gap ∗ U V + w This yields a gap in 1 1 − F(Sw) − 1 1 − F(Sm) = − gap ∗ U V + (w − m) - it is negative so long as m is suciently smaller than w. - (w − m) is likely to be a country specic eect. Data Gender wage gaps • Nopo et al. (2011) for 64 countires (cross- section) and Tyrowicz van der Velde (2016) for app. 500 data points (time and cross-section) Gender employment gaps • Goraus, Tyrowicz van der Velde (2016) for app. 1200 data points (time and cross- section) Measures of necessity and aspirational SE • Global Entrepreneurship Monitor - entrepreneurs report whether their self- employment is driven by aspiration or due to necessity. Matching - 25 countries matched for GEG and 21 for GWG in exact matching (the same year in GEM and GEG/GWG data) - 26 countries for GEG GWG in inexact matching (+/- 5 years of GEM data relative to GEG/GWG data) Results Table 1. Necessity self-employment for women (Multi-Level Regression) Necessity SE (1) (2) (3) (4) for women Country-year groups 185 53 191 175 Observations 339 702 101 616 344 308 326 663 GEG exact match 0.0060*** (0.0018) GWG exact match 0.0021 (0.0030) GEG inexact match 0.0064*** (0.0014) GWG inexact match 0.0046* (0.0025) Necessity SE - men 0.6242*** 0.6315*** 0.6237*** 0.9931*** (0.0375) (0.0597) (0.0363) (0.0488) Age -0.0001*** -0.0001*** -0.0001*** -0.0001*** Tertiary education 0.0004 0.0000 0.0004 0.0003 Knows entrepreneur 0.0071*** 0.0079*** 0.0072*** 0.0072*** Knows business angel 0.0118*** 0.0103*** 0.0116*** 0.0111*** Constant 0.0010 0.0049*** 0.0011 -0.0021 • Multi-level regression conrmed positive link between GEG/GWG and necessity self-employment. • No such link was found for aspirational entreprenuers. Conclusions • Link between ajusted gender employment gap or gender wage gap and necessity self-employment is positive and robust. • Eect of GEG is stonger than eect of GWG. • No evidence on link between GEG/GWG and aspirational self-employment was found. Acknowledgements We are grateful for long and clarifying discussions on the topic to Tomasz Mickiewicz, Saul Estrin, Irene van Staveren, Yona Rubinstein, Marcin Bi- elecki and Lucas van der Velde. Remaining errors are ours. Authors gratefully acknowledge the fund- ing support from INNOGEND project co-funded from Norway Grants in the Polish-Norwegian Re- search Programme operated by the National Cen- tre for Research and Development.